Argonne Opens a New Window Into Atomic-Scale Energy Transfer
PyRET turns a difficult materials calculation into inspectable, reusable scientific software.
Researchers at Argonne National Laboratory and the University of Chicago have released PyRET, an open-source Python package for calculating how energy moves between tiny defects inside solid materials.
The name stands for Python code for resonance energy transfer. Resonance energy transfer happens when an excited site passes energy to another site without moving an electrical charge across the full distance. In a crystal, the sites can be atomic-scale imperfections that absorb or emit light.
That sounds narrow, but these defects are central to work on optical memory, solid-state sensors, microelectronics and some quantum devices. Their interactions can preserve a useful signal, amplify it or leak energy away from the part of a device meant to hold information.
The hard part is scale. The electronic structure around a defect is measured in fractions of a nanometre. Light can carry energy across tens or hundreds of nanometres in the same device. Calculations that describe one scale do not automatically explain the other.
PyRET connects those layers. It can use wavefunctions from Quantum ESPRESSO, a widely used electronic-structure package, and link them with quantum defect calculations produced by WEST. It then models both radiative transfer, where a photon carries the energy, and non-radiative transfer between nearby defects.
The underlying methods were described in peer-reviewed Physical Review Research papers in 2024 and 2025. In the later work, the researchers calculated that placing defects inside a tuned photonic cavity could change their energy-transfer rate by nearly two orders of magnitude. A photonic cavity is a tiny structure that confines selected frequencies of light.
The newly public code matters because other teams can now inspect the implementation, reproduce the calculations and adapt them to different materials. The repository uses the GPL-3.0 licence and includes installation instructions, documentation and examples.
That openness also makes comparisons easier. A laboratory testing a new defect can keep the physical method visible while changing the material, cavity geometry or electronic input. Failed predictions can be traced to assumptions in the workflow instead of disappearing inside a proprietary service.
PyRET is not a push-button materials discovery app. Researchers still need electronic-structure inputs, familiarity with specialist simulation software and, for large calculations, substantial computing resources. The public repository is also young, with a small visible user community and no packaged releases listed yet.
Those limitations are part of the useful signal. The immediate advance is not a finished memory chip or quantum sensor. It is a more transparent bridge between theories that operate at different scales.
For working scientists, that can shorten the distance between a promising defect found in a calculation and a device design worth testing in the lab. For everyone else, PyRET is a reminder that open source in science is often less about a polished consumer tool and more about making a difficult claim testable by someone outside the original team.
Encrypted RCS Makes Messaging Private Across Platforms, but Not Yet Universal
The new protection weakens an old privacy boundary between iPhone and Android while exposing how much standards still depend on apps and carriers.
For years, the safest everyday messaging usually required everyone in a conversation to choose the same app. An iPhone group could use iMessage. Android users could use encrypted RCS in Google Messages. Mixed groups often fell back to a less protected path or moved to a separate service such as Signal or WhatsApp.
That boundary has started to change. Apple and Google began rolling out end-to-end encrypted RCS between iPhone and Android in May. The feature is included in iOS 26.5 and the latest Google Messages, appears as a lock inside supported conversations, and is enabled by default when the necessary pieces are available.
The timing matters again because Samsung ended its own Messages app for most affected US customers in July and directed them to Google Messages. Two developments that look separate are converging. Cross-platform privacy is moving into a shared industry standard, while the number of major applications implementing that standard is becoming smaller.
RCS, or Rich Communication Services, is the mobile industry’s replacement for SMS and MMS. It supports features people now expect from modern chat, including high-quality media, typing indicators, read receipts and better group conversations.
The latest security work is part of the GSMA’s RCS Universal Profile 3.0. It uses the Messaging Layer Security protocol, an open technical standard designed to protect conversations involving two people or a changing group.
