Engineers have developed a robotic arm that draws on the sensory architecture of the octopus to solve one of soft robotics’ persistent problems: how a machine can reliably grasp irregularly shaped objects without visual feedback alone.

The system integrates distributed tactile sensors across a flexible, multi-segment limb, allowing it to register contact force, surface geometry, and slip events simultaneously.

Why the octopus offers a useful mechanical model

The octopus arm is not simply a flexible appendage. Each of its eight arms contains roughly two-thirds of the animal’s total neurons, enabling semi-autonomous local processing of sensory data.

This distributed neural architecture means the animal does not need to route every tactile signal to a central brain before responding. Engineers working on dexterous manipulation have long recognized this as a functionally efficient design worth replicating in hardware.

The research team constructed their arm from soft elastomeric segments embedded with arrays of pressure-sensitive elements. Rather than relying on a single point of force measurement, the design distributes sensing across the full contact surface, producing a spatial map of pressure that updates continuously during a grasp.

Tactile sensor architecture and signal processing

The tactile sensors in the system function as piezoresistive or capacitive transducers — materials that change their electrical resistance or capacitance in proportion to applied mechanical load.

When arranged in a dense grid across the arm’s inner surface, they generate pressure maps with sufficient spatial resolution to distinguish, for example, the edge of a cylindrical object from a flat face.

Critically, the arm’s control architecture processes this tactile data locally before passing summary signals upstream. This reduces communication latency and means the limb can initiate corrective motion — tightening around a slipping object, for instance — faster than a centralized controller could respond.

The approach mirrors the ganglionic processing found in cephalopod arms, where reflex-like responses originate at the limb level rather than at the brain.

For engineers building manipulation systems for unstructured environments such as surgical robotics, subsea inspection, or warehouse automation, this matters because object geometry is rarely known in advance and visual occlusion is common once contact is made.

Tactile feedback fills that perceptual gap. Related work on soft robotic grippers has shown that compliance alone is insufficient without closed-loop sensory feedback to govern contact forces.

Structural compliance and material tradeoffs

Building a soft arm that is both compliant enough to conform to object surfaces and stiff enough to transmit useful gripping force is a recurring material tradeoff in the field. Elastomeric bodies deform under load, which helps distribute contact stress but also makes proprioception — knowing the arm’s own shape — difficult without additional strain sensors.

The research team addressed this by embedding shape-sensing elements alongside the tactile arrays, giving the controller a real-time estimate of limb configuration.

This dual-sensing approach adds fabrication complexity and raises questions about long-term durability. Soft elastomeric materials are susceptible to fatigue, tearing, and delamination at sensor integration points, particularly under repeated flexion cycles.

Whether the sensor-elastomer interface can withstand the cycle counts required for industrial deployment remains an open question the team has not fully resolved.

Constraints on deployment and scaling

The current prototype demonstrates proof-of-concept grasping across a range of object shapes, but several engineering constraints limit near-term application.

The actuators driving the soft segments — typically pneumatic or tendon-based — introduce their own latency and require external pressure sources or motor assemblies that offset the compactness the soft body provides. Miniaturizing these systems without degrading force output is a known challenge in soft robotics research.

Power consumption for continuous tactile sensing across large sensor arrays also scales non-trivially. In a system with hundreds of individual sensing elements, maintaining real-time readout requires dedicated multiplexing circuitry, adding weight and heat load that a fully untethered platform must manage within tight energy budgets.

A team of international researchers has uncovered new evidence that the Chicxulub meteorite impact, long known for causing the extinction of the dinosaurs, also created an underground environment that supported life for millions of years longer than previously thought.

This groundbreaking study not only reframes the narrative of Earth’s most infamous mass extinction event but also offers fresh insights into the origins of life on our planet and potentially others.

Meteorite impact: Catastrophe and opportunity

66 million years ago, a 6-mile-wide asteroid slammed into the Yucatán Peninsula, forming the Chicxulub crater and triggering a mass extinction that eradicated around three-quarters of Earth’s species, including all non-avian dinosaurs. The catastrophic event left a crater nearly 200 kilometers in diameter and profoundly altered the planet’s surface and subsurface environments.

