From Single Metals to High‐Entropy Alloys: How Machine Learning Accelerates the Development of Metal Electrocatalysts
X Fan, L Chen, D Huang, Y Tian… - Advanced Functional …, 2024 - Wiley Online Library
The rapid advancement of high‐performance computing and artificial intelligence
technology has opened up novel avenues for the development of various metal …
technology has opened up novel avenues for the development of various metal …
[HTML][HTML] Toward Next-Generation Heterogeneous Catalysts: Empowering Surface Reactivity Prediction with Machine Learning
X Liu, HJ Peng - Engineering, 2024 - Elsevier
Heterogeneous catalysis remains at the core of various bulk chemical manufacturing and
energy conversion processes, and its revolution necessitates the hunt for new materials with …
energy conversion processes, and its revolution necessitates the hunt for new materials with …
A Surrogate Machine Learning Model for the Design of Single-Atom Catalyst on Carbon and Porphyrin Supports towards Electrochemistry
We apply the machine learning (ML) tool to calculate the Gibbs free energy (Δ G) of reaction
intermediates rapidly and accurately as a guide for designing porphyrin-and graphene …
intermediates rapidly and accurately as a guide for designing porphyrin-and graphene …
Discovering High Entropy Alloy Electrocatalysts in Vast Composition Spaces with Multiobjective Optimization
High entropy alloys (HEAs) are a highly promising class of materials for electrocatalysis as
their unique active site distributions break the scaling relations that limit the activity of …
their unique active site distributions break the scaling relations that limit the activity of …
A computational study of electrochemical CO2 reduction to formic acid on metal-doped SnO2
Electrochemical reduction of CO 2 to formic acid (HCOOH) can contribute to the renewable
energy transition as a liquid carrier of renewably hydrogen. Here, we investigated the …
energy transition as a liquid carrier of renewably hydrogen. Here, we investigated the …
Generalized Brønsted‐Evans‐Polanyi Relationships for Reactions on Metal Surfaces from Machine Learning
F Göltl, M Mavrikakis - ChemCatChem, 2022 - Wiley Online Library
Abstract Brønsted‐Evans‐Polanyi (BEP) relationships, ie, a linear scaling between reaction
and activation energies, lie at the core of computational design of heterogeneous catalysts …
and activation energies, lie at the core of computational design of heterogeneous catalysts …
Machine learning assisted photothermal conversion efficiency prediction of anticancer photothermal agents
S Wu, Z Pan, X Li, Y Wang, J Tang, H Li, G Lu… - Chemical Engineering …, 2023 - Elsevier
Photothermal therapy (PTT) is a minimally invasive and promisingly effective strategy for
thermal ablation of tumors. There is an urgent need for the development of ideal organic …
thermal ablation of tumors. There is an urgent need for the development of ideal organic …
Iterative multiscale and multi-physics computations for operando catalyst nanostructure elucidation and kinetic modeling
Modern heterogeneous catalysis has benefitted immensely from computational predictions
of catalyst structure and its evolution under reaction conditions, first-principles mechanistic …
of catalyst structure and its evolution under reaction conditions, first-principles mechanistic …
Selective adsorption processes for fructooligosaccharides separation by activated carbon and zeolites through machine learning
Fructooligosaccharides (FOS) separation and purification are crucial for industrial
applications where adsorption methods are widely used. However, some specific process …
applications where adsorption methods are widely used. However, some specific process …
Predicting hydrogenolysis reaction barriers of large hydrocarbons on metal surfaces using machine learning: Implications for polymer deconstruction
Calculating activation energies of chemical reactions for large reaction networks is
computationally demanding. Traditional Brønsted-Evans-Polanyi (BEP) relationships are …
computationally demanding. Traditional Brønsted-Evans-Polanyi (BEP) relationships are …