TECH

Brown University engineers build brain-inspired imaging system that can ‘see’ through fog

Researchers from the Brown University School of Engineering have developed a new imaging system that can see and track moving objects in partially opaque environments like dense fog or muddy water. 

The technique, described in a study published in Advanced Science, combines a dynamic vision sensor — a camera with pixels that report only changes in brightness, rather than capturing full frames — with a spiking neural network computer model that reconstructs the moving objects spied by the sensor. In laboratory tests, the system’s reconstructed images matched the hidden targets with structural similarity scores of up to 96% in turbid water and drifting fog that would hide the objects from a traditional camera, while they simultaneously tracked the targets’ positions as they moved. 

The brain-inspired system is the first end-to-end technique that can both track and image randomly moving objects hidden by such dense scattering media, the researchers say. 

“The reason it’s hard to see objects in fog is that the light bouncing off of objects gets scattered by the fog before it reaches our eyes or the camera lens,” said Ning Zhang, a postdoctoral researcher in engineering at Brown. “This research project is about using novel imaging cameras and a brain-inspired model that can filter out that scattering process and reconstruct what's behind the fog.”

The system could eventually have a variety of real-world applications, including for self-driving cars and other autonomous vehicles, drone-based search and rescue efforts during storms or wildfires, or even medical imaging, the researchers say. 

Inspired by the brain...To develop the technique, the researchers took cues from the human visual system, which can process images with remarkable speed and efficiency. Rather than collecting a full picture all at once like a video camera, the retina responds mainly to changes in the visual field — edges, motion and flicker —and feeds that information to the brain, which builds a reconstruction of the scene over time. When it senses a change, it sends neural spikes to the brain, which are used to update the brain’s reconstruction of the world. 

The researchers were able to harness a similar architecture to create a system that processes images quickly and efficiently, but that outperforms human vision in foggy or turbid conditions. The system starts with a dynamic vision sensor that can detect light-intensity changes in individual pixels within the visual field. Because each pixel fires only when the brightness it sees changes by more than a set threshold, the sensor registers a moving object even when much of the light has been scattered by fog or some other scattering medium. And because the scattering background changes far more slowly than the moving target, the sensor largely ignores the fog and responds mainly to light that has interacted with the object. What it records is still a shapeless cloud of spikes, which is where the spiking neural network comes in. 

“The human eye is quite good at motion detection, but there are ways in which a camera, specifically a dynamic vision sensor, can be better, including that it’s sensitive to near-infrared light, which the human eye cannot see,” said Arto Nurmikko, a professor of engineering at Brown and the study’s senior author. “It captures information only about a moving object, and in doing so effectively filters out some of the fogginess while generating an output where relevant information is coded as trains of asynchronous spikes, much as the biological retina acquires data in a form the brain’s visual cortex understands.”

The key innovation in the work is a neuromorphic computer model mimicking the visual cortex: a deep spiking neural network that takes data from the vision sensor and reconstructs images of randomly moving, normally unrecognizable objects while tracking their trajectories in fractions of a second. The network runs on spikes as the fundamental unit of information. 

To test the system, the researchers projected images of moving alpha-numeric characters and silhouettes of different species of flying birds through an obscuring fog chamber or a tank of turbid water. The experiments showed that the system was able to image and track the randomly moving objects unrecognized by a standard camera system or the human eye. 

The system is also highly energy efficient. The sensor itself draws only tens of milliwatts. The spiking network uses a fraction of the energy used by a conventional neural network because it computes only on sparse spikes rather than dense frames.

The approach has limits, the researchers note. Because the sensor responds only to change, an object has to be moving relative to the camera to be seen, and the current system recovers an object’s silhouette rather than a full grayscale image. The sensor also loses sensitivity in very dim light. The team is now exploring a light-intensifier front end for low-light conditions, as well as depth-resolved approaches that can extend the method to three-dimensional targets — for example, by timing light’s travel time, or by pairing two event cameras like a pair of eyes.

“This could be useful anywhere where light-scattering by the surrounding medium is a serious problem — self-driving cars, search-and-rescue drones and underwater navigation are a few examples,” Zhang said. “The goal is to push the boundary of what we can perceive, to improve safety, healthcare and beyond.”

Engineers at Brown University have built a new brain-inspired imaging system that can track and "see" moving objects through dense fog and murky water with up to 96% accuracy.

The research was published in Advanced Science in October 2026. It solves a major problem for traditional cameras: light bouncing off fog instead of reaching the lens.

How the system works:

• Dynamic vision sensor: A special camera that records only changes in brightness (called events) instead of capturing normal video frames.

• Spiking neural network: A computer model inspired by the human brain. It processes sparse electrical signals (spikes) rather than dense data blocks.

• Filtering: The system ignores the random light scattering caused by water droplets in the fog and reconstructs what hides behind it.

Key benefits:

• High accuracy: Reconstructed images match hidden targets with up to 96% structural similarity in lab tests.

• Simultaneous tracking: It is the first system that can both image and track randomly moving objects hidden in dense fog at the same time.

• Energy efficient: The sensor uses only tens of milliwatts, and the brain-like network uses a fraction of the energy of traditional AI models.

Current limitations:

• Movement required: Because the camera reacts only to change, stationary objects cannot be seen.

• Silhouettes only: The system currently recovers object outlines (silhouettes) instead of full grayscale pictures.

• Low light: The sensor loses sensitivity in very dim environments.

Potential uses:

• Self-driving cars: Helping autonomous vehicles navigate safely through heavy mist or rain.

• Search and rescue: Guiding drones during severe storms or thick wildfires.

• Underwater navigation: Helping robots see through murky water.

