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Our email list is divided into three categories: regions, industries and job functions. Regional email can help businesses target consumers or businesses in specific areas. Israel Email Lists broken down by industry help optimize your advertising efforts. If you’re marketing to a niche buyer, then our email lists filtered by job function can be incredibly helpful.

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Israel Email Lists

Israel Email Lists

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Israel Email Database

Segmenting your prospects list by ‘who’ and what is the best way to do so. What they’ve done refers to what they have done on your website. One prospect might have downloaded a brochure, while another person may have signed up for a particular offer. A good email marketing service will let you segment your list and automate your campaigns so that they can be sent to different customer types at the time that suits you best.

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Israel Email Lists   

This is the reason why implementing an efficient Email marketing campaign is becoming more essential than ever before.
This article will provide everything you should learn about email marketing and how to design an efficient email marketing campaign right by starting from beginning to finish. Israel  email providers
How do you define email marketing?

Email marketing is a form of marketing using digital technology that includes sending out emails to customers and leads. Campaigns for promotion, newsletters and event announcements are all excellent examples of marketing via email messages. Israel Email Lists

Modern marketing through email has shifted away from standard marketing to opt-in, segmentation, as well as personalization.

Israel email lists

Israel email lists


Personalized emails can boost CTR by as much as 14 percent  email marketing email Israel

(Source: Melanin)

It’s crucial to realize that you’re an intruder in an email address of the leader. Even if you believe that your message is distinctive, it’s not. To the person who receives it, you’re just one in a million however, not always in the positive manner. Israel Email Lists

Many people are overwhelmed by tens of thousands of emails each day.

It’s crucial to be courteous when you send email to leads or customers. Find a way to make yourself stand out.
Examples of Marketing Emails

There are three kinds of emails for marketing:

Transaction emails
Promotional emails
Engagement emails

We’ll now look at these emails in more depth and then examine some examples so you’re able to quickly recognize the emails.
Transactional emails

The business sends transactional emails to offer the product or service to their customers. These emails are mostly reacting, being they are sent as a result of an action of a client.  email marketing email Israel
Transactional emails

(Source: Experimenting)

The emails are sent out when users engage with a site or application like adding products to an online shopping cart , or asking for the reset of their password. It’s a case of an transactional mailer from an American company that is a giant.
An example of a transactional email

(Source: Really Good Emails)

This email was automatically sent when a client abandoned the cart. What is the effectiveness of these emails?

More orders of 69%, leading to a massive rise in profits for businesses.
The Power of Abandoned Cart Emails

(Source: Campaign Monitor)

Transactional emails are typically used to inform customers about their order or account status. Here are a few examples of transactions-related emails: Israel  email providers

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Invoices and confirmations of orders
Delivery confirmation
Double opt-in messages Israel  email providers
Password reset emails
Cart Abandonment Reminder

While transactional emails can appear easy, they’re actually an excellent way to create brand recognition and increase reader confidence. You may believe that confirmation emails don’t need to be considered. Israel Email Lists

They are, however, among the most opened and sought-after emails among consumers.
Importance of Order Confirmation Emails

(Source: Chameleon)
Promotional emails

Then, we’ll have sales or promotional email — which are the kind of emails that will probably immediately come to mind when you hear “email marketing.”

The most effective emails for promotion encourage readers to purchase services or purchase a product.
A sample of a promotion email Israel consumer  email email

(Source: Melanin)

They’re not the only thing they can accomplish, however. When done right, these email messages will also boost the engagement of customers and increase retention. For instance, they could give your readers a great discount that will help transform leads that are uncertain to loyal customers.
Promotional email offering discounts.

(Source: Shopify)

In the above example, Ann Taylor appeals to customers with a discount of $75. on a purchase at full price that is $25 or greater.

Here are some additional samples of emails that promote a product:

Promotions that are time sensitive
Review/commendation requests.
Product update emails
Holiday Sales Emails
Emails from co-marketing or affiliate marketing

Engagement emails

Engagement emails help build relationships with leads and customers through storytelling, education for customers as well as enhancing the values of the brand.

These emails keep subscribers entertained even when they’re not in the mood to purchase anything. Israel consumer  email email
An example of an engagement email Israel Email Lists

(Source: OptinMonster)

When they’re ready to purchase, or when you have something unique to give away, they’ll be keen to purchase regardless of whether they’re first-time buyers. Engagement emails typically start by sending “welcome emails” — the first emails that subscribers receive after signing up to an email subscription.
An example of a welcome email

(Source: Flickr)

The welcome email sequence is crucial as it is the first impression of your company. For instance the welcome email above is from Product Hunt keeps it friendly and straightforward, right from the subject line all the way to the conversational tone used in your email’s body.

This is among the most frequently requested and read emails from leads that join to your list of email subscribers.
Welcome Email Earnings per email

Israel Phone Number mailing lists

Israel Phone Number mailing lists

(Source: WordStream)

There are other kinds of engagement emails, such as:Israel  email providers

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Weekly/Monthly Newsletter
Tips and tutorials
Customer stories Israel address lists
Re-engagement emails
Lead nurturing emails

What is the effect of email marketing?

Marketing via email is among the most efficient strategies because of its automated nature. That’s why 86% marketers believe that email is “important” or “very important.”
A of email marketing mailing list

You shouldn’t send marketing email campaigns if there isn’t someone to forward the messages to. Israel consumer  email email

Be aware that email marketing will not succeed unless you’ve got the right audience that is interested in receiving marketing messages from your company.

While there are a variety of ways to build an email list one of the most simple is to make an lead magnet.
An example of a lead magnet

(Source: Digital Marketer)

Consider lead magnets as a way to attract leads to your list of email subscribers. They’re highly effective as your subscribers immediately discover an incentive to sign up to an email subscription.

Here are some examples of lead magnets that are great. Israel Email Lists

In essence, the higher the worth that your lead magnet has, the greater number of people will sign up for it.

Another amazing example of a wonderful lead magnet in the five free Meal Plans. This is a great option for the mother who has to make time for dinner each evening.
Of course bloggers wish the blog content they write to become viral. Israel  email email free

This is an excellent lead-generation tool for them. There’s no need to keep worrying about how to make your blog posts go viral if you’ve got this cheat sheet!
#2 An email service provider

The email provider (ESP) gives you the ability to mass business and broadcast emails.

If you send a significant number of emails with no ESP then they’ll be deemed spam, and your readers won’t be able to receive the emails. This means that you will not be able to contact your customers as frequently as you’d like to to ensure the best conversion rate.
Email sending frequency

(Source: Retention Science) Israel  email email free

The good news is that ESPs manage all of the technical, expensive and formal requirements. All you need to sign up and utilize their services.

These are our top 5 email providers we suggest.

Note Take note that the “best” option depends on your goals for marketing, list size, and features you want. If you’re in the market for a software to market your email this review will aid you in selecting the right one for you. Israel Email Lists

Israel Phone Number lists

Israel Phone Number lists


Sandin Blue
Send Blue Home Page

SendinBlu is an all-inclusive business email marketing system which also provides SMS marketing. It lets users send more than 30 million automated messages and text messages daily. buy Israel email online

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SendinBlue also provides forms that can be used to collect new leads. These leads can later segment into specific lists and use in the email nurture campaigns. Israel address lists

Are you looking to enhance your email marketing but aren’t sure how? Don’t worry. SendinBlue’s SendinBlue workflow allows you access to many pre-built , automated campaigns that are that are tailored to your specific needs.

Below are five plans. Payment options start at just $25 per month. SMS options available for an additional charge depending on the amount of text you need. Israel  email email free
MailChimp
Mail Champ Home Page

MailChimp is home to millions of users across more than 175 countries and they utilize the information they gather to give you useful insights into how you can enhance your email marketing campaigns.

It is possible to use MailChimp to send out simple newsletters. It is also an entire marketing automation platform which uses behavioral messages and abandoned cart emails.

This means that the program is powerful enough to support a large company but is sufficient if you’re just beginning to get started. Mail Champ has it. Four plans that range between free and 299 dollars per month. Other than your free option, the cost of your monthly subscription is based on the number of contacts you have.

It is a bit more costly than other tools, but when you’re in a pinch then you need to consider alternatives that are less expensive. Alternatives to MailChimp
Constant contact
Constant contact Israel business  email email free download

Constant Contact is one of the most popular and effective marketing tools for email around the globe. With templates and editing tools that drag and drop it is possible to manage your subscribers and design professional designs for your emails with ease. Israel Email Lists

Constant contact is targeted primarily at the market for e-commerce. However, some non-profits bloggers, bloggers, and businesses also utilize it.

Israel Phone Number email

Israel Phone Number email

The service offers two plans according to the features you require. between $20 and $45. The price is correlated to the number of contacts you’ve got.

(Not certain which one you should pick. Constant Contact or MailChimp? Take a look at our comparison guide to help you choose the best option today!)
ConvertKit
ConvertKit’s home page

What is what makes ConvertKit distinctive is the fact that it’s targeted towards professional bloggers, writers, and speakers. If you’re an online creator, you won’t be wrong using ConvertKit.

ConvertKit is ideal for those who are just beginning but you should be aware that you’ll need more sophisticated features in the near future including sophisticated autoresponders. buy Israel email online

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Paid plans begin at $29 per month for 1,000 subscribers and increase in price as they go. The company also offers the option of a 14-day trial for free.
Oibar
aweber homepage Israel address lists

Oibar is the queen of simplicity, which is the reason it’s perfect for entrepreneurs and small-sized businesses.

If you are looking for dependable and easy software for sending emails and newsletters, AWeber is your choice. It has a few automated marketing tools. It’s quite basic when compared to the majority of ESPs.

Their customers praise their service’s delivery. AWeber’s delivery team monitors their servers throughout the day to ensure that your messages are delivered on time to your recipients their inboxes.

Paid plans begin at just the price of $19 per month. If you don’t have more than 25k customers on your account, you’ll be able to test any plan at no cost in 30 days.
Comparing common email service providers Israel Email Lists

Here’s a look at the support levels, prices and features of popular email marketing software that we’ve talked about above.
This book is essential to any marketer who is serious about looking to get to grips with email marketing. Israel business  email email free download
How to Automate Your Email Marketing

Although the process for automation is different between ESP to the next but there are a few common steps you can follow to automatize your email marketing plan.

