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Volker Blum

Publications and source records attributed to Volker Blum.

At least 19 recordsLinked to original sources
arXiv2026

Performance of Tkatchenko-Scheffler Dispersion Method with Updated van der Waals Radii: Importance for Alkali-Containing Systems

The Tkatchenko-Scheffler (TS) pairwise method to calculate dispersion interactions is a widely used approach to incorporate missing long-range van der Waals contributions in semilocal and hybrid density functional calculations. Despite numerous refinements of the approach to include many-body terms, the original formulation still remains highly relevant as an efficient and robust method, especially for organic and/or insulating materials. In 2018, Fedorov et al. reported updated van der Waals radii to the seminal work published in 2009. The present work examines the accuracy of the TS method with updated van der Waals radii (abbreviated as TS_2018), coupled with the semilocal Perdew-Burke-Ernzerhof density functional, for structural predictions of semiconducting and insulating materials in comparison to the non-local many-body dispersion method and the original TS method (TS_2009). Special attention is paid to materials containing alkali elements, for which the TS_2009 method exhibits a large overbinding, associated with potentially large errors in predicted atomic structures. We also consider a more narrow reformulation (TS_alkali) where only the the alkali atoms are corrected, so the method remains otherwise compatible with TS_2009. The binding energy curves of five alkali dimers are used to assess the TS_2009 and the TS_2018 methods in comparison to the random phase approximation. Using 45 inorganic solid compounds with available experimental reference data, as well as three widely studied, Cs-containing halide perovskites, CsPb$X_3$ ($X$ = Cl, Br, I), we then examine the performance of the TS_2018 and TS_alkali approaches compared to TS_2009 and the beyond-pairwise, nonlocal many-body dispersion method; the latter found to give good results as well.

cond-mat.mtrl-sci↗
arXiv2026

A Large-scale Parallel Implementation of Quasi-Four-Component Relativistic Density Functional Theory with Numeric Atom-centered Orbitals

We present a large-scale parallel implementation of fully relativistic density functional theory (DFT) for both molecules and periodic solids, using the quasi-four-component (Q4C) method and numeric atom-centered orbital basis sets. Our approach employs a domain decomposition method on nonuniform real-space integration grids, which enables order-N integration of the Q4C Hamiltonian matrix elements using efficient, distributed-memory and compute-parallel real-space operations. Next, we build the Hamiltonian and overlap matrices in a two-dimensional block-cyclic distribution layout. The resulting generalized eigenvalue problems are solved with the massively parallel ELPA eigenvalue solver library. We benchmark memory usage, parallel efficiency, and scalability across multiple MPI tasks and compute nodes. This algorithm extends the reach of fully relativistic DFT simulations for periodic solids, tested up to 3,383 atoms per unit cell (216,628 basis functions) and likely still well below the true reach of the implementation. As a demonstration, we calculate the fully relativistic band structure for a 3,383 atom-per-unit-cell doped hybrid organic-inorganic perovskite, (PEA)2(Pb1-xBix)I4 (PEA=phenethylammonium), showing nearly ideal scalability between 336 and 672 physical CPU cores.

cond-mat.mtrl-sci↗
arXiv2025

Efficient Computation of the Long-Range Exact Exchange using an Extended Screening Function

We introduce a computationally efficient screening for the Coulomb potential that also allows calculating approximated long-range exact exchange contributions with an accuracy similar to an explicit full-range evaluation of the exact exchange. Starting from the screening function of the HSE functional, i.e., the complementary error function, as zeroth order, a first-order Taylor expansion in terms of the screening parameter {\omega} is proposed as an approximation of the long-range Coulomb potential. The resulting extended screening function has a similar spatial extend as the complementary error function leading to a computational speed comparable to screened hybrid functionals such as HSE06, but with long-range exact exchange contributions included. The approach is tested and demonstrated for prototypical semiconductors and organic crystals using the PBE0 functional. Predicted energy band gaps, total energies, cohesive energies, and lattice energies from the first-order approximated PBE0 functional are close to those from the unmodified PBE0 functional, but are obtained at significantly reduced computational cost.