Brown University

TECH

GeForce RTX 5070 Ti memory gets overclocked to a scorching 39 Gbps

The GDDR7 memory used on the GeForce RTX 50 series GPUs may have considerably more memory overclocking headroom than NVIDIAs official specifications suggest, with one enthusiast pushing Samsung GDDR7 memory all the way from 28 Gbps to a scorching 39 Gbps, coincidentally a 39% overclock. This came about thanks to the mVolt+ Extreme overclock tool, which can apparently bypass the memory overclocking limits imposed by conventional GPU tuning software. A Gigabyte GeForce RTX 5070 Ti Windforce owner reports successfully running the card's Samsung GDDR7 at a +5500 MHz memory offset, corresponding to a 39 Gbps data rate.

The mVolt+ Extreme tool pushes memory overclocking limits... The mVolt+ Extreme utility stands out from conventional GPU overclocking tools by allowing the hardware to operate beyond manufacturer-imposed restrictions.

The tool had already demonstrated the ability to unlock a TDP of up to 700W for the GeForce RTX 5090 without shunt modding (though using it this way is at your own risk—given that the card tends to melt things under normal conditions, imagine the consequences with a higher TDP), surpassing the stock limit of approximately 600W.

On the RTX 5070 Ti, mVolt+ Extreme enabled a memory offset of +5500 MHz, whereas most conventional utilities allow for a maximum additional offset of +3000 MHz.

Another user in the same Reddit thread confirmed stable performance at +5500 MHz on the RTX 5070 Ti but noted that 6000 MHz remained unstable.

Results vary across users and games... Performance improvements in games were considered modest, with the exception of a 20% gain observed in Steel Nomad.

The +5500 MHz offset boosts memory speed from 28 Gbps to 39 Gbps—a 39% increase—resulting in a bandwidth of 1248 GB/s compared to the stock 896 GB/s. However, in practice, this does not translate to a proportional gain in frames per second.

Other users who replicated the procedure achieved different results: some exceeded 5000 MHz, while others remained in the 4000 to 4500 MHz range.

If you're wondering how adding 5500 MHz is even possible, and also wondering how it added 11 Gbps to the transfer rate, let me explain. GDDR7 transfers sixteen bits per clock thanks to its design. That "+5500 MHz" number is actually even more confusing, because it's an intermediate data rate number. The actual clock rate at 39 Gbps is 2437.5 MHz, and the pre-DDR data rate is 19500 MT/s. That's an increase of 5500 MT/s over the stock 14,000 MT/s, which turns into 28 Gbps when you account for DDR signaling. Here, this chart might help:

As you can see, the bandwidth increase is easier to understand. The GeForce RTX 5070 Ti has a 256-bit memory bus, so its stock 28-Gbps memory provides 896 GB/s of theoretical bandwidth. At 39 Gbps, that rises to 1,248 GB/s—a 39.3% increase, essentially matching the increase in memory data rate. That pushes the memory bandwidth well ahead of the GeForce RTX 5080, and in fact within striking distance of the GeForce RTX 5090 D V2, the slightly-neutered RTX 5090 that was built for the Chinese market before Beijing banned the boards from entering the country.

Actually getting a GeForce RTX 5070 Ti to run its RAM at 39 Gbps is quite a feat, as you'd expect. The Redditor says +5500 worked in Cyberpunk 2077 with path tracing enabled for 30 minutes, while +6000 immediately caused the graphics driver to restart. Other users have reported lower ceilings, with examples around +4500 and +5000, and at least one user reporting artifacts beyond +5500. That makes it clear that results will vary from card to card and, potentially, depending on the memory chips installed on the board.

The performance gains are also nowhere near as dramatic as the memory bandwidth increase. The original tester, /u/Sad-Victory-8319, reported roughly 1 FPS of additional performance in Cyberpunk 2077 for every +1000 MHz of memory offset, while another user reported a roughly 1.5% to 2% increase in 3DMark Speed Way when moving from +3000 to +5000. In the former test, +5500 represented roughly a 5- to 6-FPS improvement over stock memory settings. A bit unimpressive, but not unexpected; GDDR7 is so fast even at stock settings that these GPUs are almost never bandwidth-bound.

Interestingly, despite that they use the same Samsung GDDR7 memory, similar experimentation on GeForce RTX 5090 cards appears to hit a lower ceiling. Users in the Overclock.net "RTX 5090 Owners Club" thread have also been toying with the mVolt+ tool, and they report getting to roughly +4000 MHz before driver resets become an issue. Why the 5070 Ti appears capable of going substantially further isn't yet clear, but it could have to do with the half-width memory bus or the considerably higher strain on the RTX 5090's power delivery hardware.

Either way, the discovery here is notable because it suggests at least some, and possibly a majority of RTX 50-series cards have a considerable amount of untapped GDDR7 frequency headroom. Whether running a gaming GPU at these kinds of memory speeds is sensible for long-term use is a separate question, particularly considering the fairly minimal performance gains to be found from even extreme overclocks like this. Still, it's hard not to be a little impressed by the sight of "39 Gbps" memory on a GeForce RTX 5070 Ti.

mundophone

 

TECH

Visual illusion reveals what today’s AI vision is missing – York University study

Our eyes do not always tell us exactly where things are – and that may be a feature of how biological vision works, rather than simply a flaw. A new study by York University researchers uses a common illusion to ask if artificial intelligence is meant to see more like us, should it make some of the same systematic perceptual “mistakes”?

For example, after staring at something moving steadily in one direction, a stationary object viewed immediately afterward can appear slightly displaced in the opposite direction. This well-known visual illusion, called a motion aftereffect, gives scientists an unusual window into the computations underlying perception: the image itself has not moved, but our experience of where it is has changed.