However, , like every tool, is all about the way you use it.

Israel Phone Number listing

Israel Phone Number listing

When used properly, it can aid in getting your email at the appropriate people at the right moment. This is far more effective than sending the same message to every person on your list.
Automate your email campaigns by defining your segment Israel Email Lists

Segmentation groups your customers according to the information you have on them, which allows you to build more targeted campaigns.

According to Accenture the 90% of customers say they prefer buying from brands that offer relevant promotions and suggestions.
91% of customers tend to spend more when they find brands that have relevant discounts. Israel business  email email free download

(Source: Accenture)

Furthermore 72 percent of consumers claim they only engage with personal messages.
72% of consumers respond to personalized messages.

(Source: SmartHQ)

If you’re not providing the right information, you’re wasting money. With segmentation of emails, you have many options for personalizing your marketing emails.
Lead segmentation

(Source: Marketing Insider Group) buy Israel email online

Israel  email listing

You can, for instance, sort your customers according to their position within the funnel of sales. Emails you mail out at your top end of funnel ought to be different from the ones you send that are at bottom. Israel quality  email lists
The stages in the funnel of sales

(Source: WordStream)

It is possible to send more general emails to a set of new subscribers, by offering a variety of products that you can offer.

If they’ve been a subscriber for some time and are engaged via your email (like clicking on the link) You can make use of the data to determine what they’re interested in. They’re interested and will send you targeted emails regarding this product.

Cart abandonment can be a great indicator of a person who is in the middle in the funnel. Mobile phone cart abandonment rate for this second quarter was 80.6 percent. Israel  email email free download
Rates of abandonment of shopping carts online in the US

(Source: Statista)

Customers wanted to purchase, but something stopped them from buying.

Israel Phone Number email

Israel Phone Number email

This allows them to send them a follow-up message to remind the customer that their cart remains open or a message telling them that they are planning to purchase the item.

Below is an example by Rudy of how to follow up:
An example of Rudy’s follow-up email Israel Email Lists

(Source: Really Good Emails)

Other ideas to segment your emails that you can use in your email campaign are:

Could include demographic information like gender age, income level and the position of the company.
Results of Surveys or Quiz Tests Surveys provide vital demographic information and insight into your personal preferences and opinions.
Email Engagement: The most important metrics in this case are click-through and open rates. You can monitor these in your email marketing software.
Geographic Area Geographic area segmentation is an effective tool, particularly for companies where the location plays a significant role on buying decision making. Israel  email email free download
Prior Purchases – Here you will send recommendations via email for similar products that complement the previous purchases of your customers.
Spending amount to determine the types of consumers who are most likely to purchase more expensive products and which consumers are more inclined to purchase cheaper products.
Website Behavior, for instance, you could create personalized emails based on the pages that your subscribers have been to.
The time since the last purchase Customers can be split into two major groups: repeat buyers as well as new customers.

Let me introduce you to

Marketing via email isn’t only for businesses that use advanced software for marketing automation. With an easy email marketing tool, and a little imagination, you can begin creating a targeted audience and reap massive profits.

You could apply some of the suggestions in this book to your company for example, automating your email marketing campaigns by using segmentation of emails. buy Israel email online

Israel  email leads

It’s your turn now.

Which marketing approach to email do you prefer the most? Perhaps we’ve missed something crucial? Or, if you’re not sure tell us in the comments now.
Related publications Israel quality  email lists

The company announced 13 hires during H1 across engineering, product customer success, finance, sales and HR departments and already had appointed three board members earlier in the year. This includes Frederic Lachaud, Cecilie Sofie Anker Andersen, and Christoffer Feilberg, following an investment of. 2.3 million euro at the close of the year. Israel Email Lists

Israel Phone Number leads

Israel Phone Number leads

As an email advertising service, Passendo will continue to facilitate the future of email advertising for newsrooms around the world. It gives marketers and publishers unique measurement tools for email that increase revenue for clients and allowing more control over the content of ads and quality , while also helping create the world’s top category winners. Israel  email email free download

The strategy for go-to-market is rapidly evolving as the company moves into new markets in Europe and in the US as well as APAC, Passendo is already helping publishers across the world expand their revenue opportunities within the newspaper industry.

Andreas Jurgensen, CEO of Passendo Co-founder of Passendo Andreas Jurgensen, CEO of Passendo and co-founder of the company “Germany and Italy have always been on our roadmap and we are happy to go directly to these markets now that continue our exciting and fast-paced journey.”

Cesare Romano who is the executive in charge of growth accounts at Italian Passendo said: “The publishing world is beginning to realize the potential commercial benefits of advertising directly in newspapers. In a time where the advertising industry has adopted the no-cookie policy and an advertising channel that has the primary goal of protecting privacy for users can only prosper. Our mission is to assist marketers make money quickly from this channel since there’s plenty of money lying open in the world of email, particularly in countries like Italy where advertisements aren’t available. most magazines. Israel b2b email

Publishing houses like Politico Europeannews Archant as well as Groupon already exist
Use the platform for email ads of Passendo to boost direct revenues and efficiently manage printing advertising campaigns. Israel Email Lists

About Passendo

Passendo is the most popular European platform to sell news magazines. In 2016, two pioneers of the digital advertising industry and the award-winning email ad server as well as the SSP offers benefits to advertisers and publishers across the globe. Through collaboration with the biggest media companies in the world, Passendo helps them activate new and expanding revenue streams that are currently not yet tapped channel: advertising. through email, thus connecting with a wider audience and creating new opportunities.
The advances in AI/ML methods allow for a completely new paradigm in which every automated task can be given to machines for control , while experts are free to concentrate on the complexities of understanding the basic science. For instance, AI/ML-driven, autonomous management of systems for scientific research has the potential to provide systems for science that can self-regulate to produce ultra-high-performance and experimental systems that can explore autonomously issues in science, utilizing the most effective experiments and transforming the data that is accumulating into human-readable physical information. This could dramatically improve the effectiveness of facility operations as well as provide an chance to understand and study the latest developments in science and, ultimately speed up the release of thrilling scientific discoveries as well as the next generation of energy technology storage and utilization and security for the nation. Israel b2b email

Israel Phone Number Profile

Israel Phone Number Profile

In the SUFs The most significant aspect is accelerators, which are the foundation of the vast photon, electron, and neutron researchers. To allow accelerators to work effectively hundreds of component systems need to operate within tight tolerances and deliver high-quality nonlinear reactions.

Control methods that are based on static designs, or manual tuning aren’t able to deal with the real-world complexity that these control systems have, particularly because SUFs are moving toward physical-based sources. Control platforms for online systems in the future will require AI/ML methods that make use of the physical properties of devices that are known (via intricate modeling) and operational experiences in the world (via mining information in the archive of the device). In addition, new instruments for research and experimentation, like endstations equipped with synchrotron and neutron technology electron microscopes, scanner probe instruments and high-end optical systems are getting more complex and require precisely controlled hardware systems that are interconnected to handle massive amounts of data being produced in a fast-paced manner. Israel  email id list

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AI/ML algorithms can also be used to manage user-generated experiments through an independent choice of measurement conditions. With the use of fast real-time data analytics, this method will improve the quality of the experiment data, as well as decrease the time spent by instruments and will speed up studies. The results will be immediate across the entire SUF program. Israel quality  email lists

The latest research on the most recent advances in the fields of materials, chemicals and biosciences are also confronted with the same issue and so do the latest frontier research that focuses on huge and complex parameters. Analyzing multicomponent heterogeneous and non-equilibrium materials requires an in-depth study of the vast area that is defined by the materials composition as well as the background of its processing. The hunt for functional targets in materials as well as the need to identify major trends are hard to achieve using standard methods. The field requires the capability to determine, analyze, and study the material and processing parameters. This requires the development of autonomous control systems for experiments which can refresh the data collection. AI/ML autonomous experiments can assist in the synthesis of materials that is real-time and will allow access to non-equilibrium and metastable materials that can only be achieved by active control of the process of synthesis. Steered synthesis is also a great way to conduct the study of additive manufacturing technologies that rely on control and computation to generate the desired structure and material. Israel b2b email

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Research Directions

Automated control of experimental equipment can allow studies that were that were previously considered to be unsolvable. The purpose of this research is to automatize every aspect of the experimentation process, starting from the setup and tuning instruments, to synthesis and sampling, the measurement of data and analysis modeling–

9
the interpretation of data that is driven by technology in conjunction with the subsequent decision-making process. This is why it is crucial to coordinate the advancements across various technologies. Israel Email Lists

Proposed research PRO identified two areas of research which could help enhance BES research program:

1. Automating the control of facilities that improves reliability, efficiency from self-regulation, and the capacity to push the physical limits. Examples are given for accelerators and beamlines. Israel b2c email

2. Automation of the procedure for testing, which includes the automated measurement or synthesis platforms, together with AI/ML algorithms allow to explore intelligently complex problems. Examples are given for the discovery of science as well as creating new materials.