Beneath the devastation, the collision’s immense heat fractured rocks, mingled with seawater, and set off the formation of a vast hydrothermal system—an underground network of hot water and porous rocks. These conditions, the researchers say, were ideal for sustaining microbial life, creating countless microenvironments that shielded organisms from surface extremes.

Expedition 364: Drilling for answers

In 2016, scientists from the International Ocean Discovery Program and International Continental Scientific Drilling Program embarked on Expedition 364 to drill into the crater’s peak ring. There, they collected samples of potassium-rich feldspar, a mineral formed from circulating hot fluids after the impact. Dr. Annemarie Pickersgill of the Scottish Universities Environmental Research Centre (SUERC) used advanced argon-argon dating techniques to analyze the feldspar.

The results were astonishing: the hydrothermal system persisted for at least eight million years—about four times longer than previous estimates. The team’s computer models, updated with new geological and physical data, confirmed that a combination of high rock permeability, sustained heat from the impact, and natural geothermal conditions allowed the underground system to endure far longer than once believed.

Implications for astrobiology and Earth’s origins

The study has wide-reaching implications. Dr. Pickersgill noted, “Wherever on Earth you find flowing warm water, you find life… we were still surprised by the outcomes of our research.” The findings suggest that impact-generated hydrothermal systems could have incubated early life on Earth and may exist elsewhere in the solar system.

Dr. Evangelos Christou, co-author and former PhD student at the University of Glasgow, highlighted how advances in computational modeling made it possible to simulate these complex systems with unprecedented accuracy. This research could inform the search for extraterrestrial life, particularly on planets like Mars, which experienced many large impacts during periods when water was more abundant.

Next steps in the search for life

The team stresses that impact craters may be prime locations for future astrobiological exploration. The porous rocks and underground heat could have provided refuge for life, both on early Earth and on other planets. As Dr. Pickersgill observed, “These findings could help future missions to other planets determine which impact craters might have been most likely to sustain life.”

The research brought together experts from institutions including the University of Glasgow, Purdue University, University of Texas at Austin, and several others, collectively advancing our understanding of how cataclysmic impacts can also spark conditions ripe for the emergence of new life.

The study was first published in the journal Communications Earth & Environment.

A Columbia University-led team has developed a revolutionary microscopy technology that could dramatically advance 3D tissue imaging while slashing costs and complexity.

The work, led by Professor Raju Tomer and published in Nature Biotechnology, introduces a new optical framework and modular microscope add-ons that could make high-resolution imaging accessible to labs and clinics worldwide.

Breaking barriers in 3D tissue imaging

High-resolution, three-dimensional images of intact tissues are crucial for mapping neural circuits, diagnosing disease, and training artificial intelligence systems.

However, traditional imaging tools force researchers to choose between expensive, shallow-depth, oil-immersion lenses or cheaper, deep-penetrating air lenses that blur when used with chemicals that clear tissue for 3D viewing.

The HySIL innovation

The Tomer team’s innovation, dubbed HySIL (Hybrid Solid–Liquid Optics), pairs a simple curved solid lens with a custom-matched immersion liquid, allowing the two to function as a seamless optical system.

This enables even inexpensive air lenses to deliver sharp, high-resolution images through centimeter-scale tissues, regardless of the common sample preparation method—without hardware changes.

To showcase the technology, the researchers built SCOPE, a modular device that attaches to existing light-sheet microscopes, and Super-SCOPE, a proof-of-concept variant offering even higher resolution.

These technologies have also been integrated into a compact, projector-based light-sheet microscope (pLSM) developed by Tomer’s group in 2024, which is now commercially available as SLICE.

“Our design breaks the long-standing trade-off between performance and accessibility in microscopy,” Tomer explained. “By making the immersion liquid an active optical component, we achieve the performance of elite systems at a fraction of the cost—suitable for teaching labs or clinics in low-resource settings.”

