Results 121 to 130 of about 29,372 (246)

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

open access: yesAdvanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin   +7 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

A Compact Hollow Fiber Electrode Assembly Architecture for Continuous Electrochemical Marine Carbon Dioxide Removal

open access: yesAdvanced Energy Materials, EarlyView.
A coaxial, membrane‐integrated hollow fiber electrode assembly (HFEA) is developed for continuous marine carbon mineralization. By utilizing a sub‐millimeter inter‐electrode gap, the HFEA minimizes Ohmic losses, achieving 50% energy reduction and over 85% DIC removal.
Inhwan Park   +5 more
wiley   +1 more source

How Does Cultural and Colonial Heritage Affect Optimal Branding Strategies? Evidence From the Rice Sector in Senegal

open access: yesAgribusiness, EarlyView.
ABSTRACT Africa's cultural and colonial heritage has profoundly segmented rice markets. Whereas in ancient centers of rice domestication, consumers maintained preferences for local rice consistent with their cultural heritage, preferences have shifted toward imported Asian rice in coastal areas around seaports, due to prior exposure to colonial import ...
Kofi Britwum, Matty Demont
wiley   +1 more source

Resolving passive heat transfer and phase‐change heat in cryogenic CO2 deposition (Desublimation) from CO2/N2 mixtures

open access: yesAIChE Journal, EarlyView.
Abstract In cryogenic CO2 desublimation systems where phase change dominates both heat transfer and separation, conventional lumped thermal‐resistance treatments embed interfacial latent heat into an overall heat‐transfer coefficient, obscuring how phase‐change heat is partitioned between the gas phase and the coolant and limiting diagnostic insight ...
Shengwen Xiao   +2 more
wiley   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

open access: yesAdvanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows   +7 more
wiley   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

open access: yesAdvanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source

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