Automating the control of facilities

Every each time a new generation of SUFs is added to the SUFs, which increases the complexity both technical and scientific issues. Effective experiments within the SUF requires constant tuning and control in the highly-dimensional space which the responses are nonlinear and the parameters are closely connected. For example, achieving large amounts of coherent flux within an area of focus within the current synchrotron beamline depends on feedback loops that maintain beam intensity. In the ideal scenario, they can directly guarantee steady and stable wavefronts throughout the direction of the samples. A sophisticated AI/ML controlled control system that uses the physical model of beamline systems can provide an efficiency and stability previously unattainable. The current AI/ML methods must be modified to meet the specific requirements of various experimental tools. There is also the possibility to establish a common set of of AI/ML techniques that could be applied to address various control issues. Israel  email id list

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The SUFs have a huge challenge when they have to manage and adjust the experiment in a complete end-to-end method. For instance , a synchrotron beamline testing can be considered as an

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independent set of systems that have to be tuned separately or as a huge interconnected issue in which beamline performance as well as accelerator performance and measuring systems for the endstation as well as the whole experiment must be tuned to attain a particular scientific objective. Like electron microscopes, the optics sources, the source, the detector and the environment are a system in one which requires optimization to serve a particular purpose for example, synthesizing or imaging at the level of atomic size [28for example]. Israel quality  email lists

One excellent illustration of the need of online controls is SUF accelerators that provide electron, photon and neutron beams to an array of researchers. These accelerators today are tremendously complicated and include thousands of components which have dozens or hundreds of controls that need to be managed in a coordinated way. The impact of a parameter’s effect upon the efficiency the systems is typically achieved through complex, nonlinear physical processes. For example, in a storage ring , dynamic beams that are not linear determine the effectiveness of the ring’s inject as well as the length of the beam. In an XFEL that is self-amplified and spontaneous XFEL, the nonlinear beam dynamics regulate the self-bunching of electrons within the beam. The parameters of control can be linked, and the most optimal configuration can be altered as environment changes. The standard approach to controlling is to establish parameters in accordance with models of static designs, and then manually adjust subsystems. This method is not without its flaws that hamper effectiveness of the research. The performance in actual life is usually lower than simulations, because environmental variables aren’t considered in the design models. Tuning manually can increase performance , however it is laborious and depends on the expertise and experience of the person who is performing the procedure. When it comes to machines that are complicated like Linac Coherent Light Source (LCLS) designing the equipment to perform specific operations may take hours of tuning, which could be better utilized in conducting research on the user. Certain unique beam characteristics may not be available because of the issue of tuning. Israel b2c email

After you have created the correct accelerator configuration, it is also crucial to ensure that the environment is maintained while operating. At present feedback loops, they are used to stabilize subsystems, typically with linear connections that are simple in nature. orbit feedback is a prime example. However, in many cases, machine performance could be affected by the surrounding environment by various connections that aren’t well-known and need continuous compensation Israel Email Lists

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Adjusting control parameters to alter the control parameters. Traditional methods of tuning might not be suitable for this as they can cause substantial changes to control parameters and interfere with user-created experiments. Recently , automated tuning has been widely utilized for devices that range from colliders to light sources [31-41] and solutions that deal with issues of noise drift, outliers and noise. While there are a few examples of accelerator control created using AI/ML are offered (e.g., Gaussian process optimization) [34 38 34], the successful finding large, intricate parameter spaces is a significant problem. Intelligent control techniques that are able to rapidly and effectively adapt the control of variables variable that are not linear are needed. Israel b2c email

Reliability and reliability are crucial to the functioning of an SUF, which is able to serve thousands of users according to a specific time. While every component within the SUF should work consistently for a lengthy time but it’s normal to have parts fail in a large system. Since one problem could lead to the entire malfunction of the system and the recovery process is typically more costly than replacing the components during routine maintenance. Therefore, it’s crucial to know the performance and condition of the accelerator’s subsystems and components. In particular, understanding failure patterns can allow for swift recognition of the reasons for failures. This aids in speeding up the process of recovery. The ability to detect failures is vital since it helps stop them from happening by preventive maintenance or reduce the time required to repair them by initiating a protection process before the event of failure. Failure prediction is crucial for superconducting systems because quenches that fail could cause significant reductions in operating times. Israel Email Lists

AI/ML gives you a unique opportunity to overcome the difficulties that arise when operating complex SUFs. Particularly, the conventional methods of tuning treat the system as an undefined black box, but AI/ML-based techniques could be used to build an approximate representation of the physical behavior that the system is operating (see PRO 3.). An online model can be continuously enhanced and improved by incorporating the most current measurements from the machine. The ability to produce precise predictions with the model could lead to significant improvement in the efficiency of optimization algorithms within the highly-quality parameter space. Israel  email id list

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AI/ML control strategies can also be employed to adjust for the effects of environmental drift. The intention of keeping the impact at a minimum in ongoing user experiments can naturally be included in the ML’s feature of target-reward. This would allow for previously unattainable improvements in both stability and performance. The integration of the latest control and prognostic methods developed by AI/ML into operations will let it manage an SUF almost entirely with a self-learning and intelligent software, which eliminates the need for human intervention while maximizing the effectiveness of indicators. Improvements in the tuning of algorithms and parameter space search methods rapid modeling of components, and the integration of these methods into hardware systems being used. If implemented correctly these methods will bring the latest beam technology and confidence to scientists which will result in a brand new generation of advanced BES research. Israel mailing lists

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Automating the experiment

Alongside the ability to tune instruments’ algorithms, AI/ML methods can revolutionize the way experimental platforms are used in the process of automating selections of experiment conditions and measurement conditions, as well as the measurement sequences as well as the total running of the experiment. Such automation–necessarily leveraging accelerated real-time data analytics–would dramatically increase the quality of experimental datasets, reduce wasted instrument time, minimize sample damage from probes, and accelerate experimental studies. Israel customers email

Modern tests of experimental data can be multimodal as well as high-dimensional. the traditional method of fully testing a sample has become complicated since the complexity and resolution increase. For example, imaging of dynamic materials implies a 4D space, while multimodal acquisitions that combine rich spectra with scattering/diffraction patterns further broadens signal complexity. Automated control of tests can permit variables of any experiment to be affected by previous measurements, thus taking advantage of those SUFs resources to obtain the most relevant data. For instance, the study of working conditions that are constantly changing requires identifying, recording and evaluating the most significant variables. Israel Email Lists

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significant volumes within the sample because of the stimuli used. As well as selecting the most important samples, researchers could also decide on the imaging method for the subvolume. This is a huge measurement parameter space that could be difficult to explore when trying to identify particular connections between localized phenomena (e.g. dislocation motion, or the accumulation of strain at the grain boundary) and the overall irreversible process. AI/ML-based systems capable of making real-time choices are needed to control these variables. The enhanced brightness offered by modern and more efficient lighting sources, as well as the rapid advancement of ultra-fast electron microscopy methods together with the modern advancements in the field of detector technology, permit the study of intriguing motion-related phenomena on time scales that were previously unattainable. The advances in the field of light source and detection will result in the generation of several order of magnitudes more detail that has significantly smaller timescales. Research advances to a speed at which humans are able to take decisions in real-time , based on AI/ML adaptive control will become essential. Israel customers email
Modern accelerators rely on the precise control of hundreds of variables simultaneously. The conventional human-driven control of these complex nonlinear systems are not adaptable in the event of uninterrupted operation and physics-based performances. With AI/ML, it’s possible to create a “self-driving” accelerator capable of keeping track of its own health using an AI/ML analysis of the process to anticipate failures, limit downtime and then automatically adjust in real time using physical models to ensure that it is running at a constant high-performance. This can allow for a customizable shot-by-shot settings for XFEL tests, which could reduce the amount of reconfiguration time between tests from hours, days or even minutes, and increases of orders of magnitude for beam stability as it travels from the source to the detector. Israel Email Lists

Left image is courtesy of Christopher Smith, SLAC National Accelerator Laboratory Middle image is from Terry Anderson, SLAC National Accelerator Laboratory. Right image is courtesy Genevieve Martin/Oakridge Laboratory, US Department of Energy. Israel  email id list

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Similar options are offered by the self-guided nature of synthesizing materials. The modern materials have become extremely complicated due to the complex formulation, blends and composites and the structure-based hierarchical structures with various length scales of order as well as the complexity of processing non-equilibrium materials that exhibit order-dependent pathways. Although the search space is vast the proportion of materials that possess desirable properties is extremely small which makes it a very difficult “needle within the pile” search problem. In Israel mailing lists

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Contrary to the stability control concerns and stability control issues, where anomalous phenomena are usually eliminated, research in material physics must focus on the variations in order to discover fascinating anomalies that are fundamentally different from the materials with records-setting properties. Correlative searches of the traditional kind is usually not able to find important outliers since they tend to focus on interpolation and cannot do well with extrapolation, and are more likely in averaging out of relevant differences. AI/ML algorithms will improve the efficiency of searching these areas because they are capable of handling the large amount of data and also the search for subtle relationships. Israel customers email

Computing infrastructures: Real-time control with material modeling demands fast and flexible access to databases that contain previously computed results, as being able to trigger computations based on model results. This will require the creation of a new computing infrastructure capable of handling the demanding and unpredictable load that is expected to result from an experimental process that is dynamic. Ideal solutions must integrate edge computing, elastic access to central HPC resources, as well as the integration of cloud computing. Additionally, new access methods that connect to DOE compute infrastructure to enable on-demand HPC must be explored. Israel business email

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Edge computing: Ultra-fast processing of huge and complex models will require processing at the edge, using specific equipment (including graphic processing units (GPUs) as well as FPGAs, field-programmable gates(FPGAs and graphics processing units) as needed.

Practices for data: The integration of theory, experimentation and simulation with AI/ML will require major changes within the scientific community with regard to the use of data. Members of the community will have to Israel Email Lists

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spread data out more widely, but be mindful of incentives and credits and must define the standards of curation and annotation for data and aggregate. Combining the results of experiments and theory will require planning in relation to the consistency of tagging, nomenclature and formats for data representation, such that the results of different models can be easily compared and seamlessly integrated into the experiment.  email marketing email Israel

* Workflow infrastructure Infrastructure development requires to integrate existing materials as well as chemical databases into workflows that are autonomous. Flexible, simple standards need to be negotiated so that databases created by industrial partners and collaborators can easily be adapted for online environments of control. Autonomous experimental control should make use of the many probes and imaging techniques available in the DOE complex (e.g. the x-ray neutron, electron, optical as well as scanners). The development of multimodal science requires collaboration between user facilities, which will further enhance the requirements that were discussed previously in connection with sharing and curation of data.

Smart, autonomous control attempts to automatize a complicated control loop that requires the an integration of better information collection, data analysis systems modeling, as well as decision-making. This area of research needs to be accompanied by improvements in other PROs.

1. The most advanced analysis and collection strategies are required to gather and process data, providing the right insights to drive online control.

