Molecular QM TURBOMOLE capabilities for SimStack
SimStack TURBOMOLE quantum chemistry geometry optimization ricc2 workflow nodesA SimStack capability package containing molecular input models and workflow nodes for TURBOMOLE. The bundle includes single-point calculations, geometry optimization, ricc2 calculations, semiempirical calculations, and multistep optimization workflows, together with input-writing and output-parsing utilities.
Wolfgang Wenzel, Phillip Dullinger
v0.28.4
Molecular QM DFTB+ capabilities for SimStack
SimStack DFTB+ quantum chemistry tight binding excited states workflow nodesA SimStack capability package containing models and workflow nodes for molecular calculations with DFTB+. The bundle includes ground-state energy and gradient calculations, geometry optimization, excited-state calculations, Hamiltonian gradients, and serial or parallel calculations for lists of molecules.
Wolfgang Wenzel, Phillip Dullinger
v0.11.2
Molecular QM Psi4 and PySCF capabilities for SimStack
SimStack quantum chemistry Psi4 PySCF geometry optimization workflow nodesA SimStack capability package containing molecular quantum chemistry models and nodes for Psi4 and PySCF calculations. The bundle includes electronic energy calculations, geometry optimization, conformer comparison, reaction-path workflows, and file-backed density and Hessian artifacts.
Wolfgang Wenzel, Phillip Dullinger
v0.32.7
Molecular QM ORCA
SimStack ORCA quantum chemistry electronic structure geometry optimizationSimStack node and data models for preparing ORCA quantum-chemistry calculations, running single-point energy and geometry optimization calculations, and parsing their results. Requires a separately installed ORCA executable.
Wolfgang Wenzel, Phillip Dullinger
v0.1.0
Molecular QM Utilities
SimStack molecular modeling RDKit Open Babel conformersSimStack utilities and nodes for molecular structure conversion, conformer generation, and molecular-mechanics scoring and geometry optimization with RDKit and Open Babel, including PubChem naming helpers.
Wolfgang Wenzel, Phillip Dullinger
v0.5.3
Molecular QM Models
SimStack molecular quantum mechanics molecular models conformer analysisShared molecular data models for electronic-structure calculations in SimStack, including molecules, quantum-mechanical inputs and results, and nodes for importing molecule lists, building molecular databases and analysing conformer diversity.
Wolfgang Wenzel, Phillip Dullinger
v0.6.1
SimStack
SimStack workflow workflow engine scientific computing Python workflow nodesCore Python framework and runner for defining, registering and executing scientific workflow nodes with typed input and output models, task state tracking and resource configuration.
Wolfgang Wenzel, Artem Buldin, Nikita Mitiagin, Jörg Schaarschmidt, Phillip Dullinger, Celso Rego, Oliver Pettkau, Timo Strunk
v2.0.3
AnAttAl: Pyiron-based Workflow for Resistance Spot Welding Simulation
pyiron workflow resistance spot welding Abaqus Fortran simulation automationPyiron workflow for automated resistance spot welding simulation using Abaqus and an external Fortran solver
Jiangdong Zhao <Jiangdong.Zhao@mpa.uni-stuttgart.de>, Sung-Min Wi <Sung-Min.Wi@mpa.uni-stuttgart.de>
v0.0.3
Structural Analysis of Oxide Glasses
glass structural analysis RDF coordination Qn species ring statistics structure factor cavities amorphouspy atomisticsComplete structural analysis workflow for oxide glasses using amorphouspy: radial distribution functions, coordination numbers, Qn species, bond angle distributions, structure factor S(q), Guttman ring statistics, and cavity analysis.
Achraf Atila <achraf.atila@bam.de>
v0.1.0
Silica Glass via Melt-Quench
workflow glass SiO2 melt-quench LAMMPS amorphouspy SHIK molecular dynamics atomisticsMinimal workflow for producing a silica glass structure from a multi-stage melt-quench simulation using amorphouspy and LAMMPS with the SHIK interatomic potential.
Achraf Atila <achraf.atila@bam.de>
v0.1.0
DiMoGraph Active Learning of Gaussian Process Regression
pyiron scikit-learn owlready2 Gaussian process regression active learning machine learningActive learning of Gaussian Process Regression based on a network model using the workflow manager pyiron.
Florian Fuchs <florian.fuchs@enas.fraunhofer.de>, Fabian Teichert <fabian.teichert@enas.fraunhofer.de>, Philipp Schulze <pschulze@math.tu-berlin.de>
v0.1.0
Structure optimisation (pyiron_workflow)
workflow pyiron_workflow LAMMPS molecular dynamics structure optimisation atomisticsPerform structure optimisation using arbitrary atomistics engines via pyiron_workflow; demonstrated here with LAMMPS.
Han Mai <h.mai@mpie.de>
pyiron_workflow_structure_optimisation-0.0.1
Pure grain boundary properties (pyiron_workflow)
workflow pyiron_workflow LAMMPS molecular dynamics grain boundary atomisticsCompute pure grain boundary properties using arbitrary atomistics engines via pyiron_workflow; demonstrated here with LAMMPS.
Han Mai <h.mai@mpie.de>
pyiron_workflow_grain_boundary_properties-0.0.1
DiMoGraph Gaussian Process Regression
pyiron skikit-learn Gaussian process regressionDemonstrate performing Gaussian Process Regresssion of some test data with pyiron.
Florian Fuchs <florian.fuchs@enas.fraunhofer.de>, Philipp Schulze <pschulze@math.tu-berlin.de>, Fabian Teichert <fabian.teichert@enas.fraunhofer.de>
v0.1.0
MICRESS Benchmark of Early-Stage Growth from Liquid State (SimStack)
micress phase-field solidification early-stage growth benchmarkBenchmark simulation of early-stage growth from liquid state using MICRESS.
Lukas Koschmieder <l.koschmieder@access-technology.de>, Janin Eiken <j.eiken@access-technology.de>
0.1.2
MICRESS Benchmark of Early-Stage Growth from Liquid State (pyiron)
micress phase-field solidification early-stage growth benchmarkBenchmark simulation of early-stage growth from liquid state using MICRESS.
Lukas Koschmieder <l.koschmieder@access-technology.de>, Janin Eiken <j.eiken@access-technology.de>
0.2.0
Wind Turbine Rotor Blade Lifetime Extrapolation
workflow simulation fem calculixCalculate expected remaining lifetime and damage in all parts of a wind turbine rotor blade according to manufacturing parameters and operational parameters.
Sebastian Schröck <sebastian.schroeck@th-deg.de>, Alexander Seidel <alexander.seidel@tum.de>, Marc Luger <marc.luger@th-deg.de>
1.0.2
pyiron workflow: tensile test
workflow pyiron ontology sparql experiment tensile_testIn this workflow, an experimental dataset of a tensile test is obtained via sparql queries to a triple store. Then the elastic modulus of the sample is calculcated and the result is returned to a triple store.
Muhammad Hassani <hassani@mpie.de>
0.0.1
