Block model of passive seismic shear velocity and airborne electromagnetic resistivity in the Geyer area, Erzgebirge, Germany

Ryberg, Trond; Kirsch, Moritz; Haberland, Christian; Tolosana Delgado, Raimon; Viezzoli, Andrea; Gloaguen, Richard

As a means of investigating the structure of the geological subsurface and delineating Sn-W-Li greisen-hosted mineral deposits in the Geyer-Ehrenfriedersdorf area, Central Erzgebirge, Germany, we collected an ambient noise dataset which was supplemented and analysed together with airborne...

Data publication: Structure and Thermodynamics of Eu(III) and Cm(III) Complexes with Glucuronic Acid

Reese, Sebastian; Kaden, Peter; Taylor, Corey John; Kloditz, Roger; Schmidt, Moritz

TRLFS spectra; NMR spectra; QMMM data

Data publication: B₁₂X₁₁(H₂)⁻: Exploring the limits of isotopologue selectivity of hydrogen adsorption

Wulf, Toshiki

Sample ORCA 4.2.1 input files (TXT); atomic coordinates and NEB paths (XYZ); vibration files (7-column XYZ) for publication T. Wulf, J. Warneke, T. Heine: B₁₂X₁₁(H₂)⁻: exploring the limits of isotopologue selectivity of hydrogen adsorption. RSC Advances, 11:46 (2021), 28466–28475, doi:10.1039/d1ra06322g

Coupling of atomic states to particle in cell simulations

Marre, Brian Edward

Master Thesis discussing approaches to including atomic physics in PIC simulations for transient non-thermal plasmas and developing new approaches and algorithms for doing so.

1 more version(s) exist for this record

Neural Solvers

Stiller, Patrick; Zhdanov, Maksim; Rustamov, Jeyhun; Bethke, Friedrich; Hoffmann, Nico

Neural Solvers are neural network-based solvers for partial differential equations and inverse problems. The framework implements scalable physics-informed neural networks Physics-informed neural networks allow strong scaling by design. Therefore, we have developed a framework that uses data...

Dataset and scripts for A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry

Fiedler, Lenz; Shah, Karan; Cangi, Attila; Bussmann, Michael

This dataset contains additional data for the publication "A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry". Its goal is to enable interested people to reproduce the citation analysis carried out in the aforementioned publication.     Prerequesites...

HZDR Multiphase Addon for OpenFOAM

Schlegel, Fabian; Draw, Mazen; Evdokimov, Ilya; Hänsch, Susann; Khan, Harris; Lehnigk, Ronald; Li, Jiadong; Lyu, Hongmei; Meller, Richard; Petelin, Gašper; Tekavčič, Matej

The HZDR multiphase addon contains additional code for the open-source CFD software OpenFOAM, released by The OpenFOAM Foundation. The developments are dedicated to the numerical simulation of multiphase flows, in particular to the multi-field two-fluid model (Euler-Euler method). Within the...

6 more version(s) exist for this record

Raw data: "Quantification of peptide bound particles: A phage mimicking approach via site-selective immobilization on glass"

Schrader, Martin

This set contains the raw data of the fluorescence scanning experiments used in the publication of "Quantification of peptide bound particles: A phage mimicking approach via site-selective immobilization on glass" by Schrader et al..

2 more version(s) exist for this record

LDOS/SNAP data for MALA: Aluminium at 298K and 933K

Ellis, J. Austin; Fiedler, Lenz; Popoola, Gabriel A.; Modine, Normand A.; Stephens, John A.; Thompson, Aidan P.; Cangi, Attila; Rajamanickam, Siva

LDOS/SNAP data for MALA: Aluminium at 298K and 933K (liquid+solid).   Code development was done jointly by the authors. The calculations have mainly been performed by: DFT-MD snapshots / DFT calculations (LDOS data): N. A. Modine (at SNL) SNAP data generation: A. P. Thompson (at SNL) Neural...

Data associated with the publication "The relevance of electronic perturbations in the warm dense electron gas"

Moldabekov, Zhandos; Dornheim, Tobias; Böhme, Maximilian; Vorberger, Jan; Cangi, Attila

This repository contains the Kohn-Sham density functional theory (KS-DFT) and path-integral Monte-Carlo (PIMC) data used in the journal publication "The relevance of electronic perturbations in the warm dense electron gas".