Results 251 to 260 of about 4,866,929 (341)

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

open access: yesAdvanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan   +8 more
wiley   +1 more source

Artificial Intelligence Predictions in Huge Chemical Spaces: Chiroptical Properties of [6]‐helicene Family

open access: yesAdvanced Science, EarlyView.
This study shows that a local, data‐driven AI model can accurately predict diverse optical and chiroptical properties of [6]helicenes using information from close structural neighbours. Combined with genetic algorithms, it enables inverse design for tailored properties, establishing practical structure–property rules for efficient molecular discovery ...
Rafael G. Uceda   +8 more
wiley   +1 more source

Structurally Enhanced Colloidal Molecules via Carbene‐Mediated Covalent C─H Insertion Crosslinking

open access: yesAdvanced Science, EarlyView.
This work presents a nonspecific covalent crosslinking strategy to significantly enhance the structural stability of colloidal molecules (CMs) without compromising their inherent structural and physicochemical properties by rationally designing a diazo‐based crosslinker.
Liwei Dai   +7 more
wiley   +1 more source

Decoding Structure‐Property Relationships in Anion Exchange Membranes via a Chemically Informed Dual‐Channel Graph Attention Network

open access: yesAdvanced Science, EarlyView.
SPARK decodes structure‐property relationships in anion exchange membranes (AEMs) via a chemically informed dual‐channel graph attention network (DEGAT) that explicitly captures microphase separation. It outputs five‐level grades for hydroxide conductivity and alkaline stability and highlights relevant key structural units, enabling robust pre ...
Wanting Chen   +6 more
wiley   +1 more source

Shadow‐Calibrated Stereo Vision for Colorimetric Sweat Analysis

open access: yesAdvanced Science, EarlyView.
By establishing a mathematical model that reconstructs 3D structures through geometric features of object shadows under controlled illumination, and combining it with Convolutional Neural Network‐based 2D image analysis for volumetric calibration, this work enables highly accurate 3D morphological reconstruction.
Ting Xiao   +7 more
wiley   +1 more source

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