MIT researchers have developed a low-power chip that enables tiny drones and robots to build detailed 3D maps of their surroundings in real time while consuming only about 6 milliwatts of power. The system-on-a-chip, called Gleanmer, could help battery-powered autonomous machines navigate cluttered environments such as industrial ventilation systems, warehouses, tunnels, and other confined spaces where obstacle avoidance is critical.

The technology may also find applications in lightweight augmented reality headsets, allowing them to map indoor environments without draining batteries. The chip combines specialized hardware with a compact mapping algorithm that dramatically reduces the memory and energy needed to create 3D representations of the world around a robot.

Mapping without burden

Building detailed 3D maps typically requires robots to process large volumes of image data and store complex representations of their surroundings. These tasks often demand significant memory and power, making them difficult to deploy on small battery-powered devices.

Instead of relying on conventional voxel-based maps, which represent environments using millions of tiny cubes, the MIT team uses flexible ellipsoid shapes known as Gaussians. These shapes can more efficiently represent curved objects and open spaces while requiring far less memory.

The researchers paired the chip with a mapping algorithm called GMMap, which creates 3D maps from depth images in a single pass. This allows the system to discard image data almost immediately instead of repeatedly storing and processing it.

“At any point in time, we only need to store a few pixels in memory, which significantly reduces the memory footprint our algorithm requires,” said Peter Zhi Xuan Li, one of the study’s co-lead authors.

The system also avoids another common challenge in mapping. As a robot moves, it often observes the same object from multiple angles, creating overlapping representations that increase map size. The MIT team developed a method to merge overlapping Gaussians directly without returning to the original image data.

Tiny chip, big reach

This approach allowed the researchers to keep much of the active data in fast on-chip memory rather than relying on power-hungry external storage. “By having a dedicated memory that just stores the objects you’ve seen in the previous few frames, you can access the data much more efficiently,” said co-lead author Zih-Sing Fu.

In tests involving a variety of previously recorded environments, Gleanmer generated detailed 3D maps in real time while consuming about 6 milliwatts of power. According to the researchers, this is roughly 2.5% of the energy required by the best existing chip designed for map construction.

The chip can also reconstruct obstacles and free space directly from live data streamed from an iPhone camera. By reusing compact Gaussian representations during path planning, the system enables robots to calculate collision-free routes using about 20% of the energy typically required.

“This paper showcases a key example of how you can leverage co-design of the algorithm and hardware to really push energy efficiency,” said Vivienne Sze, professor of electrical engineering and computer science at MIT and senior author of the study.

The researchers believe future versions could become even more efficient by placing computing resources closer to onboard sensors. Beyond robotics, the team is also exploring whether Gaussian-based representations could help computing systems process technical drawings and complex schematics more efficiently.

The research was presented at the IEEE Very Large-Scale Integrated Circuits Symposium.

The U.S. Department of Energy has conditionally committed up to $17.5 billion in loan facilities to support the construction of as many as 10 AP1000 nuclear reactors in the United States, Brookfield Asset Management announced.

The financing package is aimed at funding long-lead equipment required for reactor construction, a step that could significantly shorten project timelines and strengthen the domestic nuclear supply chain.

The loans would support projects using Westinghouse’s AP1000 reactor technology. Westinghouse is jointly owned by Brookfield and its institutional partners, which hold a 51% stake, and Cameco, which owns the remaining 49%. According to Brookfield, the funding could accelerate construction and commercial operation schedules by as much as three years, with a goal of having 10 reactors under construction by 2030.

Fast-tracking reactor projects

The Department of Energy’s Office of Energy Dominance Financing is expected to provide as many as five separate loans, with each loan supporting two reactors.

Rather than financing completed projects, the funding is intended to help utilities and energy companies secure critical equipment early in the development process. Long-lead components are often among the biggest bottlenecks in nuclear construction because manufacturing and delivery can take several years.

Brookfield said the financing would provide project developers with greater certainty while supporting efforts to expand domestic manufacturing capacity for nuclear equipment. The announcement comes as the United States seeks additional sources of reliable electricity to meet growing demand from industry, data centers, and electrification initiatives.

Nuclear power has regained attention in recent years because reactors can provide continuous carbon-free electricity regardless of weather conditions. “Westinghouse continues to be at the forefront of major public and private partnerships that will materially accelerate the build-out of large-scale nuclear power generation, help meet growing energy demand, and support energy security in the U.S.,” said Connor Teskey, Chief Executive Officer of Brookfield Asset Management.

Supply chain gets boost

The proposed funding is tied to Westinghouse’s AP1000 reactor design, one of the few advanced large-scale reactor technologies currently licensed and operating commercially in the United States. Brookfield said the loans are expected to act as a catalyst for new nuclear development by helping project owners secure equipment orders earlier than would otherwise be possible.

Teskey added: “The loan facilities help advance President Trump’s Executive Order and serves as a catalyst for nuclear, providing the certainty needed to enhance the domestic nuclear supply chain and accelerate construction of nuclear projects that will deliver reliable baseload power around the country for decades to come.”

The funding package remains conditional. Before any money is disbursed, Westinghouse, project partners, and potential reactor owners must satisfy technical, legal, environmental, and financial requirements set by the Department of Energy.

If finalized, the loans would represent one of the largest federal financing efforts aimed at accelerating new nuclear reactor deployment in the United States in recent years.

Australia-based technology company BrainChip has launched a new hardware platform designed to classify radio frequency (RF) signals in real time while operating on less than a watt of power, targeting defense and intelligence applications that require processing at the edge.

Called the Akida Communication Reference Platform, the system is built around the company’s Akida AKD1500 neuromorphic processor and is intended for defense contractors, government agencies, software-defined radio vendors and edge AI developers.

The platform performs RF signal classification directly on-device, eliminating the need for cloud connectivity or large computing hardware. BrainChip said the system is designed for environments where power availability, thermal constraints and size limitations make conventional GPU- or FPGA-based solutions difficult to deploy.

Potential applications include handheld signal intelligence systems, unmanned aerial vehicles, satellite communications terminals and other portable defense technologies.

AI tackles RF threats

According to BrainChip, the platform can identify more than 20 signal modulation types in real time while maintaining greater than 85% accuracy at a signal-to-noise ratio of 30 decibels.

Traditional digital signal processing systems typically rely on rule-based approaches that can struggle to identify new or intentionally modified signals. BrainChip says its neuromorphic AI approach allows the system to capture unknown waveforms and use them for future model retraining, enabling adaptation to emerging wireless threats.

The company argues that this flexibility addresses a key limitation of existing RF classification systems, which often require significant computational resources and can be difficult to update for changing operational conditions.

The platform is also designed to support battery-powered deployments where continuous operation is required without access to external infrastructure.

“BrainChip’s Akida Communication Reference Platform proves that real-time signal intelligence can be condensed into a portable battery powered solution to extend the range of deployment options,” said Sean Hehir, BrainChip’s CEO.

