Results 131 to 140 of about 2,756,007 (214)

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

open access: yesAdvanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu   +5 more
wiley   +1 more source

Flexoelectricity in Photoconversion: Fundamentals, Materials, and Outlooks

open access: yesAdvanced Science, EarlyView.
Mechanical bending of a flexible cantilever induces a strain gradient in the photoactive material. The resulting flexoelectric field couples with photovoltaic and photoconductive effects, modulating charge generation, separation, and collection. A comparative analysis of oxide perovskites, halide perovskites, and two‐dimensional materials is presented,
Xiang Huang, Feng Li, Rongkun Zheng
wiley   +1 more source

Near‐Unity Selectivity Inversion Between CO2 Electroreduction and H2 Evolution via Atomic Coordination Editing

open access: yesAdvanced Science, EarlyView.
Atomic coordination editing functions as an on/off switch that toggles single‐atom catalysts between CO2 electroreduction and hydrogen evolution. ABSTRACT Precise atomic coordination editing of single‐atom catalysts (SACs) provides an effective strategy to tune their electronic structures and catalytic selectivity. Yet, achieving near‐unity selectivity
Yukun Zhao   +11 more
wiley   +1 more source

Multiferroic‐Centric Materials and Systems Engineering for Battery Applications: An Insight Into Mechanisms, Strategies, and Characterizations

open access: yesAdvanced Science, EarlyView.
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su   +13 more
wiley   +1 more source

Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami

open access: yesAdvanced Science, EarlyView.
This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning   +3 more
wiley   +1 more source

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