cond-mat.mtrl-sci↗
arXiv2025

Roadmap on Advancements of the FHI-aims Software Package

Electronic-structure theory is the foundation of the description of materials including multiscale modeling of their properties and functions. Obviously, without sufficient accuracy at the base, reliable predictions are unlikely at any level that follows. The software package FHI-aims has proven to be a game changer for accurate free-energy calculations because of its scalability, numerical precision, and its efficient handling of density functional theory (DFT) with hybrid functionals and van der Waals interactions. It treats molecules, clusters, and extended systems (solids and liquids) on an equal footing. Besides DFT, FHI-aims also includes quantum-chemistry methods, descriptions for excited states and vibrations, and calculations of various types of transport. Recent advancements address the integration of FHI-aims into an increasing number of workflows and various artificial intelligence (AI) methods. This Roadmap describes the state-of-the-art of FHI-aims and advancements that are currently ongoing or planned.

cond-mat.mtrl-sci↗
arXiv2025

Solvers for Large-Scale Electronic Structure Theory: ELPA and ELSI

In this contribution, we give an overview of the ELPA library and ELSI interface, which are crucial elements for large-scale electronic structure calculations in FHI-aims. ELPA is a key solver library that provides efficient solutions for both standard and generalized eigenproblems, which are central to the Kohn-Sham formalism in density functional theory (DFT). It supports CPU and GPU architectures, with full support for NVIDIA and AMD GPUs, and ongoing development for Intel GPUs. Here we also report the results of recent optimizations, leading to significant improvements in GPU performance for the generalized eigenproblem. ELSI is an open-source software interface layer that creates a well-defined connection between "user" electronic structure codes and "solver" libraries for the Kohn-Sham problem, abstracting the step between Hamilton and overlap matrices (as input to ELSI and the respective solvers) and eigenvalues and eigenvectors or density matrix solutions (as output to be passed back to the "user" electronic structure code). In addition to ELPA, ELSI supports solvers including LAPACK and MAGMA, the PEXSI and NTPoly libraries (which bypass an explicit eigenvalue solution), and several others.

cond-mat.mtrl-sci↗
arXiv2025

Density-Functional Perturbation Theory with Numeric Atom-Centered Orbitals

This paper represents one contribution to a larger Roadmap article reviewing the current status of the FHI-aims code. In this contribution, the implementation of density-functional perturbation theory in a numerical atom-centered framework is summarized. Guidelines on usage and links to tutorials are provided.

cond-mat.mtrl-sci↗
arXiv2024

Optical activity of chiral excitons

Recent activity in the area of chiroptical phenomena has been focused on the connection between structural asymmetry, electron spin configuration and light matter interactions in chiral semiconductors. In these systems, spin-splitting phenomena emerge due to inversion symmetry breaking and the presence of extended electronic states, yet the connection to chiroptical phenomena is lacking. Here, we develop an analytical effective mass model of chiral excitons, parameterized by density functional theory. The model accounts for parity mixing of the band edge Bloch functions resulting from polar distortions, resulting in magnetic dipole allowed transitions. Through the study of a prototypical chiral 2D hybrid perovskite semiconductor, we show that circular dichroism of the chiral exciton and its interband continuum emerges from spin-splitting via cross coupling of Rashba-like and chiral/helical spin-texture components. As a counterpoint, we apply our model to describe chiroptical properties of excitons in perovskite nanocrystals that occur without chiral lattice distortions.

cond-mat.mes-hall↗
arXiv2024

All-electron BSE@GW method with Numeric Atom-Centered Orbitals for Extended Systems

Green's function theory has emerged as a powerful many-body approach not only in condensed matter physics but also in quantum chemistry in recent years. We have developed a new all-electron implementation of the BSE@GW formalism using numeric atom-centered orbital basis sets (Liu et al., J. Chem. Phys. 152, 044105 (2020)). We present our recent developments in implementing this formalism for extended systems with periodic boundary conditions. We discuss its numerical implementation and various convergence tests pertaining to numerical atom-centered orbitals, auxiliary basis sets for the resolution-of-identity formalism, and Brillouin zone sampling. Proof-of-principle examples are presented to compare with other formalisms, illustrating the new all-electron BSE@GW method for extended systems.