Built for edge deployment

The platform is available for evaluation and partner integration as a reference design kit. It supports integration with software-defined radio front ends such as the USRP B205mini and EPIQ Sidekiq.

A host system, including devices like the Raspberry Pi 5, can be used to manage data flow and application development. BrainChip said engineering teams can use the platform to prototype intelligence, surveillance and reconnaissance capabilities, as well as broader signal intelligence applications.

The launch expands the company’s portfolio of edge AI reference platforms beyond radar and sensor-fusion systems. BrainChip says the new offering demonstrates how neuromorphic computing can be applied to RF processing workloads that traditionally require larger and more power-hungry hardware.

The release comes as defense agencies and communications providers increasingly explore AI-powered spectrum monitoring tools capable of operating in remote and contested environments. By reducing power consumption and hardware requirements, such systems could enable RF awareness capabilities in smaller platforms that previously lacked sufficient computing resources.

As military and commercial users continue pushing AI capabilities closer to sensors and data sources, low-power processors capable of running advanced inference at the edge are becoming increasingly important for real-time decision-making in disconnected environments.

Scientists have discovered a new way to control quantum light sources by twisting atomically thin layers of a material known as hexagonal boron nitride (hBN), a breakthrough that could help bring quantum technologies closer to practical use.

Researchers from the University of Technology Sydney found that rotating and restacking layers of hBN can significantly alter the color and wavelength of light emitted by quantum emitters embedded within the material.

Quantum emitters are tiny light sources that can produce single photons, making them important building blocks for future quantum computers, secure communication networks, and highly sensitive sensors. While scientists have been able to detect and study these emitters, controlling them has remained a major challenge.

The team says its approach offers a new way to tune these light sources by exploiting the unique layered structure of hBN, a material that can be repeatedly separated, twisted, and reassembled.

Twisting light into control

Lead author Dr. Angus Gale said the findings provide researchers with a new tool for manipulating quantum emitters.

“You can measure these quantum emitters and see that they exist, but it’s hard to make them work in practice. This gives us a lever to get closer to that – a step towards the realisation of quantum technologies,” said Dr Gale.

In experiments, the researchers were able to produce a significant shift in the emitted light by changing the twist angle between layers. Unlike many studies where materials are assembled once and left unchanged, the team repeatedly picked up, twisted, and restacked the layers while continuing to modify the optical properties.

“We’re leveraging the fact that this material, hexagonal boron nitride (hBN), is layered. We can pick it up, stack it, twist it, and use that twist to modify the emitters. You can’t really do that with traditional materials like diamond or silicon carbide.”

According to the researchers, the amount of tuning achieved was larger than expected and exceeded what is typically possible in many other quantum emitter platforms.

“The benefit is that we used this twistable platform to shift the emission by a very significant amount,” said Gale. “Often when you control these systems, the amount of manipulation is very limited, but in this case the shift was much larger than expected.”

New path for quantum

Rather than forcing hBN to behave like more conventional quantum materials, the team focused on taking advantage of its natural properties.

“Rather than trying to make hBN defects behave like a traditional solid-state hosts, we took advantage of hBN’s own strength: its thin, layered, twistable structure.”

Gale compared the material to slices of cheese rather than a solid block.

“With a block of cheese, you can’t really get to the flavour in the middle. But with slices, you can peel away layers, put them back together and change how they interact,” he said.

Professor Igor Aharonovich said twisting layered materials can produce entirely new physical behaviors.

“You can take two layers that don’t do much on their own, put them together at a specific angle, and suddenly you have a completely different system,” said Professor Aharonovich.

The researchers believe the approach could eventually contribute to the development of quantum computing, quantum communication, and quantum sensing technologies used in fields ranging from healthcare to cybersecurity and navigation.

The study was published in Advanced Materials.

Sensory Robotics has received safety certification for a system designed to let industrial robots operate alongside people without the protective cages commonly used on factory floors. The certification clears the way for deployment of the company’s SR-1 technology in regulated manufacturing environments across the United States and Canada.

The SR-1 system combines 3D vision technology, sensors, and real-time safety software that continuously monitors the area around robotic arms. Instead of relying on physical barriers, the system creates virtual safety zones that adjust based on human movement and machine activity.

The company says the technology can be installed on existing industrial robotic production cells, potentially allowing manufacturers to retrofit current equipment rather than replace it. The goal is to enable human workers and high-speed industrial robots to share the same workspace safely.

The certification includes cULus 1740 and ISO 13849 Performance Level d validation, standards widely recognized in industrial automation and machine safety. The approvals mark the transition of the technology from development and testing into commercial deployment.

Invisible safety zones emerge

“Without this safety certification, our technology doesn’t leave the lab, and it doesn’t reach the factory floor,” Sensory Robotics CEO Chris Edwards says. “Now, it can.”

Industrial robots have long been separated from workers by fences and cages because of the speed and force at which they operate. While collaborative robots have been designed to work closer to humans, many traditional robotic systems still require physical barriers to meet safety requirements.

Sensory Robotics says SR-1 addresses that challenge by continuously tracking people near robotic cells and adjusting robot behavior in real time.

“We designed SR-1 to continuously see people and adjust robot movements in real time,” Edwards says. “This UL certification now allows our technology to be purchased and installed on industrial robots, enabling them to safely operate alongside humans without physical barriers.”

According to the company, the certification process evaluated how the system responds to equipment failures, safety-function disruptions, and potential risks to workers. Such certifications are often required before technologies can be introduced into regulated manufacturing facilities.

Factory robots lose fences

The company argues that eliminating physical cages could free up factory floor space, improve workflow flexibility, and reduce production interruptions. Traditional robotic work cells often require complete shutdowns when workers enter restricted areas, creating downtime that can accumulate across large manufacturing operations.

“The goal is simple,” says chief operating officer Mark Gagas. “Keep people safe without stopping production every time someone enters a workspace. In traditional environments, a safety interruption can require a full robot shutdown and restart, sometimes taking up to 10 minutes per incident. Add that up across a production line, and those delays compound into high operational costs.”

The company says its system is already attracting interest from sectors including automotive, aerospace, logistics, manufacturing, and defense. Sensory Robotics also received a $1.25 million Department of Defense SBIR Phase II grant and additional support through the University of Cincinnati’s innovation ecosystem.

“These combined certifications are the key that unlocks real-world industrial adoption and approval for companies to purchase fenceless human-robot collaboration systems like SR-1,” Gagas says. “It means regulated manufacturing environments can now trust and deploy this technology into their robots with confidence.”

Europe’s defense industry is accelerating the development of a new long-range cruise missile capable of striking targets more than 2,000 kilometers (1,243 miles) away. At Eurosatory 2026 in Paris, the joint venture Rheinmetall Destinus Strike Systems announced plans to fast-track the introduction of the Ruta Block 3 missile while beginning production of two shorter-range systems, Kryla and Ruta Block 2.

