7-Apr-2026 Machine-learning guides discovery of multi-principal element alloys as electrocatalyst for hydrogen evolution reaction HEP Data Cooperation Journals This study develops an ML-assisted approach for accelerating the discovery of HER electrocatalysts in multi-principal element alloys. With ultralow material costs and record-breaking electrocatalytic metrics, the NbZnCo2 alloy exhibits exceptional potential for industrial alkaline water electrolyzers. Journal Acta Physico-Chimica Sinica
7-Apr-2026 Machine learning potentials for property predictions of two-dimensional group-III nitrides HEP Data Cooperation Journals A high-precision machine learning potential based on the Deep Potential method was constructed to systematically investigate the lattice dynamics, thermodynamic properties, mechanical behaviors, and thermal transport of two-dimensional Group-III nitrides with first-principles accuracy. Journal Acta Physico-Chimica Sinica
7-Apr-2026 LASPAI: AI-powered platform for the future atomic simulation HEP Data Cooperation Journals A web-based platform integrating generalized global neural network potentials and diffusion generative models was developed to resolve the accuracy-efficiency dilemma and democratize access to complex atomic simulations. Journal Acta Physico-Chimica Sinica
7-Apr-2026 High-rate and long-cycling P2-type cathode material for sodium-ion batteries HEP Data Cooperation Journals A multi-element doping strategy was employed to design a stable P2-type cathode (P2-Na0.67Zn0.05Ni0.23Fe0.1Mn0.57Ti0.05O2) that suppresses high-voltage phase transition, demonstrating a capacity retention of over 85% after 300 cycles at a 3C rate. Journal Acta Physico-Chimica Sinica
7-Apr-2026 Data-driven framework unlocks fast track to high-performance MnO2 cathodes HEP Data Cooperation Journals This study develops a high-accuracy machine-learning framework to predict and optimize metal-doped MnO2 cathodes for aqueous zinc-ion batteries, validated through experiments and DFT, enabling rapid performance guidance. Journal Acta Physico-Chimica Sinica
7-Apr-2026 CADD and AI for the next-generation therapeutics HEP Data Cooperation Journals The deep integration of computer-aided drug discovery (CADD) and artificial intelligence (AI) is ushering in a new era of precision and efficiency in next-generation therapeutics by reshaping R&D paradigms, unlocking the potential of biological big data, and accelerating the development of innovative therapies. Journal Pharmaceutical Science Advances
6-Apr-2026 Artificial intelligence for organelle segmentation in live-cell imaging Research Recently, Assoc. Prof. Bo Peng (Northwestern Polytechnical University) and Prof. Lin Li (Xiamen University), et al., systematically reviewed the evolution of organelle segmentation algorithms in live-cell imaging, highlighting key challenges such as three-dimensional segmentation, simultaneous multi-organelle segmentation, and cross-modality generalization. Journal Research Funder National Natural Science Foundation of China, Key Research and Development Program of Shaanxi, Fujian Provincial Natural Science Foundation of China, Innovation Foundation for Doctorate Dissertation of Northwestern Polytechnical University, Postdoctoral Fellowship Program of CPSF, Startup Program of XMU, Fundamental Research Funds for the Central Universities, Australian Research Council
6-Apr-2026 Turning biomass into better rubber: Biochar emerges as a sustainable alternative to carbon black Biochar Editorial Office, Shenyang Agricultural University A new review highlights how biochar, a carbon-rich material made from agricultural and organic waste, could help transform the rubber industry by reducing reliance on fossil-derived carbon black while maintaining strong material performance. Journal Biochar
6-Apr-2026 More than a pretty picture, star-shaped nanomaterial changes energy storage University at Buffalo University at Buffalo researcherscreated the first-ever star-shaped vanadyl hydroxide (VOOH) and shown that this shape can fundamentally alter how the material stores energy. Journal Nanoscale
6-Apr-2026 Genomic study reveals heartworm’s ancient origins and global journey Texas A&M University For decades, scientists have assumed canine heartworms spread globally alongside modern dog movement, but new genomic research co-authored by researchers from the Texas A&M College of Veterinary Medicine and Biomedical Sciences (VMBS) suggests that assumption may be incomplete, pointing instead to a far older and more complex evolutionary history. Journal Communications Biology Funder Canine Research Foundation, Dogs Victoria, Australian Companion Animal Health Foundation