In collaboration with academic partners, the team demonstrated pLSM-SCOPE’s capabilities on whole mouse, salamander, and cavefish brains (for neural circuit mapping), lab-grown human brain tissues (for disease and development studies), and intact human cancer biopsies (for 3D pathology). HySIL is versatile and can enhance other types of microscopes, including confocal and two-photon systems.

Jack Glaser, co-founder and CEO of MBF Bioscience—an industry partner—praised the technology’s practical impact: “HySIL offers the rare combination of lower cost and higher performance. Engineering this into a reliable system makes advanced imaging broadly available to working labs.”

For decades, tissue analysis has largely relied on thin, two-dimensional slices, but the new technology enables affordable, accessible 3D imaging—crucial for visualizing the full architecture of tissues.

Hanina Hibshoosh, Professor of Pathology and Cell Biology at Columbia University Irving Medical Center, emphasized: “3D imaging lets you see entire tissue structures, not just cross-sections. Affordable tools like pLSM-SCOPE will be essential as AI expands our ability to analyze tissue data.”

A transformative step for research, medicine and AI

The research was supported by the National Institutes of Health, and Columbia University has filed patent applications on the technologies. Tomer has served as a consultant for MBF Bioscience, with several co-authors also employed there. Other Columbia contributors include Professors Rene Hen, Christopher Makinson, and Maria Tosches, as well as a team of postdoctoral fellows, doctoral candidates, and research staff.

Tomer concluded, “Access to dense, tissue-scale image datasets will transform biology and medicine as both increasingly depend on detailed imaging.”

Engineers have studied how jumping spiders see and used this unusual biological model to create a working 3D imaging device called SpiderCam. Unlike traditional depth cameras, SpiderCam avoids the usual bulk and high energy use. Their research could lead to smaller, more efficient sensors for robotics, medical devices, and autonomous systems where saving space and power is important.

How spider vision differs from conventional optics

Most jumping spiders have a layered retina in their main eyes that can capture images at different focal depths at the same time. Each layer is set at a different depth, so the same light creates several blurred images at once.

The spider’s nervous system uses the differences in blur between layers to figure out depth. It does this without needing two cameras, time-of-flight pulses, or special light projectors.

Most 3D cameras use one of three methods: comparing images from two separate sensors, measuring the time it takes for light to bounce back (like LiDAR), or projecting patterns of light onto a scene.

Each of these methods requires additional hardware, such as more lenses, more light sources, or wider spacing between sensors, which makes it hard to make them small. The spider’s way, called depth from defocus, uses just one eye and doesn’t need any of that extra equipment.

Translating biology into a functional sensor

The research team built a multi-layered optical system that copies the spider’s retina. They used a special lens and aperture setup to split light in a way that creates both sharp and blurred images on a stack of sensors. Then, computer processing turns the differences in blur into a detailed depth map.

As a result, this sensor works passively. It does not need to send out infrared pulses or project patterns, which means it uses much less power.

The elimination of an active illumination source also means the device works in outdoor daylight without the signal-washout problems that plague many IR-based depth sensors.

Calibration is a challenge for depth-from-defocus systems. The way blur relates to depth is very sensitive to small differences in the lens and how the device is made, so each unit may need its own calibration. This could make mass production more difficult unless the assembly process is highly precise.

Depth accuracy and working range trade-offs

Depth-from-defocus systems have a inherent limit on accuracy, determined by the lens opening and the sensor’s resolution. Bigger lens openings help measure depth more accurately up close, but they also shorten the range over which the system works well.

Because of this, the spider-inspired design has to be adjusted for a specific distance range. This means it is less flexible than LiDAR, which can measure depth over much longer distances.

This trade-off is fine for close-up applications, such as surgical cameras, drones avoiding nearby obstacles, or robots handling objects. But it does not work well for self-driving cars that need to see far ahead at high speeds.

Fabrication and integration outlook

Stacking photodetector layers with precisely spaced optical elements at small form factors requires fabrication processes compatible with existing CMOS foundry workflows — something the research team appears to have considered in the sensor’s design.

Whether the layered stack can be produced at wafer scale without accumulating alignment errors that degrade depth accuracy remains a central engineering question before any commercial iteration is feasible.

More broadly, this research shows that biological visual systems evolved to work well with very limited energy and space. This makes them good models for engineers who need to design efficient hardware under similar limits.

The jumping spider’s retina has been shaped by those pressures across millions of generations, and the depth-sensing solution it arrived at — passive, monocular, multi-focal — is one that silicon engineers are only now beginning to replicate with sufficient fidelity to be useful.

A research team has fabricated a functional computer chip using molybdenum disulfide (MoS2), a two-dimensional semiconductor material, integrating 1,400 transistors onto a single chip — a milestone in the effort to build AI-capable hardware beyond the limits of conventional silicon.

The work addresses a specific bottleneck in modern computing: the energy cost of running machine learning workloads on silicon-based devices. As AI models grow in parameter count, the gap between what silicon can efficiently deliver and what inference tasks demand has widened considerably.

What MoS2 brings to chip design

MoS2 belongs to a family of transition metal dichalcogenides — layered materials that can be exfoliated or grown down to a single atomic layer, typically around 0.65 nanometers thick. Unlike silicon, which degrades in electrical performance below approximately 5 nanometers, MoS2 retains a direct bandgap at the monolayer scale.

That property allows transistors built from it to switch cleanly between on and off states even at extreme thinness, which is the fundamental requirement for digital logic.

The bandgap in monolayer MoS2 sits at approximately 1.8 electronvolts (eV), compared to silicon’s 1.12 eV. A wider bandgap generally translates to lower leakage current — the parasitic drain that wastes energy in densely packed transistor arrays. For AI inference tasks running millions of switching cycles per second, that reduction in leakage carries direct power savings.

Fitting 1,400 transistors onto a single MoS2 chip is a meaningful step beyond prior demonstrations, which have typically remained in the range of tens to a few hundred devices.

The researchers reportedly achieved this by refining gate dielectric deposition — the insulating layer that sits between the gate electrode and the semiconductor channel — to reduce interface defects that would otherwise scatter charge carriers and degrade switching speed.

The fabrication challenge

Scaling 2D semiconductor devices is not a straightforward extension of silicon process flows. MoS2 films grown by chemical vapor deposition (CVD) frequently contain grain boundaries — interfaces between crystalline domains — that act as scattering sites and increase resistance. Achieving uniform coverage across a full wafer while controlling grain size remains an open problem in the field.

Contact resistance at the metal-to-MoS2 junction also poses a persistent obstacle. In silicon transistors, highly doped source and drain regions reduce this resistance to negligible levels.

In MoS2, the absence of established doping protocols means engineers must rely on work-function-matched metal contacts, a solution that works in laboratory devices but has proven difficult to reproduce at wafer scale.

These fabrication constraints put the 1,400-transistor chip in a different context from commercial silicon, where leading-edge nodes pack billions of transistors per square centimeter. The MoS2 result is better understood as a proof of circuit-level functionality rather than a density record.

Where this fits in the post-silicon roadmap

The semiconductor industry has operated under a de facto assumption that silicon will reach physical scaling limits sometime in the 2030s, prompting sustained investment in alternative channel materials.

MoS2 and other 2D materials appear in the International Roadmap for Devices and Systems (IRDS) as candidate channel replacements for sub-1nm nodes, precisely because their atomic thinness sidesteps the quantum tunneling problem that degrades silicon at those dimensions.

Whether MoS2 can transition from research chips to manufacturable products depends less on the physics, which appears favorable, and more on whether CVD growth processes can hit the defect-density targets that foundry-level yield requires. The 1,400-transistor result suggests circuit complexity is no longer the binding constraint — materials uniformity and contact engineering are.