“Today’s AI vision systems are impressive, but they still do not always see the world the way we do. This study captures the promise of NeuroAI and what it can do when neuroscience and artificial intelligence are brought together. By using smart experiments to reveal the computations biological vision uses and AI still lacks, we can use those insights to build better, more brain-like artificial systems,” says senior author York Assistant Professor Kohitij Kar, the Canada Research Chair in Visual Neuroscience and a member of York’s Centre for Vision Research and Centre for Integrative and Applied Neuroscience.

Current AI vision systems can often determine where an object is accurately, but they generally do not reproduce the way recent visual experience can reshape that answer. In humans, staring at motion can make a subsequently viewed stationary object appear displaced even though its pixels have not moved. The researchers found a corresponding change in the primate visual cortex – but not in the AI models they tested.

To gain better insight into the issue, the researchers examined whether artificial neural network models capture the same history-dependent changes in spatial representations seen in biological vision, or whether their position representations primarily reflect the physical properties of the image. The researchers, including the paper’s first author and York graduate student Elizaveta Yakubovskaya, used precise measurements to find out where AI differs from biological vision and how that gap could be bridged.

“Combining recordings from primate visual cortex with human perception experiments, we used motion adaptation to induce a visual illusion and make a stationary object appear slightly shifted in position, then asked whether the brain and AI showed the same effect. Human observers reported the illusion, and neural representations of position in the primate inferior temporal (IT) cortex shifted in the same direction, even though the image itself had not changed,” says Yakubovskaya.

The researchers leveraged motion adaptation to show where perceived and pixel-based positions diverge, allowing them to test the behavioral relevance of IT codes. The findings not only further our understanding of IT’s role in spatial information encoding but provide a new benchmark to evaluate dynamic vision models.

“There is a growing question in AI about whether increasingly capable systems will become more like us or increasingly different from us,” says Kar of the Faculty of Science and a member of the York-led Connected Minds. “If we want AI that works with humans and understands the world in more human-compatible ways, we cannot focus only on whether it gets the right answer. We also need to understand the computations that produce human perception and behavior. Neuroscience gives us a way to discover those computations and, potentially, build them into AI,” adds Kar.

Visual illusions reveal that today’s AI vision is missing history-dependent, dynamic perceptual computations that allow biological brains to interpret a changing world rather than just recording static pixels.

A recent study from York University published in Current Biology highlights a fundamental gap between artificial intelligence and primate vision:

The core findings:

• The Illusion Divide: When humans and macaque monkeys look at a stationary object after experiencing motion adaptation (a motion aftereffect), they perceive the object as physically shifted in position, even though the image hasn’t changed.

• Neural Mirroring: Recordings from the primate inferior temporal (IT) cortex show that biological brain cells actually shift their spatial position codes to match this subjective, illusory perception.

• AI Failure: Current state-of-the-art artificial neural networks and AI vision models do not replicate this shift. They remain rigid and strictly tethered to static pixel coordinates.

What AI is missing:

• Passive vs. Active Processing: Human eyes and primate brains do not operate like digital cameras that capture raw, objective pixels frame by frame.

• Temporal Integration: Biological vision actively blends immediate visual history and recent temporal experience into its spatial calculations.

• Perceptual Alignment: Illusions are not just computational mistakes; they are the functional byproduct of an adaptive brain that predicts and prioritizes what is useful for survival based on context. AI lacks this fluid, context-aware framework

A new study from York University reveals that today’s AI vision lacks history-dependent, dynamic perceptual computations that allow biological brains to shift object position based on recent visual experience.

The illusion and the experiment:

• The motion aftereffect: When humans or primates watch steady motion in one direction and then look at a stationary object, the object appears slightly shifted in the opposite direction.

• The biological response: Neural recordings from the macaque inferior temporal (IT) cortex show that the brain's spatial position codes shift dynamically to mirror this illusion, even though the physical image has not changed.

• The AI blind spot: When tested on the same visual paradigm, standard artificial vision networks show no adaptation; their internal coordinates remain rigid and strictly tethered to static pixels.

What AI vision is missing:

• Adaptive processing: Biological vision does not act like a passive digital camera cataloging raw pixels. It actively integrates immediate visual history into how it constructs reality.

• Perceptually aligned coordinates: AI lacks the capacity to encode position based on dynamic, context-aware neural computations.

• A new neuroAI benchmark: Researchers suggest that future AI must be trained on these adaptable perceptual mechanisms—rather than just static pixel accuracy—to work safely and intuitively alongside humans

York University

SAMSUNG

Samsung's Exynos 2700 enters mass production with 10% higher output than Exynos 2600, says leaker

Tipster Ice Universe claims Samsung has begun front-end wafer mass production of the Exynos 2700, a 2nm chipset built on the company's SF2P node. Initial output is reportedly 10% higher than the Exynos 2600's, and internal Geekbench 6 runs allegedly show a 9.5% multi-core lead over Qualcomm's Snapdragon 8 Elite Extreme Gen 6.

Samsung has reportedly started mass production of the Exynos 2700, its next flagship smartphone chipset, according to tipster Ice Universe. The leaker claims the 2nm processor has entered front-end wafer production, moving beyond the limited sampling stage that comes before a commercial ramp.

Ice Universe further alleges that this initial run is roughly 10% larger than the Exynos 2600's at the same point in its cycle. The Exynos 2700 is expected to be fabricated on SF2P, an enhanced version of the SF2 process behind the Exynos 2600. Samsung announced the Exynos 2600 in December 2025 as the world's first 2nm chipset built with gate-all-around (GAA) transistors. It uses a 10-core CPU in a one-plus-three-plus-six layout, led by an Arm C1-Ultra prime core clocked at 3.80GHz.

