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Atomic neighborhoods in semiconductors provide new avenue for designing microelectronics

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Atomic neighborhoods in semiconductors provide new avenue for designing microelectronics


An illustration of the semiconductor material investigated for this study, which is composed of germanium with small amounts of silicon and tin. The germanium atoms are depicted as gray spheres, the silicon as red and tin as blue. Credit: Minor et al/Berkeley Lab

Inside the microchips powering the device you’re reading this on, the atoms have a hidden order all their own. A team led by Lawrence Berkeley National Laboratory (Berkeley Lab) and George Washington University has confirmed that atoms in semiconductors will arrange themselves in distinctive localized patterns that change the material’s electronic behavior.

The research, published in Science, may provide a foundation for designing specialized semiconductors for quantum-computing and optoelectronic devices for defense technologies.

On the , semiconductors are crystals made of different elements arranged in repeating . Many semiconductors are made primarily of one element with a few others added to the mix in small quantities. There aren’t enough of these trace additives to cause a throughout the material, but how these atoms are arranged next to their immediate neighbors has long been a mystery.

Do the rare ingredients just settle randomly among the predominant atoms during material synthesis, or do the atoms have preferred arrangements, a phenomenon seen in other materials called short-range order (SRO)? Until now, no microscopy or characterization technique could zoom in close enough, and with enough clarity, to examine tiny regions of the crystal structure and directly interpret the SRO.

“It’s an interesting scientific question because SRO dramatically changes the properties of a material. Our colleagues have predicted SRO theoretically in semiconductors, but this is the first time the individual structure of these SRO domains has been shown experimentally,” said co-lead author Andrew Minor, director of the National Center for Electron Microscopy at Berkeley Lab’s Molecular Foundry and a professor of Materials Science and Engineering at UC Berkeley.

Minor’s lab is part of the Center for Manipulation of Atomic Ordering for Manufacturing Semiconductors (µ-Atoms), a Department of Energy (DOE) Energy Frontier Research Center focused on understanding atomic ordering in semiconductors. “Our results are exciting because the property that’s being changed by this local ordering is the most important property for microelectronics, the band gap, which is what controls the electronic properties,” he said.

The breakthrough moment came when first author Lilian Vogl, who was then a postdoctoral researcher in Minor’s lab, was studying a sample of germanium containing a small amount of tin and silicon using a powerful type of recently pioneered by the group called 4D-STEM. The initial results were too muddled to parse the faint signals from the electrons diffracting off the tin and silicon from the strong signals off the tidily arranged germanium, so she implemented an energy-filtering device on the system to improve contrast.

When the next dataset started appearing on her monitor, she quickly realized there was a new kind of result. The faint signals were clearer, and repeating patterns emerged, indicating that the atoms have preferred order after all.

To validate her findings and learn what these patterns meant, Vogl collected more data with the energy-filtering 4D-STEM and used a pre-trained neural network to sort the diffraction images. The tool identified six recurring motifs representing particular atomic arrangements in the sample material, but the Berkeley Lab team still couldn’t determine the exact atomic structures that were generating the motifs. To interpret their experimental results, they turned to µ-Atoms collaborators at George Washington University led by co-lead author Tianshu Li, a professor of Civil and Environmental Engineering.

Li’s team generated a highly accurate and efficient machine-learning potential capable of modeling millions of atoms in the material’s structure, allowing Vogl to perform simulated 4D-STEM on different possible structural arrangements until she found matches for the motifs in the experimental data.

“It’s remarkable that modeling and experiment can work seamlessly to unravel SRO structural motifs for the first time,” said Li, whose team had previously predicted SRO and its impact and helped motivate the current study.

“Proving SRO experimentally is not an easy task, let alone identifying its structural motifs. Signals from SRO can easily be obscured by defects or inherent movement of atoms at room temperature, and until now there was no clear way to separate them. This work represents the first step toward our broader goal.”

Shunda Chen, a research scientist in Li’s group who developed the model, said, “With these models, which combine machine learning with first-principles calculations, we can replicate experimental procedures with high fidelity and pinpoint the structural motifs that would otherwise remain hidden.”

Follow-up work initiated by other µ-Atoms members at the University of Arkansas and at Sandia National Laboratories is already yielding insights into how these short range-order motifs affect the semiconductor’s electronic properties, and the scientists hope that manipulating the order to enable new types of devices and processing routes will be possible soon.

“We’re going to be able to really push the boundaries beyond current capabilities by designing semiconductors at the atomic scale,” said Vogl, who is now group leader of the Environmental & Analytical Electron Microscopy Group at the Max Planck Institute for Sustainable Materials.

“We are opening the door to a new era of information technology at the atomic scale, unlocking the deterministic placement of SRO motifs for tailoring of band structures that could impact a wide variety of technologies, from topological quantum materials to neuromorphic computing to optical detectors.”

