TECH

Dog-bone design helps 2D nanoribbon transistors stay fast and efficient as widths shrink

Transistors, small semiconductor-based switches that control the flow of electricity, are central components of all electronic devices, from computers to smartphones, wearables, sensors and smart appliances. Over the past decades, electronics engineers have been continuously working to boost the speed and performance of transistors while also reducing their size.

A promising approach for miniaturizing transistors entails the use of two-dimensional (2D) semiconductors, materials that are only one or a few atoms thick. Despite their potential, most high-performing 2D transistors have so far been demonstrated using relatively wide channels, and it has remained unclear whether their performance can be preserved when the channels are made much narrower.

Researchers at Stanford University recently developed new compact transistors based on narrow strips of monolayer 2D semiconducting materials known as nanoribbons. These transistors, introduced in a paper published in Nature Nanotechnology, were found to perform remarkably well despite their small size, outperforming previously developed nanoribbon transistors based on the same 2D materials.

"We wanted to reduce 2D transistors in all dimensions, including width," Eric Pop, senior author of the paper, told Tecplor. "Using a monolayer 2D semiconductor, the channel is automatically sub-nanometer thin, but to be technologically relevant, such transistors should also be very small in both length and width."

The team's recent study specifically focused on reliably reducing the transistors' width without significantly affecting their performance.

"Most academic works have looked at the 2D channel's thickness and length, which motivated us to systematically study width scaling in these materials and their devices," said Tara Peña, co-first author of the paper.

To prevent nanoribbon delamination (i.e., peeling from the surface during fabrication), the researchers employed a new approach, patterning 2D semiconductors into a dog bone-like shape. Metal contacts were integrated on the wider regions of this bone-like pattern, acting as anchors.

"This approach allowed us to study many nanoribbon channels as the narrow part of the dog bone, for several 2D semiconductors," said Pop. "In future industry use cases, the anchoring of nanoribbons will need to be achieved in a more compact way."

Using their approach, the researchers fabricated nanoribbon transistors based on three different monolayer 2D semiconductors, namely MoS2, WS2 and WSe2. Electrical measurements showed that the narrow nanoribbon channels retained good transistor behavior across all three materials.

"Importantly, the nanoribbons all behaved well with our nanofabrication approach at dimensions down to about 25 nanometers, including both n- (MoS2, WS2) and p-type behavior (WSe2)," explained Pop.

"This means that the edges are not fundamentally limiting the performance of these materials, and the edges could be further improved. The WS2 transistors were also able to carry about one hundred times higher current density than previous demonstrations, partly due to our improved contacts."

When they tested their newly developed transistors, Pop and his colleagues were surprised to discover that they did not show higher off-state leakage than wider transistors based on the same 2D materials. This suggests that despite their reduced width, the edges of the nanoribbons did not cause excess leakage, which is important for low-power operation.

"Another important part of our approach to reach the narrowest widths was how we etched the transistor channels," said Anton Persson, co-first author of the paper. "Instead of etching the channel in one step, we used two separate etching steps, which etched the channel from opposite sides. This allowed us to form narrower channels than with the conventional one-step approach."

The transistors developed by the researchers achieved good on-state currents of 560 µA/µm for n-type MoS2, 420 µA/µm for n-type WS2 and 130 µA/µm for p-type WSe2. Notably, all three transistors performed better than most other nanoribbon 2D transistors introduced in the past.

"We found that nothing dramatic happens when the transistors become very narrow," said Persson. "We were concerned that the etched-out edges of these semiconductors would cause problems, but the devices still behaved well or at least similarly to their wider counterparts. This suggests that these monolayer 2D semiconductor channels are relatively robust when scaled down in width."

Future research directions...The design and fabrication strategies introduced by this research team could soon be refined further and used to create other electronic components based on 2D semiconductors. This study demonstrated the potential of these strategies for realizing extremely small devices.

"The 'dog-bone' design and multi-step etching approaches both helped with adhesion and achieving narrower widths," said Peña.

"We also believe reducing electron beam dose and polymer contamination during the fabrication process allowed us to obtain 'cleaner' edges for our 2D nanoribbons. We hope our work will inspire other groups (and industry) to think carefully about how to limit sources of disorder that ultimately impact 2D device performance."

Pop and his colleagues are now planning further studies aimed at evaluating their proposed design and patterning approach. They will also try to realize nanoribbons that can operate at lower voltages, with improved edges and smaller contacts.

