Papers citing Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems
Inverse design of 3d molecular structures with conditional generative neural networks
Nature Communications · 2022
Niklas W. A. Gebauer, Michael Gastegger, Stefaan S. P. Hessmann, Klaus‐Robert Müller, Kristof T. Schütt
Read original paper ↗ ·Finite-field coupling via learning the charge response kernel
Electronic Structure · 2022
Yunqi Shao, Linnéa Andersson, Lisanne Knijff, Chao Zhang
Read original paper ↗ ·Theoretical Modeling of Electrochemical Proton-Coupled Electron Transfer
Chemical Reviews · 2022
Robert E. Warburton, Alexander V. Soudackov, Sharon Hammes‐Schiffer
Read original paper ↗ ·Machine learning potential for interacting dislocations in the presence of free surfaces
Scientific Reports · 2022
Daniele Lanzoni, Fabrizio Rovaris, Francesco Montalenti
Read original paper ↗ ·Estudo computacional das reações de borilação de substratos insaturados catalisadas por Ag e Cu
Venue not supplied by source · 2022
Ivanna Gisele Rosenda Domingos
Read original paper ↗ ·Deep Generative Models for Materials Discovery and Machine Learning-Accelerated Innovation
Frontiers in Materials · 2022
Addis Fuhr, Bobby G. Sumpter
Read original paper ↗ ·New Insights and Predictions into Complex Homogeneous Reactions Enabled by Computational Chemistry in Synergy with Experiments: Isotopes and Mechanisms
Accounts of Chemical Research · 2022
Jialing Lan, Xin Li, Yuhong Yang, Xiaoyong Zhang, Lung Wa Chung
Read original paper ↗ ·A genetic mixed-integer optimization of neural network hyper-parameters
The Journal of Supercomputing · 2022
Kyle Spurlock, Heba Elgazzar
Read original paper ↗ ·Atomistic modeling of Li- and post-Li-ion batteries
Physical Review Materials · 2022
Holger Euchner, Axel Groß
Read original paper ↗ ·Predicting the future of excitation energy transfer in light-harvesting complex with artificial intelligence-based quantum dynamics
Nature Communications · 2022
Arif Ullah, Pavlo O. Dral
Read original paper ↗ ·Alchemical geometry relaxation
The Journal of Chemical Physics · 2022
Giorgio Domenichini, O. Anatole von Lilienfeld
Read original paper ↗ ·Fragmentation Method for Computing Quantum Mechanics and Molecular Mechanics Gradients for Force Matching: Validation with Hydration Free Energy Predictions Using Adaptive Force Matching
The Journal of Physical Chemistry A · 2022
Dong Zheng, Ying Yuan, Feng Wang
Read original paper ↗ ·Exploring the robust extrapolation of high-dimensional machine learning potentials
Physical review. B./Physical review. B · 2022
Claudio Zeni, Andrea Anelli, Aldo Glielmo, Kevin Rossi
Read original paper ↗ ·Thermal Stability of Metal–Organic Frameworks (MOFs): Concept, Determination, and Model Prediction Using Computational Chemistry and Machine Learning
Industrial & Engineering Chemistry Research · 2022
Harold U. Escobar-Hernandez, Lisa M. Pérez, Pingfan Hu, Fernando A. Soto, Maria I. Papadaki, Hong-Cai “Joe” Zhou, Qingsheng Wang
Read original paper ↗ ·Exploring Complex Reaction Networks Using Neural Network-Based Molecular Dynamics Simulation
The Journal of Physical Chemistry Letters · 2022
Qingzhao Chu, Kai Luo, Dongping Chen
Read original paper ↗ ·Machine learning of material properties: Predictive and interpretable multilinear models
Science Advances · 2022
Alice E. A. Allen, Alexandre Tkatchenko
Read original paper ↗ ·Deeper learning in electrocatalysis: realizing opportunities and addressing challenges
Current Opinion in Chemical Engineering · 2022
John A. Keith, James R. McKone, Joshua David Snyder, Maureen Han-Mei Tang
Read original paper ↗ ·High-fidelity molecular dynamics trajectory reconstruction with bi-directional neural networks
Machine Learning Science and Technology · 2022
Ludwig Winkler, Klaus‐Robert Müller, Huziel E. Sauceda
