Machine Learning Joins Forces With Quantum Physics to Accelerate Clean Energy Materials Discovery
A new review argues that integrating density functional theory with machine learning has matured into a powerful, experimentally validated engine ...
A new review argues that integrating density functional theory with machine learning has matured into a powerful, experimentally validated engine ...
A new open-source Python package called QEGuard applies explicit eligibility checks before allowing parameters from prior Quantum ESPRESSO simulations to ...
A new computational study reveals that quantum electron sharing between atoms, rather than classical electrostatics, drives the exceptional stability of ...
An ethanolic extract of the widespread weed Cosmos sulphureus inhibited mild steel corrosion in hydrochloric acid by up to 92.77 ...
Researchers have developed an interpretable multitask deep learning framework, trained on density functional theory calculations, that simultaneously predicts how strongly ...
A machine-learning-driven statistical analysis of a six-metal high-entropy alloy reveals that its CO tolerance in alkaline hydrogen oxidation arises from ...
Researchers have combined quantum-mechanical simulations, neural networks, and Bayesian statistics to cut the voltage prediction error of a physics-based lithium-ion ...
First-principles calculations show that swapping A-site atoms in MA2N4 two-dimensional materials yields five compounds, including MoC2N4 and ZrGe2N4, capable of ...
Scientists converted a polysaccharide from the medicinal plant Polygonatum cyrtonema Hua into Schiff-base-functionalized carbon dots that anchor silver nanoparticles for ...
First-principles calculations reveal that hydrostatic pressure drives layered cadmium iodide through a semiconductor-to-metal transition and a topological insulating phase near ...
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© 2025 Scienmag - Science Magazine