The companies say the Ruta Block 3 is designed for strategic deep-strike missions against high-value and hardened targets. The missile will carry a warhead of up to 250 kilograms (551 pounds) and be launched from standard shipping containers, allowing deployment from land vehicles and maritime platforms. According to the joint venture, the system can be made ready to fire in about two minutes.

The program is being developed with NATO qualification in mind, a step that would make the missile available to NATO and European Union member states. The announcement comes as European countries continue to expand domestic defense manufacturing capabilities and reduce reliance on non-European suppliers.

The missile family is being developed through a partnership that combines Destinus’ missile technologies with Rheinmetall’s manufacturing and defense production expertise. The companies have already signed a term sheet and say a final shareholders’ agreement is close to completion.

Container launch, rapid strike

Ruta Block 3 is the most advanced missile in the joint venture’s roadmap, but production will begin with two existing systems. The first is Kryla, a compact cruise missile carrying a 50-kilogram warhead designed for saturation attacks. The missile can be launched from containers, giving existing artillery units access to cruise missile capabilities.

The second system, Ruta Block 2, carries a 551-pound warhead and is intended for attacks on hardened and high-value targets. Like Ruta Block 3, it launches from standard containers rather than dedicated missile launchers.

“Together we are advancing NATO qualification on an accelerated path, embedded in existing programmes for European defense ministries. This allows us to rapidly provide European armed forces with a ready-to-deploy, certified and fully European effector,” says Roman Köhne, Head of Division Weapon and Ammunition, Rheinmetall.

European supply chain focus

The joint venture says all three missiles will be produced through a fully European supply chain. To support that goal, Rheinmetall Destinus Strike Systems plans to establish a facility in Germany for final assembly, integration, and testing. Initial delivery readiness is targeted for 2026.

The companies also emphasize the flexibility offered by containerized launch systems, which can be transported through existing logistics networks and deployed across a wide range of platforms.

“We are firmly committed to launch from standard sea containers. This gives our customers maximum flexibility: our systems can be deployed across virtually any land and sea platform and through existing logistics chains – concealed and brought to firing readiness in the shortest time,” says Mikhail Kokorich, Founder and CEO of Destinus.

Under the partnership, Destinus will provide the missiles’ core technology while Rheinmetall will supply warheads and booster rocket motors, creating what the companies describe as a fully European deep-strike missile portfolio.

Phoenix Semiconductor has won a Phase II SBIR contract from the U.S. Defense Logistics Agency to develop drop-in replacements for obsolete microelectronic components used in defense systems.

Based in Austin, Texas, the company will design and validate four legacy chips facing supply shortages across military platforms. The program aims to maintain critical systems without requiring redesigns of existing hardware or software, addressing long-standing issues tied to discontinued semiconductors.

One of the key projects under the contract is the recreation of the Signetics 82S100 Bipolar Field-Programmable Logic Array, originally introduced in 1975 and discontinued in the late 1980s. The chip supports the Catapult Assisted Take-Off but Arrested Recovery system used to launch aircraft from Nimitz-class aircraft carriers.

Phoenix is working with Naval Air Systems Command on the project. The goal is to deliver a form-fit-function replacement that avoids expensive system-level changes, which can require extensive certification and shipyard time across fleets.

Keeping legacy systems alive

Defense platforms often remain in service for decades, while semiconductor lifecycles last only a fraction of that time. This mismatch has created a persistent obsolescence problem across the defense supply chain. The Department of Defense estimates redesign and replacement efforts can cost around $5 million over five years per instance, while broader diminishing manufacturing sources and material shortages mitigation costs exceed $2.4 billion annually.

Phoenix says its Phase I program demonstrated cycle-accurate replacement chips that were successfully tested in a live commercial system without requiring hardware or software changes. The company’s method focuses on producing form, fit, and function compatible components that can be directly inserted into existing systems, reducing downtime and eliminating the need for full requalification in critical defense applications.

Reviving retired defense chips

Ryan Hatcher, CEO and founder of Phoenix Semiconductor, said the award validates its approach. “This DLA SBIR Phase II award and our work with NAVAIR is a direct validation of what Phoenix has built — a faster, more cost-effective path to restoring access to mission-critical microelectronics that power the platforms our warfighters depend on. Working alongside our partners, we are proving that American ingenuity can solve one of the most pressing vulnerabilities in our defense industrial base — without multi-million-dollar redesigns and years of delay.”

Tackling defense obsolescence crisis

The program also aligns with the Defense Logistics Agency’s modernization and supply chain strategy and provisions in the FY2025 National Defense Authorization Act covering microelectronics obsolescence mitigation, supply chain risk management, and domestic manufacturing expansion.

Phoenix’s patent-pending approach does not require new silicon fabrication or original wafers. The company says its drop-in components are designed to match original form, fit, and function, allowing military systems to continue operating without redesigns while reducing cost and lead times for legacy part replacement.

By focusing on legacy component replication, the company aims to reduce dependency on fragile global supply chains and shorten repair timelines for aging defense systems. The approach could also support other industries that rely on long-life industrial hardware systems worldwide.

Researchers in Austria have developed a new battery management system (BMS) that can detect hidden damage and track aging inside electric vehicle batteries, potentially improving safety, performance, and lifespan.

The technology was developed through the EU-funded Nemo project by Graz University of Technology (TU Graz), Vrije Universiteit Brussel, and several industry partners. Unlike conventional battery management systems that mainly monitor voltage, current, and temperature, the new approach provides direct insight into conditions inside battery cells.

Current battery systems often rely on external calculations to estimate battery health. As a result, damage or aging inside individual cells can be difficult to identify until performance begins to decline.

The researchers say the new models and algorithms allow the battery management system to independently identify faults, monitor cell degradation, and determine when maintenance may be needed.

Looking inside batteries

A key part of the project involved improving the system’s ability to detect safety risks before they become serious problems.

“The battery management system is an important tool for operating electric vehicles more safely and sustainably,” said Christoph Drießen from the Vehicle Safety Institute at TU Graz.

To train the system, researchers deliberately damaged battery cells in laboratory tests. Some cells were mechanically deformed to simulate incidents such as minor parking impacts. The resulting data was then used to develop algorithms capable of recognizing similar signs of damage in real-world batteries.

The system relies on electrochemical impedance spectroscopy (EIS), a sensor-based technique that measures electrical resistance inside battery cells. This allows engineers to collect information directly from within the battery rather than inferring its condition through external measurements alone.

Researchers say this additional layer of monitoring could help identify damaged cells at an earlier stage, reducing safety risks and allowing maintenance before larger problems develop.

“If we recognise faults and damage to individual battery cells at an early stage via the BMS, many dangers can be avoided,” Drießen said.

Smarter aging detection

Beyond safety, the researchers also focused on understanding how batteries age over time.

