Papers citing Deep dive into machine learning density functional theory for materials science and chemistry
Effect of Molecular and Electronic Geometries on the Electronic Density in FLO-SIC
Springer proceedings in physics · 2022
Simon Liebing, Kai Trepte, Sebastian Schwalbe
Read original paper ↗ ·CENT2: Improved charge equilibration via neural network technique
Physical review. B./Physical review. B · 2022
Ehsan Rahmatizad Khajehpasha, Jonas A. Finkler, Thomas D. Kühne, S. Alireza Ghasemi
Read original paper ↗ ·Morphological evolution via surface diffusion learned by convolutional, recurrent neural networks: Extrapolation and prediction uncertainty
Physical Review Materials · 2022
Daniele Lanzoni, Marco Albani, Roberto Bergamaschini, Francesco Montalenti
Read original paper ↗ ·Accelerating equilibration in first-principles molecular dynamics with orbital-free density functional theory
Physical Review Research · 2022
Lenz Fiedler, Zhandos A. Moldabekov, Xuecheng Shao, Kaili Jiang, Tobias Dornheim, Michele Pavanello, Attila Cangi
Read original paper ↗ ·The fourth-order expansion of the exchange hole and neural networks to construct exchange–correlation functionals
The Journal of Chemical Physics · 2022
Étienne Cuierrier, Pierre-Olivier Roy, Rodrigo Wang, Matthias Ernzerhof
Read original paper ↗ ·Accessible and Efficient Modeling of Chromophores with Time-Independent Excited-State Density Functional Tight-Binding: Concepts and Applications
ACS symposium series · 2022
Megan Y. Deshaye, Zoe A. Pollard, Alessandro L. Banducci, Alyssa Goodey, Chanatkran Prommin, Narissa Kanlayakan, Nawee Kungwan, Tim Kowalczyk
Read original paper ↗ ·Classical and quantum machine learning applications in spintronics
Digital Discovery · 2023
Kumar Ghosh, Sumit Ghosh
Read original paper ↗ ·Edge Based Architecture for Total Energy Regression Models for Computational Materials Science
Lecture notes in computer science · 2023
Kangmo Yeo, Sukmin Jeong, Soo-Hyung Kim
Read original paper ↗ ·Machine-Learning for Static and Dynamic Electronic Structure Theory
Challenges and advances in computational chemistry and physics · 2023
Lenz Fiedler, Karan Shah, Attila Cangi
Read original paper ↗ ·The atom sampling method for mesoscale molecular dynamics and its application to graphene assemblies
Physical Chemistry Chemical Physics · 2023
Xiong Pan, Hanhui Jin, Xiaoke Ku, Jianren Fan
Read original paper ↗ ·Prediction-accuracy improvement of neural network to ferromagnetic multilayers by Gaussian data augmentation and ensemble learning
Computational Materials Science · 2023
Kenji Nawa, Katsuyuki Hagiwara, Kohji Nakamura
Read original paper ↗ ·Assessing the accuracy of hybrid exchange-correlation functionals for the density response of warm dense electrons
The Journal of Chemical Physics · 2023
Zhandos A. Moldabekov, Mani Lokamani, Jan Vorberger, Attila Cangi, Tobias Dornheim
Read original paper ↗ ·Electronic density response of warm dense matter
Physics of Plasmas · 2023
Tobias Dornheim, Zhandos A. Moldabekov, Kushal Ramakrishna, Panagiotis B. Tolias, Andrew Baczewski, D. Kraus, Thomas R. Preston, D. A. Chapman, Maximilian Böhme, T. Döppner, Frank R. Graziani, M. Bönitz, Attila Cangi, Jan Vorberger
Read original paper ↗ ·Recent advances in density functional theory approach for optoelectronics properties of graphene
Heliyon · 2023
Lukman Olatomiwa Agbolade, Tijjani Adam, Clement-Andi Edet, Akeem Adekunle Adewale, Abdullah Chik, Mohammed Mohammed, Subash C.B. Gopinath, U. Hashim
Read original paper ↗ ·ænet-PyTorch: A GPU-supported implementation for machine learning atomic potentials training
The Journal of Chemical Physics · 2023
Jon López-Zorrilla, Xabier M. Aretxabaleta, In Won Yeu, I. Etxebarria, Hegoi Manzano, Nongnuch Artrith
Read original paper ↗ ·Electronic specific heat capacities and entropies from density matrix quantum Monte Carlo using Gaussian process regression to find gradients of noisy data
The Journal of Chemical Physics · 2023
William Z. Van Benschoten, Laura Weiler, Gabriel J. Smith, Songhang Man, Taylor DeMello, James J. Shepherd
Read original paper ↗ ·Predicting electronic structures at any length scale with machine learning
npj Computational Materials · 2023
