e-SIM Market is set to grow Substantially during the Forecast Timeframe

Embedded subscriber identity module (eSIM) is an embedded chip inside your smartphone which can be rewritten during porting to a different mobile network service provider. eSIMs are currently used as the second SIM in dual SIM handset. The global eSIM market report by Market Research Future (MRFR) covers estimations and projections for the period of 2019 to 2024 (forecast period) while considering drivers, challenges, opportunities, and trends. The COVID-19 outbreak and its implications have been explored and outlined in high detail.

Market Scope

The global eSIM market is expected to expand at 28.0% CAGR during the forecast period to reach a size of USD 913.9 million in 2024.

The market is driven by the expansion of internet of things (IoT), large number of smartphone users, and limitations of physical SIM cards. Developments of smart vehicles, robots, and industrial machines which can operate eSIMs are evidence of its vast potential. The standard set by eSIMs for relaying data in a machine-to-machine (M2M) ecosystem can fuel the market demand over the forecast period.

Rollout of next-generation communication networking technologies, shift of bandwidth as per network, and large number of M2M systems can drive market growth. The large shelf life of eSIMs and applications in smart devices can bolster the demand of the global eSIM market. Collaboration between eSIM manufacturers and smartphone manufacturers mark a new consumer buying pattern for consumer electronic devices. Availability of eSIMs for corporate customers in South Africa due to their frequency in business travel and their success can lead to its offering to civilians in the coming years.

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Segmentation

The global eSIM market has been segmented on the basis of end user.

Based on end user, the eSIM market has been segmented into consumer electronics, automotive, energy & utilities, transportation & logistics, manufacturing, and retail. The consumer electronics segment accounted for the largest market share in 2018. This can be attributed to procurement of laptops, tablets, smartphones, and wearables. On the other hand, the manufacturing segment is expected to register the highest CAGR of 29.0% during the forecast period.

Regional Analysis

Geographically, the global eSIM market has been segmented into Asia Pacific (APAC), North America, Europe, the Middle East & Africa (MEA), and South America.

North America dominated the region in terms of market share in the eSIM market. The market growth is attributed to the presence of many eSIM network service providers that offer network support to eSIM devices. The leading players in the region include Virgin Mobile, Deutsche Telekom AG, Verizon Wireless and AT&T.

Europe was the second-largest market in the eSIM market in 2018. According to the MRFR analysis, Germany is expected to gain the lead in the region followed by the UK, Spain, and the rest of Europe. Some of the factors responsible for the market growth include the presence of a large number of platform vendors who provide the underlying hardware for eSIM integration, presence of 5G network, and relief provided to tourists due to access to various carriers.

APAC may gain a large share of the global eSIM market by 2024 owing to the growing smartphone subscriber base. Japan, China, India, and Indonesia are deemed to be lucrative for the market owing to the influx of various tourists and introduction of policies by their respective governments. Recently, the Japanese government has proposed a new policy for switching between carriers without changing phone numbers. Surge in number of IoT connections and adoption of consumer electronic devices can favor the regional market growth.

Competitive Outlook

Giesecke+Devrient GmbH, NXP Semiconductors, NTT Docomo, Inc., Sierra Wireless, Infineon Technologies AG, STMicroelectronics, Singtel, Deutsche Telekom AG, Gemalto NV, and Telefonica S.A. are key players of the global eSIM market. The drive towards open market devices by carriers and phone manufacturers seems to be the primary strategy of players in the market. Recently, Orange and OPPO have decided to partner for driving the demand of eSIMs in IoT devices and smartphones.

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How to choose a suitable 4G cellular router

4G cellular connections are widely being used by businesses to connect their sites to the internet or to other sites on their Wide Area Network (WAN). Using 4G can be very useful if you need sites connected fast, or in remote places, or perhaps for backup or disaster recovery scenarios. A 4G connection for businesses almost invariably involves the use of a 4G router that contains one or more slots for SIM cards, plus the means to connect cellular aerials and the local area network (LAN) of the site.