A die shot of the Exynos 2700, leaked by semiconductor research firm SemiAnalysis in early September, points to a reworked 10-core CPU with two prime cores instead of one. The chip reportedly pairs an Arm C2-Ultra core at 4.24GHz and four C2-Pro cores at 3.74GHz with a C1-Ultra core at 3.36GHz and four C1-Pro cores at 2.88GHz. The die also indicates LPDDR6 memory support, 24MB of system-level cache, a large NPU and an Xclipse 970 GPU with the same eight WGPs as the Exynos 2600's Xclipse 960.

Samsung's internal testing reportedly places the Exynos 2700 9.5% ahead of Qualcomm's Snapdragon 8 Elite Extreme Gen 6 in the Geekbench 6 multi-core benchmark, partly due to a reported 4.00GHz target frequency for the chip's prime core. The leaked results include no power consumption figures or other efficiency metrics, so the performance claim cannot yet be weighed against energy use.

Qualcomm chipsets are still expected to power Galaxy S27 models sold in the US and China. Samsung's MX mobile division is reportedly assessing performance, thermals, cost, and SF2P manufacturing capacity before deciding whether a larger Exynos 2700 order makes economic sense. Staying with the Snapdragon 8 Elite Extreme Gen 6 and Snapdragon 8 Elite Gen 6 also carries a high cost, since both are manufactured on TSMC's 2nm N2P process. Samsung has not confirmed whether the Galaxy S27 Ultra will use the Exynos 2700 in any market.

A veritable "internal war" is currently underway between Samsung System LSI and the MX division, as the former advocates for the inclusion of the Exynos 2700 in the Galaxy S27 Ultra.

Samsung MX, on the other hand, is taking a much more cautious approach, evaluating factors such as performance, thermal behavior, cost, and production capacity regarding the 2-nanometer process.

Nevertheless, there is considerable excitement within the South Korean giant, particularly after the Exynos 2700 achieved a multi-core score 9.5% higher than that of the Snapdragon 8 Elite Extreme Gen 6 on Geekbench.

Regarding the Geekbench results, the Qualcomm chip scored 12,856 points, whereas the Exynos 2700 managed to reach 14,000 points.

Samsung is not currently commenting on the leaks, but component production for the Galaxy S27 has already begun, and development of One UI 9.5 is progressing rapidly.

The Samsung Galaxy S27 Pro – along with the vanilla and plus models – will use the Exynos 2700 in Korea and Europe. These models will switch to a Snapdragon 8 Elite Gen 6 chip for the US and China.

As for the Galaxy S27 Ultra, that one is still up in the air. Samsung System LSI, which designs the Exynos chips, has confidence in the 2700 and is pushing to get it adopted on the top-tier S-phone. This would help the division’s earnings, of course, but it will also signal that the chip is good enough for an Ultra-class flagship.

Samsung MX, the division building the phones, has the final say, however. Right now it is considering multiple factors – benchmark and thermal performance as well as the price of Qualcomm’s chips and the production capacity for Exynos 2700 chips.

A while back, the news came out that internal testing had shown that the Exynos 2700 beats the Snapdragon 8 Elite Extreme Gen 6 on the multi-core Geekbench test by 9.5%. However, the Snapdragon still has the edge in the single-core test.

The Exynos 2700 will be fabbed on Samsung’s SF2P, a second generation 2nm Gate-All-Around (GAA) node. Compared to the first-gen node (SF2), which was used for the Exynos 2600, SF2P offers a 12% performance improvement, a 25% reduction in power usage and an 8% decrease in chip area. There will be some architectural improvements too, of course, with the Exynos 2700 likely using Arm C2 CPU cores (the 2600 used C1 cores).

Apparently, it takes three-four months from the moment a chipset goes into mass production to having the final product ready. The timing works out just right for a February or March launch of the Galaxy S27 series.

Samsung typically unveils new Exynos flagships shortly before the turn of the year, as it did with the Exynos 2600 on 19 December 2025. An official Exynos 2700 announcement is therefore expected in December 2026, or possibly earlier.

Galaxy S27...The Galaxy S27 Pro will be the new addition to the family. The model will feature a smaller screen than the S27+, yet it is expected to be a more advanced option, with features closer to those of the Ultra. The aim is to offer a premium experience in a more compact device.

Samsung Display is also expected to begin mass production of OLED screens for the new generation this month. The company has reportedly set an annual target of 47 to 48 million panels for the Galaxy S27 line—a figure more than 10% higher than the estimated volume for the Galaxy S26 series.

Privacy Display may come to more models... Another expected highlight is the expansion of Privacy Display, a feature that makes it difficult for people standing next to the user to view the screen.

In the current generation, the technology is reportedly restricted to the Galaxy S26 Ultra. For the Galaxy S27 line, it is expected to appear on the S27 Pro as well. The S27 and S27+ models are not expected to receive the feature. Notably, the Galaxy S27 Ultra might only mask part of the screen.

Demand for the technology in the current generation reportedly influenced Samsung's plans to expand its presence across the smartphone family.

Costs...Despite the expected increase in component production, Samsung intends to reuse some parts from the Galaxy S26 line for the new devices.

The company also reportedly has ambitious plans for the Galaxy S27 Pro. Samsung's display division expects to produce between 2 million and 3 million panels for the model by the end of this year, and between 4 million and 5 million next year. It is worth noting that while the Galaxy S27 may be significantly more powerful, the price is also expected to rise.

mundophone

 

TECH

Cement-based supercapacitors could power next-generation ‘smart’ buildings

Imagine a future in which the very concrete beneath your feet and around your windows does more than hold a building upright. In that future, the same material that forms slabs, stairs, and load-bearing walls also stores the electricity generated by rooftop solar panels, releasing it in bursts to light corridors, run sensors, and keep emergency systems alive during outages. That vision moved a significant step closer to reality with the publication of a peer-reviewed study in ACS Nano, in which researchers report an efficient, energy-storing cement supercapacitor that, crucially, performs as well as commercial concrete in mechanical tests. 

