Density Functional Theory

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25 papers6 papers in the last four weeks, up 100% on the four weeks before. 0.0% of all new papers.

All-electron machine-learned orbital-free density functional for periodic CHNO systems
Oct 13, 2026Marc K. Ickler, Andreas Hermann, Fred A. HamprechtDensity Functional Theory Computational Quantum Chemistry
Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, 69120, Germany. · Centre for Science at Extreme Conditions and SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, EH9 3FD, United Kingdom.
Electron-Density-Informed Molecular Property Prediction Using Surrogate Functionals
Oct 9, 2026Manuel V. Klockow, Simon Wagner, Roman Remme +2Density Functional Theory Molecular Property Prediction
Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University 69120 Heidelberg, Germany
A structure-preserving neural density functional for the ions of a polymer electrolyte
Oct 8, 2026Liyao LyuDensity Functional Theory Materials Science
School of Artificial Intelligence and Data Science, University of Science and Technology of China, Hefei, Anhui, China · Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu, China · Suzhou Big Data & AI Research and Engineering Center, Suzhou, Jiangsu, China
Physics-Aligned Electronic Ground-State Learning Improves Generalization
Oct 7, 2026Eike S. Eberhard, Xaver Kainz, Viktor Kotsev +2Physics-Informed ML OOD Generalization
Technical University of Munich (TUM) · Munich Data Science Institute (MDSI) · Munich Center for Machine Learning (MCML) +1
Equivariant Flow Matching for Electron Density Prediction
Oct 2, 2026Chenxing Liang, Chengdong Wang, Yuchao Lin +2Computational Quantum Chemistry Quantum Chemistry
Department of Computer Science and Engineering, Texas A&M University · Department of Materials Science and Engineering, Texas A&M University · Department of Electrical and Computer Engineering, Texas A&M University +2
Scaling Density Functional Theory with Gaussian Splatting
Sep 25, 2026Andrés Guzmán-Cordero, Cindy Zhang, Majdi Hassan +3Density Functional Theory Computational Quantum Chemistry
Mila - Quebec AI Institute · Université de Montréal · Princeton University +2
Complete Neural Electronic Initialization Accelerates Materials DFT
Sep 18, 2026Felix Ærtebjerg, Jonas Elsborg, Arghya BhowmikQuantum Chemistry Computational Materials Science
Department of Energy Conversion and Storage, Technical University of Denmark
Neural-Network Solutions to Real-Space Charge Density and Generalization
Sep 14, 2026Yuxuan Zeng, Tong Xie, Taoyuze Lv +1Neural Surrogate Modeling Equivariant Neural Networks
School of Artificial Intelligence & Data Science, University of Science and Technology of China · Suzhou Institute for Advanced Research, University of Science and Technology of China
Learning the Kohn-Sham map with neural operators for quasi-linear scaling density functional theory
Aug 24, 2026Danish Khan, Maurice D. Hanisch, Nikolai Argatoff +3Density Functional Theory Computational Quantum Chemistry
Department of Computing and Mathematical Sciences, California Institute of Technology · Department of Mathematics, ETH Zürich · Division of Chemistry and Chemical Engineering, California Institute of Technology +1
When do machine-learned exchange-correlation improvements inherit into density-functional tight binding?
Aug 14, 2026Can Polat, Mustafa Kurban, Erchin Serpedin +1Density Functional Theory Computational Materials Science
Department of Computer and Electrical Engineering, Texas A&M University, College Station, TX, USA · Department of Electrical and Computer Engineering, Texas A&M University at Qatar, Doha, Qatar · Department of Prosthetics and Orthotics, Ankara University, Ankara, Turkey +1
Equivariant learning of a transferable three-dimensional classical density functional
Aug 13, 2026Bingqing ChengDensity Functional Theory
Department of Chemistry, UC Berkeley, California 94720, United States · Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, 94720, United States · Bakar Institute of Digital Materials for the Planet, UC Berkeley, California 94720, United States
Density-Functional Excited-State Gradients and Nonadiabatic Couplings on a Consumer GPU from a Contraction-DAG
Aug 6, 2026Rubén Darío GuerreroQuantum Chemistry Computational Quantum Chemistry
NeuroTechNet S.A.S., 1108831, Bogot´a, Colombia · Quantum and Computational Chemistry Group (QCCG), Universidad Nacional de Colombia, Bogot´a, Colombia
A Fixed-Point Neural Operator for Size- and Functional-Transferable Hamiltonian Prediction
Jun 12, 2026Yunhong Lou, Xihang Yue, Xinran Wei +2Quantum Chemistry Molecular Property Prediction
1Zhejiang University, Hangzhou, China. · 2Zhongguancun Academy, Beijing, China. · 3Zhongguancun Institute of Artificial Intelligence, Beijing, China.
Derivative Informed Learning of Exchange-Correlation Functionals
Jun 2, 2026Eike S. Eberhard, Luca A. Thiede, Abdul Aldossary +5Quantum Chemistry Density Functional Theory
Technical University of Munich, Munich, Germany · Munich Data Science Institute, Munich, Germany · Munich Center for Machine Learning, Munich, Germany +4
Pushing the accuracy of on-top functionals with agent-driven supervised learning
May 7, 2026Yuhao Chen, Dayou Zhang, Donald G. Truhlar +1Quantum Chemistry Density Functional Theory
Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, Shanghai Frontiers Science Center of Molecule Intelligent Syntheses, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200062, China · Department of Chemistry, Chemical Theory Center, and Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455-0431, USA · Chongqing Key Laboratory of Precision Optics, Chongqing Institute of East China Normal University, Chongqing 401120, China +1
Agentic Discovery of Exchange-Correlation Density Functionals
May 6, 2026Titouan Duston, Jiashu Liang, Yuanheng Wang +6Quantum Chemistry Density Functional Theory
ByteDance Seed · Princeton University · Work done at ByteDance Seed
A self-evolving agent for explainable diagnosis of DFT-experiment band-gap mismatch
Apr 29, 2026Yue Li, Bijun TangAI Agents for Scientific Discovery Materials Science
School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798.
Kohn-Sham Hamiltonian from Effective Field Theory: Quasiparticle Band Narrowing from Frozen Core Dynamics
Apr 28, 2026Xiansheng Cai, Han Wang, Kun ChenDensity Functional Theory Quantum Many-Body Physics
Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China
Transferable SCF-Acceleration through Solver-Aligned Initialization Learning
Apr 23, 2026Eike S. Eberhard, Viktor Kotsev, Timm Güthle +1Quantum Chemistry Density Functional Theory
1Technical University of Munich (TUM) · 2Munich Data Science Institute (MDSI) · 3Munich Center for Machine Learning (MCML)
Surrogate Functionals for Machine-Learned Orbital-Free Density Functional Theory
Apr 22, 2026Roman Remme, Fred A. HamprechtSurrogate Modeling Quantum Chemistry
Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University
ChargeFlow: Flow-Matching Refinement of Charge-Conditioned Electron Densities
Mar 25, 2026Tri Minh Nguyen, Sherif Abdulkader Tawfik, Truyen Tran +1Computational Materials Science Quantum Chemistry
Deakin University, Geelong, VIC 3216, Australia
Design Space of Self--Consistent Electrostatic Machine Learning Interatomic Potentials
Mar 16, 2026William J. Baldwin, Ilyes Batatia, Martin Vondrák +2Density Functional Theory Machine Learning Interatomic Potentials
Engineering Laboratory, University of Cambridge, Trumpington St, Cambridge, UK · University of Bayreuth, Bavarian Center for Battery Technology (BayBatt), Bayreuth, Germany · Fritz-Haber-Institute of the Max-Planck-Society, Berlin, Germany
Orbital Transformers for Predicting Wavefunctions in Time-Dependent Density Functional Theory
Mar 3, 2026Xuan Zhang, Haiyang Yu, Chengdong Wang +3Quantum Chemistry Density Functional Theory
Department of Computer Science and Engineering, Texas A&M University · Department of Materials Science and Engineering, Texas A&M University · J. Mike Walker ’66 Department of Mechanical Engineering, Texas A&M University +2
TritonDFT: Automating DFT with a Multi-Agent Framework
Mar 2, 2026Zhengding Hu, Kuntal Talit, Zhen Wang +8Scientific Workflow Automation Density Functional Theory
University of California, San Diego · University of California, Merced · Los Alamos National Laboratory
A fully differentiable framework for training proxy Exchange Correlation Functionals for periodic systems
Feb 17, 2026Rakshit Kumar Singh, Aryan Amit Barsainyan, Bharath RamsundarComputational Quantum Chemistry Density Functional Theory
Deep Forest Sciences

