New York University researchers have trained an AI model to learn chemical patterns associated with stability in drug-like molecules and accurately predict where their hydrogen atoms should be positioned.

Their research, published in the journal Chemical Science, addresses a longstanding challenge in molecular design and drug discovery: how to rapidly and reliably determine the stable form of molecules that share a molecular formula but readily convert into different forms. 

The novel physics-constrained AI framework PHICS realizes a full closed loop spanning multiscale inverse design and experimental validation. Leveraging interface, phase, and carrier engineering, PHICS breaks long-standing material trade-offs to yield composite phase-change materials that achieve simultaneous enhancements in thermal conductivity and electrical insulation while maintaining high thermal storage density, paving new pathways for designing advanced electronic thermal management materials.

UCLA researchers developed a scalable, energy-efficient optical-neural system for deepfake video detection. The system combines a lightweight digital front-end with a spatially-multiplexed optical decoder, simultaneously analyzing ≥15 video streams in a single optical pass. On the Celeb-DF dataset, it experimentally achieved accuracy/sensitivity/specificity of 97.79/99.86/95.72%, respectively. Researchers also demonstrated robustness against video degradation, noise, compression, misalignments, and adversarial attacks, highlighting the potential of optical computing for high-throughput and multiplexed content moderation and security-critical AI applications.

Until now, organic light-emitting diodes have not been compatible with the high-precision, but chemically harsh manufacturing processes used in the semiconductor industry. Researchers at ETH Zurich and the University of Helsinki have developed light-emitting polymers that also serve as photoresists and can be precisely patterned using photolithography – an established process in the chip industry. This enables the production of tiny, coloured OLED pixels for screens, as well as precise light sources for research and medical technology.

Researchers have developed a fast, non-intrusive diagnostic approach for resolving the electron-density evolution of plasma generated by microscale explosive detonation. By combining microwave Rayleigh scattering with high-speed imaging, optical emission spectroscopy, thermodynamic calculations, and finite-element simulations, the study quantitatively determines the time-resolved electron density of HMX detonation plasma. The electron density reaches the order of 10²⁵ m⁻³, persists for approximately 1.91 μs, and exhibits a pronounced multi-peak evolution associated with the pulsation of detonation products.

Astrophysicists from The University of Hong Kong (HKU), working with a research team led by Beijing Normal University (BNU), have developed a more physically realistic approach to testing how ultralight, or “fuzzy”, dark matter could influence gravitationally lensed images. The study is the first to make gravitational-lensing predictions directly from three-dimensional wave simulations of fuzzy dark matter. The simulations reproduce the observed image positions of a well-studied lensed quasar more closely than commonly used modelling approaches, highlighting the potential of high-resolution gravitational-lensing observations to probe the nature of dark matter. The findings of this research study have been published in The Astrophysical Journal Letters.

Researchers from the Xishuangbanna Tropical Botanical Garden (XTBG) of the Chinese Academy of Sciences and their collaborators revealed that plant community turnover and nematode body width play fundamental roles in shaping soil nematode diversity across different spatial scales. Their findings highlight that protecting the variety of plant species is essential for preserving nematode diversity and that a nematode's body width largely determines how it spreads across the environment.

Lactic acid is a key building block for biodegradable plastics, but producing it efficiently from renewable biomass remains challenging. Researchers have now developed a defect-engineered metal-organic framework catalyst that converts glucose into lactic acid with substantially improved efficiency, while also showing activity toward raw biomass feedstocks.