End-to-end encryption means the message content is encrypted on the sender’s device and can be decrypted only by devices in the conversation. Apple, Google, mobile carriers and an observer on the network should not be able to read that content while it is being delivered. The protocol also authenticates senders and updates the group’s cryptographic keys when membership changes.
This protection is different from ordinary transport encryption. Transport encryption can secure a message between a phone and a server, then expose it at the server before another protected connection begins. End-to-end encryption keeps the content protected through the intermediaries.
It does not make a conversation invulnerable. A compromised phone can reveal messages after decryption. A recipient can copy or photograph what appears on screen. Services may still retain operational information needed to route traffic, and backup protection depends on the device and account settings around the conversation. The lock is meaningful, but it is not a promise that every surrounding system has become private.
The important shift is not a new chat feature. It is that encryption can now follow the communication format rather than the brand of phone.
Private messaging apps proved that end-to-end encryption could work at global scale. Their weakness as a default is coordination. Before the protection helps, every participant must install the service, create an account and agree to use it. A standards-based approach can protect the ordinary conversation a person starts with a phone number, without asking the group to reorganize first.
That has particular value for mixed-device families, schools, neighborhood groups and small organizations. Many routine conversations do not justify a debate over which app to install. Improving the path people already use raises the baseline for everyone who would otherwise continue with SMS.
Standards also outlast individual product decisions. Apple, Google and carriers can change interfaces and business strategies while still supporting the same interoperable format. Other compliant clients could, in principle, join later without inventing another private network.
The rollout also shows the limit of that ideal. Encryption remains labeled as beta. It requires a recent Apple operating system, the latest Google Messages on Android, supported devices and participating carriers. Apple says availability will expand over time, which means an RCS conversation may be encrypted for one contact and not another.
Users therefore need to look for the lock rather than assume that every colorful chat bubble has the same protection. If the required support is missing, a conversation may use unencrypted RCS or fall back to SMS or MMS. The visual similarity between these paths can conceal a major security difference.
Samsung’s decision adds another complication. Moving customers to Google Messages improves consistency and gives more Android users the client involved in the encrypted rollout. It also removes a prominent alternative messaging app in the US. The protocol may be industry-wide, but Google now controls the main Android interface through which many people experience it.
This is a recurring pattern in technology. An open standard can reduce dependence on one platform while implementation consolidates around a few large vendors. Interoperability and market diversity are related, but they are not the same achievement.
Encrypted RCS will not replace dedicated private messengers. Signal still offers a more focused privacy model. Other services have broader international networks, richer communities or stronger control over backups and identity.
The value of RCS is more ordinary. It upgrades the least deliberate messages, the ones sent before anyone thinks about choosing a secure service. That is where standards often have their greatest effect. They turn a protection from an enthusiast’s preference into infrastructure that can disappear into daily use.
The rollout is incomplete, carrier-dependent and concentrated in two major apps. Those are real limitations. Still, a lock appearing in an iPhone-to-Android conversation marks a useful change in what people should expect. Private communication no longer has to stop at the edge of a device ecosystem. The next test is whether that expectation becomes reliable enough that users no longer need to inspect every thread to know which privacy rules apply.
AI Crawlers Are Turning Websites Into Metered Suppliers
Publishers and online businesses are gaining tools to measure, block and charge machine visitors, but pricing can also reduce discovery.
The web’s familiar business exchange is becoming less reliable. Search engines traditionally copied information from websites, then sent people back through links. Those visits could become advertising impressions, subscriptions or sales.
AI crawlers often complete only the first half of that exchange. They fetch pages to train models, build search indexes or answer a user’s question inside another product. The website still supplies the material, but the person may never arrive.
This is now an operating issue, not just a dispute between publishers and AI companies. Product catalogs, travel data, documentation, research archives and specialist databases can all become inputs to an automated service. New infrastructure is giving their owners a choice that was difficult to enforce before. Let the machine in, block it, or ask it to pay.