The TU Graz team developed a model that predicts changes in battery cell volume during charging and discharging cycles. Excessive expansion can increase mechanical pressure inside a battery pack, raising the risk of cracks, deformation, internal short circuits, and temperature spikes.

Meanwhile, researchers at Vrije Universiteit Brussel developed models that track aging and service-life changes within individual cells.

According to the team, existing battery checks mainly reveal how much overall capacity has been lost compared to a battery’s original condition. The new approach aims to provide a more detailed picture of what is happening inside the cells as they age.

“Up to now, a test only showed how much the capacity has decreased compared to the original battery condition,” said Drießen.

“But the new models also give us an insight into the changes within the cells as they age. This enables adjustments that are beneficial for performance, service life and safety.”

Despite the added functionality, researchers say the enhanced battery management system would not significantly increase the size or weight of existing systems. A demonstrator has already been built at the battery module level, while a follow-up project will focus on advancing the technology toward industrial deployment.

The study appears in Journal of Power Source.

Scientists have discovered that seismic waves from Japan’s devastating 2011 earthquake traveled to Earth’s core and back, triggering a second tectonic slip event that shifted the country eastward by up to 6 millimeters.

The newly identified event occurred about 16 minutes after the magnitude 9.0 Tohoku-Oki earthquake struck off Japan’s northeastern coast. Researchers say the waves traveled roughly 3,600 miles (5,800 kilometers) through the planet, reflected off Earth’s liquid outer core, and returned to the surface.

The returning waves appear to have triggered movement along major tectonic plate boundaries around Japan, creating a broad seismic event that had gone unnoticed for years.

The findings help explain a mysterious signal recorded by Japan’s extensive GPS network shortly after the earthquake. Stations across the country registered a sudden eastward shift at nearly the same time, even though no known aftershock had occurred.

Mystery signal explained

The 2011 Tohoku-Oki earthquake ranks among the most powerful ever recorded. Along with the tsunami it generated, the disaster claimed about 20,000 lives and produced one of the most comprehensive sets of earthquake measurements ever collected.

Years later, however, one piece of data continued to puzzle scientists. GPS stations detected a synchronized eastward movement across Japan that did not match any known aftershock activity.

“Most of the time, we would see an offset like this when there’s actual earthquake happening. But here there was no known aftershock at this time, so we were quite curious,” said Sunyoung Park, a geophysicist at the University of Chicago and lead author of the study.

Park and her colleagues ruled out several possible explanations, including an undersea landslide and slow fault movement. Instead, they concluded that seismic energy from the original quake had traveled deep into Earth, struck the outer core, and rebounded back toward the crust.

When the waves returned, they triggered additional slip along plate boundaries surrounding Japan. Researchers believe the intense shaking from the main earthquake may have weakened these faults, making them more susceptible to later movement.

Core bounce effects

The newly recognized event stretched across roughly 1,800 miles (3,000 kilometers), making it the broadest seismic event ever recorded, according to the researchers.

The team estimates it released energy comparable to a magnitude 7.5 earthquake. It also involved multiple major plate boundaries, including the Pacific-Okhotsk boundary and the Philippine Sea-Eurasian boundary.

Scientists have long known that seismic waves can travel through Earth and reflect off deep internal structures. However, this is the first documented case in which those reflected waves appear to have triggered tectonic slip near the surface.

“It’s striking because this is both an unprecedented length and area for a seismic event, and it is a previously unrecognized source of seismic hazard,” said Park.

The discovery could influence how researchers think about large earthquakes and their lingering effects.

“This indicates that large earthquakes can influence the fault even after the main shaking is over,” Park said.

The researchers say the finding highlights how much remains unknown about the behavior of large earthquakes and the complex interactions between seismic waves and tectonic plates.

The study was published in the journal Science.

Mach Industries has won a Defense Innovation Unit (DIU) contract to develop a long-range unmanned aircraft designed to launch from austere locations and ships without large flight decks.

The aircraft, called Atlas, is being developed for the DIU’s Runway Independent Maritime Expeditionary Strike (RIMES) program. Mach Industries will serve as the aircraft integrator, working with propulsion company Whisper Aero.

According to the solicitation, the Department of the Navy is seeking an unmanned aerial system capable of conducting long-range strikes while operating from expeditionary sites with minimal infrastructure or from ships that lack conventional runways.

Mach said Atlas is designed to meet those requirements with a hybrid-electric propulsion system, runway-independent operations, a 1,000-pound payload capacity, and a range of 1,400 nautical miles.

Built for austere operations

The aircraft combines Mach Industries’ platform development capabilities with Whisper Aero’s JetFoil propulsion technology.

Unlike conventional fixed-wing aircraft that require runways, Atlas is being designed to operate from unimproved landing zones while retaining the control characteristics of a fixed-wing platform. The companies say the approach could give military units greater flexibility in contested environments where traditional airfields may be unavailable or vulnerable.

Excited to announce Atlas, our VTOL strike and logistics aircraft for the Navy. pic.twitter.com/fvbLWujnVN

— Mach Industries (@Mach_Industries) June 16, 2026

The aircraft is also intended to support distributed operations, a growing focus for the U.S. military as it prepares for conflicts in which logistics networks could come under attack.

In recent testimony before the House Armed Services Committee, Under Secretary of Defense for Research and Engineering Emil Michael identified contested logistics as one of the Pentagon’s critical technology priorities. The challenge centers on sustaining military operations when transportation routes, supply chains, and support infrastructure are disrupted.

Mach says Atlas addresses that challenge by reducing infrastructure requirements for launch and recovery while simplifying maintenance through a highly redundant propulsion architecture and a lower part count.

“Mach’s speed to prototype and production, coupled with Whisper Aero’s novel aerodynamics and propulsion makes Atlas a revolutionary air mobility platform,” said Nathan Diller, President and Chief Strategy Officer at Mach Industries.

Quiet propulsion advantage

A key feature of the aircraft is Whisper Aero’s JetFoil technology, which the company says improves efficiency while reducing acoustic signatures.

The system is designed to generate lift and thrust more efficiently than traditional approaches, helping extend range while allowing operations from confined locations. Lower noise levels could also make the aircraft more difficult to detect during missions.

“We developed JetFoil to propel the next generation of conventional, short, and vertical takeoff and landing aircraft silently and efficiently,” said Mark Moore, CEO of Whisper Aero.

According to Moore, the technology allows Atlas to meet RIMES requirements while operating from smaller naval vessels. “With JetFoil, Atlas can effectively meet the needs of the RIMES mission to operate even from destroyer class vessels.”

The award adds to Mach Industries’ expanding defense portfolio. Founded in 2023, the company says it is currently flying five different platforms and has manufactured more than 250 aircraft. Over the past two months, it has also conducted flight operations in four countries under complex electromagnetic conditions.

If successful, Atlas could provide the Navy and joint force with a long-range strike platform capable of operating from locations where traditional aircraft cannot, while reducing dependence on large runways and established air bases.