"For example, here we showed pretty good behavior is possible at 1 V drain-to-source voltage," explained Pop. "It will be important to achieve good behavior at 0.5 V on both the drain and gate, in order for these to be considered viable alternatives to silicon nanosheet transistors."

As part of their next studies, the researchers are curious to determine how far their downscaling approach can go before the performance of transistors starts declining.

"We expect that the devices will eventually start to degrade as the channels become even narrower, but we do not yet know at what width that happens," said Persson. "Understanding what happens below 10 nanometers in width will eventually be important if 2D semiconductors are to be compared seriously with future silicon nanosheets."

"Understanding how various strains and defects impact these ultra-scaled 2D nanoribbons will also be critical, which will require sophisticated materials characterization approaches," added Peña.

2D nanoribbons are ultra-narrow, strip-like structures of two-dimensional (2D) materials (like graphene, transition-metal dichalcogenides, or boron nitride) with widths typically scaled to under 50 nanometers. By restricting 2D sheets into 1D-like ribbons, researchers unlock tunable bandgaps, high charge mobility, and superior quantum edge effects.

Why 2D nanoribbons matter:

-Bandgap engineering: Unlike pristine 2D sheets (such as zero-bandgap graphene), nanoribbons exhibit tunable electronic bandgaps, which are strictly dictated by their precise width and edge orientation.

-Enhanced performance: Nanoribbon architectures offer highly exposed active edges that facilitate rapid electron transport and improved charge mobility, making them ideal for scaling down semiconductor logic devices.

-Quantum confinement: The extremely narrow channels lead to quantum effects, giving rise to unique magnetic behaviors, spin-filtering capabilities, and potential applications in quantum computing.

Key applications:

-Next-generation nanoelectronics: Nanoribbons are highly promising for the creation of ultra-compact Field Effect Transistors (FETs). For instance, researchers have developed high-speed, 35 nm channel nanoribbon transistors using monolayer 2D semiconductors to maintain performance despite shrinking dimensions.

-Energy storage & catalysis: The high surface-area-to-volume ratio and edge activity allow 2D nanoribbons (like those derived from unzipped carbon nanotubes) to act as excellent catalysts for hydrogen evolution, oxygen reduction, and energy storage.

-Optoelectronics: Their tunable optical and electrical properties make them prime candidates for advanced solar cells, sensors, and photodetectors.

Common types:

-Graphene nanoribbons (GNRs): The most well-studied type, often created using bottom-up molecular polymerization or unzipping of carbon nanotubes. They are prized for ballistic electron transport.

-Transition-metal dichalcogenide (TMD) nanoribbons: Materials like MoS₂ are naturally semiconducting and thin, making them optimal for extreme miniaturization in modern computing without the leakage currents found in traditional silicon.

-Boron nitride nanoribbons (BNNRs): Structurally similar to graphene but with a large bandgap, often used as an insulating dielectric layer or combined with graphene in heterostructures.

mundophone

DIGITAL LIFE

OECD warns of AI-induced “cognitive laziness”

Over-reliance on generative models may impair human judgment in the long run, according to new OECD data pointing to a pattern of AI-induced cognitive laziness. The document indicates that repeatedly delegating analytical tasks to automated systems can weaken autonomous intellectual skills and diminish critical capacity when these tools are unavailable.

Picture the scene. You’re behind the wheel in an unfamiliar city. Twenty years ago, a crumpled map lay on the passenger seat, eyes shuttling between paper and road, the mind charting streets, landmarks, intersections. Today, a soft, synthetic, almost reassuring voice takes care of everything. Attention drifts off, memory dissolves, and thought becomes a simple act of obedience. The comfort is total, almost anesthetic.

In the same way, when a question arises, there’s no need to search, to doubt, to build an answer step by step. You simply pose it to a machine. Within seconds, an artificial intelligence delivers a clear, well-argued, polished synthesis. The slowness of reasoning has vanished, replaced by immediate efficiency.

We now live in a world of universal assistance, a world where everything seems fluid, rational, effortless. These tools promise to free us from the burden of tedious tasks, to augment our capabilities, to make life simpler. Yet behind this technological comfort lurks a discreet paradox: as we delegate our cognitive faculties, we risk losing the ability to use them. By being constantly assisted, we cease to exercise what made us unique: autonomous thought.