The decision-making algorithm must be pre-trained using artificial data generated by conducting virtual experiments, and continuously upgraded based on the most advanced physical models. Israel business email

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4. The sets of training needed for AI/ML algorithms should include a shared infrastructure for data. Israel mailing lists

The most critical advances that are required are the AI/ML methods developments that have been identified that will allow for an unprecedented level of computational effectiveness as well as complex (see the section about Enabling Capabilities within Computer Sciences and Mathematics)

* Search/optimization: New developments in search/optimization and data mining techniques are needed to manage the large, high-dimensional, and complex spaces that are inherent to scientific issues.

The advanced method of detection of correlation could allow failure prediction in accelerators as well as self-calibration tools for experiments. The identification of correlations between data could also enable new measurement multimodal methods. buy Israel  email email

* Quantification of uncertainty Online control algorithms that properly include cost and uncertainty from experiments are needed. The range of applications calls for a variety of strategies that include Bayesian strategies, techniques for learning by repetition as well as active learning.

* Approximations: Fast approximations in both the analysis of data as well as material or system modeling are essential for the autonomous experimental loop to operate in real-time. Israel Email Lists

* Physics using AI/ML: Equation-learning strategies can be used to aid the creation of theory in physics as well as chemistrysince they allow the direct calculation of physical equations based on data [61-62(61-62). From a theoretical point of view the numerical solutions that are purely mathematical can be beneficial, but they restrict further development achieved using analytic solutions. Although ML tends to create numerical solutions, advancements are being made in learning equations. The process of obtaining equations from data yields a more straightforward and easily interpretable result that is quickly converted into different types and an easier formulation of the results.

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Potential Impact

Intelligent automation is a great way to transform science, permitting scientists to tackle greater problems and also freeing scientists to consider the science at a deeper level. However, it is becoming increasingly apparent that the current method does not fully exploit the capabilities of the latest scientific instruments. The explosive growth in the brightness of synchrotrons [63as well as similar trends for other advanced experimental tools (e.g. the latest electron microscopes which can attain massive frame rates of up to 100 000 images per second) might not be fully utilized because of the current limitations of analysis pipelines. Automating workflows for experimental work allows researchers to make the most from the potential of current instruments, and also allow them to tackle issues that were previously thought to be too complex. Figure 3 illustrates the increase of synchrotron publication output as well as increased brightness as time passes. buy Israel  email email

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Figure 3. Synchrotron’s light source brightness has increased exponentially over the course of time (left) and has even surpassed the rapid scaling observed in Microelectronics (Moore’s law). The output of a publication (right) comes

Synchrotrons also have increased, although they are not as significant as the properties of the source. This suggests that the existing light sources are not utilizing their full potential (i.e. the an efficient utilization of resources already in use could result in dramatic increases in the efficiency of scientific research). Left image reprinted using permissions from J. Stohr and H. C. Siegmann, Magnetism: From Fundamentals to Nanoscale Dynamics (Springer, 2006). | Right

Image courtesy of Apurva Mehta SLAC National Accelerator Laboratory Israel Email Lists

The latest accelerator features are typically linked to more complex installation and operation. For instance storage rings that have high brightness typically features a tiny safe operating space, also known by the term dynamic aperture. This aperture can be particularly narrow in the commissioning phase, as many mistakes haven’t been rectified. The performance of a possible storage ring design could be limited due to the necessity to reserve an overhead of a dynamic aperture that could be reduced through advanced tuning techniques. In addition, the rapid implementation of difficult XFEL operating modes will permit different kinds of scientific experiments through the delivery of novel designs of beams for users. The advancement of self-contained accelerators will transform the development and operation of the next accelerators, as well as the operation of large SUFs as a whole the control of machines is largely automated, the tuning of accelerators will be performed through efficient computers that are consistent The central control program will be aware of the state of the accelerator’s subsystems and components and will be able to take adjustments and maintenance decisions. The ability to guarantee the performance of the design by using advanced techniques for tuning will have a significant impact on the design of accelerators. AI/ML technologies are able to provide unimaginable capabilities and accessibility for future accelerators.
Advanced autonomous experimentation has the potential for revolutionizing chemistry, materials and bioscience research through the discovery of the most exotic and high-performance materials. Israel  email Profile

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In the midst of complex. It is hard to quantify the potential impact, and the scope of research which will yield. There is a significant potential impact on problems that are currently impeded by the complexity of material composition such as blends and formulations biomaterials and biomimetic system and alloys. Certain kinds of metallic glass may offer the potential to produce extremely high strength-to-weight ratios [64]. A perfect “steel in the near future” material that will provide transformational improvements in applications that require it (e.g. aerospace) is currently hidden within the vast array of alloys that could be imagined and enhanced by the sheer size of the processing area that one has to consider in order to make and quash the metastable states that are glassy. In general research into pathways-dependent phenomena could be transformed through autonomous exploration. Self-assembling materials have a range of non-equilibrium state that are only accessible with the correct processing history [65,66]. In a few instances the researchers are able use “pathway engineering” where a goal that is not achievable using equilibrium processing techniques is chosen and enforced following the proper order [67]. Synthetic platforms that are controlled online could expand on these initial breakthroughs, allowing Israel  lists researchers navigate the complex assemblies and navigate the entire range of complex self-assembling materialssuch as block copolymers (68-69) Liquid crystals [70supramolecular structure [71nanoparticle superlattices [72-75] and DNA into crucial structural patterns. The study of a variety of functional materials can be significantly enhanced by close connections with the right material modeling. For example, design of advanced thermoelectrics would benefit from experimental searches with coupling of structural/spectroscopic probes, operando functional measurements, and structure-property modeling. Similar to studies on quantum heterostructures have already benefited greatly from precise physical simulations. The integration of these models into the measuring loop could enhance the search for new materials that are geared toward quantum applications of information science. buy Israel  email email

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An expanded research program in autonomous experiments could be expected to have immediate and long-term benefits. In the short term (3-5 years) dedicated research will result in a collection of highly specialized tools, such as AI/ML algorithms, models as well as hardware systems that allow autonomous exploration of sample. In the longer term (10 years) it will be possible to develop robust, generalized autonomous synthesis platformsthat will be able to tackle a variety of chemical, material and bioscience challenges while also revealing the latest physical concepts. In the end, the aim of autonomous research is to free scientists from the responsibility of micromanaging the process of conducting experiments, which includes optimizing the experimental conditions, which allows scientists to solve scientific issues at a higher degree.

A lot of the tools for experimentation developed in the DOE complex can benefit from the most advanced AI/ML control techniques. The AI/ML techniques proposed will enhance efficiency and stability, enhancing users of all experiments with increased availability and reliability, and improving the quality of the research that is carried out, which will benefit the most innovative and cutting-edge research programs. As these advanced experimental tools underlie a wide variety of modern scientific studies–from geosciences chemistry to biosciences to energy research–improvements would have broad benefits throughout the BES research program.

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“Steel for the future”

The most amazing new materials can be discovered. Where can we look for them?

Conventional alloys are made by mixing together a tiny amount of different metals. The idea is that they are just a small portion of the possible range of alloys. High-entropy alloys have more elements than traditional alloys, vastly expanding the parameter range of compositions that are possible. These alloys are likely to have records-setting physical properties (e.g. strength-to-weight ratio) particularly if they are in metastable and frustrated states like those that are found in metallic glass can be discovered. But the vastness of these parameters cannot be explored with conventional techniques, or even high-throughput searches, as high-performance materials constitute an isolated island within a vast ocean of non-interesting materials. Autonomous experimental models, that draw the inputs from accelerated modeling, can effectively search for these parameters, identifying fascinating outliers, and then guiding future research in a meaningful direction. If properly implemented, these methods could lead to the high-performance metals that are to come, which will provide significant applications in transportation, aerospace, as well as energy harvesting. Left image courtesy K. G. Yager, Brookhaven National Laboratory. Right image distributed by Brookhaven National Laboratory under a Creative Commons Attribution Noncommercial License Israel  email Profile

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The structure of the Intrinsically Disordered Proteins

The structural description
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biomolecule. AI/ML methods could be employed to discover how to optimally combine neutron scattering data high-performance molecular simulations that run in real-time. This will allow AI/ML-driven directing of simulations towards experimental results in neutron scattering, which could significantly reduce the time required to solve. A significant increase in the capacity to understand the structure of a system could be a huge influence on the structure biology of biosystems with flexible structures. Similar challenges are possible in electron and x-ray microscopy. as current approaches attempt to are able to reconstruct the typical structure, innovative methods in AI/ML are beginning to uncover conformational modifications [80-81]. Israel Email Lists

Top left image reprinted from fast-facts-about-high -flux-isotope-reactor-oak-ridge-national-laboratory. Courtesy of Oak Ridge National Laboratory. | Bottom left image reprinted from supercomputing-neutrons-unite-unravel-structures-intrinsically-disordered-protein. Right image Reprinted by Shrestha, U. R.; Juneja, P.; Zhang, Q.; Gurumoorthy, V.; Borreguero, J. M.; Urban, V.; Cheng, X.; Pingali, S. V.; Smith, J. C.; O’Neill, H. M.; and Petridis, L. “Generation of the configurational ensemble for an Intrinsically Disordered Protein Using Unbiased Dynamics Simulation.” Dynamics Simulation.” Proc. Natl. Acad. Sci. U.S.A. 116 (2016): 20446-20452. doi: 10.1073/pnas.1907251116.

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PRO 3. Facilitate offline design and optimization of facilities and Experiments

Key question: How do we enable virtual laboratories–offline design and optimization of facility operation and experiments–to achieve new scientific goals?

Introduction Israel  email id list

The main challenge in SUFs is the creation and optimization of experiments and facilities in order to reach scientific goals. On the other hand Modern SUFs are home to expensive and complicated accelerators which can be difficult to construct, design and maintain. They are also time-consuming and require meticulously planned sequences of actions, such as formulating the hypothesis, conducting the experiment(s) as well as analyzing their results and then theory-experiment using data analytics for drawing conclusions. The most important challenge is to improve the design of experiments at the facility and individual levels in order to speed up the discovery of knowledge from science reduce redundancy and extract the maximum amount of physics knowledge of each experiment.