There are so many types of 4g routers in market supporting various kinds of features. In order to purchase a suitable 4g router for your application, you should take the time to consider some of the following questions…

1.    What’s The Router Going To Be Used For?

Not all 4G routers are created equal – so depending whether you’re using a router for business or leisure is going to decide the level of capability you require. One of the big differences to consider from the outset is whether you need a device that’s able to use more than one cellular connection to provide an internet connection.

If you’re a business user then the answer here is likely to be a yes – and the feature you’re looking for is referred to as a ‘multi-SIM’ capability.

Performance and reliability is the primary reason multi-SIM is appropriate for businesses, If your end users or customers rely on stable and robust communication, then the cost of a slow or intermittent connection might run to far more than inconvenience.

4G routers that use only 1 SIM are targeted at leisure users or business sites with few users for whom performance is less of an issue.

2.    Be Aware Of The Multi-SIM/SIM Failover Difference

There’s a big distinction between a router that offers multi-SIM capability and one that offers merely a SIM failover service.

If the router you’re looking at has two SIM slots it doesn’t necessarily mean it offers two cellular connections – instead, it might just mean that there’s room for a ‘back up’ sim should the primary cellular connection experience a service issue.

Routers that offer true multi-SIM technology combine 2 or more connections – and in some instances can bond 2 or more SIMs to provide a high capacity connection. If you’re not sure how many SIMs will suffice, consider what’s needed for you network applications to run – and check against connection speed of the SIMs you’re planning to use.

3.    Is SIM Bonding Or Load Balancing Right For Your Business?

When using more than one SIM, depending on the types of application you’re running, you’ll need to decide whether bonding or load balancing your cellular connections is right for you.

If you’re bonding, you’re essentially using the router technology to combine all of your 4G connections into one – whereas with load balancing you’re attributing a single connection to each application or end user. Owing to its stability, many companies favor bonding to increase internet speed – and since it’s unlikely that you’re ever going to be using the full capacity of your connection, any issues with a single connection aren’t noticeable.

4.    Do You Have Priority Applications That Must Run?

A lot of businesses have core applications that have to run for service to be provided. It’s not just dropped connections that cause application issues, you might have applications for which a slowed connection can cause problems. This can especially be the case if you have real-time applications.

If this is the case for you, looking for a router that offers traffic prioritisation at the point of configuration is a good idea. You’ll be able to make sure mission critical applications continue to run, even if others are slowed or halted.

5.    How Important Is Reporting On Data?

Relying on the different carriers to provide accurate information on your data use can sometimes prove taxing – for many this isn’t done as standard, so takes time and effort if you want to get certain figures.

If you’re keen on keeping an eye on data use then finding a router with built-in reporting capabilities can be very helpful. In doing so you can compile crucial information on budgets, application use and much more.

6.    Do You Need To Access Your Network Wirelessly?

There are a variety of reasons that wireless access to your network can be helpful – the physical setting of your network might require it, guest users might not want to (or be able to) plug an RJ45 cable into their device, printers and other network peripherals might be awkwardly located – and so forth.

Not all 4G routers offer a wireless connection – but some do, so if your business could benefit from the flexibility that brings, be sure to check – it’s not always built in.

7.    Will You Be Connecting To Devices That Are Inconvenient To Provide Mains Power To?

4G routers will often be connected to a small switch, a wireless network access point or other low power equipment. When you’re connecting small sites, vehicles and outdoor locations it is sometimes inconvenient to plug all of these into mains power. In these situations, it simplifies the installation if you can power them over an Ethernet cable, using Power Over Ethernet (POE). If you’re in this situation, you might want to consider looking for a router that can provide power to other equipment via Power Over Ethernet.

Not essential – but a nice feature to take advantage of if you’ve got the need.

8.    Do You Have The Budget To Upgrade Again Down The Line?”

4G technology has now been around for quite some time – and while it offers excellent performance against anything that’s gone before there will be a time it gives way to a more sophisticated technology. Some routers that are currently on the market are capable of handling the next generation of connectivity – often referred to as 4G+ or 6LTE.