The U.S. Army has awarded defense and technology company Palladyne AI two contracts to test its AI-powered swarm software and reusable strike drone with soldiers during field exercises in Colorado and California.

The contracts, awarded under the Army’s Disruptive Applications Broad Agency Announcement, will support operational validation of the company’s SwarmOS autonomy platform and the Gremlin-X unmanned aerial vehicle.

The technologies will be evaluated by soldiers from the Army’s 4th Infantry Division during reconnaissance and target acquisition exercises. Palladyne AI said the demonstrations will use Army-specified platforms and the Android Team Awareness Kit (ATAK), a command-and-control system widely used by U.S. forces.

The effort reflects the Army’s growing interest in autonomous systems that can operate in environments where communications are limited or disrupted.

One operator, many drones

SwarmOS is an autonomy software stack designed to allow a single operator to control multiple autonomous systems from different manufacturers at the same time.

According to the Utah-based company, the software runs on edge hardware and is designed to function in degraded or denied communications environments. Rather than relying on centralized control infrastructure, the platform enables autonomous systems to coordinate with one another while operating in the field.

“The hardest problem in autonomous systems isn’t making one platform smart, it’s making heterogeneous platforms from different manufacturers collaborate intelligently without dependence on centralized infrastructure that adversaries can target and defeat,” said Dr. Denis Garagic, Chief Technology Officer and Principal Investigator, Palladyne AI.

He added: “We solved that.”

The Army exercises will evaluate how the software supports reconnaissance and target acquisition missions while integrating with existing military command-and-control tools.

Reusable strike drone

The second technology being tested is Gremlin-X, a Group 2 multirotor drone being developed as a reusable loitering munition.

Unlike traditional loitering munitions that are typically lost after striking a target, Gremlin-X is designed to return and be recovered after a mission. The company said this approach could reduce costs because only the munition payload would need replacement rather than the entire aircraft.

Gremlin-X is intended to operate in denied, degraded, intermittent, and limited communications environments, often referred to as DDIL conditions. The drone is being developed to support small, dispersed military formations that may need to engage targets without relying on centralized command networks.

Beyond the 4th Infantry Division exercises, Palladyne AI plans to demonstrate SwarmOS, IntelliSwarm, and Gremlin-X during Northern Strike 26-2, a large U.S. military training exercise involving more than 9,000 participants.

“This contract marks a decisive shift in how the U.S. Army is engaging with autonomous systems, moving from evaluation to funded operational use in the field,” said Doug Dynes, President of Palladyne Aerospace and Defense.

The company said the demonstrations will help validate the technologies in operational settings and could support future defense opportunities as the military continues exploring autonomous systems, drone swarms, and human-machine teaming concepts for battlefield operations.

European Space Agency (ESA) engineers are assembling one of Europe’s most advanced robotic arms, a system designed to handle samples and perform complex tasks during future missions to the Moon and Mars.

Known as the Sample Transfer Arm (STA), the robot can extend up to 2.4 meters and move with seven degrees of freedom, giving it a range of motion similar to a human arm. The system is equipped with cameras, sensors, and onboard electronics that allow it to perceive its surroundings and perform tasks with a high level of autonomy.

The robotic arm was originally developed as part of the joint NASA-ESA Mars Sample Return campaign. Its role was to transfer Martian samples collected by NASA’s Perseverance rover for eventual return to Earth.

Although the future of Mars Sample Return remains uncertain, the technology is now being positioned for a wider range of applications, including future lunar exploration missions.

Human-like space helper

The arm features a shoulder, elbow, and wrist configuration similar to a human arm. At its tip is a gripper capable of handling objects with millimeter-level precision.

The system also includes a sophisticated force and torque sensor that acts as a sense of touch. The sensor measures how an object is being pushed, pulled, or twisted in three-dimensional space, allowing the arm to manipulate items with greater accuracy.

Position sensors embedded throughout the joints continuously calculate the location of the arm’s tip, helping maintain precise control during operations.

Engineers say this level of precision could prove useful for a variety of activities in space, including collecting geological samples, transferring equipment, and supporting astronauts during surface missions.

The robotic arm also contains its own electronics unit, which acts as the system’s control center. Cameras mounted on the arm provide visual awareness, enabling the robot to detect and interact with objects in its environment.

Ready for testing

Teams at Italian aerospace company Leonardo are currently completing the integration of the system at the company’s facility in Nerviano, near Milan.

In the coming weeks, engineers will begin testing the arm in simulated space environments to evaluate its performance before any future deployment.

The project brings together companies and suppliers from across Europe. The industrial consortium is led by Leonardo and includes GMV and AVS from Spain, Maxon from Switzerland, 3DPlus from France, and COMOTI from Romania, along with suppliers from Denmark, Greece, and Germany.

The arm incorporates several specialized systems designed for spaceflight. These include a flexible wrist mechanism that allows softer contact with objects, a flat electrical harness that carries hundreds of signals throughout the arm, and structural mechanisms that help withstand the forces experienced during launch and landing.

European space agencies view advanced robotics as a key capability for future exploration missions, particularly as crews prepare for longer stays on the Moon and eventual missions to Mars.

With its ability to see, feel, and autonomously manipulate objects, the Sample Transfer Arm could become an important tool for handling samples and supporting scientific operations beyond Earth.

Researchers at Harvard University have developed a semiconductor chip that can synthesize 64 different DNA sequences in parallel using electric currents and a water-based enzymatic process, potentially offering an alternative to conventional DNA manufacturing methods.

The chip uses localized electrical control to trigger DNA synthesis at selected sites on its surface. The team says the approach avoids the solvent-heavy phosphoramidite chemistry widely used to produce synthetic DNA today.

Synthetic DNA is a key tool in modern biotechnology, supporting applications ranging from diagnostics and genome engineering to cancer research. While enzymatic DNA synthesis has emerged as a more environmentally friendly alternative, it has struggled to match the scale of conventional methods.

According to the researchers, enzymatic approaches have so far been limited to producing about a dozen DNA sequences simultaneously. In the new study, the chip generated 64 distinct DNA sequences in parallel, with each sequence reaching up to 39 nucleotides in length.

Electricity guides DNA

DNA synthesis occurs one nucleotide at a time. After each addition, a temporary blocking group must be removed before the next nucleotide can be attached.

To control this process, the Harvard team designed a chip with 64 synthesis sites. Each site contains two concentric ring electrodes surrounding DNA strands anchored at the center.

When activated, the inner electrode generates protons that lower the pH around a selected DNA strand. This acidic environment enables enzymatic DNA growth. At the same time, the outer electrode consumes diffusing protons, preventing the low-pH region from spreading to neighboring sites.

By repeating this process across selected locations during each synthesis cycle, the chip can build many different DNA sequences simultaneously.

The work builds on a semiconductor platform originally developed for neuroscience applications.