Oct 13, 2026J/K move · Enter open · S save

All-electron machine-learned orbital-free density functional for periodic CHNO systems

Marc K. Ickler, Andreas Hermann, Fred A. Hamprecht

Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, 69120, Germany. · Centre for Science at Extreme Conditions and SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, EH9 3FD, United Kingdom.

Density Functional Theory Computational Quantum Chemistry Quantum Chemistry Computational Materials Science

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We introduce STRUCTURES-P, a machine-learned all-electron orbital-free density functional for periodic CHNO systems. Electrostatics are evaluated analytically in an atom-centered Gaussian basis, while an equivariant network learns the kinetic and exchange-correlation energy from energies and gradients of non-ground-state densities. Minimizing the functional from a superposition of atomic densities recovers the Kohn-Sham ground state: on held-out crystals, the density error falls from 6.7% to 0.4% of the electron count and the energy error reaches 0.25 mHa per atom, half that of a same-architecture interatomic potential. A single functional can be trained for both isolated molecules and periodic systems, and the model generalizes to larger unit cells. It largely preserves relative-energy rankings and reproduces convex-hull vertices on the tested H-N composition slice. Together, these results demonstrate the viability of machine-learned all-electron orbital-free DFT for variational density optimization and energy evaluation in fixed-geometry solids.