Cloudflare introduced an Attribution Business Insights dashboard in July to show customers how bots use their sites. It separates crawlers used for model training from those used for search or an agent acting on a person’s request. It also compares how frequently each operator crawls a site with how many visitors it refers back.
That separation is essential. A bot fetching a page because a customer asked an assistant to compare two products may create a commercial opportunity. A training crawler collecting thousands of pages produces no immediate visitor. Treating both as generic AI traffic hides the difference in value.
The measurements are still evolving. Cloudflare initially reported that 52 percent of crawler requests in June were for training. An independent recheck on August 1 found that Cloudflare had reclassified part of that traffic as mixed purpose. The corrected series put training at 44.54 percent of AI crawler requests in July, still the largest single declared purpose. Search and user-triggered requests together accounted for about 14.23 percent.
The correction does not reverse the business problem, but it is a warning against building policy around one headline number. A site needs its own traffic data before deciding what access is worth.
Cloudflare is also developing a Monetization Gateway that can charge for web pages, datasets, APIs and tools used by AI agents. It relies on x402, an open payment protocol named after the web’s largely unused “402 Payment Required” status code.
The sequence is simple in principle. An automated client requests a protected resource. The server returns a price and payment instructions. The client pays, repeats the request with proof, and receives the resource after verification. Cloudflare plans to perform the metering and payment check at the edge of its network, before the request reaches the customer’s server.
The first version will use stablecoins, digital tokens designed to track conventional currencies. That makes fractions-of-a-cent payments possible without requiring every agent to open an account with every website. Sellers would be able to retain the tokens or redeem them for conventional money.
This is not a finished mass-market payment channel. The gateway currently has an early-access waitlist, and the important buyers still have to support the protocol. Cloudflare’s position between websites and visitors also gives it a commercial interest in making metered access a new infrastructure category.
Other approaches are forming alongside it. The Really Simple Licensing standard lets publishers declare terms such as free use, attribution, subscriptions, payment per crawl or payment when content contributes to an AI-generated answer. Unlike an enforced payment gate, a licensing declaration still depends on crawler compliance or an infrastructure provider willing to block noncompliant requests.
The immediate task is not to put a price on every page. It is to identify which digital assets lose value when they are copied and which gain value through wider discovery.
A public product page may work best when search engines, shopping assistants and customer-triggered agents can read it freely. The business wants the product considered, even if the buyer arrives through a new interface. A continuously updated pricing feed, proprietary comparison table or specialist research archive is different. It may deserve authenticated access, usage limits or a fee because it directly improves another company’s product.
That suggests a layered policy. Keep marketing information accessible. Measure which bots fetch it and whether they produce referrals or attributable sales. Place high-cost or high-value data behind clearer terms. Rate-limit repetitive requests that add server expense without creating a useful relationship. Reserve payment gates for material that has a plausible machine customer.
Pricing also requires experimentation. Charging too little can fail to cover data creation and payment administration. Charging too much can make an agent select a rival source or omit the business entirely. A per-request fee may suit a live API, while a license or revenue share may fit an archive whose value appears across many answers.
Independent analysis from Brookings warns that AI licensing could reproduce the same concentration that shaped search and social media. Large publishers can negotiate private agreements. Smaller sites may depend on collective licensing groups or intermediaries that control measurement, enforcement and payment.
There are technical uncertainties too. Crawlers can disguise themselves, ignore declared rules or obtain data from third parties. Stablecoin settlement introduces accounting and compliance work. A paid request proves that a transaction occurred, but it does not by itself show how the purchased information will be stored, combined or reused.
The practical change is that website access is becoming a business decision rather than a default. For years, most organizations treated automated crawling as a technical matter handled through a small text file and firewall rules. Now the same traffic can affect distribution, infrastructure cost, data licensing and sales.
The most useful response is neither a universal block nor an open door. It is a clearer inventory of what the site offers, who consumes it and what the business receives in return. Metered access will matter only when that exchange is valuable enough for both sides to keep making it.