physics.chem-ph↗
arXiv2024

Roadmap on Data-Centric Materials Science

Science is and always has been based on data, but the terms "data-centric" and the "4th paradigm of" materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of Artificial Intelligence (AI) and its subset Machine Learning (ML), has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research.

cond-mat.mtrl-sci↗
arXiv2024

Efficient All-electron Hybrid Density Functionals for Atomistic Simulations Beyond 10,000 Atoms

Hybrid density functional approximations (DFAs) offer compelling accuracy for ab initio electronic-structure simulations of molecules, nanosystems, and bulk materials, addressing some deficiencies of computationally cheaper, frequently used semilocal DFAs. However, the computational bottleneck of hybrid DFAs is the evaluation of the non-local exact exchange contribution, which is the limiting factor for the application of the method for large-scale simulations. In this work, we present a drastically optimized resolution-of-identity-based real-space implementation of the exact exchange evaluation for both non-periodic and periodic boundary conditions in the all-electron code FHI-aims, targeting high-performance CPU compute clusters. The introduction of several new refined Message Passing Interface (MPI) parallelization layers and shared memory arrays according to the MPI-3 standard were the key components of the optimization. We demonstrate significant improvements of memory and performance efficiency, scalability, and workload distribution, extending the reach of hybrid DFAs to simulation sizes beyond ten thousand atoms. As a necessary byproduct of this work, other code parts in FHI-aims have been optimized as well, e.g., the computation of the Hartree potential and the evaluation of the force and stress components. We benchmark the performance and scaling of the hybrid DFA based simulations for a broad range of chemical systems, including hybrid organic-inorganic perovskites, organic crystals and ice crystals with up to 30,576 atoms (101,920 electrons described by 244,608 basis functions).

cond-mat.mtrl-sci↗
arXiv2023

First-Principles Approach for Coupled Quantum Dynamics of Electrons and Protons in Heterogeneous Systems

The coupled quantum dynamics of electrons and protons is ubiquitous in many dynamical processes involving light-matter interaction, such as solar energy conversion in chemical systems and photosynthesis. A first-principles description of such nuclear-electronic quantum dynamics requires not only the time-dependent treatment of nonequilibrium electron dynamics but also that of quantum protons. Quantum mechanical correlation between electrons and protons adds further complexity to such coupled dynamics. Here we extend real-time nuclear-electronic orbital time-dependent density functional theory (RT-NEO-TDDFT) to periodic systems and perform first-principles simulations of coupled quantum dynamics of electrons and protons in complex heterogeneous systems. The process studied is electronically excited state intramolecular proton transfer of o-hydroxybenzaldehyde in water and at a silicon (111) semiconductor-molecule interface. These simulations illustrate how environments such as hydrogen-bonding water molecules and an extended material surface impact the dynamical process on the atomistic level. Depending on how the molecule is chemisorbed on the surface, excited state electron transfer from the molecule to the semiconductor surface can inhibit ultrafast proton transfer within the molecule. This work elucidates how heterogeneous environments influence the balance between the quantum mechanical proton transfer and excited electron dynamics. The periodic RT-NEO-TDDFT approach is applicable to a wide range of other photoinduced heterogeneous processes.

physics.chem-ph↗
arXiv2022

Large scale quantum chemistry with Tensor Processing Units

We demonstrate the use of Google's cloud-based Tensor Processing Units (TPUs) to accelerate and scale up conventional (cubic-scaling) density functional theory (DFT) calculations. Utilizing 512 TPU cores, we accomplish the largest such DFT computation to date, with 247848 orbitals, corresponding to a cluster of 10327 water molecules with 103270 electrons, all treated explicitly. Our work thus paves the way towards accessible and systematic use of conventional DFT, free of any system-specific constraints, at unprecedented scales.

physics.comp-ph↗
arXiv2022

Roadmap on Electronic Structure Codes in the Exascale Era

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing.

cond-mat.mtrl-sci↗
arXiv2022

Exact constraints and appropriate norms in machine learned exchange-correlation functionals