“A defining feature of the chip was precision current injection, which we used to permeabilize neuronal membranes for intracellular access,” said Donhee Ham, John A. and Elizabeth S. Armstrong Professor of Engineering and Applied Sciences at Harvard.

“At a certain point, we wondered whether that same current control could be redirected from cells to molecules – replacing the neuron-facing electrodes with ring-electrode pairs that could localize pH for DNA synthesis. It worked.”

Data storage potential

Beyond biological applications, the researchers explored whether the technology could support DNA-based data storage.

Using the 64 synthesized DNA sequences, the team encoded a 169-byte text message, demonstrating the platform’s potential for storing digital information in DNA molecules.

The researchers believe a water-based synthesis approach could become increasingly important if DNA production scales dramatically in the future.

“DNA data storage asks DNA synthesis to operate at a scale far beyond today’s needs,” said Woo-Bin Jung, co-first author of the study.

“That is why enzymatic synthesis in water can matter. If far more than 64 sequences can be synthesized in parallel, it could offer an environmentally friendly route toward writing DNA at very large scale.”

The team also attempted to increase the density of synthesis sites on the chip. While those experiments failed, they revealed that the main limitation came from the chemistry used to remove blocking groups rather than from the chip’s electronic architecture.

“The chip did what we asked it to do: it localized low pH at selected sites,” said Han Sae Jung, co-first author of the study. “The limitation came from the deprotection chemistry, not from the silicon.”

The study was published in Nature Electronics.

American startup PsiQuantum has begun construction on a facility in Moreton Bay, Australia, where it plans to build and deploy what it calls the world’s first utility-scale, fault-tolerant quantum computer.

The California-based quantum computing company broke ground on the site alongside representatives from the Australian government, the Queensland government, and local officials. The project is expected to become a key part of Australia’s push to establish itself as a hub for advanced computing technologies.

The facility will be developed in multiple phases and will house the infrastructure needed to support PsiQuantum’s photonic quantum computing architecture. One of the first major components arriving at the site will be a large cryogenic plant designed to cool the quantum system.

PsiQuantum said the cryoplant, being built by Linde Engineering, is expected to be delivered in the second half of 2027. The company ordered the system in late 2024 and described it as one of the largest cryogenic cooling plants ever built for a quantum computing application.

Race toward utility

The cooling system will be followed by cryogenic cabinets that will contain photonic quantum chips. These cabinets will be connected using conventional optical fiber, forming the foundation of the company’s planned utility-scale machine.

Unlike many quantum computing efforts that remain focused on laboratory-scale systems, PsiQuantum is pursuing a photonics-based approach designed to scale using existing semiconductor manufacturing processes and optical networking technologies.

“Building a quantum computer that solves real world problems is one of the great engineering challenges of our time. For decades, quantum computing has held the promise of transforming what humanity can achieve through computation, and today in Australia we are beginning to turn that promise into reality,” said Victor Peng, Chief Executive Officer of PsiQuantum.

The company believes fault-tolerant quantum computers could eventually tackle problems beyond the reach of conventional computing systems. Potential applications include drug discovery, materials development, energy research, logistics, manufacturing, agriculture, and financial modeling.

PsiQuantum also sees quantum computing as a complement to emerging computational technologies rather than a replacement. The company said future industrial computing systems are likely to combine quantum and classical technologies to accelerate scientific discovery and solve increasingly complex problems.

Building local capability

The Moreton Bay facility is also expected to support workforce development in Australia’s growing quantum technology sector. The site sits within the Moreton Bay Central Innovation Precinct, close to a TAFE Centre of Excellence and the University of the Sunshine Coast’s Moreton Bay campus.

According to the company, the project will create jobs in engineering, technical operations, advanced manufacturing, research, and professional services. The location is intended to help students, technicians, apprentices, and engineers move directly into careers linked to quantum technologies.

“Australia has been part of this journey from the very beginning,” said Prof. Jeremy O’Brien, Co-Founder and Executive Chair of PsiQuantum.

The groundbreaking follows the opening of PsiQuantum’s Test and Validation Lab at Griffith University in Brisbane in May 2026. The laboratory houses cryogenic equipment used to test photonic quantum chips and supporting systems that will eventually be deployed at the Moreton Bay site.

If completed as planned, the facility will become one of the world’s most ambitious efforts to build a fault-tolerant quantum computer at industrial scale.

The U.S. Department of Defense (DoD) has awarded Parallel Works, an Illinois-based software company spun out of Argonne National Laboratory, a contract to provide a unified platform that connects military supercomputing centers with secure commercial cloud infrastructure.

The contract, granted under the department’s High Performance Computing Modernization Program (HPCMP), will allow scientists, engineers, and acquisition professionals across the DoD to access both on-premises and cloud-based computing resources through a single interface. The goal is to speed up the development and deployment of high-performance computing (HPC) and artificial intelligence (AI) workloads used for defense research and operations.

Parallel Works said its ACTIVATE High Security Platform (HSP) will act as the control plane linking Defense Supercomputing Resource Centers (DSRCs) with commercial cloud services. The platform is designed to let users move workloads across environments while maintaining security requirements for sensitive data.

The company said researchers will be able to test and deploy workloads on emerging cloud infrastructure before those capabilities are integrated into the DoD’s supercomputing centers.

Connecting defense computing

The platform has been approved at Impact Level 5 (IL5), one of the highest security classifications for non-classified DoD cloud environments. According to the company, it is among a small number of software platforms approved to handle export-controlled workloads, including International Traffic in Arms Regulations (ITAR) and Controlled Unclassified Information (CUI).

The system is intended to address growing demand for computing power driven by AI development, simulation workloads, and digital modernization programs across the military.

“AI-driven warfare and the ramp to digital modernization are demanding far more model-sharing options than legacy infrastructure can provide,” said Keith Obenschain, Chief Technology Officer at HPCMP.

The platform offers on-demand access to cloud compute resources, allowing users to avoid traditional queue delays associated with shared supercomputing systems. It also enables organizations to expand computing capacity by distributing workloads across multiple environments and cloud providers.

Parallel Works said users will have access to cloud infrastructure from providers including Amazon Web Services, Microsoft Azure, Google Cloud, and Oracle Cloud.

Accelerating mission deployment

As part of the contract rollout, the Naval Research Laboratory has already implemented the platform to support weather forecasting workloads.

According to the company, the system automates forecasting workflows while securely coordinating computing resources across defense and cloud environments. The approach is intended to improve reliability, speed up processing, and help redistribute workloads when demand spikes.

“The HPCMP contract allows our platform to support a broad range of mission-critical HPC and AI workloads across the DOD teams,” said Matthew Shaxted, CEO of Parallel Works.

The company said the environment can also serve as a secure testing ground for AI development tools and next-generation cloud architectures before they are adopted within the DoD’s existing supercomputing infrastructure.

The contract reflects a broader push by the U.S. military to combine traditional supercomputing resources with commercial cloud services as AI models and data-intensive applications continue to increase computing requirements across defense operations.

