Nature Research Intelligence Topics Topic summaries Engineering Fluid Mechanics and Thermal Engineering Computational Methods in Fluid Flow, Heat and Mass Transfer Computational methods are now a ...
Researchers at The Hong Kong University of Science and Technology (HKUST) School of Engineering have developed a novel reinforcement learning–based generative model to predict neural signals, creating ...
Human memory and attention are core cognitive functions that shape perception, learning, and decision-making. And whilst decades of research have provided ...
A computational method for finding transition states in chemical reactions, greatly reducing computational costs with high reliability, has been devised. Compared to the most widely used existing ...
A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...
A team of physicists has developed a groundbreaking method for detecting congestive heart failure with greater ease and precision than previously thought possible. This multidisciplinary study, ...
Researchers from Chinese Academy of Sciences propose a hierarchical Physics-Informed AI framework that balances model fidelity with speed, paving the way for reliable Digital Twins Researchers from ...
Beauty R&D is shifting toward “materials intelligence,” using AI and atom-level simulation to model ingredient interactions, ...
Scientists at La Jolla Institute for Immunology (LJI) have developed a new computational method for linking molecular marks on our DNA to gene activity. Their work may help researchers connect genes ...
Computational methods are now a cornerstone in the study of fluid flow, heat transfer and mass transfer phenomena, underpinning modern simulations that inform both fundamental research and engineering ...