The work, led by corresponding author Jing Zhong together with colleagues Wencai Ren and Haiping Wu, demonstrates that cement need not be a passive, inert filler in the built environment. Instead, it can be engineered into an active electrochemical component, one that is 3D printable, structurally robust, and capable of powering real electronic devices.

To understand why this result matters, it helps to distinguish supercapacitors from the lithium-ion batteries that dominate consumer electronics. Batteries store large amounts of energy through slow chemical reactions, which is why they take hours to charge and degrade over hundreds or thousands of cycles. Supercapacitors, by contrast, store energy electrostatically, in the electric field that forms at the interface between an electrode and an electrolyte.

They hold relatively small amounts of energy compared with batteries, but they take that energy in and release it extremely rapidly, and in some designs they can survive millions of charge-discharge cycles without significant degradation. That combination of speed and durability makes them attractive for applications where power is needed in short, repeated bursts rather than as a long-duration reserve. For a building fitted with solar panels, supercapacitors embedded in the structure could absorb surges of renewable electricity as they arrive and discharge them on demand, smoothing the mismatch between when energy is generated and when it is actually used.

The central challenge in turning cement into a supercapacitor is that ordinary concrete is a poor electrical conductor. Cement hydrates into a porous, mineral-rich matrix that is excellent at bearing compressive loads but terrible at shuttling electrons and ions. The research team’s solution was to build conductivity directly into the material. They mixed carbon nanotubes, carbon black, and cement together to form a printable electrode ink. Carbon nanotubes are cylindrical structures of carbon atoms just nanometers in diameter, renowned for their exceptional electrical conductivity and mechanical strength. Carbon black, a much cheaper amorphous form of carbon, provides additional conductive pathways and helps form a percolating network throughout the composite. Blended into wet cement, these carbon additives transform the paste from an insulator into an electrode material, while the cement itself continues to cure and harden much as it would in any construction application.

Geometry proved to be just as important as chemistry. Using a 3D printer, the team deposited the electrode ink onto a small concrete slab in a pattern resembling interlocked fingers, a configuration known in electrochemistry as an interdigitated electrode design. In this arrangement, two sets of parallel electrode fingers alternate with one another, like the interlaced fingers of two hands held together without touching. The significance of this geometry lies in the distance that charged ions must travel. In a conventional two-plate capacitor, ions in the electrolyte have to migrate across the entire gap separating the electrodes, which slows the device down and wastes energy as internal resistance. With interdigitated electrodes, every finger of one polarity sits immediately adjacent to fingers of the opposite polarity, so ions move only short distances laterally. As the researchers note, this shortened travel distance made the overall supercapacitor more efficient than previous iterations of cement-based energy storage, which had struggled with exactly this ionic transport bottleneck.

A remarkable feature of the design is that the electrolyte is not added as a separate liquid component but arises from the cement itself. As the cement within the slab hydrated, the chemical reaction that gives concrete its strength, its pores filled with water and dissolved ions that could easily travel between the electrodes. In other words, the very process that turns printable ink into hardened concrete simultaneously creates the ionic medium the supercapacitor needs to function. This monolithic approach, in which electrode, electrolyte, and structural support are one continuous piece of material, is what the study’s title refers to in describing monolithic 3D-printed interdigitated cement-based supercapacitors for structural energy storage. It eliminates the interfaces and packaging that complicate conventional devices and means the energy-storage function can, in principle, be printed wherever a builder wants it within a larger concrete element.

Of course, an energy-storage device embedded in a building is useless if it compromises the building’s safety. Concrete in structural applications must meet strict compressive strength standards, and any multifunctional material has to prove it can carry loads without failing. The researchers therefore subjected their cement supercapacitor to mechanical testing and found that its compressive strength was comparable to that of commercial concrete used in slabs and stairs. This is the result that elevates the work from a laboratory curiosity toward practical relevance. Previous attempts at cement-based energy storage often faced a trade-off, in which adding conductive carbon or porosity weakened the material. Here, the team achieved a device that is simultaneously an electrode, an electrolyte-filled capacitor, and a structural material meeting the expectations placed on ordinary construction concrete.

The researchers also demonstrated that their devices do real electrical work. Three supercapacitors printed on the same slab and wired together successfully powered a small array of LEDs, a modest demonstration on its own but an important proof of concept showing that multiple devices fabricated from a single concrete element can be connected into a functioning energy system. Looking ahead, the team envisions these supercapacitors powering everything from emergency lighting to self-powered sensors. That second application deserves particular attention. Modern buildings increasingly depend on distributed sensor networks that monitor temperature, occupancy, air quality, and structural health, and wiring or periodically replacing batteries for thousands of such sensors is costly and cumbersome. Sensors embedded in or on concrete that draw their operating power from the concrete itself would remove that maintenance burden entirely, enabling dense, self-sustaining monitoring of the built environment.

Like any emerging technology, the cement supercapacitor has identified limits, and the team was candid about one of them. The devices operated stably under moderate heating and cooling, but at around zero degrees Fahrenheit, or minus 18 degrees Celsius, their performance started to wane. This matters because the electrolyte in the system is water-based, arising from the hydration of the cement, and water loses its ionic mobility as it approaches freezing. In cold climates, where buildings must perform year-round, a supercapacitor that fades in deep winter would be a serious limitation. The researchers state that future research will focus on fortifying the supercapacitors against cold-weather conditions, an engineering challenge that will likely involve strategies to keep the pore solution ionically active at low temperatures. It is a reminder that multifunctional materials must satisfy the demands of every function they take on, including environmental resilience across the full range of conditions a building experiences.