It’s this slow drift—what I call cognitive laziness—that I’d like to discuss today. A laziness born not from disinterest, but from delegation. That of a mind that gradually surrenders to the machine to sort, choose, decide. The temptation of shortcuts becomes permanent, the fatigue of thinking disappears, and with it, the effort that forged lucidity.

Students who use digital assistants for academic assignments show a drop in performance on analog assessments. The OECD’s *Digital Education Outlook 2026* report reveals that introducing these platforms into the educational ecosystem creates an illusion of technical proficiency. Statistical data collected by the international organization suggests that the initial quality of schoolwork produced with computational support does not translate into retained knowledge.

In-person exams conducted without network access showed a reversal in grades for students who rely on automation. Removing intellectual friction during the research and writing phases hinders the consolidation of concepts in long-term memory. The OECD warns of the risk of widespread intellectual disengagement in educational institutions if language models continue to be integrated without criteria for maintaining analog-based analysis.

The illusion of competence in the professional environment... A decline in autonomous judgment is also becoming apparent in the corporate world—a phenomenon researchers liken to the loss of spatial awareness caused by the systematic use of GPS. A study cited by Harvard Business School measured the performance of professionals assisted by generative models. The results show that immediate gains in speed can come at the cost of quality or rigor in certain tasks, particularly when users encounter problems that lie beyond the AI's capabilities.

Professionals using the technology completed tasks 25.1% faster. However, when dealing with complex problems outside their specific area of ​​expertise, users showed a 19-percentage-point higher likelihood of making serious errors. The study further suggests that many employees accept incorrect machine-generated answers without verification, reinforcing the risk of over-reliance on AI in learning and operational oversight.

The loss of critical friction also affects system development and software coding. Research from Stanford University focusing on the use of autonomous computational assistants found that automation reduces the natural skepticism of technical operators. The study quantified output quality and found that professionals assisted by algorithms produce solutions with a higher rate of structural security flaws.

The research highlights a specific cognitive bias in which the user assumes automated work is correct due to the tool's seamless interface. This dynamic eliminates traditional manual validation processes, leading to an accumulation of logical errors that overwhelms senior professionals during the auditing phase. Reliance on generative models alters work structures, necessitating the reintroduction of verification methodologies based on primary sources.

Data presented by the OECD and academic institutions demonstrate that digital tools should serve to amplify, not replace, human intellect. Mitigating skill erosion requires creating artificial barriers that force a period of mental deliberation before resorting to algorithms. The sustainability of technological evolution depends on organizations' ability to preserve critical thinking as a strategic asset that cannot be entirely delegated to automation.

mundophone

TECH

SpaceX targets US consumers with Starlink mobile service push

SpaceX has told investors it is considering launching a standalone Starlink mobile service for US consumers, according to the Financial Times. SpaceX president Gwynne Shotwell raised the possibility during the company's IPO roadshow, saying SpaceX could build its own terrestrial US mobile network and sell directly to consumers rather than through carrier partners.

SpaceX is reportedly preparing to launch a direct-to-consumer mobile service in the US using its Starlink satellite network. According to a report from the Financial Times, the Elon Musk-helmed company is looking to build its own US mobile network” to directly compete against telecommunication giants like AT&T, Verizon, and T-Mobile.

While SpaceX currently works alongside T-Mobile to provide some extra cellular connectivity in rural regions, the company is now reportedly considering its own Starlink retail product. At a recent IPO roadshow, SpaceX president Gwynne Shotwell hinted to investors that the company is exploring creating its own network infrastructure.

In a sense, the groundwork for this move has already been quietly laid out. Over the course of late 2023 and last year, SpaceX bought close to $20 billion worth of wireless spectrum licenses from EchoStar. Those airwaves give Starlink the ability to build an affordable, strong direct-to-cell service without having to rely completely on other telecom companies. Oppenheimer analysts believe that as Starlink branches off into more direct-to-consumer products, it could seriously shake up the $1.6 trillion US comms industry.

SpaceX has told investors it plans to launch a Starlink mobile service for U.S. ‌consumers, the Financial Times reported on Friday, in ‌a move that could allow the Elon Musk-led company to compete directly with ​Verizon, AT&T and T-Mobile.

Here are some details:

• SpaceX already offers direct-to-cell connectivity with T-Mobile in the U.S., providing supplemental coverage from space to extend internet access to remote areas.