If budgets are tight and you’d like a router that can keep up with advances in technology, look for something that supports these cutting edge developments – it might cost you a little more in the short term but could save you a costly upgrade should you require faster connectivity in the future.

If your cases or projects are used in M2M&IoT fields, E-Lins Technology’s series 4G M2M routers will be good choice for you, maybe you can take a short view of their products from their website.

“Proximity Magnetism” Could remote communication   Be a Building Block for Quantum Computers

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This diagram shows the layered structure analyzed for its  Grid Analytics System magnetic properties. Yellow spheres represent tellurium atoms; light blue spheres represent antimony-bismuth; and black spheres represent sulfur. The black sphere with an arrow represents an atom of dopant, and green spheres with arrows show atoms of europium. Different colored arrows show various ways an europium ion can be affected by the interface between the materials: within the plane via Heisenberg interaction (orange), between the planes (green) through super-exchange interaction, or spin-polarized states at the topological insulator surface (blue).

Researchers reveal an unusual magnetic behavior that could be used to probe a variety of exotic physical phenomena, and could ultimately be used to produce key components of future quantum computers.

An exotic kind of magnetic behavior, driven by the mere proximity of two materials, has been analyzed by a team of researchers at MIT and elsewhere using a technique called spin-polarized neutron reflectometry.

The novel phenomenon occurs at the boundary between a ferromagnet and a type of material called a topological insulator, which blocks electricity from flowing through all of its bulk but whose surface is, by contrast, a very good electrical conductor. In the new work, a layer of topological insulator material is bonded to a ferromagnetic layer. Where the two materials meet, an effect takes place called proximity-driven magnetic order, producing a localized and controllable magnetic pattern at the interface.

The research is described in a paper appearing this week in the journal Physical Review Letters, written by MIT doctoral student Mingda Li, postdoc Cui-Zu Chang, professor of nuclear science and engineering Ju Li, senior scientist Jagadeesh Moodera, and seven others.

This “proximity magnetism” effect could create an energy gap, a necessary feature for transistors, in a topological insulator, making it possible to turn a device off and on as a potential building block for spintronics, says Mingda Li, the lead author of the paper. “However, the proximity effect is usually weak,” he says, without this team’s use of a magnetic topological insulator “to enhance it and lock new magnetic order near the interface.”

“This could be a building block of quantum computers,” Moodera says. “It also opens up some fundamental new phenomena” for study by physicists.

“The interaction at the interface makes this exotic phenomenon possible,” Chang adds.

O cloud VMS ne of the new findings of this research is that the magnetism induced by the proximity of the two materials is not just at the surface, but actually extends into the interior of the topological insulator material. “We were able to show that the magnetism exists inside the topological insulator,” Moodera says.

Possible applications of the new findings include the creation of spintronics, transistors based on the spin of particles rather than their charge. These are expected to have low energy dissipation if based on topological insulators, and are a very active area of research.

Because the interface produces a channel with virtually no dissipation, it can act as “a perfect quantum wire,” Ju Li says. “It cannot be better than that for a quantum conductance channel. So having this precise control of the magnetic structure could lead to novel quantum spintronics.”

He adds that the findings, in addition to near-term practical applications, “from a physics point of view, opens up a huge area of productive work.” This includes the study of predicted physical phenomena such as Majorana fermions, particles predicted in 1937 but not yet observed, which, unlike all known subatomic particles, serve as their own antiparticles. These theorized particles “have yet to be explored. It opens another avenue to explore these things,” he says.

“The significance of this work is threefold,” says Qi-Kun Xue, a professor of physics at Tsinghua University in China who was not involved in this work. The three areas, he says, are “to demonstrate proximity magnetism, the enhancement of such magnetism … and the tunability of this interfacial m wi fi  agnetic structure.” He adds that the finding is a significant step toward a device application of magnetic topological insulators. “In particular,” he explains, “the consistent results from independent experimental tools” make the results “robust.”