Lenz Fiedler, Normand A. Modine, Steve Schmerler, Dayton J. Vogel, Gabriel A Popoola, Aidan P. Thompson, Sivasankaran Rajamanickam, Attila Cangi
Read original paper ↗ ·Development of a machine-learning-based ionic-force correction model for quantum molecular dynamic simulations of warm dense matter
Physical Review Materials · 2023
Joshua Hinz, Valentin V. Karasiev, S. X. Hu, Deyan I. Mihaylov
Read original paper ↗ ·Equation of state predictions for ScF3 and CaZrF6 with neural network-driven molecular dynamics
The Journal of Chemical Physics · 2023
John P. Stoppelman, Angus Paul Wilkinson, Jesse G. McDaniel
Read original paper ↗ ·The rise of the machines: A state-of-the-art technical review on process modelling and machine learning within hydrogen production with carbon capture
Gas Science and Engineering · 2023
William George Davies, Shervan Babamohammadi, Yang Yang, Salman Masoudi Soltani
Read original paper ↗ ·Machine learning the electronic structure of matter across temperatures
Physical review. B./Physical review. B · 2023
Lenz Fiedler, Normand A. Modine, Kyle D. Miller, Attila Cangi
Read original paper ↗ ·Orbital-Free Density Functional Theory: An Attractive Electronic Structure Method for Large-Scale First-Principles Simulations
Chemical Reviews · 2023
Wenhui Mi, Kai Luo, Samuel B. Trickey, Michele Pavanello
Read original paper ↗ ·Graph neural networks for predicting structural stability of Cd- and Zn-doped γ -CsPbI3
Computational Materials Science · 2023
Roman A. Eremin, Innokentiy S. Humonen, Alexey A. Kazakov, Vladimir D. Lazarev, Anatoly P. Pushkarev, Semen Budennyy
Read original paper ↗ ·Physics-enhanced neural networks for equation-of-state calculations
Machine Learning Science and Technology · 2023
Timothy J. Callow, Jan Nikl, Eli Kraisler, Attila Cangi
Read original paper ↗ ·Advancements in cathode materials for potassium-ion batteries: current landscape, obstacles, and prospects
Energy Advances · 2023
Titus N. Masese, Godwill Mbiti Kanyolo
Read original paper ↗ ·A dual-cutoff machine-learned potential for condensed organic systems obtained via uncertainty-guided active learning
Physical Chemistry Chemical Physics · 2024
Leonid Kahle, Benoît Minisini, Tai Bui, Jeremy T. First, Corneliu Buda, Thomas Goldman, E. Wimmer
Read original paper ↗ ·Combining stochastic density functional theory with deep potential molecular dynamics to study warm dense matter
Matter and Radiation at Extremes · 2024
Tao Chen, Qianrui Liu, Yu Liu, Liang Sun, Mohan Chen
Read original paper ↗ ·Investigating the electronic properties of novel titanium oxonitridophosphate, Ti 5 P 12 N 24 O 2 , through structural distortions at the titanium sites
Journal of Materials Chemistry C · 2024
Peter Ufondu, Teak D. Boyko, Monika M. Pointner, Lucien Eisenburger, Wolfgang Schnick, A. Moewes
Read original paper ↗ ·Rational Design of Battery Materials Through Spectroscopic Characterization and Computational Modeling of Redox Orbitals
Topics in applied physics · 2024
Kosuke Suzuki, Hasnain Hafiz, Veenavee Nipunika Kothalawala, B. Barbiellini, Hiroshi Sakurai, Arun Bansil
Read original paper ↗ ·Uncertainty-Aware Surrogate Modeling of High-Throughput DFT Data for Rapid Materials Screening
Journal of Artificial Intelligence for Materials Science · 2024
Daniel Fischer, Laura Meier, Thomas Braun
Read original paper ↗ ·Development of a machine learning finite-range nonlocal density functional
The Journal of Chemical Physics · 2024
Zehua Chen, Weitao Yang
Read original paper ↗ ·Expanding the Horizons of Machine Learning in Nanomaterials to Chiral Nanostructures
Advanced Materials · 2024
Vera A. Kuznetsova, Áine Coogan, Dmitry Botov, Yulia A. Gromova, Elena V. Ushakova, Yurii K. Gun’ko
Read original paper ↗ ·Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units
Journal of Chemical Information and Modeling · 2024
Hatem Helal, Jesun Firoz, Jenna A. Bilbrey, Henry W. Sprueill, Kristina M. Herman, Mario Michael Krell, Tom Murray, Manuel Lopez Roldan, Mike Kraus, Ang Li, Payel Das, Sotiris S. Xantheas, Sutanay Choudhury
Read original paper ↗ ·Inverting the Kohn–Sham equations with physics-informed machine learning
Machine Learning Science and Technology · 2024