The broader implications reach toward what researchers call smart buildings, structures that generate, store, and manage energy within their own fabric. As Jing Zhong explains, if building materials could not only support structures but also store energy, sense their surroundings, and even interact with people, buildings would become more than passive shelters. They could become truly smart environments. The study, published in ACS Nano under the title Monolithic 3D-Printed Interdigitated Cement-Based Supercapacitors for Structural Energy Storage, was supported by funding from the Guangdong Hailong Construction Technology Company Limited, a subsidiary of China State Construction International Holdings Limited, an indication that the construction industry itself sees commercial potential in structural energy storage. 

Considerable work remains before supercapacitor walls appear on job sites, including scaling from small slabs to full structural elements, integrating renewable generation and power electronics, and solving the cold-weather performance gap. But the foundational demonstration is now on the table: a cement-based supercapacitor that stores energy efficiently, prints into interdigitated geometries, powers LEDs, and matches commercial concrete in compressive strength. The walls of future buildings may not merely shelter their occupants. They may quietly hold the charge that keeps those buildings alive.

Cement-based supercapacitors are emerging as a promising technology to transform passive buildings into active energy storage infrastructure, paving the way for the next generation of smart buildings. Research led by institutions such as MIT (Massachusetts Institute of Technology) combines cement, water, and conductive additives—such as carbon black or graphitic carbon by-products—to create an internal fractal network capable of conducting and storing electricity.

How the technology works: Unlike conventional batteries that rely on slow chemical reactions, supercapacitors store energy electrostatically:

1. Conductive mixture: Carbon black (a highly conductive and affordable material) is mixed with cement and water. Due to the carbon's water-repellent nature, interconnected filaments form as the cement cures.

2. High surface area: This reaction creates a vast internal network of microscopic channels within the concrete block, resulting in an enormous surface area.

3. Electrolyte: The material is soaked in a standard electrolyte (such as potassium chloride), allowing ions to accumulate on the conductive cement plates to retain the charge.

Advantages for smart buildings:

• Integrated Structural Storage: Eliminates the need for rooms dedicated to heavy lithium-ion battery banks. Walls, foundations, and slabs themselves function as the building's energy storage system.

• Renewable Energy Support: Helps smooth out the intermittency of local clean energy sources, such as solar panels and wind turbines, by storing surplus energy generated during the day for use during peak evening hours. 

• Dedicated Power Supply: In recent laboratory tests released in October 2026 by the American Chemical Society (ACS), 3D-printed devices embedded in a concrete slab demonstrated mechanical strength comparable to commercial cement and were capable of powering LED arrays and autonomous sensors.

• Long Lifecycle: Supercapacitors charge and discharge almost instantaneously and withstand tens of thousands of cycles without suffering the severe degradation that affects standard batteries.

Current challenges...Although laboratory advances show that a standard-sized residential foundation could store enough energy to meet a home's daily needs, the technology still faces hurdles before reaching the commercial market. Energy density remains lower than that of lithium batteries, and tests indicate that performance drops in extremely cold climates (near -18°C), necessitating further research into chemically fortifying the material for low-temperature conditions.

ACS Nano

 

SONY

Sony Xperia 10 VIII: More expensive, barely better

The Sony Xperia 10 VIII remains a lightweight and compact mid-range smartphone with increasingly rare features such as a headphone jack and microSD support. The most important upgrade over its predecessor is the significantly brighter OLED display. However, given the higher price, mediocre performance, and numerous unchanged components, the overall progress is limited.

The Sony Xperia 10 VIII is one of the more compact smartphones, but it’s a bit on the thicker side at 8.3 mm. We measured 8.5 mm at the outer edges, and up to 10.1 mm including the camera. Weighing 168 g, it’s relatively light and fits comfortably in the hand.

With its rather thick screen bezels, the Sony smartphone looks a bit dated. On the other hand, the display isn’t interrupted by a camera, and the two speakers face forward. The build quality impresses in our test with even and tight gaps. During torsion tests, the Xperia 10 Mk 8 remains rigid and silent. 

The phone is both dust- and water-resistant according to IP65/IP68 standards. Access to the SIM card and microSD slot is also tool-free. 

The Xperia 10 VIII is available in Misty Lilac, Matte Gray, and Frozen White color options.

The Sony Xperia 10 VIII is once again available only with 128 GB of storage, though this can still be expanded using a microSD card. Another rarity is the built-in headphone jack. But that’s about it for the special features. 

For a €600 smartphone, USB 2.0 feels rather meager. Additionally, connected storage devices formatted with NTFS cannot be read. Bluetooth 5.4 and NFC are also on board.

Although the microSD card reader is slightly faster in testing than its predecessor, it still isn’t exactly setting the world on fire. On the plus side, the card can be swapped out without any additional tools.

Software: Only four years of Android version updates...The Sony Xperia 10 VIII ships with Google Android 16 and receives four years of version updates as well as two additional years of security patches.

Sony preinstalls a few of its own apps but is sparing with third-party apps. Only Facebook, Instagram, and LinkedIn come preinstalled. 

However, these apps cannot be completely uninstalled but only disabled.

Sony remains rather vague regarding the Xperia 10 VIII when it comes to sustainability aspects. The housing contains recycled plastic, but the manufacturer does not specify the exact percentage of recycled material. 

The packaging consists of paper and Sony’s original blended material made from bamboo, sugarcane fibers, and recycled paper. Sony also does not provide a product-specific carbon footprint.