The work included researchers at the National Institute of Standards and Technology, Brookhaven National Laboratory, Northeastern University, and Boston College. It was supported by the National Science Foundation, the Office of Naval Research, and the Department of Energy.

Publication: Mingda Li, et al., “Proximity-Driven Enhanced Magnetic Order at Ferromagnetic-Insulator–Magnetic-Topological-Insulator Interface,” Phys. Rev. Lett., 2105, 115, 087201; doi:10.1103/PhysRevLett.115.087201

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E-SIM Card Market : Emergence of Advanced Technologies and Global Industry Analysis

The global E-SIM card market is rising steadily due to the several advantages of E-SIM card over conventional SIM cards. E-SIM card allows changing mobile network operator at a few clicks, a feature distinct to them. For instance, ability to switch network providers over the air in machine to machine systems such as smart meters and connected cars has substantial advantages in terms of reducing logistics and operational costs.

The compact design of E-SIM and standardization of technical specifications for Embedded SIM technology is another distinct feature that sets E-SIM cards apart from conventional SIM cards. This is because Embedded SIM technology is standardized by Groupe Speciale Mobile Association, which comprises more than 800 mobile operators worldwide. Further, compact design of E-SIM cards is advantageous to original equipment manufacturers for increasing the battery size or to provide additional storage in electronic devices.

A report by Transparency Market Research predicts the global E-SIM card market to rise at a healthy 13.5% CAGR between 2017 and 2025. Progressing at this rate, the market is anticipated to display an opportunity of US$14,613.1 mn by 2025 increasing from US$4,095.6 mn in 2016.

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In terms of application, the global E-SIM card market has been segmented into machine to machine (M2M), wearable and companion devices, smartphones, and tablets and laptops. The segment of M2M, among these, contributed the leading revenue contribution in 2016. M2M is further sub-segmented into connected cars, utility, and others. Of them, connected cars is expected to expand at a CAGR of over 15% between 2017 and 2025 backed by the rising adoption of E-SIM card in the automotive industry for weather information and infotainment.

The commercialization of Embedded SIM for smartphones is expected in 2019. The segment is expected to rise at a robust CAGR of 26.3%between 2019 and 2025.

The key segments into which the global E-SIM card is divided based on geography are North America, Asia Pacific, Europe, Middle East and Africa, and South America. In 2016, Europe stood as the leading revenue generation region and is expected to display substantial CAGR over the forecast period. The supremacy of the region is due to the favorable government initiatives for the implementation of “Industry 4.0” technology and solutions. The U.K., France, and Germany are the leading revenue contributors to the Europe E-SIM card market.

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North America held the second-leading revenue share in the global market in 2016 with the U.S. contributing the leading revenue. The region is expected to display significant growth over the forecast period. The increased adoption of technology as well as home to key industry players is driving the growth of this regional market.

Asia Pacific, amongst all, is expected to rise with the leading CAGR over the forecast period. The growth of this region is backed by the rising adoption of embedded SIM technology in M2M devices across several countries such as China and Japan.

South Africa and Gulf Cooperation Council are the leading revenue generating regions in the Middle East and Africa. The E-SIM card market in South America is driven by the rising adoption of embedded SIM in utilities to provide smart metering solutions. Brazil is the leading revenue contributing domestic market to the E-SIM card market in the region.

Some prominent players operating in the global E-SIM card market profiled in this report are Apple Inc., Samsung, Gemalto N.V., Giesecke & Devrient GmbH, NTT DOCOMO Inc., OT-Morpho, Telefonica S.A., Deutsche Telekom AG, Sierra Wireless Inc., and ST Microelectronics.

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Transparency Market Research (TMR) is a market intelligence company, providing global business information reports and services. Our exclusive blend of quantitative forecasting and trends analysis provides forward-looking insight for thousands of decision makers. We have an experienced team of Analysts, Researchers, and Consultants, who us e proprietary data sources and various tools and techniques to gather, and analyze information. Our business offerings represent the latest and the most reliable information indispensable for businesses to sustain a competitive edge.