Read original paper ↗ ·Mechanistic Insights into Enzyme Catalysis from Explaining Machine-Learned Quantum Mechanical and Molecular Mechanical Minimum Energy Pathways
ACS Physical Chemistry Au · 2022
Zilin Song, Francesco Trozzi, Hao Tian, Chao Yin, Peng Tao
Read original paper ↗ ·GraphRXN: A Novel Representation for Reaction Prediction
Research Square · 2022
Baiqing Li, Shimin Su, Chan Zhu, Jie Lin, Xinyue Hu, Lebin Su, Zhunzhun Yu, Kuangbiao Liao, Hongming Chen
Read original paper ↗ ·Data-Driven Mapping of Inorganic Chemical Space for the Design of Transition Metal Complexes and Metal-Organic Frameworks
ACS symposium series · 2022
Jon Paul Janet
Read original paper ↗ ·Mechanistic Inference from Statistical Models at Different Data-Size Regimes
ACS Catalysis · 2022
Danilo Machado Lustosa, Anat Milo
Read original paper ↗ ·Simple Model and Spectral Analysis for a Fluxional Catalyst: Intermediate Abundances, Pathway Fluxes, Rates, and Transients
ACS Catalysis · 2022
Baron Peters
Read original paper ↗ ·Machine learning analysis of dynamic‐dependent bond formation in trajectories with consecutive transition states
Journal of Physical Organic Chemistry · 2022
Jesse Melville, Cal Hargis, Michael T. Davenport, R. Spencer Hamilton, Daniel H. Ess
Read original paper ↗ ·Applications of Artificial Intelligence and Machine Learning Algorithms to Crystallization
Chemical Reviews · 2022
Christos Xiouras, Fabio Cameli, Gustavo Lunardon Quilló, Michail E. Kavousanakis, Dionisios G. Vlachos, Georgios D. Stefanidis
Read original paper ↗ ·Toward Explainable Artificial Intelligence for Regression Models: A methodological perspective
IEEE Signal Processing Magazine · 2022
Simon Letzgus, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus‐Robert Müller, Grégoire Montavon
Read original paper ↗ ·BIGDML—Towards accurate quantum machine learning force fields for materials
Nature Communications · 2022
Huziel E. Sauceda, Luis E. Gálvez-González, Stefan Chmiela, Lauro Oliver Paz‐Borbón, Klaus‐Robert Müller, Alexandre Tkatchenko
Read original paper ↗ ·Efficiently searching extreme mechanical properties via boundless objective-free exploration and minimal first-principles calculations
npj Computational Materials · 2022
Joshua Ojih, Mohammed Al‐Fahdi, Alejandro David Rodriguez, Kamal Kumar Choudhary, Ming Hu
Read original paper ↗ ·Heterogeneous catalyst design by generative adversarial network and first-principles based microkinetics
Scientific Reports · 2022
Atsushi Ishikawa
Read original paper ↗ ·Ab initio machine learning of phase space averages
The Journal of Chemical Physics · 2022
Jan Weinreich, Dominik Lemm, Guido Falk von Rudorff, O. Anatole von Lilienfeld
Read original paper ↗ ·Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character across Known Transition Metal Complex Ligands
Journal of Chemical Theory and Computation · 2022
Chenru Duan, Adriana Ladera, Julian C. -L. Liu, Michael G. Taylor, Isuru Rangana Ariyarathna, Heather J. Kulik
Read original paper ↗ ·Design, Synthesis, Docking, DFT, MD Simulation Studies of a New Nicotinamide-Based Derivative: In Vitro Anticancer and VEGFR-2 Inhibitory Effects
Molecules · 2022
Eslam B. Elkaeed, Reda G. Yousef, Hazem Elkady, Ibraheem M. M. Gobaara, Bshra Ali A. Alsfouk, Dalal Z. Husein, Ibrahim M. Ibrahim, Ahmed M. Metwaly, Ibrahim H. Eissa
Read original paper ↗ ·Machine Learning for Designing Mixed Metal Halides for Efficient Ammonia Separation and Storage
The Journal of Physical Chemistry C · 2022
Armando de Rezende, Mahdi Malmali, Pavlo O. Dral, Hans Lischka, Daniel Tunega, Adélia J. A. Aquino
Read original paper ↗ ·Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery
Chemical Reviews · 2022
Haoxin Mai, Tu C. Le, Dehong Chen, David Alan Winkler, Rachel A. Caruso
Read original paper ↗ ·Tackling Disorder in γ‐Ga 2 O 3