KAIST researchers have developed a simulation-based method to predict how small future transistors can become before quantum effects begin to interfere with their operation, a breakthrough that could help engineers design next-generation semiconductor chips more efficiently.

The team used atom-level quantum mechanical calculations to identify the scaling limits of transistors, the tiny switches that control the flow of electricity in electronic devices. The findings could help chipmakers continue shrinking transistors beyond current technology nodes while reducing costly trial-and-error during development.

As the semiconductor industry enters the so-called 2 nm era, the physical dimensions of transistors remain significantly larger than 2 nanometers. One of the biggest obstacles to further miniaturization is quantum tunneling, a phenomenon in which electrons leak through barriers that would normally block them, making it difficult to control current flow.

Understanding where that limit lies has been challenging because it is nearly impossible to directly measure the atomic-scale interactions occurring where metal contacts connect to semiconductor channels.

Chasing atomic limits

To overcome that challenge, the KAIST team relied on first-principles calculations, a computational approach that predicts material behavior using the laws of physics rather than experimental data.

Building on a previously developed framework known as multi-space constrained-search density functional theory (MS-DFT), the researchers conducted virtual transfer length method experiments, a standard technique used to measure contact resistance between metal electrodes and semiconductor materials.

The simulations allowed the team to examine how electrons move across metal-semiconductor interfaces and determine the critical tunneling length, the point at which electron leakage begins to affect transistor performance.

The researchers applied the method to monolayer molybdenum disulfide (MoS2), a two-dimensional semiconductor considered a promising candidate for future transistor channels because it can be manufactured at atomic-layer thickness.

Their analysis showed that electron penetration into the channel varies depending on the choice of metal electrode and the atomic structure of the contact interface. As a result, the minimum achievable transistor size is not fixed but depends on material selection and device design.

Beyond today’s nodes

According to the study, the critical tunneling length changes based on the work function of the metal and the geometry of the contact structure. This means engineers can potentially tune transistor scaling limits by selecting different materials and interface configurations.

Among the combinations studied, the team found that electron leakage could be suppressed at dimensions below 4 nanometers, suggesting future transistors may be scaled even further than current technologies allow.

The researchers also proposed a design strategy that combines two-dimensional semiconductors with different properties to reduce power consumption in future chips.

“This study is significant because it presents a new physical criterion for defining how small next-generation transistors can become,” said Professor Yong-Hoon Kim.

“By computationally analyzing quantum mechanical phenomena in the sub-10 nm regime, which are difficult to probe experimentally, we have opened a path toward utilizing these findings in next-generation transistor design.”

The team believes the approach could provide chip designers with a platform for predicting transistor performance and scaling limits before fabrication begins, potentially shortening development cycles for future AI and high-performance computing chips.

The study was published in the journal npj Computational Materials.

Genesis AI has unveiled Eno, its first general-purpose robot, as the company pushes toward building machines that can work across factories, laboratories, hospitals, hotels and eventually homes.

The robot combines Genesis AI’s custom hardware with GENE, the company’s robotics foundation model, which serves as Eno’s control system. According to the company, the robot is designed to perform complex tasks, adapt to changing environments and complete objectives with minimal human intervention.

Genesis AI said Eno differs from traditional industrial robots because it is built to operate as a physical agent rather than execute a fixed set of commands. The company claims the system can understand goals, reason through changing conditions, retain memory and carry out multi-step tasks over extended periods.

The announcement comes as companies across the robotics sector race to develop humanoid and general-purpose robots capable of handling a wider range of real-world jobs with less specialized programming.

Built beyond humanoids

Instead of closely resembling a human, Eno uses a wheeled base topped by an adjustable tower structure. The robot can change its height and reach in real time and fold into a more compact form when not in use.

Its most human-like features are its robotic hands. Genesis AI says the hands match the form and function of human hands, allowing Eno to use existing tools and interact with environments already designed for people.

“The only path to creating a robot that can truly deliver value to society and excel in the real world is through intentional design and a single, comprehensive system,” said Zhou Xian, co-founder and CEO of Genesis AI.

“From day one we’ve approached our design and engineering through a production mindset built around bringing our hardware, software and intelligence together as a whole.”

The company said Eno was designed alongside GENE so that the robot’s body and intelligence system function as a single platform. GENE is intended to give the robot human-level dexterity and the ability to handle long-horizon tasks that require planning and adaptation.

Showing robotic intent

One of Eno’s distinguishing features is an optional built-in screen that displays the robot’s reasoning process, operational status and intended actions in real time.

Genesis AI said the feature is designed to improve transparency and help people understand what the robot is doing as it works alongside human operators.

“What Genesis is building with Eno is a fundamentally new model for extending human capability through advanced robotics,” said Eric Schmidt, former Google CEO and Genesis AI investor.

“The breakthrough is not replacing human expertise, but amplifying it — making advanced robotics genuinely useful, accessible, and scalable across industries.”

According to the company, Eno could eventually manage entire workflows rather than perform isolated actions. Examples include keeping production lines supplied, coordinating tasks across facilities and preparing workspaces for the next shift.

Genesis AI plans to begin production and targeted customer deployments before the end of 2026. Initial deployments will focus on manufacturing, logistics and laboratory environments, followed by hospitality and healthcare settings. Consumer-focused applications are expected at a later stage.

The company recently raised $105 million in seed funding and says additional robotic platforms are already under development as part of its broader roadmap for general-purpose robotics.

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SpaceX has agreed to acquire coding startup Cursor in a $60 billion all-stock deal, according to a filing with the U.S. Securities and Exchange Commission (SEC). The acquisition deepens the Elon Musk-led company’s push into artificial intelligence software and developer tools just days after its record-breaking Nasdaq debut.

The deal brings San Francisco-based Anysphere, the company behind Cursor, under the SpaceX umbrella as thje company looks to strengthen its position against rivals such as OpenAI and Anthropic in the fast-growing AI coding market.

SpaceX announced the massive deal in a post on X, saying: “SpaceX has exercised the option to acquire @cursor_ai in an all-stock transaction with the goal of building the world’s most useful AI models.”

SpaceX has exercised the option to acquire @cursor_ai in an all-stock transaction with the goal of building the world’s most useful AI models.

For the past few months, SpaceXAI has been jointly training a model with Cursor, which will be released in Cursor and Grok Build soon.… https://t.co/X5mepgXgjJ

— SpaceX (@SpaceX) June 16, 2026

The company added that it has been jointly training a model with Cursor over the past several months and plans to release it in both Cursor and Grok Build, xAI’s coding agent, in the near future.

Code meets compute

The acquisition comes after an agreement between the two companies in April that gave SpaceX the right to acquire Cursor at a predetermined valuation. According to SpaceX’s SEC filing, the companies also entered into a compute partnership under which SpaceX would provide GPU cluster capacity and collaborate on improving existing models, including Grok, while potentially developing new AI products together.