Each TMR Syndicated Research report covers a different sector – such as pharmaceuticals, chemical, energy, food & beverages, semiconductors, med-devices, consumer goods and technology. These reports provide in-depth analysis and deep segmentation to possible micro levels. With wider scope and stratified research methodology, our syndicated reports thrive to provide clients to serve their overall research requirement.

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An Insight on 4G Wireless Routers

4G Wireless Router is a kind of router with a 4G network module for 4G network. 4G/LTE Router is a wireless gateway for your wireless terminals to access the internet. The 4G router connects to the mobile network with the latest 4G technology and can distribute it in different ways, for example via separate LAN ports or WiFi. Depending on your type of 4G router, you can share the connection with multiple users. The feature of the 4G router is that it has one or two SIM card slots. Some may also have Ethernet port or not. Usually, the 4G wireless router would provide internet connection through WiFi. The LTE WiFi router usually has one SIM card slot, after SIM card plugin, it could be the access point for multiple WiFi-enabled devices, such as PC, laptop, tablets, smart phones etc...

 The 4G Routers with Ethernet ports and SIM card slot are usually 4G Stationary router for home or office use in a small group of people. However, some new 4G pocket WiFi routers are configured with Ethernet port for WAN or LAN or together. These 4G portable WiFi routers with Ethernet port make the gadget could be taken for outdoor activities. It's a new series of the 4G Router. 

In this case, it's also called 4G WiFi Router. Usually, the 4G Router with Ethernet ports are for LAN, and there are 4 LAN ports, sometimes, there may be 1 or 2 ports. The most important is that it must have two external antenna port to support MIMO data transmission. For the LTE router without any LAN ports, we call them 4G LTE Mobile Hotspot, 4G LTE MiFi or 4G Mobile WiFi. Some people call them portable 4G router and they can support at least 5 users to access the internet with peak speed up to 100Mbps. 4GLTEmall.com offers all kinds of 4G Router per customers' preference and their network status. They are all unlocked to make the 4G Routers could roam in different LTE networks. 

A 4G LTE Router usually has an input slot for SIM card, some 4G LTE Routers are with dual SIM card slots. With the data plan of your mobile provider, you can connect to the internet anytime and anywhere. Sometimes, you may need log in the web interface of the LTE router to do some simple settings for the network. After connecting with the wireless 4G network, your 4G LTE Router could provide internet access through LAN port or WiFi. Your devices can get connected to the router and surf.

A 4G Wireless router uses the 4G mobile network and under optimal conditions, it supports 4G network speeds of up to 100 Mbps download and 50 Mbps upload. You, therefore, benefit from mobile broadband connections that are up to ten times faster than the 3G connections. With the LTE network and technology development, the 4G LTE WiFi router could provide much faster speeds than ever. According to the LTE Category, 4G LTE Routers can be divided to LTE Cat.3 router, LTE Cat.4 router, LTE Cat.6 router, LTE Cat.11, Cat.12, Cat.13 router, LTE Cat.16 router and LTE Cat.18 routers. The latest LTE Cat.16 routers and LTE Cat.18 routers are also called LTE Advanced Pro (LTE-A Pro) routers. The 4G LTE Router provide download speeds up to 100Mbps(LTE Cat.3), 150Mbps(LTE Cat.4), 300Mbps(300Mbps), 450Mbps(LTE Cat.9), 600Mbps(LTE Cat.11), or 1Gigabit/s(LTE Advanced Pro) based different LTE technologies.

Previously, WAN support was a service that was only offered to large companies to recover from very serious failures. It was very expensive and only served to recover critical data.

However, today, almost all companies (regardless of their size or field of activity) need to have a failure recovery system to stay connected. Not having WAN support means losing connections between offices, customers and suppliers.

Not only does data transmission fail, but telephony over IP (ToIP) also stops working. For many years, the option that was proposed was to hire a second operator to enjoy a double fixed line installation as a measure of resistance to failures.

However, this solution was very expensive because the wiring of the alternative fixed line had to be installed and the expenses associated with it had to be paid. The real alternative came with the implementation of the 3G mobile network and, later, with the 4G / LTE networks.