Because of the difficulty and expense of research conducted at SUFs and the difficulty in re-creating all aspects of the facility and experiment the long-term trials and errors to create optimal experiments are not always feasible. This could significantly limit the range of experiments that can be conducted. Additionally, the complete understanding of the probe (e.g. on the beamline) could be used for the postexperiment analysis of data, but this is seldom performed due to the lack of availability or the intricacy of measurements as well as incompatibility with the experiments. For instance the wavefronts of x-rays generated by an XFEL could be useful to users, however, the measurement is not available to the experiment on that same wavefront. So, a mix of virtual diagnostics and simulations is essential. Israel  email Profile

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Examples of optimization and planning challenges in modern SUFs are determining the best conditions for synthesis of a new material; choosing the appropriate combination of multimodal tests to tackle a structural inversion issue optimising the settings of particular instruments to meet objectives in terms of computational and

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experimental and creating accurate continuous calibrated models of accelerators to aid in study and analysis. Recently, the application of AI/ML methods has proven potential in cases that require path planning and optimization in the face of uncertainties [82]. In the same way the design and optimization of experiments should be conducted in a controlled environment that allows exploring the parameters in silico because only a tiny number of experiments are carried out in real labs and the time required for experiments is expensive. Israel  email

To achieve this goal is the requirement for the creation of a digital replica of every SUF that lets users develop, run and optimize their experiments in an uninvolved, safe environment controlled by AI/ML, so that they can seamlessly switch to the actual facility, which will speed up the time to discovery in science [83]. Virtual laboratory environment (figure 4) must be tightly coupled to the laboratory facilities to adjust their simulations to reflect reality (e.g. running online experiments that simulate what is happening at SUFs). In addition, these virtual labs require high-fidelity and a mixture of precise and speedy simulations designed to ensure a high-quality reproduction of the fundamental physics involved in the lab measurement or synthesis. Israel  email id list

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Figure 4. Virtual laboratories allow for the optimization of experiments and accelerate training. They also provide beginning points, and allow for automated creation of analysis codes and workflows to conduct scientific experiments from beginning to end from the initial idea to execution. | Image courtesy Rama Vasudevan, Oak Ridge National

Laboratory

Research Directions

The main goal of research is to develop physically exact, virtual laboratory environments of facilities for experiments which guide the design process to synthesis or characterization in silica, tightly linked to the real facilities, and constantly refreshed based upon real-world experiences to ensure accurate reproduction. This will facilitate AI/ML-assisted and automated design of optimal strategies for experiments and analysis workflows to aid in knowledge acquisition. buy Israel email online

Virtual laboratory environments for virtual laboratories must include:

* Rapid simulations

Rapid on-the fly methods (including models that simulate surrogate) within the virtual world to simulate the results

Acceleration of simulations using hardware techniques (e.g., FPGA, GPUs) and higher-quality numerical approximators like DNNs

* Accurate simulations, theory-experiment-matching

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– The First Principles Model (e.g. of predictions derived from heterostructures)

calibration of models in physics with observations in a continuous manner and the proper theory-experiment matching routines

* User interfaces Israel  email leads

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Interactive, immersive 360deg environments that allow users to create and run virtual tests, analyse data, and revise the scientific hypothesis

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Once constructed digital twins, they would later be able to: Israel  email

* Design and planning experiments

AI/ML enabled context-specific experiments design, as well as AI/ML-generated analysis workflows

AI/ML-guided plan-making using such techniques as reinforcement learning [84 as well as genetic algorithms, to find the most effective sequence of measurements needed to answer a scientific inquiry

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* Facility optimization

• Expedited accelerator design and precise control of accelerator

Statistics on the most commonly used patterns for instruments and opportunities to optimize (e.g. co-location of several instruments

Instruments and staffing)

The digital twins will broaden the range of possibilities for experiments, since advanced planning could allow the completion of larger-scale projects.

One illustration of the anticipated benefits of digital twins and the difficulties involved stems from the modern accelerators. The creation of a high-fidelity digital twin requires a precise model that will be able to predict accelerator’s performance and particle beam’s characteristics. This model of the accelerator is essential to the design analysis, interpretation, and analysis of user-created experiments and the continual advancement of the machine because the model can be utilized in accelerator tuning as well as control and upgrade research. Israel Email Lists

Virtual laboratories can

Additionally, they assist with the process of onboarding users and training to make facility operations more efficient. They also assist in the planning and design of new and existing facilities.

A accelerator is designed using a design model which is

The simulation model is based on the physics process which are involved. The design model forms the base for the operation of the machine such as setting the working parameters for accelerator parts. The actual device frequently diverges from the model. Due to the different characteristics between the design model and the actual machine it is common for accelerators to not meet the performance desired with the minimum effort to alter and control parameter. buy Israel email online

The calibration of a physics model using measurements could help bridge the gap between the model machine. It could allow for the detection and the correction of mistakes in the machine , as well as the precise predictions of the machine’s performance. The current method of calibration for models is usually based on minimising models’ predictions and measurements using least-square fitting. This is only applicable to a few subsystems that have high-quality measurable signals like the storage ring or linear optics of linac [85-88] that may be susceptible to significant over- or under-fitting [89and over-fitting [89]. Innovative AI/ML algorithms like Bayesian Inference Techniques [90] may provide precise and thorough model calibration, covering greater and more extensive than traditional methods. Some examples include calibration for storage rings nonlinear beam dynamics, or models from start-to-end of XFELs. AI/ML can also be used to predict accelerator

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components, especially when it comes to forecasting abnormalities or the likelihood of failure. Predictive models can be used to plan for preemptive maintenance to avoid scheduled downtime. These models also allow for rapid identification of cause of failures, speeding the recovery process and decreasing the likelihood of recurrence of the fault. Rapid tuning and prediction of faults both require rapid processing of modeling and control algorithms, which are AI/ML-accelerated. Israel Email Lists

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It is important to note that physics-based modeling for a complicated system might require a large amount of computer simulation. The complexity of accelerators as well as experimental system, along with the accuracy needed for simulations, require expensive computing resources. This constraint is a hindrance to software that need frequent and speedy model evaluations. For instance, studies on the LCLS-II could benefit from the knowledge of the photon beam’s characteristics that can be predicted using this model but by long hours of computer-generated simulation and therefore, the knowledge gained could not be accessible in real-time. AI/ML could enable modeling that is thousands of times more efficient than physics-based modeling , by using flexible neural networks as well as different models trained using experiments or simulation data to substitute for first-principles simulations. Surrogate models are constantly refined and updated to provide high-quality predictions of machine performance , with highly quick predictions. Israel  email leads

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Another potential benefit that digital twins could provide is that they can speed up the time needed to create chemical and materials with desired characteristics. If a desired structure is predicted using the first principles model, a series syntheses can be performed in a virtual setting and a portion of the real-world experiments used to calibrate and ground the models used in synthesis. In the end, the most efficient characterization techniques can be identified in the virtual twin to establish whether the structure that is of interest was created; in the ideal scenario the analysis algorithms could be generated by the digital twin in order to decrease the amount of time. This is an especially vital aspect of facility operation along with research and development that allows both to be improved simultaneously. Israel  email

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For first-principles modelsthat require fast approximates for the materials’ interaction potentials utilized in a range of simulation codebases could allow for a significant increase in the size of simulations in addition to a more efficient integration with the real-time platforms for experimental research (PRO 2.) . One of the biggest difficulties in performing molecular simulations is sampling complex phase space. This makes many processes beyond the capabilities of the present computers, but also the ones planned for coming years. Recent advancements have been made in the sampling process using ML [92for example]. For instance, Boltzmann generators are an algorithm in ML that determines the invertible transformation of the Boltzmann distribution and the Gaussian distribution. In terms of concept, this research demonstrates an avenue to address one of the biggest obstacles in the use of molecular simulations to understand the material’s behavior based on the molecular components. This research should be an integral part of the capability development for the SUF community of users since they appear to represent an important paradigm shift. In addition, improvements for other areas of molecular simulation are required. For instance, nonequilibrium dynamics are not yet handled through Boltzmann generators. Israel  email providers

To meet the diverse nature of SUFs there are a variety of models must be evaluated and implemented to create an electronic twin. AI/ML models are ideally able to detect significant physical parameters, and ensure that they can be changed without retraining the entire system. This could allow for the co-design method, in which the parameters of the physics model are determined and refined in conjunction with data collection. It is also exciting to see the creation of models using AI/ML that can be predictive for a variety of similar but distinct physical issues. Convolutional neural network (CNNs) are a combination of the computational capabilities of networks that have nodes that carry out local convolutions on datasets. The convolution hierarchy is a natural way to aggregate elements and thus can be utilized to describe complex physical phenomena. For instance, the assemblage of colloids, nanoparticles block co-polymers, proteins and liquid crystals could be represented by a generalized CNN model,

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which is built on the fundamental physical physics of anisotropically interacted components, with every particular system represented by slightly different weights for the network. The ability to map known physical parameters to CNN weights would provide benefit, and result in an easily interpretable ML model from which the meaning of the weights retrained can be deduced. Additionally, what’s the most requested by researchers in science are AI/ML models that provide meaningful physical insights. In this regard, research in an interpretable AI/ML that can be applied to specific scientific issues can be very beneficial.
To attain the degree of precision and speed facility modeling that is required in the new digital twin paradigm, the development and enhancement of capabilities is required to meet the requirements of: Israel Email Lists

• Adoption of a comprehensive data management system that offers the facility with all of its status information from monitoring through diagnostics readbacks. This system will provide the facility’s operation data in a uniform, easily accessible format to aid in the use of ML techniques for creating digital twins. The record of data across the facility must be synced.

* Development of AI/ML algorithms that train facility-scale models on heterogeneous inputs from various sources and formats and are able to apply physical-principle restrictions on model AI/ML. Israel  email providers

* Design of facilities control systems that are able to accommodate AI/ML flow demands (e.g. permitting local GPU integration, or the remote access of low latency GPU accessibility).

* The development of AI/ML techniques to accurately assess the uncertainties of AI/ML models on the scale of a vast scale and with various input and output types to guarantee that the digital twin’s accuracy. Israel  email leads

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AI/ML technology advances

AI/ML developments that are needed to make the virtual lab environment include:

* Rapid in-inverse structure prediction based on scans or spectral measurements, including uncertainty quantification.