Machine learning techniques have received growing attention as an alternative strategy for developing general-purpose density functional approximations, augmenting the historically successful approach of human designed functionals derived to obey mathematical constraints known for the exact exchange-correlation functional. More recently efforts have been made to reconcile the two techniques, integrating machine learning and exact-constraint satisfaction. We continue this integrated approach, designing a deep neural network that exploits the exact constraint and appropriate norm philosophy to deorbitalize the strongly constrained and appropriately normed SCAN functional. The deep neural network is trained to replicate the SCAN functional from only electron density and local derivative information, avoiding use of the orbital dependent kinetic energy density. The performance and transferability of the machine learned functional are demonstrated for molecular and periodic systems.

physics.chem-ph↗
arXiv2022

Nuclear-Electronic Orbital Approach to Quantization of Protons in Periodic Electronic Structure Calculations

The nuclear-electronic orbital (NEO) method is a well-established approach for treating nuclei quantum mechanically in molecular systems beyond the usual Born-Oppenheimer approximation. In this work, we present a strategy to implement the NEO method for periodic electronic structure calculations, particularly focused on multicomponent density functional theory (DFT). The NEO-DFT method is implemented in an all-electron electronic structure code, FHI-aims, using a combination of analytical and numerical integration techniques as well as a resolution of the identity scheme to enhance computational efficiency. After validating this implementation, proof-of-concept applications are presented to illustrate the effects of quantized protons on the physical properties of extended systems such as two-dimensional materials and liquid-semiconductor interfaces. Specifically, periodic NEO-DFT calculations are performed for a trans-polyacetylene chain, a hydrogen boride sheet, and a titanium oxide-water interface. The zero-point energy effects of the protons, as well as electron-proton correlation, are shown to noticeably impact the density of states and band structures for these systems. These developments provide a foundation for the application of multicomponent DFT to a wide range of other extended condensed matter systems.

physics.comp-ph↗
arXiv2022

Boron nitride on SiC(0001)

In the field of van der Waals heterostructures, the twist angle between stacked two-dimensional (2D) layers has been identified to be of utmost importance for the properties of the heterostructures. In this context, we previously reported the growth of a single layer of unconventionally oriented epitaxial graphene that forms in a surfactant atmosphere [F. C. Bocquet, et al., Phys. Rev. Lett. 125, 106102 (2020)]. The resulting G-R0$^\circ$ layer is aligned with the SiC lattice, and hence represents an important milestone towards high quality twisted bilayer graphene (tBLG), a frequently investigated model system in this field. Here, we focus on the surface structures obtained in the same surfactant atmosphere, but at lower preparation temperatures at which a boron nitride template layer forms on SiC(0001). In a comprehensive study based on complementary experimental and theoretical techniques, we find -- in contrast to the literature -- that this template layer is a hexagonal B$_x$N$_y$ layer, but not high-quality hBN. It is aligned with the SiC lattice and gradually replaced by low-quality graphene in the 0$^\circ$ orientation of the B$_x$N$_y$ template layer upon annealing.

cond-mat.mtrl-sci↗
arXiv2021

Localized resolution of identity approach to the analytical gradients of random-phase approximation ground-state energy: algorithm and benchmarks

We develop and implement a formalism which enables calculating the analytical gradients of particle-hole random-phase approximation (RPA) ground-state energy with respect to the atomic positions within the atomic orbital basis set framework. Our approach is based on a localized resolution of identity (LRI) approximation for evaluating the two-electron Coulomb integrals and their derivatives, and the density functional perturbation theory for computing the first-order derivatives of the Kohn-Sham (KS) orbitals and orbital energies. Our implementation allows one to relax molecular structures at the RPA level using both Gaussian-type orbitals (GTOs) and numerical atomic orbitals (NAOs). Benchmark calculations show that our approach delivers high numerical precision compared to previous implementations. A careful assessment of the quality of RPA geometries for small molecules reveals that post-KS RPA systematically overestimates the bond lengths. We furthermore optimized the geometries of the four low-lying water hexamers -- cage, prism, cyclic and book isomers, and determined the energy hierarchy of these four isomers using RPA. The obtained RPA energy ordering is in good agreement with that yielded by the coupled cluster method with single, double and perturbative triple excitations, despite that the dissociation energies themselves are appreciably underestimated. The underestimation of the dissociation energies by RPA is well corrected by the renormalized single excitation correction.

physics.chem-ph↗