Results 121 to 130 of about 113,020 (264)

Computational and Data‐Driven Strategies for Lignocellulosic Biomass Valorization: From Multiscale Modeling to Digitalized Biorefinery Design

open access: yesAdvanced Science, EarlyView.
This Review critically connects structural recalcitrance, molecular modeling, solvent and catalyst design, pyrolysis, machine learning, reactor simulation, and FAIR digital infrastructure. Emphasis is placed on experimentally validated information transfer across scales, uncertainty and applicability domains, and the recycle, durability, techno ...
Abdullahi Bello Umar   +9 more
wiley   +1 more source

Bridging Chemical Literature and Molecular Graphs: LLM‐Augmented Enantioselectivity Prediction for Iridium‐Catalyzed Asymmetric C–H Borylation

open access: yesAdvanced Science, EarlyView.
A machine‐learning framework for asymmetric C–H borylation bridges multi‐entity 3D molecular graphs and chemical literature. Atom‐resolved mechanistic annotations extracted by large language models augment three‐component graph encoding of catalyst, substrate, and product. The model predicts enantioselectivity with high accuracy on unseen scaffolds and
Zhe Wang   +4 more
wiley   +1 more source

Updatable Closed‐Form Evaluation of Arbitrarily Complex Multiport Network Connections

open access: yesAdvanced Electronic Materials, EarlyView.
The inverse design of electrically large wave devices often uses reduced‐order multiport models with discrete optimization, requiring many evaluations of complex interconnections between subsystems that differ only in a few blocks. This paper introduces a closed‐form framework enabling efficient Woodbury low‐rank updates of related, previous ...
Hugo Prod'homme, Philipp del Hougne
wiley   +1 more source

Advancing Energy Materials by In Situ Atomic Scale Methods

open access: yesAdvanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
Progress in in situ atomic scale methods leads to an improved understanding of new and advanced energy materials, where a local understanding of complex, inhomogeneous systems or interfaces down to the atomic scale and quantum level is required. Topics from photovoltaics, dissipation losses, phase transitions, and chemical energy conversion are ...
Christian Jooss   +21 more
wiley   +1 more source

Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries

open access: yesAdvanced Energy Materials, EarlyView.
This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu   +5 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

Implicit Learning and Tacit Knowledge

open access: yesJournal of Experimental Psychology: General, 1989
openaire   +1 more source

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