Industrial routers have been widely used in the M2M industry in the IoT industry chain, such as smart grid, intelligent transportation, smart home, finance, mobile POS terminals, supply chain automation, industrial automation, intelligent building, fire protection, public safety, environmental protection, weather , digital medical, remote sensing, military, space exploration, agriculture, forestry, water, coal, petrochemical and other fields.

An industrial router is a rugged device used to connect two or more networks to transmit signals only to the desired port. The gateway converts standard Ethernet to Industrial Ethernet protocols, wireless and wired interfaces, or Ethernet and fieldbus communication protocols. Processor performance ranges from 200 to 1500 MIPS, and on-chip memory capacity is typically greater than 256 KB L2 cache. This factory automation unit is rugged and suitable for use in harsh industrial environments where fan cooling is required.

Industrial router WCDMA/HSDPA/HSUPA Router wireless router adopts high-performance 32-bit industrial-grade ARM9 communication processor, with embedded real-time operating system as software support platform, and the system integrates a full range of communication links from logic link layer to application layer. Support static and dynamic routing, PPP server and PPP client, VPN (including PPTP and IPSEC), DHCP server and DHCP client, DDNS, firewall, NAT, DMZ host and other functions. Provide users with secure, high-speed, stable and reliable wireless routing network for routing and forwarding of various protocols. This product has been widely used in finance, water conservancy, environmental protection, electricity, postal, meteorological and other industries.

It has three-layer system protection: On the basis of the original two-level (software protection + CPU built-in watchdog protection, external hardware watchdog protection) system protection, the first-level system monitoring and protection SWP (System Watch Protect) is added, completely solved. Industry "fake online", "fake crash", "downtime" and other difficult issues.

Perfect VPN: The new router fully supports all the VPN functions in the industry (PPTP+MPPE, IPSEC+L2TP), and solves the problem that the original router cannot support IPSEC due to system problems.

large cache: can provide 32M customer transmission data cache to solve data loss caused by network bottlenecks

High-speed processing CPU: It adopts industrial-grade CPU with more high-speed ARM9 than the original, which can process various protocol data conversions at higher speed and avoid data re-transmission and loss caused by slow CPU processing.

Memory management MMU: new CPU with memory management MMU, can prevent system instability caused by system memory abnormalities

Real-time operating system: The new system uses real-time operating system RTOS, which can receive and send data more quickly and in real time, avoiding data loss problem.

Complete protocol stack: The new system is loaded with a complete TCP/IP protocol stack, and the network communication performance is excellent.

Support real-time clock: support real-time clock SNTP protocol, online update time

Support a variety of wake-up methods: phone, SMS, local data wake up

Support online time period management

Excellent EMC performance: It is tested by electric power 3000V electric shock test, which is especially suitable for use in industrial environment. The system is stable and reliable.

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Source: https://modem-routers-manufacturer.blogspot.com/2018/10/an-insight-on-4g-wireless-routers.html

New Artificial Intelligence System To  best industrial wifi router  Aid In Materials Fabrication

www.inhandnetworks.com

Using a new artificial-intelligence system that would pore through research papers to deduce “recipes” for producing particular materials, scientists hope to close the materials-science automation gap.

In recent years, research efforts such as the Materials Genome Initiative and the Materials Project have produced a wealth of computational tools for designing new materials useful for a range of applications, from energy and electronics to aeronautics and civil engineering.

But developing processes for producing those materials has continued to depend on a combination of experience, intuition, and manual literature reviews.

A team of scientists at MIT, the University of Massachusetts at Amherst, and the University of California at Berkeley hope to close that materials-science automation gap, with a new artificial-intelligence system that woul industrial IoT router  d pore through research papers to deduce “recipes” for producing particular materials.

“Computational materials scientists have made a lot of progress in the ‘what’ to make — what material to design based on desired properties,” says Elsa Olivetti, the Atlantic Richfield Assistant Professor of Energy Studies in MIT’s Department of Materials Science and Engineering (DMSE). “But because of that success, the bottleneck has shifted to, ‘Okay, now how do I make it?’”