* AI/ML-assisted speedups to dynamical simulations that are optimized to work with specific devices. Israel  email

* RL , and Bayesian learning algorithms to facilitate efficient exploration of multidimensional parameter spaces with uncertainty.

* Learning by feature with realistic experimental constraints for theory-experiment match.

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Potential Impact

Digital twins of SUFs could provide new ways of thinking in experiments in research in science. Potential impacts include:

* The order of magnitude is reduced in the time between theory and real-world application of a new material phenomenon (e.g. of a novel electrical topological order to the”synthesis “recipe” to make the material). Israel  email providers

* The best experimental design for specific mechanistic problems such as the mechanism for long lifetimes of semiconductors’ carriers for photovoltaics, or high electromechanical responses of ferroelectric relaxors. Israel Email Lists

* Speedy accelerator design cycles and thorough analysis of the parameter space can maximize the performance of your facility.

* Non-invasive virtual diagnostics that give real-time information that facilitates automated user experiments and accelerator operation.

* Enablement of tests that were previously impossible due to the perceived risk of the absence of routines for analysis or the complexity of the procedures.
While the latest scientific research and operational information are shared among the various SUFs, the majority of data analytics infrastructure, workflows, and infrastructure are splintered. Operating in isolation and a absence of tools for analyzing and searching data sets can lead to repetitive research, unneeded experiments as well as missed chances to use the wealth of data that facilities collect. The rapid improvement of data sharing analysis, curation, and processing will accelerate research across different facilities, creating innovative tools for multimodal, research that involves multiple users and establishing an experiment platform to test an AI/ML next-generation applications for both the BES as well as SUFs communities [93].

This article outlines the potential for establishing an open data repository for facilities to store the outputs from the BES SUFs. To make sharing of data easier the repository needs infrastructure that can accommodate the entire lifecycle of data AI/ML tools for the automatic recording and structuring metadata and annotated, curated high-quality datasets that will aid future applications; tools that create, organize, and analyse both data and metadata; and lastly benchmark data sets to aid in the development of new AI/ML models as well as advance study across SUFs. Israel Email Lists

The development of a searchable, common repository for scientific data can speed up experiment design, and allow hypothesis-making and comparisons of observations. The integration of diverse data sources from science will allow for the automatic creation of benchmark datasets that are based on heterogeneous data from experiments and simulations These training sets can help speed the development of AI/ML algorithms discussed in this report as well as aid in the advancement of AI/ML capabilities in science throughout all of the DOE complex. The result of the repository could be scientific domain-specific schemas as well as abstractions. This will broaden search beyond basic metadata exploration to research that is based on scientific concepts like crack development in composite materials or the transition of a phase in simulations. This could lead to coordinated efforts towards creating standards, formats and priority across SUFs. Israel address lists
In 2025 in 2025, by 2025, BES SUFs are expected to produce thousands of petabytes of data each year. While user groups of their own can collect research out of their data sources, the scientific community has not had an opportunity to harness the full range of data gathered to enhance the SUFs and increase discovery. This PRO outlines the concept of a shared data repository that covers facilities as well as scientific domains. The repository should have infrastructure throughout the lifecycle of data and would have critical capabilities for the acquisition of data and metadata and curation of datasets with high value search; and multimodal multiexperiment analysis. AI/ML could be used to enhance this process by utilizing autonomous curation of data to collect the context, provenance, and quality of data, and tools that facilitate large-scale, multimodal searching and analysis. The objective is to coordinate the continuous curation,

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creation and application of massive amounts of knowledge and data and related models, workflows computations, experiments, and workflows. Then, the byproducts are reviewed and discussed, such as the development of benchmark datasets and coordination efforts focused on emerging scientific themes. The vast majority of topics within PRO 4 are discussed in greater detail in ASCR Israel  email

Computing infrastructures: Real-time control with material modeling demands fast and flexible access to databases that contain previously computed results, as being able to trigger computations based on model results. This will require the creation of a new computing infrastructure capable of handling the demanding and unpredictable load that is expected to result from an experimental process that is dynamic. Ideal solutions must integrate edge computing, elastic access to central HPC resources, as well as the integration of cloud computing. Additionally, new access methods that connect to DOE compute infrastructure to enable on-demand HPC must be explored. Israel business email

Edge computing: Ultra-fast processing of huge and complex models will require processing at the edge, using specific equipment (including graphic processing units (GPUs) as well as FPGAs, field-programmable gates(FPGAs and graphics processing units) as needed.

Practices for data: The integration of theory, experimentation and simulation with AI/ML will require major changes within the scientific community with regard to the use of data. Members of the community will have to

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spread data out more widely, but be mindful of incentives and credits and must define the standards of curation and annotation for data and aggregate. Combining the results of experiments and theory will require planning in relation to the consistency of tagging, nomenclature and formats for data representation, such that the results of different models can be easily compared and seamlessly integrated into the experiment.  email marketing email Israel

* Workflow infrastructure Infrastructure development requires to integrate existing materials as well as chemical databases into workflows that are autonomous. Flexible, simple standards need to be negotiated so that databases created by industrial partners and collaborators can easily be adapted for online environments of control. Autonomous experimental control should make use of the many probes and imaging techniques available in the DOE complex (e.g. the x-ray neutron, electron, optical as well as scanners). The development of multimodal science requires collaboration between user facilities, which will further enhance the requirements that were discussed previously in connection with sharing and curation of data.

Smart, autonomous control attempts to automatize a complicated control loop that requires the an integration of better information collection, data analysis systems modeling, as well as decision-making. This area of research needs to be accompanied by improvements in other PROs.

1. The most advanced analysis and collection strategies are required to gather and process data, providing the right insights to drive online control.

The decision-making algorithm must be pre-trained using artificial data generated by conducting virtual experiments, and continuously upgraded based on the most advanced physical models. Israel business email

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4. The sets of training needed for AI/ML algorithms should include a shared infrastructure for data. Israel mailing lists

The most critical advances that are required are the AI/ML methods developments that have been identified that will allow for an unprecedented level of computational effectiveness as well as complex (see the section about Enabling Capabilities within Computer Sciences and Mathematics)

* Search/optimization: New developments in search/optimization and data mining techniques are needed to manage the large, high-dimensional, and complex spaces that are inherent to scientific issues.

The advanced method of detection of correlation could allow failure prediction in accelerators as well as self-calibration tools for experiments. The identification of correlations between data could also enable new measurement multimodal methods.

* Quantification of uncertainty Online control algorithms that properly include cost and uncertainty from experiments are needed. The range of applications calls for a variety of strategies that include Bayesian strategies, techniques for learning by repetition as well as active learning.

* Approximations: Fast approximations in both the analysis of data as well as material or system modeling are essential for the autonomous experimental loop to operate in real-time.

* Physics using AI/ML: Equation-learning strategies can be used to aid the creation of theory in physics as well as chemistrysince they allow the direct calculation of physical equations based on data [61-62(61-62). From a theoretical point of view the numerical solutions that are purely mathematical can be beneficial, but they restrict further development achieved using analytic solutions. Although ML tends to create numerical solutions, advancements are being made in learning equations. The process of obtaining equations from data yields a more straightforward and easily interpretable result that is quickly converted into different types and an easier formulation of the results.

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Potential Impact

Intelligent automation is a great way to transform science, permitting scientists to tackle greater problems and also freeing scientists to consider the science at a deeper level. However, it is becoming increasingly apparent that the current method does not fully exploit the capabilities of the latest scientific instruments. The explosive growth in the brightness of synchrotrons [63as well as similar trends for other advanced experimental tools (e.g. the latest electron microscopes which can attain massive frame rates of up to 100 000 images per second) might not be fully utilized because of the current limitations of analysis pipelines. Automating workflows for experimental work allows researchers to make the most from the potential of current instruments, and also allow them to tackle issues that were previously thought to be too complex. Figure 3 illustrates the increase of synchrotron publication output as well as increased brightness as time passes.

Figure 3. Synchrotron’s light source brightness has increased exponentially over the course of time (left) and has even surpassed the rapid scaling observed in Microelectronics (Moore’s law). The output of a publication (right) comes

Synchrotrons also have increased, although they are not as significant as the properties of the source. This suggests that the existing light sources are not utilizing their full potential (i.e. the an efficient utilization of resources already in use could result in dramatic increases in the efficiency of scientific research). Left image reprinted using permissions from J. Stohr and H. C. Siegmann, Magnetism: From Fundamentals to Nanoscale Dynamics (Springer, 2006). | Right

Image courtesy of Apurva Mehta SLAC National Accelerator Laboratory

The latest accelerator features are typically linked to more complex installation and operation. For instance storage rings that have high brightness typically features a tiny safe operating space, also known by the term dynamic aperture. This aperture can be particularly narrow in the commissioning phase, as many mistakes haven’t been rectified. The performance of a possible storage ring design could be limited due to the necessity to reserve an overhead of a dynamic aperture that could be reduced through advanced tuning techniques. In addition, the rapid implementation of difficult XFEL operating modes will permit different kinds of scientific experiments through the delivery of novel designs of beams for users. The advancement of self-contained accelerators will transform the development and operation of the next accelerators, as well as the operation of large SUFs as a whole the control of machines is largely automated, the tuning of accelerators will be performed through efficient computers that are consistent The central control program will be aware of the state of the accelerator’s subsystems and components and will be able to take adjustments and maintenance decisions. The ability to guarantee the performance of the design by using advanced techniques for tuning will have a significant impact on the design of accelerators. AI/ML technologies are able to provide unimaginable capabilities and accessibility for future accelerators.
Advanced autonomous experimentation has the potential for revolutionizing chemistry, materials and bioscience research through the discovery of the most exotic and high-performance materials. Israel  email Profile

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In the midst of complex. It is hard to quantify the potential impact, and the scope of research which will yield. There is a significant potential impact on problems that are currently impeded by the complexity of material composition such as blends and formulations biomaterials and biomimetic system and alloys. Certain kinds of metallic glass may offer the potential to produce extremely high strength-to-weight ratios [64]. A perfect “steel in the near future” material that will provide transformational improvements in applications that require it (e.g. aerospace) is currently hidden within the vast array of alloys that could be imagined and enhanced by the sheer size of the processing area that one has to consider in order to make and quash the metastable states that are glassy. In general research into pathways-dependent phenomena could be transformed through autonomous exploration. Self-assembling materials have a range of non-equilibrium state that are only accessible with the correct processing history [65,66]. In a few instances the researchers are able use “pathway engineering” where a goal that is not achievable using equilibrium processing techniques is chosen and enforced following the proper order [67]. Synthetic platforms that are controlled online could expand on these initial breakthroughs, allowing Israel  lists researchers navigate the complex assemblies and navigate the entire range of complex self-assembling materialssuch as block copolymers (68-69) Liquid crystals [70supramolecular structure [71nanoparticle superlattices [72-75] and DNA into crucial structural patterns. The study of a variety of functional materials can be significantly enhanced by close connections with the right material modeling. For example, design of advanced thermoelectrics would benefit from experimental searches with coupling of structural/spectroscopic probes, operando functional measurements, and structure-property modeling. Similar to studies on quantum heterostructures have already benefited greatly from precise physical simulations. The integration of these models into the measuring loop could enhance the search for new materials that are geared toward quantum applications of information science.