• SpaceX is ‌now considering launching ⁠a Starlink retail product and could build its own terrestrial U.S. mobile network, President Gwynne Shotwell ⁠told investors during a recent IPO roadshow, the FT report said, citing sources.

• Reuters could not immediately verify the report. ​SpaceX did ​not immediately respond to ​a Reuters request for comment ‌outside regular business hours.

• In September last year, SpaceX bought wireless spectrum licenses from EchoStar for its Starlink satellite network for about $17 billion and then again for $2.6 billion in November, giving it the ability to quickly create a strong ‌and affordable direct-to-cell service by ​using EchoStar's wireless airwaves.

• SpaceX will ​disrupt the $1.6 trillion U.S. ​communications industry as its satellite broadband unit ‌Starlink expands, brokerage firm Oppenheimer said ​in a ​note earlier this month.

• SpaceX's record valuation is grounded in Starlink, which has over 10 million subscribers, and ​a launch business ‌that analysts and investors say has transformed access to ​orbit.

This aggressive expansion into the mobile sector fits well with SpaceX’s overall push to squeeze every last drop of revenue out of their Starlink satellite internet service while satisfying new shareholders after its recent public offering pushed its valuation past the $2 trillion mark. As we recently reported, Starlink ended its free dish perks to shift to a new hardware rental model. Rather than offer the Standard dish as a free rental on Residential plans, the company now charges a $10 monthly kit fee.

The complementary Mini dish perk for the $130/month Residential Max plan was also retired. Those hardware monetization moves pave the way for the launch of a new, highly portable Starlink Standard Gen 4 kit and an upgraded Mini dish with a built-in battery.

Though its new terrestrial mobile network is focused on everyday consumers, SpaceX’s ambitions stretch further into heavy enterprise computing. SpaceX has been quietly working on building out a separate AI Orbital Data Center satellite constellation called Starmind. Designed to launch as a prototype in early 2027, the Starmind project will consist of up to a million AI-powered satellites intended to offload heavy computing workloads into orbit. By relying on limitless solar power and natural vacuum cooling, SpaceX aims to avoid the space, power, and water limits that are choking down Earth-bound AI data centers.

TECH

Plain-language AI workflow tool could cut cloud energy use and costs dramatically

Agentic workflows are artificial intelligence-powered software systems that chain together multiple models and external tools to tackle complicated tasks, like analyzing a video and answering questions about it. But the way these highly fragmented systems are designed and deployed often causes inefficiencies that can lead to wasted computation, energy and cost.

To improve efficiency, researchers from MIT and Microsoft developed an intelligent system that streamlines the process of designing agentic workflows and automatically optimizes how those workflows are implemented. With this new method, a developer can describe what they want the agentic workflow to do in plain language, without needing to specify all the details of their application in advance.

The system automatically figures out the best models and tools to use, as well as the ideal hardware configuration and computational resource allocation when the workflow is executed by a cloud provider. It adjusts those configurations on the fly based on each user's priorities, such as minimizing costs or maximizing speed.

When tested on several agentic workloads, this new system reduced the number of computational units needed for deployment, significantly cutting energy requirements and costs compared with traditional approaches without hampering performance.

"Agentic workflows are getting very complicated and quickly becoming the backbone of what cloud providers are doing. Energy usage is a huge concern, so we need to be very careful about how efficient these workflows are. It is very easy to over-allocate resources, wasting energy and money. Enabling a cloud provider to intelligently make these workflows more resource-optimal is a win for everyone involved," says Gohar Chaudhry, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on this system posted to the arXiv preprint server.

He is joined on the paper by Adam Belay, an associate professor of EECS and a member of the MIT Computer Science and Artificial Intelligence Laboratory; senior author Ricardo Bianchini, technical fellow and corporate vice president at Microsoft Azure; and others at Microsoft Azure. The paper will be presented at the USENIX Symposium on Operating Systems Design and Implementation (OSDI 26), held in Seattle, July 13–15.

A configuration conundrum...An agentic workflow is a system composed of several autonomous AI agents that collaboratively use various models and tools, like databases or Python programs, to dynamically complete a multistep task, such as data processing or code generation. These workflows can serve as behind-the-scenes processes that power user-facing applications.

Typically, developers must hard-code all technical choices upfront. They need to define which AI agents, models and tools to use, and the order in which to use them. They also must specify the hardware that runs the workflow and how to balance trade-offs like speed versus cost.