Sony does not offer a self-repair program for the Xperia 10 VIII. For hardware defects, the manufacturer refers users to its repair service and authorized service centers.

Sony isn’t exactly generous when it comes to supporting a wide range of mobile frequencies, and this applies to both 4G and 5G. Within Europe, however, this isn’t a problem; it’s only during intercontinental travel that one or two bands may be missing.

Although Wi-Fi 7 isn’t built in, at least 6 GHz Wi-Fi is supported. In testing, this not only delivers high data transfer rates but also ensures stable performance.

The Xperia 10 VIII's satfix is fast and accurate outdoors, even though the smartphone only supports single-band GNSS. It doesn’t take much longer indoors, but it is significantly less precise and also fluctuates considerably.

On a bike ride, we compare the smartphone’s positioning capabilities with those of a Garmin Venu 2. The two devices largely agree on the recorded total distance, differing by only 10 m. 

While the smartwatch tracks the distance traveled more accurately by the lake, the Xperia phone is more precise in the city center.

The call quality of the Sony Xperia 10 VIII felt quite natural when held to the ear, though the suppression of background noise could be better.

Only a nano-SIM card and/or an eSIM can be used.

Cameras: Slow dual-lens system in the Xperia 10 VIII...As for the cameras, everything remains the same — they’re identical to those on the Xperia 10 VII. Despite the small front-facing sensor, it takes pretty good selfies in daylight. However, the camera only records video in HD or full HD at 30 fps. 

The main rear sensor is complemented by an ultra-wide-angle lens. The former features natural white balance and could benefit from a bit more dynamic range, depending on the subject. 

In low light, the camera still produces decent shots, though these require a long exposure time. The ultra-wide-angle lens offers a balanced overall composition, but the image becomes slightly blurry at the edges. Zooming is exclusively digital, and the maximum magnification possible is 6x.

The main camera records videos in ultra HD (30 fps) at best. However, this resolution — as well as full HD at 60 fps — is only available to the main sensor. 

At 168 grams, the Sony Xperia 10 VIII is one of the lighter and more manageable smartphones around. Build quality is convincing, and the chassis carries an IP68 rating. While the wide display bezels look somewhat dated, the screen remains free of notches and punch-hole cutouts. The tool-free microSD slot and increasingly rare 3.5 mm headphone jack are also practical additions. However, with just 128 GB of internal storage and USB 2.0, the feature set feels rather unambitious considering the price. The 6.1-inch OLED display represents the biggest improvement over the Xperia 10 VII. Sony has increased brightness by around 50%, which makes a noticeable difference outdoors. Color reproduction is good, although HDR is not supported. The PWM frequency of 480 Hz could also cause discomfort for sensitive users.

Performance is another area where little has changed: Sony once again uses the Snapdragon 6 Gen 3. It is fast enough for everyday tasks, but occasional stutters are noticeable. Demanding games quickly push the Adreno 710 to its limits. Under sustained load, the Xperia also gets noticeably warm and throttles somewhat. Sony has carried over the cameras from the previous model as well. The main camera delivers natural white balance and still produces decent images in low light, although its dynamic range could be better. The ultrawide camera loses noticeable sharpness toward the edges. The main camera can record video at up to Ultra HD resolution at 30 fps.

On the positive side, the Xperia offers accurate positioning, fast 6 GHz Wi-Fi, and decent call quality. The stereo speakers also sound respectable, although they tend to distort slightly at maximum volume. The 5,000 mAh battery delivers almost 20 hours of runtime in our testing and takes 69 minutes to fully recharge. The Xperia 10 VIII therefore remains an unusual smartphone thanks to its headphone jack, microSD support, good battery life, and bright OLED display. However, there is very little progress over the Xperia 10 VII. Considering the substantial price increase, the aging SoC, USB 2.0, 128 GB of storage, and unchanged cameras are difficult to overlook.

The Sony Xperia 10 VIII stands out with its bright OLED display, good battery life, precise location tracking, and rare extras like a headphone jack and microSD slot. The smartphone's build quality, light weight, and compact design are also appealing. 

However, the high price is offset by a slow Snapdragon 6 Gen 3 processor, only 128 GB of storage, USB 2.0, and unchanged cameras from the previous generation.

The lack of HDR support and occasional stuttering also detract from the overall impression. That being said, compared to the Xperia 10 VII, the significantly brighter display in particular stands out as a real improvement. 

Other new features are relatively minor. Given the substantial price increase, Sony offers too little added value overall compared to its predecessor.

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TECH

Screen effect: Young people's reading skills are declining — and experts fear the impact on anxiety and loneliness

During the 1990s and early 2000s, it was common to hear that this was one of the most well-prepared generations in history. Access to universities was growing, and there was optimism regarding the effects of educational expansion. A few decades later, professors and researchers are raising a different concern: many young people seem to struggle more with reading long, complex texts.

In the United States, university professors report students who cannot keep up with reading lists that were once considered standard. The phenomenon involves changes in education, the loss of reading habits, and a daily life dominated by screens and rapid stimuli.

The problem has already reached American universities. Jessica Hooten Wilson, a professor at Pepperdine University, told *Fortune* that the difficulty observed in some students goes beyond critical thinking.

According to her, there are students who struggle to comprehend even specific sentences and more complex sentence structures.

Other professors report a similar shift. Reading assignments of 25 to 40 pages between classes—once considered normal—are now viewed by some students as a burden that is difficult to manage.

In this context, artificial intelligence tools have entered the equation. Instead of reading the full material, some students turn to chatbots to generate summaries of key points.

This method may speed up studying, but it also eliminates some of the context, nuances, and details found during a full reading.

Consequently, universities have begun adapting their classes. Some have reduced the volume of required reading. Others have started conducting group readings in class or replacing some written content with audio and video.

