Abstracts:
13.10.2026 - Mohammad Bagheri - Accelerated Discovery of Low-Dimensional Materials via Universal Machine-Learning Interatomic Potentials
Low-dimensional materials have attractive properties that drive intense efforts toward the discovery of novel materials. However, experiments are tedious for systematic discovery, and the conventional computational methods are often tuned to two-dimensional (2D) materials, overlooking other low-dimensional materials.
This talk introduces an interatomic force constant (FC)-based dimensionality classification method to systematically identify novel low-dimensional materials [1]. It then demonstrates how combining this approach with universal machine-learning interatomic potentials (UMLIPs) enables the quantification of FCs with first-principles accuracy across a large set of materials from the Materials Project, uncovering 0D clusters, 1D chains, and 2D layered materials that conventional geometric descriptors have not recognized.
[1] Bagheri et al., J. Phys. Chem. Lett. 14 (35), 7840–7847 (2023).
[2] Bagheri et al., Chem. Mater. 38 (5), 2395–2402 (2026).
08.09.2026 - Oscar Moreno Segura - Efficient scanning-probe spectroscopy using Wannier-based nonequilibrium Green's functions
Scanning tunneling microscopy and spectroscopy (STM/STS) provide powerful tools for probing electronic properties at the atomic scale. On the theoretical side, density functional theory (DFT) and Wannier-based methods allow realistic first-principles descriptions of complex nanosystems. However, modeling nonequilibrium transport remains a significant challenge, especially in superconducting hybrid systems where particle-hole correlations must be treated explicitly. Accurate and efficient theoretical simulations are therefore essential for interpreting experimental measurements and understanding the underlying transport mechanisms.
Here, we present a workflow that combines Wannierized first-principles electronic structure calculations with the nonequilibrium Green's function formalism to enable efficient simulations of STM experiments [1]. This approach builds upon standard DFT packages to construct compact transport Hamiltonians that retain the electronic properties of realistic materials. Superconductivity is incorporated through an effective pairing potential within the Nambu-spinor formalism, while the coupling to the STM tip and substrate electrodes is treated within the wide-band limit approximation.
Within this framework, transport quantities such as current-voltage characteristics are evaluated in closed analytical form. This substantially reduces the computational cost of spectroscopic calculations. The method provides a unified and computationally efficient approach for modeling superconducting hybrid nanostructures featuring spin-orbit coupling, magnetic textures, and spin polarization. Representative applications demonstrate its robustness and versatility for both simple model systems and realistic ab initio molecular structures relevant to modern STM experiments.
[1] O. Moreno Segura et al., manuscript in preparation (2026).
09.06.2026 - Mohit Verma: Continuum Solvent Models beyond the black box: From Smooth Cavities to Nonequilibrium Generalized Poisson Response
Most electronic-structure calculations begin with an isolated molecule or cluster, while experiments often take place in solution, electrolyte, or other complex environments. Continuum solvent models provide an efficient way to include such environmental effects without explicitly simulating all solvent molecules. This talk introduces the physical idea behind polarizable continuum models: how a molecular charge density polarizes a dielectric medium, and how the resulting reaction field modifies the electronic structure. The aim is to open the “solvent keyword” black box and show what these models can and cannot describe.
19.05.2026 - Daniel Solis Rodriguez: QM/MM Partition Schemes: From Substractive to Additive – What Each One Does
QM/MM methods let us study large systems by treating a small region with quantum mechanics and the environment with molecular mechanics. This talk compares three partitioning strategies: the original subtractive scheme, its multi-layer extension (ONIOM), and the physically more accurate additive scheme. With the main question to answer: Does the MM region polarize the QM region?
14.04.2026 - Rasmus Ikonen: ASE Database: What It Is, How to Use It, and Why?
As data-driven methods, machine learning and high-throughput calculations become increasingly integral part of computational chemistry and materials science, efficient handling of atomic-structure data is more important than ever. One tool that can simplify data storage, retrieval, and analysis within the ASE ecosystem is ASE database. This presentation introduces the core features of the ASE database and includes practical demonstrations to illustrate its application.
17.03.2026 - Maxim Laborenz: DFT Geometry Optimization: How do DFT codes like GPAW, Orca or cp2k find the ground state configuration?
Density functional theory (DFT) based computational support is fundamental for about 20 years already in understanding quantum chemistry and many-body physics. Perhaps the most important feature is finding the ground state geometry of any atomic ensemble. At the core of DFT ground state geometry optimization lies a theoretical framework called "Ehrenfest-Dynamics" (ED). This talk explains the ED framework, sheds light on how geometry optimization in DFT codes works, gives an ED research example and discusses its current implementation critically.
