Results 111 to 120 of about 17,094,571 (296)
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
Trump Tariffs 2.0: Assessing the Impacts on US Distilled Spirits Imports
ABSTRACT The proposed 25% tariff on Mexico and Canada could have significant repercussions on US imports of distilled spirits. This study estimates US import demand across various spirit categories (e.g., tequila, whiskey) and assesses the potential impact of the proposed tariff.
Andrew Muhammad
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
This collection consists of a logbook kept by William A. Newton while he served with the quartermaster of the 33rd Arkansas Infantry, as well as correspondence and documents of the Newton ...
Newton, Earnest Joseph, Jr., 1917-2003; Newton, William A., 1829-1908
core +1 more source
A New Algorithm to Approximate Bivariate Matrix Function via Newton-Thiele Type Formula
A new method for computing the approximation of bivariate matrix function is introduced. It uses the construction of bivariate Newton-Thiele type matrix rational interpolants on a rectangular grid. The rational interpolant is of the form motivated by Tan
Rongrong Cui, Chuanqing Gu
doaj +1 more source
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
wiley +1 more source
Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei +9 more
wiley +1 more source
Complementarity Problems in GAMS and the PATH Solver [PDF]
A fundamental mathematical problem is to find a solution to a square system of nonlinear equations. There are many methods to approach this problem, the most famous of which is Newton?s method.
Ferris, Michael C. +5 more
core
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai +3 more
wiley +1 more source
Adaptive Collision Sensitivity for Efficient and Safe Human–Robot Collaboration
An adaptive collision‐sensitivity framework uses each robot link's effective mass to estimate contact forces online and decide when collaborative robots should stop or continue. Tested on simulated and real UR10e and simulated KUKA arms, it maintains conservative force estimates while reducing unnecessary stops and increasing task productivity. What is
Lukas Rustler +2 more
wiley +1 more source

