Results 201 to 210 of about 3,006,412 (323)

ThermoPred: AI-Enhanced Quantum Chemistry Data Set and ML Toolkit for Thermochemical Properties of API-Like Compounds and Their Degradants. [PDF]

J Chem Inf Model
Santos DP, Dias-Silva JR, Júnior LHKQ, de Oliveira HCB.   +3 more
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

SIREN: suite for intelligent RNAi design and evaluation of nucleotide sequences. [PDF]

Bioinform Adv
Vargas-Mejía P, Vega-Arreguín J.
europepmc   +1 more source

Comparison of thermodynamic database models and APT data for strength modeling in high Nb content γ–γ′ Ni-base superalloys

, 2015
S. Antonov, M. Detrois, D. Isheim, D. Seidman, R. Helmink, R. Goetz, Eugene Sun, S. Tin   +7 more
semanticscholar   +1 more source

Atomistic Insights Into Lithium Alloying and Crystallization at Metal Interlayers in Zero‐Excess Lithium Batteries

Advanced Energy Materials, EarlyView.
Molecular dynamics simulations with machine learning potentials, combined with experiments, reveal how interlayer metals govern Li alloying and crystallization in zero‐excess lithium batteries. Mg and Zn promote solid‐solution alloy‐mediated pathways that influence Li diffusion and structural uniformity, while Bi forms ordered intermetallics with more ...
Neubi F. Xavier Jr., Nicolas Rospars, Mohammed Srout, Matthew K. Sharpe, Pablo Hernández‐Martín, Callum D. McAleese, Satheesh Krishnamurthy, Tao Chen, Celia Polop, Andrea Ingenito, Qiong Cai   +10 more
wiley   +1 more source

M4SF-17LL010301071: Thermodynamic Database Development

, 2017
M. Zavarin, T. Wolery
openaire   +2 more sources

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
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, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Improved Pitzer activity model for Tc(iv) solubility and hydrolysis in the Tc(iv)-Na⁺-K⁺-Ca²⁺-Mg²⁺-H⁺-Cl^--OH^--H₂O(l) system. [PDF]

RSC Adv
Kiefer C, Fellhauer D, Altmaier M, Gaona X.   +3 more
europepmc   +1 more source

Excipient Emulsion–Based Delivery Systems for Enhancing Carotenoid Bioavailability: Advances in Formulation and Gastrointestinal Fate

AgriFood: Journal of Agricultural Products for Food, EarlyView.
Excipient emulsion systems improve carotenoid solubilization, protect against degradation, and enhance gastrointestinal absorption through optimized formulation and digestion behavior. ABSTRACT Carotenoids are bioactive compounds that contribute to human health through antioxidant, provitamin A, and disease‐preventive effects.
Tugce Ceyhan, Elifsu Nemli, Esra Capanoglu, Merve Tomas   +3 more
wiley   +1 more source

Mechanistic study of <i>TFE3</i> breakage in <i>TFE3</i>-rearranged renal cell carcinoma: the perspective of non-canonical DNA structures and their stability. [PDF]

Front Genet
Zhang X, Dang Q, Pan X, Deng Z, Xu Y, Gan W, Guo H.   +6 more
europepmc   +1 more source