More information:
Lilian M. Vogl et al, Identification of short-range ordering motifs in semiconductors, Science (2025). DOI: 10.1126/science.adu0719

Citation:
Atomic neighborhoods in semiconductors provide new avenue for designing microelectronics (2025, September 25)
retrieved 25 September 2025
from https://techxplore.com/news/2025-09-atomic-neighborhoods-semiconductors-avenue-microelectronics.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.





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Amazon Will Pay $2.5 Billion to Settle FTC Suit That Alleged ‘Dark Patterns’ in Prime Sign-Ups

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Amazon Will Pay .5 Billion to Settle FTC Suit That Alleged ‘Dark Patterns’ in Prime Sign-Ups


In the six-year time frame established in the settlement, anyone who “unsuccessfully attempted” to cancel their Prime subscription online is eligible to get paid up to $51 from Amazon. People who signed up for Prime during that same period can also get up to $51 if they signed up through a “challenged enrollment flow”—a page with a confusing interface that may lead to people inadvertently making a purchase. Previous court filings established that in some cases, some users may have selected “two-day shipping” on an item and not realized that, in doing so, they were also signing up for Amazon Prime.

An FTC spokesperson tells WIRED that automatic payments will go out to some customers within 90 days.

“The rest of eligible consumers will receive a notification from Amazon, and will have the opportunity to submit a simple claim form,” the FTC says. “Amazon is required to post information about this to Amazon.com and the app. The settlement also requires Amazon to have an independent third party who will monitor their compliance with these claims.”

The court filing says that Amazon is also “permanently” barred from structuring Prime sign-ups with a confusing “negative option feature” where a customer is assumed to be making a purchase unless they actively refuse it.

For example, the filing says, a button that reads “No thanks, I don’t want free shipping” does not clearly indicate that a customer will be signed up for Prime unless they click it. Amazon also has to make it obvious when a person is choosing to sign up for Prime, and include language like “Join Prime” in its user interface. Similarly, Amazon has to clearly communicate when a Prime subscription is subject to auto-renewals by using words like “renew.”

The initial complaint, which was filed by the FTC in June 2023, alleged that while Amazon had improved its process for canceling Prime memberships, the company had spent years knowingly complicating the cancellation process.

An attachment on a May 7 court filing includes an email chain with Amazon employees from December 2020, which was described as “privileged and confidential” in the subject line. In the email, a manager of Prime content and marketing paraphrased key points that came up in a recent “US prime performance meeting.”

“Subscription is driving a bit of a shady world,” reads one paraphrased quote, attributed to an unnamed person at the meeting.

“We should lean away from experimenting with sign-up clarity, and focus more on driving overall members and increasing confirmation that you are prime,” reads a different paraphrased quote from another person at the meeting, included in the same attachment.

A different attachment shows that Amazon was aware that customers were frustrated. A company slide presentation dated September 17, 2017, focused specifically on customer service complaints about “unintentional” Prime sign-ups. (A different attachment, which includes an email chain dated September 25, 2017, appears to refer to the presentation. Two dozen people were asked to “delete the PowerPoint document” and send “confirmation” once they had.)

One customer complaint in the presentation claims that they were “tricked” into signing up for a free trial for Amazon Prime when they selected two-day shipping on a purchase, not knowing that this would also sign them up for a trial for Prime.

“I DO NOT LIKE YOUR SERVICE,” reads another complaint. “THIS IS CRAP THAT I ORDERED A PRODUCT IN AMAZON ADS [sic] ME TO A PROGRAM WITH AUTO BILLING THAT I DID NOT SIGN UP FOR. I WILL NOT USE AMAZON AND TELL EVERYONE ABOUT THIS TYPE OF CRAP YOU ARE PULLING.”

“IT IS SNEAKY AND BLOODY DISHONEST FORCING SOMETHING THE [sic] I NEVER WANTED,” reads another complaint.

The same Amazon slide presentation noted that confusing Prime sign-ups were leading to an increased burden on Amazon’s customer service workers, as well as a “loss of customer trust.”



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Solar-powered system produces green hydrogen directly from air moisture

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Solar-powered system produces green hydrogen directly from air moisture


by Yin Huajie; Zhao Weiwei, Hefei Institutes of Physical Science, Chinese Academy of Sciences

Self-sustaining air water harvesting and proton exchange membrane water electrolysis based on ordered porous carbon. Credit: Yin Huajie

A team led by Prof. Yin Huajie from the Hefei Institute of Physical Science of the Chinese Academy of Sciences has developed a solar-powered system that produces green hydrogen directly from atmospheric moisture without relying on external water or energy sources.

The results are published in Advanced Materials.

Proton Exchange Membrane Water Electrolysis (PEMWE) technology is one of the primary routes for producing green hydrogen, drawing significant attention due to its and high-purity hydrogen output. However, the PEMWE process heavily relies on high-purity water as the reaction raw material, limiting its application in water-scarce regions. Atmospheric water harvesting (AWH), as an emerging approach to obtaining pure water, holds promise as a viable solution to the water shortage issue in the production of green hydrogen.

