Results 141 to 150 of about 95,657 (238)

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

open access: yesAdvanced 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.   +10 more
wiley   +1 more source

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

open access: yesAdvanced 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   +19 more
wiley   +1 more source

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

open access: yesAgriFood: 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   +3 more
wiley   +1 more source

AI in chemical engineering: From promise to practice

open access: yesAIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew   +4 more
wiley   +1 more source

Solid–liquid equilibria in the LiOH–ethanol–water system: Solubility measurements and thermodynamic modeling

open access: yesAIChE Journal, EarlyView.
Abstract The demand for LiOH is driven by the growth of the electric vehicle industry. Evaporative crystallization of LiOH·H2O is energy intensive, whereas ethanol‐based antisolvent crystallization has emerged as a more sustainable alternative. From a process design perspective, the crystallization yield depends on the ethanol dosage, and thermodynamic
Xiaoqi Xu   +3 more
wiley   +1 more source

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