Helmholtz Institute Freiberg for Resource Technology
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1328 research outputs found
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Data Publication: What is the speed limit of martensitic transformations?
Measured synchrotron data and calculated thermal evaluation during irradiation with the laser pulse
Data publication: Impact of intervention on the spread of COVID-19 in India: A model based study
This contains a set of MATLAB scripts and data that were used to generate the figures and results in the manuscripts
C++ & