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Smartphones may soon be able to track hidden objects using LiDAR

Modern smartphones are packed with incredible technology, from high-resolution cameras and advanced graphics chips to AI processors. In premium models, this hardware includes LiDAR (light detection and ranging), which helps power augmented reality features and improve depth sensing.

And that capability could soon be in for a seriously impressive upgrade. Researchers at the Massachusetts Institute of Technology (MIT) have developed an algorithm that lets a phone’s LiDAR sensor detect objects hidden around corners. Details are in a paper published in the journal Nature.

Typically, this type of non-line-of-sight (NLOS) capability is found in labs and relies on bulky, expensive research-grade hardware. But the team’s breakthrough makes it possible for consumer LiDAR sensors to peek behind obstacles.

New framework helps robots turn complex language into precise 3D actions

Over the past few decades, roboticists worldwide have introduced increasingly advanced robots that can understand human instructions, move in their surroundings and reliably complete basic manual tasks. While they perform well in some scenarios, many of these robots still struggle to translate the instructions of users into precise and executable actions that would allow them to successfully complete desired tasks.

Recently, computer scientists have been trying to improve how robots respond to user commands or queries using vision-language models (VLMs), artificial intelligence (AI) systems trained to process both images and texts. These models can typically interpret basic requests such as “place the bottle onto the plate,” yet they often do not exhibit the spatial reasoning capabilities required to interpret more elaborate instructions and translate them into executable actions in real-world settings.

Researchers at the Chinese University of Hong Kong, the Zhejiang Humanoid Robot Innovation Center Co. Ltd and other institutes recently introduced Retrieval-Augmented Manipulation (RAM), a framework that could improve the ability of robots to connect abstract instructions with three-dimensional (3D) representations of the space around them. The new framework, presented in a Science Robotics paper, was found to improve the spatial reasoning capabilities of robots, allowing them to reliably follow more elaborate instructions, without requiring task-specific training.

‘Designer’ superconducting diamond: Researchers uncover path to multi-modality quantum chips

Diamond is extremely valuable to science and technology not for its sparkle but for its extreme hardness, high thermal conductivity, transparency to a large fraction of the light spectrum, and a host of other exceptional properties. Two decades ago, scientists discovered another advantage: under the right conditions, diamond can become a superconductor—allowing electricity to flow through it with zero resistance.

Until recently, though, they knew little about how that happens, limiting its use in high-tech applications.

Now researchers from the Pennsylvania State University, the University of Chicago Pritzker School of Molecular Engineering (PME), and the U.S. Department of Energy National Quantum Information Science Research Center Q-NEXT, led by Argonne National Laboratory, have uncovered new insights into the physics behind the phenomenon by carefully creating high-quality diamond, isolating electronic signatures from material noise, and revealing the fundamental mechanisms that had long remained hidden.

Novel porous gel changes color, shrinks and hardens when it detects target molecules

Researchers at Kyoto University and Tohoku University have developed a new porous polymer gel that selectively recognizes specific molecules (referred to as “guests” in the study) through coordination chemistry and converts these invisible molecular-scale interactions into strikingly visible, macroscale deformation.

The study demonstrates how subtle differences in molecular structure can directly alter the shape, color, and mechanical properties of a soft material, opening new possibilities for “smart” stimuli-responsive materials and molecularly programmable soft matter that can sense and react to its environment.

Molecular recognition is a central concept in supramolecular chemistry and biology, where molecules selectively interact through precisely arranged chemical interactions. While most artificial molecular recognition systems rely on noncovalent interactions such as hydrogen bonding, the present study instead exploits coordination interactions —a type of chemical “handshake”—between metal centers and electron-rich guest molecules.

Scientists generate electricity from ambient moisture using everyday ingredients

In a study published in Nano Energy, researchers from Queen Mary, the University of Warwick, Imperial College London, and Universitas Mercatorum report a highly stable, biodegradable Moisture-Electric Generator (MEG). The device is fabricated from food-grade materials including gelatin, sodium chloride (table salt), and activated carbon, and harnesses humidity—typically a major challenge for electronics—as its energy source.

This approach represents a significant shift in electronic design, transforming atmospheric moisture from a limitation into a functional energy input.

Using pulsars as ultra-precise gravitational probes to ‘weigh’ neighboring galaxies

Researchers at The University of Alabama in Huntsville (UAH), a part of The University of Alabama System, have identified a promising new method for measuring the mass of galaxies orbiting the Milky Way by using pulsars, some of the universe’s most precise natural clocks, to detect tiny gravitational effects across our galaxy.

The work, published on the arXiv preprint server, offers a novel approach for studying the hidden dark matter contained within nearby satellite galaxies. The findings could have broad implications for astrophysics and cosmology.

The study was authored by UAH astrophysicists Dr. Thomas Donlon, postdoctoral research assistant II, and Dr. Sukanya Chakrabarti, a professor and Pei-Ling Chan Endowed Chair in the College of Science, in collaboration with Dr. Jason A. S. Hunt, an astrophysicist at the University of Surrey, U.K. The research examines how the gravitational pull of neighboring dwarf galaxies subtly disturbs the Milky Way.

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