In the filing, SpaceX described software development as a strategically important AI use case because it generates structured, verifiable data and frequent user feedback. The company said Cursor’s coding workflows provide valuable developer interaction data, including coding prompts, iteration cycles and software architecture decisions that could help improve model training and inference.

Cursor has emerged as one of the fastest-growing AI software companies since its founding in 2022. Reports suggest that the company has reached roughly $2.6 billion in annualized business-to-business revenue and has recently been discussing a funding round that would have valued it at $50 billion.

The startup’s coding assistant is widely used by developers to generate, edit, and review software code. Cursor counts major companies such as Stripe, Adobe and Nvidia among its users, while Nvidia CEO Jensen Huang has described it as his “favourite enterprise AI service.”

Data powers expansion

SpaceX said the acquisition will help advance its broader AI strategy by integrating its models more directly into developer workflows and expanding distribution through high-engagement software products.

“We look forward to working closely with the Cursor team to advance our frontier AI capabilities,” SpaceX said in its announcement.

Cursor also welcomed the deal, posting on X: “We’re excited to join forces with @SpaceX to advance the frontier of useful AI. Expect significant improvements to Cursor soon.”

We're excited to join forces with @SpaceX to advance the frontier of useful AI. Expect significant improvements to Cursor soon. https://t.co/62IMr2sgEy

— Cursor (@cursor_ai) June 16, 2026

The acquisition follows SpaceX’s blockbuster stock market debut last week. Reuters reported that the company’s valuation climbed above $2 trillion after the listing. The company’s shares surged further Tuesday, briefly pushing SpaceX past Amazon by market value.

SpaceX expects the transaction to close during the third quarter of 2026, subject to regulatory approvals. Once completed, the deal would give the company direct control of one of the industry’s most prominent AI coding platforms while expanding access to developer data that it believes can strengthen future versions of Grok and other AI models.

Researchers in Australia have developed a neuromorphic vision chip that can see, process, and store visual information in a single device, mimicking how the human eye and brain work together. The small chip, built using doped indium oxide, is designed to reduce reliance on external processors and enable faster decision-making in applications such as autonomous systems.

The work was led by engineers at RMIT University, with contributions from Deakin University and the University of Melbourne. The team says the device combines sensing, processing, and memory functions in one platform, removing the need for separate hardware components that typically slow down machine vision systems.

Unlike conventional imaging systems that capture data and send it to external processors, the new chip performs computation directly where the light is detected. The sensing layer, which is thousands of times thinner than a human hair, is engineered to respond to light and retain information over time, allowing it to function more like a biological visual system.

The researchers say this integrated approach could reduce energy consumption and improve response speed in real-time environments. The device was tested using ultraviolet light, and the team is now working to extend its capabilities to visible and infrared light for broader applications.

Brain-like vision system

The chip is designed to mimic the way the human eye captures light and how the brain processes and stores visual input. It performs multiple tasks on a single platform, including sensing incoming light, processing signals, and storing visual information for later use.

Team leader Professor Sumeet Walia said the goal was to remove the delay and energy cost of transferring data between separate systems. “We’ve made real-time decision making a possibility with our invention, because it doesn’t need to process large amounts of irrelevant data and it’s not being slowed down by data transfer to separate processors.”

The device also showed the ability to retain visual information for longer periods without frequent electrical refresh signals, which reduces energy use and improves efficiency.

First author and RMIT PhD researcher Aishani Mazumder said the system draws inspiration from how the brain processes information. “Neuromorphic vision systems are designed to use similar analog processing to the human brain, which can greatly reduce the amount of energy needed to perform complex visual tasks compared with today’s technologies.”

Toward autonomous machines

The researchers say the technology could be used in self-driving cars, autonomous robots, and monitoring systems that operate in dangerous environments. Possible applications include object recognition in vehicles, detection systems in remote or hazardous areas, and advanced imaging for forensics and industrial inspection.

Because the chip integrates multiple functions into a single element, it could also support longer-term autonomous operation without heavy computational infrastructure. The team says this makes it suitable for systems that need to adapt quickly to changing environments.

The device mimics the retina’s ability to capture an entire image and the brain’s ability to interpret and store it, enabling a more compact and efficient approach to machine vision. The researchers believe this could eventually lead to vision systems that improve with experience, similar to biological systems.

The team used specialized nanofabrication and microscopy facilities at RMIT University, with support from the Australian Research Council and the National Computational Infrastructure.

The study appears in the journal Advanced Functional Materials.

Canadian-based critical minerals company E3 Lithium has commissioned Phase 2 of its Clearwater Project Demonstration Facility in Alberta and confirmed lithium concentrations of 75.8 milligrams per liter in brine produced during ongoing reservoir testing.

The company said the latest results support the consistency of lithium-bearing brine chemistry across the Clearwater Project and the broader Bashaw District, a key factor as it advances plans for commercial lithium production.

The demonstration facility is currently being used to test reservoir performance over an extended period. Brine is pumped from a production well and immediately reinjected into a separate injection well, allowing engineers to evaluate flow behavior and reservoir response under operating conditions.

According to the Alberta-based company, the facility achieved stable production and injection through the well pair. During early operations, an electrical submersible pump maintained the targeted flow rate of 1,400 cubic meters per day.

Brine tests confirm consistency

The company regularly collected brine samples during operations and sent them to an independent third-party laboratory for analysis. Results confirmed lithium concentrations of 75.8 mg/L, matching expectations for the resource.

E3 said the reservoir data generated through the testing campaign will be used to update its reservoir development plan and support a feasibility study for the Clearwater Project.

The next stage of operations will focus on analyzing the relationship between brine and natural gas within the reservoir. The information is expected to support the design of the front end of a future commercial processing plant.

The demonstration facility forms part of E3’s broader effort to reduce technical risks before moving toward large-scale lithium production.

“With Phase 2 operations underway, E3 has begun a series of project-scale de-risking activities for the Clearwater Project,” said Chris Doornbos, CEO and chair of E3 Lithium.

The company added that the current campaign has already processed more brine through the two new wells than all of its previous testing programs combined.

Scaling toward production

Lithium demand continues to grow as automakers and battery manufacturers seek additional supplies of the metal used in electric vehicle batteries and energy storage systems.

For E3, the demonstration facility serves as a bridge between laboratory-scale testing and commercial deployment. Data collected from reservoir operations, brine chemistry studies, and future process testing will be used to refine engineering designs and operating plans.

“We have already moved more brine through these two wells than E3 has handled through all its previous testing combined, and we expect to continue to operate the pump as needed over the coming 24 months,” Doornbos said.

He added that confirmation of reservoir performance and lithium grades at the new wells strengthens confidence in the predictability of the resource.

The company plans to continue operating the demonstration facility while advancing front-end engineering design work and completing a feasibility study for the project. The resulting data will help determine the design of a future commercial facility and support decisions related to full-scale development.