The scientists envision a database that contains materials recipes extracted from millions of papers. Scientists and engineers could enter the name of a target material and any other criteria — precursor materials, reaction conditions, fabrication processes — and pull up suggested recipes.

As a step toward realizing that vision, Olivetti and her colleagues have developed a machine-learning system that can analyze a research paper, deduce which of its paragraphs contain materials recipes, and classify the wo smart vending  rds in those paragraphs according to their roles within the recipes: names of target materials, numeric quantities, names of pieces of equipment, operating conditions, descriptive adjectives, and the like.

In a paper appearing in the latest issue of the journal Chemistry of Materials, they also demonstrate that a machine-learning system can analyze the extracted data to infer general characteristics of classes of materials — such as the different temperature ranges that their synthesis requires — or particular characteristics of individual materials — such as the different physical forms they will take when their fabrication conditions vary.

Olivetti is the senior author on the paper, and she’s joined by Edward Kim, an MIT graduate student in DMSE; Kevin Huang, a DMSE postdoc; Adam Saunders and Andrew McCallum, computer scientists at UMass Amherst; and Gerbrand Ceder, a Chancellor’s Professor in the Department of Materials Science and Engineering at Berkeley.

Filling in the gaps

The scientists trained their system using a combination of supervised and unsupervised machine-learning techniques. “Supervised” means that the training data fed to the syst industrial wireless router  em is first annotated by humans; the system tries to find correlations between the raw data and the annotations. “Unsupervised” means that the training data is unannotated, and the system instead learns to cluster data together according to structural similarities.

Because materials-recipe extraction is a new area of research, Olivetti and her colleagues didn’t have the luxury of large, annotated data sets accumulated over years by diverse teams of researchers. Instead, they had to annotate their data themselves — ultimately, about 100 papers.

By machine-learning standards, that’s a pretty small data set. To improve it, they used an algorithm developed at Google called Word2vec. Word2vec looks at the contexts in which words occur — the words’ syntactic roles within sentences and the other words around them — and groups together words that tend to have similar contexts. So, for instance, if one paper contained the sentence “We heated the titanium tetracholoride to 500 C,” and another contained the sentence “The sodium hydroxide was heated to 500 C,” Word2vec would group “titanium tetracholoride” and “sodium hydroxide” together.

With Word2vec, the researchers were able to greatly expand their training set, since the machine-learning system could infer that a label attached to any given word was likely to apply to other words clustered with it. Instead of 100 papers, the researchers could thus train their system on around 640,000 papers.

Tip of the iceberg

To test the system’s accuracy, however, they had to rely on the labeled data, since they had no criterion for evaluating its performance on the unlabeled data. In those tests, the system was able to identify with 99 percent accuracy the paragraphs that contained recipes and to label with 86 percent accuracy the words within those paragraphs.

The scieintists hope that further work will improve the system’s accuracy, and in ongoing work they are exploring a battery of deep learning techniques that can make further generalizations about the structure of materials recipes, with the goal of automatically devising recipes for materials not considered in the existing literature.

Much of Olivetti’s prior research has concentrated on finding more cost-effective and environmentally responsible ways to produce useful materials, and she hopes that a database of materials recipes could abet that project.

“This is landmark work,” says Ram Seshadri, the Fred and Linda R. Wudl Professor of Materials Science at the University of California at Santa Barbara. “The authors have taken on the difficult and ambitious challenge of capturing, through AI methods, strategies employed for the preparation of new materials. The work demonstrates the power of machine learning, but it would be accurate to say that the eventual judge of success or failure would require convincing practitioners that the utility of such methods can enable them to abandon their more instinctual approaches.”

This research was supporting by the National Science Foundation, Office of Naval Research, the Department of Energy, and seed support through the MIT Energy Initiative. Kim was partially supported by Natural Sciences and Engineering Research Council of Canada.

Publication: Edward Kim, et al. “Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning,” Chem. Mater., 2017, DOI: 10.1021/acs.chemmater.7b03500

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