Released DFTK version 0.7.22: https://dftk.org/releases with initial support for exact exchange and #HybridDFT and notable #performance engineering for #GPU-based #response calculations. Special thanks to Augustin Bussy (CSCS) and Tobias Schäfer (TU Wien) as well as all other #dftk contributors.
#densityfunctionaltheory #condensedmatter #dfpt #physics #simulation #planewave
DFTB+ based calculation of timedependent charge transport in zigzag nanoribbon using the Zandpack code
Our work is also described in a scientific highlight from the NCCR Marvel collaboration: https://nccr-marvel.ch/highlights/AD-DFPT-Herbst
#dftk #algorithmicdifferentiation #densityfunctionaltheory #dft
Released #dftk version 0.7.19: https://dftk.org/releases with support for #hubbard corrections (#DFT+U) and various #gpu-related #performance improvements.
#densityfunctionaltheory #condensedmatter #dfpt #response #physics #simulation #planewave
New preprint https://arxiv.org/abs/2511.06957
A #perspective discussing Moreau-Yosida (MY) techniques in #densityfunctionaltheory.
MY regularisation has enabled to import tools from #convexanalysis into #dft
providing a new mathematical understanding of the most important atomistic simulation approach
and new robust algorithms for Kohn-Sham #dft.
Thanks to my co-authors from the #hylleraas centre and #oslomet for insightful discussions.
Within density-functional theory, Moreau-Yosida regularization enables both a reformulation of the theory and a mathematically well-defined definition of the Kohn-Sham approach. It is further employed in density-potential inversion schemes and, through the choice of topology for the density and potential space, can be directly linked to classical field theories. This perspective collects various appearances of the regularization technique within density-functional theory alongside possibilities for their future development.
New preprint: https://arxiv.org/abs/2509.07785
We present an implementation of AD-DFPT, a unification of #automaticdifferentiation with classical #dfpt response techniques for #densityfunctionaltheory (#dft). We demonstrate its use for #property predition, #uncertainty propagation, design of new #materials as well as the #machinelearning of new #dft models.
#condensedmatter #planewave #response #physics #simulation #computation
We present a differentiation framework for plane-wave density-functional theory (DFT) that combines the strengths of algorithmic differentiation (AD) and density-functional perturbation theory (DFPT). In the resulting AD-DFPT framework derivatives of any DFT output quantity with respect to any input parameter (e.g. geometry, density functional or pseudopotential) can be computed accurately without deriving gradient expressions by hand. We implement AD-DFPT into the Density-Functional ToolKit (DFTK) and show its broad applicability. Amongst others we consider the inverse design of a semiconductor band gap, the learning of exchange-correlation functional parameters, or the propagation of DFT parameter uncertainties to relaxed structures. These examples demonstrate a number of promising research avenues opened by gradient-driven workflows in first-principles materials modeling.
This week the @MatMat group takes part in the #psik conference (https://www.psik2025.net/) at #epfl
with plentey of cutting-edge talks on #materials #modeling and simulations of #condensedmatter.
My contribution has been a short talk on #error quantification and propagation in #densityfunctionaltheory simulations leveraging the built-in #automaticdifferentiation framework of the #dftk code for automatic
gradient computation.
Slides: https://michael-herbst.com/talks/2025.08.25_Psik.pdf
Postdoc in Theoretical chemistry at TU Dresden for proton difusion
Technische Universität Dresden
See the full job description on jobRxiv: https://jobrxiv.org/job/technische-universitat-dresden-27778-postdoc-in-theoretical-chemistry-at-tu-dresden-for-proton-difusion/
#2Dmaterials #densityfunctionaltheory #membrane #moleculardynamics #quantumchemistry...
https://jobrxiv.org/job/technische-universitat-dresden-27778-postdoc-in-theoretical-chemistry-at-tu-dresden-for-proton-difusion/?fsp_sid=1173
As part of the #cecam workshop on perspectives of the atomistic simulation environment (#ase) I delivered a talk on our #materials #modeling ecosystem juliamolsim.org written in the #julialang
programming language and showed some examples: #automaticdifferentiation through the simulation pipeline, seamless #gpu usage, #error propagation and many more
Slides: https://michael-herbst.com/talks/2025.06.23_ASE_perspectives.pdf
#julialang demo: https://michael-herbst.com/talks/2025.06.23_ASE_perspectives_demo.tar.gz
#dftk #densityfunctionaltheory #condensedmatter #planewave #simulation
Michael Herbst
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MatMat
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