Advanced Materials · 2022
Laura E. Ratcliff, Takayoshi Oshima, Felix Nippert, Benjamin M. Janzen, Elias Kluth, R. Goldhahn, Martin Feneberg, Piero Mazzolini, Oliver Bierwagen, Charlotte Wouters, Musbah Nofal, M. Albrecht, Jack E. N. Swallow, Leanne A. H. Jones, P. Thakur, Tien‐Lin Lee, Curran Kalha, Christoph Schlueter, Tim D. Veal, Joel Basile Varley, Markus R. Wagner, Anna Regoutz
Read original paper ↗ ·Microscopic principles of chemical engineering after fossil fuels
Resources Chemicals and Materials · 2022
Jianzhong Wu
Read original paper ↗ ·Density functional theory based computational investigations on the stability of highly active trimetallic PtPdCu nanoalloys for electrochemical oxygen reduction
Faraday Discussions · 2022
Lichang Wang, Rotimi Ore, Peshala Jayamaha, Zhi‐Peng Wu, Chuan‐Jian Zhong
Read original paper ↗ ·Toward full ab initio modeling of soot formation in a nanoreactor
Carbon · 2022
Qingzhao Chu, Chenguang Wang, Dongping Chen
Read original paper ↗ ·A Statistical Modeling Approach to Catalyst Generality Assessment in Enantioselective Synthesis
ChemRxiv · 2022
Junshan Lai, Jiajing Li, Isaiah O. Betinol, Yutao Kuang, Jolene P. Reid
Read original paper ↗ ·Data-driven models for ground and excited states for Single Atoms on Ceria
npj Computational Materials · 2022
Julian Geiger, Albert Sabadell‐Rendón, Nathan Daelman, Núria López
Read original paper ↗ ·Accurate large-scale simulations of siliceous zeolites by neural network potentials
npj Computational Materials · 2022
Andreas Erlebach, Petr Nachtigall, Lukáš Grajciar
Read original paper ↗ ·Quantitatively Determining Surface–Adsorbate Properties from Vibrational Spectroscopy with Interpretable Machine Learning
Journal of the American Chemical Society · 2022
Xijun Wang, Shuang Jiang, Wei Hu, Sheng Ye, Tairan Wang, Fan Wu, Yang Li, Xiyu Li, Guozhen Zhang, Xin Chen, Jun Jiang, Yi Luo
Read original paper ↗ ·Extending machine learning beyond interatomic potentials for predicting molecular properties
Nature Reviews Chemistry · 2022
Nikita S. Fedik, R.I. Zubatyuk, Maksim Kulichenko, Nicholas Lubbers, Justin S. Smith, Benjamin T. Nebgen, Richard A. Messerly, Ying Wai Li, Alexander I. Boldyrev, Kipton M. Barros, Olexandr Isayev, Sergei Tretiak
Read original paper ↗ ·Machine learning-facilitated multiscale imaging for energy materials
Cell Reports Physical Science · 2022
Guoxu Zhang, Yajie Song, Wei Zhao, Hanwen An, Jiajun Wang
Read original paper ↗ ·Large dataset of molecular and reaction energies from multi-level quantum chemical methods
ChemRxiv · 2022
Surajit Nandi, Tejs Vegge, Arghya Bhowmik
Read original paper ↗ ·Benchmarking PES‐Learn's machine learning models predicting accurate potential energy surface for quantum scattering
International Journal of Quantum Chemistry · 2022
Apoorv Kushwaha, T. J. Dhilip Kumar
Read original paper ↗ ·Large dataset of molecular and reaction energies from multi-level quantum chemical methods
ChemRxiv · 2022
Surajit Nandi, Tejs Vegge, Arghya Bhowmik
Read original paper ↗ ·Heterogeneous catalysis mediated by light, electricity and enzyme via machine learning: Paradigms, applications and prospects
Chemosphere · 2022
Wentao Zhang, Wenguang Huang, Jie Tan, Qingwei Guo, Bingdang Wu
Read original paper ↗ ·Machine Learning Accelerated Discovery of Promising Thermal Energy Storage Materials with High Heat Capacity
ACS Applied Materials & Interfaces · 2022
Joshua Ojih, Uche Onyekpe, Alejandro David Rodriguez, Jianjun Hu, Chengxiao Peng, Ming Hu
Read original paper ↗ ·Auto Machine Learning Assisted Preparation of Carboxylic Acid by TEMPO‐Catalyzed Primary Alcohol Oxidation
Chinese Journal of Chemistry · 2022
Jia Qiu, Yougen Xu, Shimin Su, Yadong Gao, Peiyuan Yu, Zhixiong Ruan, Kuangbiao Liao
Read original paper ↗ ·