The problem may begin long before university...The signs are not limited to college students.

Educational data from the United States also reveals difficulties among younger students. In some schools, full books have been replaced by shorter excerpts, reducing students' exposure to lengthy texts. Recent results from U.S. assessments indicate that students are underperforming compared to their counterparts from a decade ago in certain areas. Experts have even used the term "learning recession" to describe part of this trend.

While the pandemic exacerbated various educational issues, it does not account for everything; some negative trends were already evident prior to 2020.

Similar signs are appearing outside the United States. In France, data cited by neuroscientist Michel Desmurget point to reading difficulties among a segment of young adults.

In Spain, conversely, recent indicators regarding the reading habits of children and adolescents are more positive. Even so, teachers report issues with attention and reading comprehension in the classroom.

A major concern is the rise of so-called "skimming" or superficial reading.

Instead of following a text from beginning to end, the reader searches for keywords, highlighted phrases, and quick information. While this behavior is quite useful in certain situations, it differs from the deep reading required to grasp complex arguments.

According to teachers in the United States, some students struggle to maintain focus on long texts.

This difficulty can also trigger an emotional reaction. When individuals come to believe they cannot comprehend a particular book or article, they may avoid reading altogether, thereby losing even more practice.

The result is a potential cycle: less reading leads to reduced familiarity with complex texts, making the next reading experience even more challenging.

Books also help us understand others...The concern extends beyond academic grades. Research links reading habits to various cognitive and social benefits. Books—particularly narratives—expose readers to perspectives, experiences, and situations different from their own.

This can foster skills related to empathy and the understanding of other people.

Michel Desmurget further argues that reading provides valuable knowledge about the world and helps develop the tools needed to analyze information critically. For this reason, researchers and educators fear that a prolonged decline in deep reading could leave young people more vulnerable to simplistic interpretations and misinformation.

Some experts also raise a broader hypothesis: a society that reads less might lose one of the cultural activities that help people share experiences and discuss ideas.

This does not mean that abandoning books directly causes anxiety or loneliness; these phenomena have multiple causes. However, researchers are debating whether the loss of reading-related habits might contribute to an environment of greater isolation.

Our language also seems to be getting simpler...The transformation isn't limited to the reader.

Research has found signs of simplification across various forms of communication. Studies analyzing song lyrics over recent decades have observed shifts in linguistic complexity.

Analyses of political speeches have also identified changes in vocabulary and message structure.

Even certain contemporary books feature more accessible language compared to works from earlier eras.

There is no single explanation for this; cultural, commercial, educational, and technological changes are occurring simultaneously.

But there is one factor impossible to ignore: screens.

Smartphones have changed our relationship with information...Television was already competing with books decades before the internet arrived.

Studies cited by Desmurget show that the leisure time adolescents devoted to reading had already dropped sharply during the second half of the 20th century.

Smartphones and social media have intensified this battle for attention.

Spending hours consuming digital content simply means having less time available for other activities. However, researchers are also studying how the format of these platforms influences the way we consume information.

Short videos, notifications, and infinite feeds provide constant stimulation. Information must grab attention quickly before the user swipes to the next piece of content.

Ángel Barbas, a professor of Communication Theory at UNED, argues that this information avalanche fosters rapid processing and can make it difficult to sustain deep reading.

A generation raised without pauses...To blame young people exclusively would be to ignore the environment in which they grew up.

Generation Z spent much of their childhood and adolescence in an already digitized world. Generation Alpha is growing up in an even more connected environment.

Ariadna Vilalta, author of *Una vida siempre en línea* ("A Life Always Online"), highlights a childhood marked by constant stimulation and few moments of pause.

There is also a shift in life away from screens. In many families, safety concerns have curtailed children's autonomy to play and socialize without supervision. More time spent indoors can also mean more time in front of electronic devices.

Screens, therefore, can be both a cause and a consequence of much broader social shifts.

Reading could become a new kind of privilege...The most worrying consequence may only emerge in the long run.

If the ability to grapple with complex texts becomes increasingly rare, skills related to interpretation, argumentation, and critical thinking could end up being distributed unequally.

In this scenario, families with greater resources could continue to provide books, quiet environments, quality schools, and less reliance on screens, while other groups would have fewer opportunities to develop these habits.

Digital disconnection is already being framed as a sort of modern luxury. Reading could follow the same path. The challenge, then, is not simply to convince a generation to swap smartphones for books. It is to rebuild spaces for attention, silence, and time—allowing children and young people to learn something no technology has rendered obsolete: how to pause before a complex idea and devote enough time to truly understand it.

Young people's reading skills and habits are declining primarily due to the constant distraction of smartphones, social media, and short-form digital content that shorten attention spans and replace deep reading.

Recent reports, assessments, and analyses highlight several core factors contributing to this trend:

Key causes of the decline:

• Digital distractions and Short-Form Media: Platforms like TikTok, Instagram Reels, and general smartphone use train young brains to skim information and crave fast-paced entertainment. This makes focusing on long, dense, or complex texts feel difficult and frustrating.

• The rise of generative AI: Tools that instantly supply ready-made answers reduce the need for young people to wrestle with text, analyze information, and build vocabulary or comprehension skills independently.

• Loss of foundational instruction time: Disruptions from the COVID-19 pandemic caused lasting gaps in basic reading fluency, vocabulary, and comprehension.

• Inadequate teacher training: Many school districts mandate early literacy screenings, but teachers often lack sufficient professional development or confidence to interpret screening data and apply effective instructional methods.

• Simpler books and skimming habits: Even popular modern literature features shorter sentences and simpler structures, reducing the regular mental exercise required to parse sophisticated arguments or literary works

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