This is especially challenging because agentic workflows bring together multiple black-box models and diverse tools, each with its own configuration options, which may be offered by different companies. If a new AI model is released that would improve the application's accuracy or efficiency, the developer would need to start from scratch to implement it.

"Even if you wanted to do all this manually, it is unlikely that you'll be able to configure the workflow optimally because the space of possible configurations is so large," Chaudhry says.

In addition, the cloud data center that deploys the application for customers can't see inside the workflow to allocate its hardware resources in the most efficient manner at the time of the user's request.

With this new system, called Murakkab (an Urdu word that means a composition of things), the researchers sought to optimize the entire agentic workflow process.

Murakkab manages end-to-end workflow life-cycle: from development to optimized deployment and execution. Credit: arXiv (2025)

Dynamic decision-making...First, Murakkab enables developers to create an agentic workflow by describing their intent for the application in high-level terms, rather than detailing how the many components of that workflow should be combined. For instance, a developer might describe a video Q&A application that extracts key frames, generates a transcript and then answers user queries about the video.

"There are many ways to do this, and all these different models and tools have implications on how fast the application can finish the task," he says.

Murakkab takes the developer's straightforward specifications and automatically identifies the best existing models and tools to put together into the workflow. It also determines which components need to run sequentially and which can be run in parallel to boost performance.

"The platform makes configuration decisions dynamically over time, so if a new model or GPU accelerator comes out tomorrow, the developer doesn't need to worry about that," he says.

When the cloud provider deploys that application for a customer, Murakkab optimizes the workflow by configuring its components to meet the user's constraints, such as prioritizing accuracy while meeting a latency requirement. It adaptively identifies ideal hardware allocations and deployment schedules to maximize efficiency in real time, then generates a workflow that is ready for the cloud provider to execute.

"Our system also gives cloud providers visibility into multiple workloads, so the provider can share computational resources in the most efficient manner while satisfying the constraints of users," he says.

When tested on diverse agentic workflows for video Q&A and code generation, Murakkab met user requirements while using only about 35% of the computation required by other methods. It consumed only about 27% as much energy for less than 25% of the cost.

The dynamic nature of Murakkab also enables users to balance trade-offs. In one instance, the system lowered energy consumption of an agentic workflow by more than an order of magnitude with only about a 2% drop in accuracy for the customer.

The system was also able to identify an unexpectedly ideal configuration for a model that selects video frames, optimizing performance for a video Q&A task. This type of optimization would be nearly impossible for a developer to do manually, Chaudhry says.

Next, the researchers plan to expand their system to more complex workflows and larger computing clusters while exploring opportunities to optimize new agentic applications. "There is a lot of potential to make these workflows more resource-optimal so they consume far less energy, but we need to be thinking about this at the scale of major cloud platforms," says Chaudhry.

Provided by Massachusetts Institute of Technology 

TECH

Operation Endgame neutralizes dangerous malware networks

Europol announced a global offensive that resulted in the dismantling of malware networks, involving the takedown of hundreds of servers dedicated to digital extortion campaigns and credential harvesting. The joint law enforcement action, dubbed Operation Endgame, neutralized the operational nodes of the SocGholish, Amadey, and StealC criminal infrastructures.

The intervention, coordinated directly from The Hague by Europol’s European Cybercrime Centre and Eurojust, took place over the last two weeks. Financial and cyber authorities identified and froze illicit digital assets valued at over €41 million.

In terms of pure technological infrastructure, the operation took down 326 active servers and seized administrative control of 142 internet domains. These computing resources directly supported the spread of malicious agents and the centralized management of compromised computer networks.

Operation Endgame: Strategy Targets the Digital Crime Assembly Line... The focus of this operation represents a methodological shift in the activities of international law enforcement agencies. Instead of directing efforts toward the isolated mitigation of incidents or specific virus variants, police forces focused on dismantling the distribution chains for shared cybercrime services.

This integrated approach caused severe operational disruption within the access-provision ecosystem. According to technical reports validated by Microsoft—a private-sector partner in the operation—the Amadey and StealC tools alone were directly linked to active infections on more than 140,000 personal computers worldwide during the first half of May 2026.

The chain of these threats followed a corporate model of task division. The Amadey agent secured initial access to victims' systems, while StealC carried out the systematic extraction of passwords, access keys, and stored identities for subsequent sale on underground forums.