Vincent Martinetto, Karan Shah, Attila Cangi, Aurora Pribram−Jones
Read original paper ↗ ·X-ray-induced atomic transitions via machine learning: A computational investigation
Physical Review Research · 2024
Laura Budewig, Sang-Kil Son, Zoltán Jurek, Malik Muhammad Abdullah, Marina Tropmann-Frick, Robin Santra
Read original paper ↗ ·Discovery of magnesium-aluminum alloys by generative model and automatic differentiation approach
Modelling and Simulation in Materials Science and Engineering · 2024
Shuwei Cheng, Zhelin Li, Hongfei Zhang, Xiaohong Yan, Shibing Chu
Read original paper ↗ ·Reproducibility of real-time time-dependent density functional theory calculations of electronic stopping power in warm dense matter
Physics of Plasmas · 2024
Alina Kononov, Alexander J. White, K. A. Nichols, S. X. Hu, Andrew Baczewski
Read original paper ↗ ·A review of the application of Density Functional Theory and machine learning for oxidative coupling of methane reaction for ethylene production
Chemical Engineering Communications · 2024
Lord Ikechukwu Ugwu, Yasser Morgan, Hussameldin Ibrahim
Read original paper ↗ ·Two-Dimensional Carbon-Based Nanoporous Membranes for High-Performance Sustainable Desalination: A Simulation Calculation Investigation
Research Square · 2024
Yubo Xing, Xiaoyang Zhao, Peng Dong, Kun Meng
Read original paper ↗ ·Extrapolation of polaron properties to low phonon frequencies by Bayesian machine learning
Physical review. B./Physical review. B · 2024
Pranav Kairon, John Sous, Mona Berciu, Roman V. Krems
Read original paper ↗ ·Multi-objective Optimization-Oriented Generative Adversarial Design for Multi-principal Element Alloys
Integrating materials and manufacturing innovation · 2024
Ziyuan Li, N. Birbilis
Read original paper ↗ ·Phonon Transport in Defect-Laden Bilayer Janus PtSTe Studied Using Neural-Network Force Fields
The Journal of Physical Chemistry C · 2024
Lijun Pan, Jesús Carrete, Zhao Wang, Georg K. H. Madsen
Read original paper ↗ ·AI for science in electrochemical energy storage: A multiscale systems perspective on transportation electrification
Nexus · 2024
Shuangqi Li, H. Oliver Gao, Fengqi You
Read original paper ↗ ·Untangling high-temperature thermal expansion and lattice thermal conductivity behavior of vanadium using machine-learned molecular dynamics
Physical review. B./Physical review. B · 2024
Samiran Malgope, Mayanak K. Gupta, Sourav Bag, R. Mittal, Shovit Bhattacharya, Ajay Singh, Samrath Lal Chaplot
Read original paper ↗ ·Quantum chemical package Jaguar: A survey of recent developments and unique features
The Journal of Chemical Physics · 2024
Yixiang Cao, Ty Balduf, Michael D. Beachy, M. Chandler Bennett, Arteum D. Bochevarov, Alan D. Chien, Pavel A. Dub, Kenneth G. Dyall, James W. Furness, Mathew David Halls, Thomas F. Hughes, Leif D. Jacobson, H. Shaun Kwak, Daniel S. Levine, Daniel T. Mainz, Kevin B. Moore, Mats Svensson, Pablo E. Videla, Mark A. Watson, Richard A. Friesner
Read original paper ↗ ·Ensemble Generalization of the Perdew–Zunger Self-Interaction Correction: A Way Out of Multiple Minima and Symmetry Breaking
Journal of Chemical Theory and Computation · 2024
Sebastian Schwalbe, Wanja Timm Schulze, Kai Trepte, Susi Lehtola
Read original paper ↗ ·Ab Initio Calculation of Coupling-Constant Averaged Exchange–Correlation Holes for Spherically Symmetric Atoms
The Journal of Physical Chemistry A · 2024
Lin Hou, Tom J. P. Irons, Yanyong Wang, James W. Furness, Andrew M. Teale, Jianwei Sun
Read original paper ↗ ·Generalizing deep learning electronic structure calculation to the plane-wave basis
Nature Computational Science · 2024
Xiaoxun Gong, Steven G. Louie, Wenhui Duan, Yong Mao Xu
Read original paper ↗ ·Bridging the gap in electronic structure calculations via machine learning
Nature Computational Science · 2024
Attila Cangi
Read original paper ↗ ·Evaluation of machine learning models for the accelerated prediction of density functional theory calculated 19F chemical shifts based on local atomic environments
Artificial Intelligence Chemistry · 2024
Sophia Li, Emma Wang, Leia Pei, Sourodeep Deb, Prashanth Prabhala, Sai Hruday Reddy Nara, Raina Panda, Shiven Eltepu, Marx Akl, Larry McMahan, Edward Njoo
Read original paper ↗ ·