An expanded research program in autonomous experiments could be expected to have immediate and long-term benefits. In the short term (3-5 years) dedicated research will result in a collection of highly specialized tools, such as AI/ML algorithms, models as well as hardware systems that allow autonomous exploration of sample. In the longer term (10 years) it will be possible to develop robust, generalized autonomous synthesis platformsthat will be able to tackle a variety of chemical, material and bioscience challenges while also revealing the latest physical concepts. In the end, the aim of autonomous research is to free scientists from the responsibility of micromanaging the process of conducting experiments, which includes optimizing the experimental conditions, which allows scientists to solve scientific issues at a higher degree.

A lot of the tools for experimentation developed in the DOE complex can benefit from the most advanced AI/ML control techniques. The AI/ML techniques proposed will enhance efficiency and stability, enhancing users of all experiments with increased availability and reliability, and improving the quality of the research that is carried out, which will benefit the most innovative and cutting-edge research programs. As these advanced experimental tools underlie a wide variety of modern scientific studies–from geosciences chemistry to biosciences to energy research–improvements would have broad benefits throughout the BES research program.

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“Steel for the future”

The most amazing new materials can be discovered. Where can we look for them?

Conventional alloys are made by mixing together a tiny amount of different metals. The idea is that they are just a small portion of the possible range of alloys. High-entropy alloys have more elements than traditional alloys, vastly expanding the parameter range of compositions that are possible. These alloys are likely to have records-setting physical properties (e.g. strength-to-weight ratio) particularly if they are in metastable and frustrated states like those that are found in metallic glass can be discovered. But the vastness of these parameters cannot be explored with conventional techniques, or even high-throughput searches, as high-performance materials constitute an isolated island within a vast ocean of non-interesting materials. Autonomous experimental models, that draw the inputs from accelerated modeling, can effectively search for these parameters, identifying fascinating outliers, and then guiding future research in a meaningful direction. If properly implemented, these methods could lead to the high-performance metals that are to come, which will provide significant applications in transportation, aerospace, as well as energy harvesting. Left image courtesy K. G. Yager, Brookhaven National Laboratory. Right image distributed by Brookhaven National Laboratory under a Creative Commons Attribution Noncommercial License Israel  email Profile

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The structure of the Intrinsically Disordered Proteins

The structural description
of biosystems that are flexible pose of biosystems that are flexible pose
major challenge in biology
due to the the protein’s intrinsic nature. Israel  lists
disorder. It is crucial to achieve
structural information for
understand protein function.
To assist in decoding the
Complexity of disordered
biomolecule, a combination
of neutron scattering as well as
molecular technology with high-performance
Simulations can be utilized to
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of 3D structures
biomolecule adopts)[79].
However, this combination is Small-angle neutron scattering as well as Hamiltonian replica exchange
currently , it could take weeks to
Incorporating the correct molecular dynamics simulation that can produce the
details for an individual configurational ensemble of the flexible protein.

biomolecule. AI/ML methods could be employed to discover how to optimally combine neutron scattering data high-performance molecular simulations that run in real-time. This will allow AI/ML-driven directing of simulations towards experimental results in neutron scattering, which could significantly reduce the time required to solve. A significant increase in the capacity to understand the structure of a system could be a huge influence on the structure biology of biosystems with flexible structures. Similar challenges are possible in electron and x-ray microscopy. as current approaches attempt to are able to reconstruct the typical structure, innovative methods in AI/ML are beginning to uncover conformational modifications [80-81].

Top left image reprinted from https://www.energy.gov/ne/articles/7-fast-facts-about-high -flux-isotope-reactor-oak-ridge-national-laboratory. Courtesy of Oak Ridge National Laboratory. | Bottom left image reprinted from https://www.ornl.gov/news/supercomputing-neutrons-unite-unravel-structures-intrinsically-disordered-protein. Right image Reprinted by Shrestha, U. R.; Juneja, P.; Zhang, Q.; Gurumoorthy, V.; Borreguero, J. M.; Urban, V.; Cheng, X.; Pingali, S. V.; Smith, J. C.; O’Neill, H. M.; and Petridis, L. “Generation of the configurational ensemble for an Intrinsically Disordered Protein Using Unbiased Dynamics Simulation.” Dynamics Simulation.” Proc. Natl. Acad. Sci. U.S.A. 116 (2016): 20446-20452. doi: 10.1073/pnas.1907251116.

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PRO 3. Facilitate offline design and optimization of facilities and Experiments

Key question: How do we enable virtual laboratories–offline design and optimization of facility operation and experiments–to achieve new scientific goals?

Introduction

The main challenge in SUFs is the creation and optimization of experiments and facilities in order to reach scientific goals. On the other hand Modern SUFs are home to expensive and complicated accelerators which can be difficult to construct, design and maintain. They are also time-consuming and require meticulously planned sequences of actions, such as formulating the hypothesis, conducting the experiment(s) as well as analyzing their results and then theory-experiment using data analytics for drawing conclusions. The most important challenge is to improve the design of experiments at the facility and individual levels in order to speed up the discovery of knowledge from science reduce redundancy and extract the maximum amount of physics knowledge of each experiment.

Because of the difficulty and expense of research conducted at SUFs and the difficulty in re-creating all aspects of the facility and experiment the long-term trials and errors to create optimal experiments are not always feasible. This could significantly limit the range of experiments that can be conducted. Additionally, the complete understanding of the probe (e.g. on the beamline) could be used for the postexperiment analysis of data, but this is seldom performed due to the lack of availability or the intricacy of measurements as well as incompatibility with the experiments. For instance the wavefronts of x-rays generated by an XFEL could be useful to users, however, the measurement is not available to the experiment on that same wavefront. So, a mix of virtual diagnostics and simulations is essential. Israel  email Profile

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Examples of optimization and planning challenges in modern SUFs are determining the best conditions for synthesis of a new material; choosing the appropriate combination of multimodal tests to tackle a structural inversion issue optimising the settings of particular instruments to meet objectives in terms of computational and experimental and creating accurate continuous calibrated models of accelerators to aid in study and analysis. Recently, the application of AI/ML methods has proven potential in cases that require path planning and optimization in the face of uncertainties [82]. In the same way the design and optimization of experiments should be conducted in a controlled environment that allows exploring the parameters in silico because only a tiny number of experiments are carried out in real labs and the time required for experiments is expensive. Israel  email

To achieve this goal is the requirement for the creation of a digital replica of every SUF that lets users develop, run and optimize their experiments in an uninvolved, safe environment controlled by AI/ML, so that they can seamlessly switch to the actual facility, which will speed up the time to discovery in science [83]. Virtual laboratory environment (figure 4) must be tightly coupled to the laboratory facilities to adjust their simulations to reflect reality (e.g. running online experiments that simulate what is happening at SUFs). In addition, these virtual labs require high-fidelity and a mixture of precise and speedy simulations designed to ensure a high-quality reproduction of the fundamental physics involved in the lab measurement or synthesis.

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Figure 4. Virtual laboratories allow for the optimization of experiments and accelerate training. They also provide beginning points, and allow for automated creation of analysis codes and workflows to conduct scientific experiments from beginning to end from the initial idea to execution. | Image courtesy Rama Vasudevan, Oak Ridge National

Laboratory

Research Directions

The main goal of research is to develop physically exact, virtual laboratory environments of facilities for experiments which guide the design process to synthesis or characterization in silica, tightly linked to the real facilities, and constantly refreshed based upon real-world experiences to ensure accurate reproduction. This will facilitate AI/ML-assisted and automated design of optimal strategies for experiments and analysis workflows to aid in knowledge acquisition.

Virtual laboratory environments for virtual laboratories must include:

* Rapid simulations

Rapid on-the fly methods (including models that simulate surrogate) within the virtual world to simulate the results

Acceleration of simulations using hardware techniques (e.g., FPGA, GPUs) and higher-quality numerical approximators like DNNs

* Accurate simulations, theory-experiment-matching

– The First Principles Model (e.g. of predictions derived from heterostructures)

calibration of models in physics with observations in a continuous manner and the proper theory-experiment matching routines

* User interfaces Israel  email leads

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Interactive, immersive 360deg environments that allow users to create and run virtual tests, analyse data, and revise the scientific hypothesis

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Once constructed digital twins, they would later be able to: Israel  email

* Design and planning experiments

AI/ML enabled context-specific experiments design, as well as AI/ML-generated analysis workflows

AI/ML-guided plan-making using such techniques as reinforcement learning [84 as well as genetic algorithms, to find the most effective sequence of measurements needed to answer a scientific inquiry

Virtual diagnostics offer real-time data for accelerator operation as well as the analysis of data from user experiments

* Facility optimization

• Expedited accelerator design and precise control of accelerator

Statistics on the most commonly used patterns for instruments and opportunities to optimize (e.g. co-location of several instruments

Instruments and staffing)

The digital twins will broaden the range of possibilities for experiments, since advanced planning could allow the completion of larger-scale projects.

