Results 91 to 100 of about 214 (209)

Ab initio study of HfPdY (Y = Si, Ge, Sn): insights into electronic, optical, and thermoelectric behavior

Discover Chemistry
This work presents a comprehensive first-principles investigation of the structural, electronic, optical, and thermoelectric properties of half-Heusler alloys HfPdX (X = Si, Ge, Sn) using density functional theory within the generalized gradient ...
Rilwan O. Balogun, I. Otete, C. A. Ejelonu, Akudo P. Ijezie, Edith Ofor, M. I. Babalola   +5 more
doaj   +1 more source

Review on Clustering and Aggregation Modeling Methods for Distribution Networks with Large-Scale DER Integration

Energies
As the global response to climate change and energy crises accelerates, the large-scale integration of heterogeneous distributed energy resources (DERs) is rapidly transforming traditional passive distribution networks into active distribution networks ...
Ye Yang, Yetong Luo, Jingrui Zhang
doaj   +1 more source

The Importance of Metal‐Organic Framework Linker Atoms for CO2 Reduction: A DFT Study

Advanced Science, EarlyView.
Using DFT, we examine the role of linker atoms in CO2 reduction on copper‐based metal organic frameworks (Cu MOFs). Our calculations reveal that linker atoms may serve as both CO2 and H‐shuttling sites and suggest linker electrostatics as a descriptor for linker activity. ABSTRACT Although the metal within the secondary building unit of a metal‐organic
Ugochukwu Nwosu, Samira Siahrostami
wiley   +1 more source

Structure-Based Discovery of TEAD Protein Inhibitors Targeting the Hippo Pathway in Cancer: An Integrative Computational Study

Chemistry Proceedings
The TEA domain (TEAD) transcription factors are important parts of the Hippo signaling cascade and are important therapeutic targets in cancer research because they help control cell growth, avoid apoptosis, and cause tumors to form.
Purva R. Borkar, Rahul D. Jawarkar, Pravin N. Khatale, Pramod V. Burakle   +3 more
doaj   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Synergistic Spin‐Polarization and Single‐Atom Engineering in Magnetic Heterojunctions for Efficient Solar Water Splitting

Advanced Science, EarlyView.
High‐throughput screening led to the identification of 67 Z‐scheme heterojunctions (comprising 2D magnetic transition metal halides and non‐magnetic transition metal chalcogenides). For CrI3/MoTe2 and CrI3/WTe2, electronic structure analysis demonstrated that synergistic crystallographic point group and built‐in electric field effects generate a ...
Hongyang Ren, Zhenzhou Guo, Huirong Wu, Peilin Huang, Jie Yang, Jie Zhang, Guangqian Ding, Hongkuan Yuan, Biao Wang   +8 more
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

Advanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue, Dushuo Feng, Yuefei Zhang, Yang Zhang, Yalong Jiao, Aijun Du, Guoping Gao   +6 more
wiley   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

Advanced 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, Longfei Lv, Fan Zhang, Si Zhou, Weiwei Gao, Jijun Zhao   +5 more
wiley   +1 more source

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

Advanced 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, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source