If those process questions are resolved, ultra-thin MoS2 chips could eventually find a first deployment not in high-performance data center accelerators but in edge AI devices, where the combination of low leakage current and physical thinness aligns with strict power and form-factor budgets.

This work was first published in the journal Nature Electronics.

China has unveiled the Z-21, a heavy attack helicopter that military analysts are comparing directly to the Boeing AH-64E Apache Guardian, the United States Army’s primary rotary-wing strike platform. The aircraft’s emergence marks a concrete step in China’s effort to field a domestically produced heavy attack helicopter capable of operating in high-intensity contested environments.

Airframe design and propulsion

The Z-21 follows a tandem-seat, twin-engine configuration consistent with modern dedicated attack helicopter doctrine. Its airframe geometry — including stub wings for weapon pylons and a narrow fuselage cross-section — mirrors the layout optimized for survivability and aerodynamic performance in nap-of-the-earth flight.

The helicopter is reported to be powered by turboshaft engines developed domestically, a departure from earlier Chinese rotorcraft programs that relied heavily on foreign powerplant technology. Precise engine designation and shaft horsepower output have not been officially confirmed by the People’s Liberation Army (PLA).

Weapons and sensor suite

The Z-21 is equipped with a chin-mounted cannon and provisions for air-to-ground missiles, anti-tank guided munitions, and unguided rocket pods across four hardpoints on its stub wings. Reports indicate integration of a millimeter-wave fire control radar — analogous to the Longbow radar mast system on the AH-64E — enabling over-the-horizon target acquisition and engagement in degraded visibility conditions.

A multi-spectral targeting system mounted in a nose turret is expected to provide infrared and day/TV imaging for precision engagement. These are capabilities the AH-64E has carried operationally for over a decade, meaning the Z-21 would be entering the field at a level of sensor maturity the Apache already surpasses in software and network integration.

How it stacks up against the AH-64E Apache

The AH-64E Apache operates with Link 16 datalink compatibility, manned-unmanned teaming (MUM-T) with reconnaissance drones such as the MQ-1C Gray Eagle, and a target handoff system that allows crews to pass fire missions across platforms in near-real time.

Whether the Z-21 has achieved comparable network interoperability within PLA joint-force architecture remains unclear from available information.

On gross weight and payload, the Z-21 appears to fall in a similar class to the Apache’s roughly 10,400 lb (4,717 kg) maximum takeoff weight, though official Chinese specifications have not been released. This matters operationally: payload capacity directly constrains the missile and fuel load carried on a given mission profile, affecting both range and lethality.

Survivability features

The AH-64E incorporates radar-absorbent materials, infrared suppression on exhaust outlets, and a ballistically tolerant rotor system designed to sustain hits from 23 mm projectiles. It is not yet established whether the Z-21 meets comparable protection standards.

Engine reliability and maintenance logistics for domestically produced Chinese turboshafts also carry uncertainties, given the historical difficulties PLA aviation programs have faced in achieving consistent turbine performance at scale.

For readers interested in how rotary-wing platforms fit into broader strike architectures, the US Army’s Future Attack Reconnaissance Aircraft program offers relevant context on next-generation attack helicopter requirements being pursued in parallel.

Strategic context for PLA rotary aviation

The Z-21’s development fits within a wider PLA modernization effort that has prioritized closing capability gaps in close air support and anti-armor warfare. Taiwan Strait contingency planning, as well as high-altitude operations along the Sino-Indian border where the Z-10 medium attack helicopter has already deployed, likely informed the Z-21’s design requirements.

A heavier, more capable platform extends the PLA’s ability to conduct sustained attack helicopter operations in mountainous or fortified terrain where ordnance load matters.

Until the Z-21 completes operational testing and enters confirmed PLA service, claims about its combat effectiveness relative to the AH-64E remain speculative. The gap between a prototype photograph and a battle-ready weapons system in serial production is one that Chinese aerospace programs have historically taken years to close.

💾