One illustration of the anticipated benefits of digital twins and the difficulties involved stems from the modern accelerators. The creation of a high-fidelity digital twin requires a precise model that will be able to predict accelerator’s performance and particle beam’s characteristics. This model of the accelerator is essential to the design analysis, interpretation, and analysis of user-created experiments and the continual advancement of the machine because the model can be utilized in accelerator tuning as well as control and upgrade research.

Virtual laboratories can

Additionally, they assist with the process of onboarding users and training to make facility operations more efficient. They also assist in the planning and design of new and existing facilities.

A accelerator is designed using a design model which is

The simulation model is based on the physics process which are involved. The design model forms the base for the operation of the machine such as setting the working parameters for accelerator parts. The actual device frequently diverges from the model. Due to the different characteristics between the design model and the actual machine it is common for accelerators to not meet the performance desired with the minimum effort to alter and control parameter.

The calibration of a physics model using measurements could help bridge the gap between the model machine. It could allow for the detection and the correction of mistakes in the machine , as well as the precise predictions of the machine’s performance. The current method of calibration for models is usually based on minimising models’ predictions and measurements using least-square fitting. This is only applicable to a few subsystems that have high-quality measurable signals like the storage ring or linear optics of linac [85-88] that may be susceptible to significant over- or under-fitting [89and over-fitting [89]. Innovative AI/ML algorithms like Bayesian Inference Techniques [90] may provide precise and thorough model calibration, covering greater and more extensive than traditional methods. Some examples include calibration for storage rings nonlinear beam dynamics, or models from start-to-end of XFELs. AI/ML can also be used to predict accelerator components, especially when it comes to forecasting abnormalities or the likelihood of failure. Predictive models can be used to plan for preemptive maintenance to avoid scheduled downtime. These models also allow for rapid identification of cause of failures, speeding the recovery process and decreasing the likelihood of recurrence of the fault. Rapid tuning and prediction of faults both require rapid processing of modeling and control algorithms, which are AI/ML-accelerated.

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It is important to note that physics-based modeling for a complicated system might require a large amount of computer simulation. The complexity of accelerators as well as experimental system, along with the accuracy needed for simulations, require expensive computing resources. This constraint is a hindrance to software that need frequent and speedy model evaluations. For instance, studies on the LCLS-II could benefit from the knowledge of the photon beam’s characteristics that can be predicted using this model but by long hours of computer-generated simulation and therefore, the knowledge gained could not be accessible in real-time. AI/ML could enable modeling that is thousands of times more efficient than physics-based modeling , by using flexible neural networks as well as different models trained using experiments or simulation data to substitute for first-principles simulations. Surrogate models are constantly refined and updated to provide high-quality predictions of machine performance , with highly quick predictions. Israel  email leads

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Another potential benefit that digital twins could provide is that they can speed up the time needed to create chemical and materials with desired characteristics. If a desired structure is predicted using the first principles model, a series syntheses can be performed in a virtual setting and a portion of the real-world experiments used to calibrate and ground the models used in synthesis. In the end, the most efficient characterization techniques can be identified in the virtual twin to establish whether the structure that is of interest was created; in the ideal scenario the analysis algorithms could be generated by the digital twin in order to decrease the amount of time. This is an especially vital aspect of facility operation along with research and development that allows both to be improved simultaneously. Israel  email

For first-principles modelsthat require fast approximates for the materials’ interaction potentials utilized in a range of simulation codebases could allow for a significant increase in the size of simulations in addition to a more efficient integration with the real-time platforms for experimental research (PRO 2.) . One of the biggest difficulties in performing molecular simulations is sampling complex phase space. This makes many processes beyond the capabilities of the present computers, but also the ones planned for coming years. Recent advancements have been made in the sampling process using ML [92for example]. For instance, Boltzmann generators are an algorithm in ML that determines the invertible transformation of the Boltzmann distribution and the Gaussian distribution. In terms of concept, this research demonstrates an avenue to address one of the biggest obstacles in the use of molecular simulations to understand the material’s behavior based on the molecular components. This research should be an integral part of the capability development for the SUF community of users since they appear to represent an important paradigm shift. In addition, improvements for other areas of molecular simulation are required. For instance, nonequilibrium dynamics are not yet handled through Boltzmann generators.

To meet the diverse nature of SUFs there are a variety of models must be evaluated and implemented to create an electronic twin. AI/ML models are ideally able to detect significant physical parameters, and ensure that they can be changed without retraining the entire system. This could allow for the co-design method, in which the parameters of the physics model are determined and refined in conjunction with data collection. It is also exciting to see the creation of models using AI/ML that can be predictive for a variety of similar but distinct physical issues. Convolutional neural network (CNNs) are a combination of the computational capabilities of networks that have nodes that carry out local convolutions on datasets. The convolution hierarchy is a natural way to aggregate elements and thus can be utilized to describe complex physical phenomena. For instance, the assemblage of colloids, nanoparticles block co-polymers, proteins and liquid crystals could be represented by a generalized CNN model, which is built on the fundamental physical physics of anisotropically interacted components, with every particular system represented by slightly different weights for the network. The ability to map known physical parameters to CNN weights would provide benefit, and result in an easily interpretable ML model from which the meaning of the weights retrained can be deduced. Additionally, what’s the most requested by researchers in science are AI/ML models that provide meaningful physical insights. In this regard, research in an interpretable AI/ML that can be applied to specific scientific issues can be very beneficial.
To attain the degree of precision and speed facility modeling that is required in the new digital twin paradigm, the development and enhancement of capabilities is required to meet the requirements of:

• Adoption of a comprehensive data management system that offers the facility with all of its status information from monitoring through diagnostics readbacks. This system will provide the facility’s operation data in a uniform, easily accessible format to aid in the use of ML techniques for creating digital twins. The record of data across the facility must be synced.

* Development of AI/ML algorithms that train facility-scale models on heterogeneous inputs from various sources and formats and are able to apply physical-principle restrictions on model AI/ML.

* Design of facilities control systems that are able to accommodate AI/ML flow demands (e.g. permitting local GPU integration, or the remote access of low latency GPU accessibility).

* The development of AI/ML techniques to accurately assess the uncertainties of AI/ML models on the scale of a vast scale and with various input and output types to guarantee that the digital twin’s accuracy. Israel  email leads

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AI/ML technology advances

AI/ML developments that are needed to make the virtual lab environment include:

* Rapid in-inverse structure prediction based on scans or spectral measurements, including uncertainty quantification.

* AI/ML-assisted speedups to dynamical simulations that are optimized to work with specific devices. Israel  email

* RL , and Bayesian learning algorithms to facilitate efficient exploration of multidimensional parameter spaces with uncertainty.

* Learning by feature with realistic experimental constraints for theory-experiment match.

Potential Impact

Digital twins of SUFs could provide new ways of thinking in experiments in research in science. Potential impacts include:

* The order of magnitude is reduced in the time between theory and real-world application of a new material phenomenon (e.g. of a novel electrical topological order to the”synthesis “recipe” to make the material).

* The best experimental design for specific mechanistic problems such as the mechanism for long lifetimes of semiconductors’ carriers for photovoltaics, or high electromechanical responses of ferroelectric relaxors.

* Speedy accelerator design cycles and thorough analysis of the parameter space can maximize the performance of your facility.

* Non-invasive virtual diagnostics that give real-time information that facilitates automated user experiments and accelerator operation.

* Enablement of tests that were previously impossible due to the perceived risk of the absence of routines for analysis or the complexity of the procedures.
While the latest scientific research and operational information are shared among the various SUFs, the majority of data analytics infrastructure, workflows, and infrastructure are splintered. Operating in isolation and a absence of tools for analyzing and searching data sets can lead to repetitive research, unneeded experiments as well as missed chances to use the wealth of data that facilities collect. The rapid improvement of data sharing analysis, curation, and processing will accelerate research across different facilities, creating innovative tools for multimodal, research that involves multiple users and establishing an experiment platform to test an AI/ML next-generation applications for both the BES as well as SUFs communities [93].

This article outlines the potential for establishing an open data repository for facilities to store the outputs from the BES SUFs. To make sharing of data easier the repository needs infrastructure that can accommodate the entire lifecycle of data AI/ML tools for the automatic recording and structuring metadata and annotated, curated high-quality datasets that will aid future applications; tools that create, organize, and analyse both data and metadata; and lastly benchmark data sets to aid in the development of new AI/ML models as well as advance study across SUFs.

The development of a searchable, common repository for scientific data can speed up experiment design, and allow hypothesis-making and comparisons of observations. The integration of diverse data sources from science will allow for the automatic creation of benchmark datasets that are based on heterogeneous data from experiments and simulations These training sets can help speed the development of AI/ML algorithms discussed in this report as well as aid in the advancement of AI/ML capabilities in science throughout all of the DOE complex. The result of the repository could be scientific domain-specific schemas as well as abstractions. This will broaden search beyond basic metadata exploration to research that is based on scientific concepts like crack development in composite materials or the transition of a phase in simulations. This could lead to coordinated efforts towards creating standards, formats and priority across SUFs.
In 2025 in 2025, by 2025, BES SUFs are expected to produce thousands of petabytes of data each year. While user groups of their own can collect research out of their data sources, the scientific community has not had an opportunity to harness the full range of data gathered to enhance the SUFs and increase discovery. This PRO outlines the concept of a shared data repository that covers facilities as well as scientific domains. The repository should have infrastructure throughout the lifecycle of data and would have critical capabilities for the acquisition of data and metadata and curation of datasets with high value search; and multimodal multiexperiment analysis. AI/ML could be used to enhance this process by utilizing autonomous curation of data to collect the context, provenance, and quality of data, and tools that facilitate large-scale, multimodal searching and analysis. The objective is to coordinate the continuous curation, creation and application of massive amounts of knowledge and data and related models, workflows computations, experiments, and workflows. Then, the byproducts are reviewed and discussed, such as the development of benchmark datasets and coordination efforts focused on emerging scientific themes. The vast majority of topics within PRO 4 are discussed in greater detail in ASCR Israel  email