WordPress under monitoring following the mitigation of malware networks...The impact of the campaign linked to the SocGholish vector necessitated the urgent cleanup of 14,971 legitimate websites that had been compromised. The malicious code affected pages belonging to everyday service businesses—such as auto repair shops and restaurants—by exploiting vulnerabilities in content management platforms.

The tactic involved distributing fake web browser updates. Cybercriminals compromised the code integrity of WordPress installations and forced the display of fraudulent pop-up alerts, which downloaded the harmful executable file as soon as the user agreed to the installation.

Technical analysis links the SocGholish network to the Russian-based collective Evil Corp. This criminal organization has a long-standing history of developing large-scale financial threats, having been directly responsible for creating the Zeus and Dridex malware, as well as maintaining ties to global money laundering schemes. Operation Endgame relied on the real-time sharing of tactical data via SIENA, Europol’s secure communication platform. The Joint Cybercrime Action Taskforce ensured the alignment of national investigations to prevent the loss or scattering of evidence.

The effort combined operational expertise from the Royal Canadian Mounted Police, the Danish Police, Germany’s Federal Criminal Police Office, the Netherlands’ National High Tech Crime Unit, the UK’s National Crime Agency, and US federal agencies. The private sector contributed security experts from Microsoft, Proofpoint, IBM X-Force, Bitdefender, and the Shadowserver Foundation. In the context of information recovery, the operation enabled the retrieval of approximately 27 million sets of credentials that were in the attackers' possession. Europol began sharing this data with victim notification networks—including the NoMoreLeaks platform and the HaveIBeenPwned portal—to rapidly alert affected users.

Frequently Asked Questions (FAQ)

-What distinguishes Operation Endgame from other law enforcement actions?

This operation focused on the simultaneous neutralization of the entire technical supply chain of the cybercrime operation. By simultaneously disabling the servers supporting three malware variants, authorities cut off the supply of access and the harvesting of credentials that fueled subsequent digital extortion attacks.

-How did the SocGholish malware infect WordPress-based platforms?

SocGholish exploited vulnerabilities in WordPress-managed websites to inject malicious code. This code displayed fake web browser update alerts to visitors. Clicking the alert downloaded code that granted attackers remote control of the user's computer.

-How can users check if their credentials were recovered during this operation?

International authorities transferred the 27 million recovered records to trusted security databases, such as the HaveIBeenPwned service. Website owners and individual users can submit their addresses to these portals to confirm if they appear on the list of compromised accounts.

Key points:

-Seizure of over €41 million in crypto assets of criminal origin.

-Removal of 326 servers and administrative takeover of 142 domains used by the malware networks.

-Mitigation of the impact on 14,971 legitimate websites running on the WordPress content management system.

-Recovery and protection of 27 million access credentials stolen from users worldwide.

mundophone

TECH

AI-powered holographic display could bring Star Trek-style 3D images closer

Sci-fi holodecks and floating 3D projections just took a meaningful step closer to reality. In a study published earlier this month, researchers at the UCLA Samueli School of Engineering and the California NanoSystems Institute (CNSI) unveiled a method for projecting complex 3D scenes in a single shot, using a blend of artificial intelligence and physical light-programming optics.

Led by Dr. Aydogan Ozcan, the UCLA team took aim at one of the most stubborn bottlenecks in holographic display development, a problem the researchers call dense depth multiplexing.

To build a convincing three-dimensional image out of light, engineers typically slice a 3D object into layers and project those layers at different depths at once. As the depth layers pack closer together to create a solid, fluid illusion, the light waves bleed into one another. This phenomenon, known as diffraction-induced cross-talk, blurs the images and erodes depth selectivity, working against the natural focus cues that make a 3D display comfortable to look at in the first place.

Conventional fixes leaned on heavy computation or on time-sequential scanning that assembles the volume one slice after another, an approach that makes real-time 3D projection slow and power-hungry.

The UCLA solution is a hybrid digital-optical design that splits the workload between code and physical optics. At the front end sits a digital encoder, a neural network that does much of its work in the frequency domain. It reads the target scene across depth, pulls out features at several scales, tags each layer with its axial position, and compresses the whole stack into one phase pattern that the optics can later unpack.

That pattern then feeds a diffractive decoder, a passive stack of optical surfaces whose structure was shaped by machine learning. As light travels through the custom surfaces, the structure itself steers each image to its assigned depth and damps the bleed between planes. Notably, the team found that simply throwing more resolution at the encoder was not enough on its own. The learned optical decoder did the decisive work of pulling adjacent depths apart.