In this study, the researchers developed a self-sustaining system that couples photothermal atmospheric water harvesting with proton exchange membrane electrolysis.

The system uses hierarchically as an adsorbent to capture moisture from the air, which is evaporated by solar heat and fed into a custom-built electrolyzer for . The porous material is fabricated through template synthesis and calcination, followed by surface oxidation to improve water affinity.

It demonstrates remarkable performance. Even under low humidity conditions (as low as 20%), it maintains stable water collection and evaporation performance. Under 40% humidity, the system reached a hydrogen production rate of nearly 300 mL per hour with excellent cycle stability and long-term reliability.

Field tests further confirmed that it can continuously produce green hydrogen using only solar energy, with zero carbon emissions and no external energy input.

This work provides a new pathway for sustainable hydrogen production in water-scarce regions, according to the team.

More information:
Bo Fu et al, Solar‐Driven Atmospheric Water Production Through Hierarchically Ordered Porous Carbon for Self‐Sustaining Green Hydrogen Production, Advanced Materials (2025). DOI: 10.1002/adma.202511336

Provided by
Hefei Institutes of Physical Science, Chinese Academy of Sciences

Citation:
Solar-powered system produces green hydrogen directly from air moisture (2025, September 25)
retrieved 25 September 2025
from https://techxplore.com/news/2025-09-solar-powered-green-hydrogen-air.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.





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Okta CEO: AI security and identity security are one and the same | Computer Weekly

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Okta CEO: AI security and identity security are one and the same | Computer Weekly


At its annual Oktane customer conference in Las Vegas, Nevada, identity and access management specialist Okta has been expanding its vision to be a first-port-of-call when it comes to securing non-human identities (NHIs) as a swelling wave of artificial intelligence (AI) agents causes their numbers to swell dramatically.

Among the announcements made today are new capabilities within both the Okta and Auth0 platforms that the supplier said will enable users to integrate AI agents seamlessly into their identity security fabrics.

A study released earlier in 2025 by Okta revealed that although 91% of organisations were already deploying agentic AI in search of productivity gains, but also that just 10% of organisations are today putting any form of cyber governance in place to manage agents – so Okta believes the risk is also rising, and fast.

Such risks are no longer theoretical; Okta cited incidents such as the now infamous breach which an AI bot built on the Paradox AI platform and used by fast-food giant McDonalds in its hiring process exposed the personal data of millions of job applicants to hackers who correctly guessed that its password was ‘123456’.

Okta CEO Todd McKInnon compared unleashing AI agents on an organisation’s environment to creating a lot of individual new insider threats.

“AI agents are a powerful new identity type. They can act independently, on their own or on behalf of a user or a team or a company,” said McKinnon. “They can access tools, apps or data, they can plan or complete tasks on their own. The pace here of innovation is absolutely stunning.

“These AI agents and the potential here, are getting very, very powerful and it’s happening very quickly.

“Without identity security AI security collapses. AI security is identity security, you can’t be successful in one without the other,” said McKinnon.

Okta for Agents

Officially launched today, the firm’s new Okta for AI Agents concept will integrate AI agents into identity security fabrics to provide an end-to-end security wrap around them.

Among other things, the service provides tools to enable agent discovery and identification of risky – or rogue shadow – agents, centralised controls to manage their access, and automated governance to enforce wider security policies and manage their overall security journeys or ‘lifecycles’.

Notable among the features of the new package, Okta is talking up Cross App Access (XAA), a protocol which extends OAuth to secure agent-driven and application-to-application interactions. With support from partners such as AWS, Box, Google Cloud, Salesforce and many others, Okta said XAA will shift control from individual apps to the wider identity layer, bringing real-time visibility, policy-driven security, and safer agentic integrations.

“Enterprises everywhere are grappling with how to safely harness AI with company data. Our customers rely on Glean to unify that knowledge and empower AI agents to take meaningful action,” said Sunil Agrawal, CISO at AI data platform Glean, which has been working with Okta on XAA.

“Glean agents act strictly on behalf of the user – with no extra privileges. XAA takes that principle even further and represents the next step toward making it more secure and seamless for AI agents to connect across systems. We’re excited to support this emerging protocol and to help guide the industry toward standards-based agent interactions.”

Kristen Swanson, senior vice president of design and research at Okta, added. “The modern enterprise requires an identity security fabric that can unify silos and reduce the attack surface. Our latest innovations weave agents into that fabric to manage their entire identity lifecycle, leveraging open standards like Cross App Access that help elevate the entire industry and create a more secure AI-powered ecosystem.”

Elsewhere at Oktane, Okta unveiled Verifiable Digital Credentials (VDC), a new platform designed to reduce AI-powered fraud and potential friction during employee onboarding or other similar processes by enabling organisations to digitally prove a user’s identity and eligibility, and establish ongoing trust.



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