Schematic and numerical simulation results of the diffractive snapshot 3D display architecture(image above)

The results are striking. In numerical simulations, the system scaled up to volumetric scenes built from 28 distinct depth slices, holding separation between layers at distances on the order of a single wavelength of light, though fidelity softened slightly for slices buried in the middle of the stack. The researchers also showed the projection planes could be repositioned on demand rather than locked to fixed depths.

To prove the concept was more than a digital exercise, the team built a physical prototype that runs in visible red light at 650 nanometers. That setup paired the encoder with a single-layer decoder to project two depth planes, and the captured intensity patterns closely tracked the simulations while clearly beating a free-space setup with no decoder at all.

What makes the approach attractive for consumer electronics is its efficiency. Because the diffractive decoder is entirely passive, it bends and filters light without drawing any power of its own, moving work that would otherwise hammer a processor into the optics themselves. The team did flag a trade-off worth watching, since pushing for brighter output raised the diffraction efficiency but reintroduced speckle and cross-talk, leaving a balance to strike between brightness and clarity.

By easing the computational and energy demands tied to depth-resolved 3D projection, this light-programming framework could help pave the way for compact near-eye AR/VR optics, volumetric microscopy, and real-time 3D visualization. For now the researchers frame the work as a proof of concept, with multi-layer fabrication, full-color operation, and viewer-facing systems still on the road ahead.

mundophone

 

TECH

Forza Horizon 6 too arcadey? Steam's most popular racing sim is on sale for $5 until tomorrow

According to SteamDB, Assetto Corsa is the most popular racing simulation on Steam and should be a welcome alternative for anyone looking for a change from the arcade-heavy driving feel in FH6. The game is currently available on Steam at a 75% discount for around $5 – but only until tomorrow.

If the arcade-heavy driving feel in Forza Horizon 6 is starting to wear thin, Steam currently has an interesting alternative: Assetto Corsa is once again available with a 75% discount, dropping the price to around $5 instead of $20. According to SteamDB, the racing sim regularly attracts more than 10,000 concurrent players, making it the most popular racing simulation on Steam ahead of titles such as Automobilista 2 and rFactor 2. Anyone looking for a more authentic driving experience with realistic vehicle physics, laser-scanned tracks and extensive modding support should find plenty to like here. The offer is only available until tomorrow, June 25, at 7 p.m CEST / 10 a.m. PDT.

Unlike Forza Horizon 6, Assetto Corsa aims to be as realistic as possible. Vehicles react noticeably to weight, tire pressure, road surface and load transfer. Brake too late, accelerate too early or take the wrong line through a corner, and you will quickly lose valuable seconds – or end up in the gravel trap. The vehicle roster includes more than 170 licensed cars across multiple classes, from road cars and GT racers to Formula cars and historic classics. Races take place on numerous officially licensed tracks, including Monza, Imola and the Nürburgring. Thanks to a very active modding community, many additional cars and tracks have been added over the years.

The Steam reviews speak for themselves: Assetto Corsa has more than 170,000 reviews with a very positive average rating of 92%. Players should not expect an elaborate campaign, but many fans still regard it as a thoroughly successful racing simulation. Alongside the excellent driving feel, the realistic force-feedback effects are frequently praised. To make full use of that added immersion, however, a compatible sim-racing wheel such as the Logitech G G29 SE (currently around $370 on Amazon) is recommended. Alternatively, Assetto Corsa can also be played with a controller or, thanks to its “Verified” status, on the Steam Deck.

Steam's most popular racing simulation, Assetto Corsa, is on sale for 75% off (dropping to roughly $5 from $20). This massive discount is only valid until tomorrow, June 25.

The base game offers an incredibly realistic, physics-based driving experience that's widely celebrated for its modding community. If you are jumping into this deal, here are the essential next steps:

Get the Ultimate Edition: It is highly recommended to pick up the Assetto Corsa Ultimate Edition, as most of the game's best mods require the included DLC tracks and cars.

Essential Mods: The community strongly agrees that installing Content Manager, Custom Shaders Patch (CSP), and Pure will totally overhaul the game's graphics, physics, and UI.

Online Racing: Once you are comfortable behind the wheel, you can join online racing platforms like Low Fuel Motorsports to participate in structured races, practice sessions, and qualifying.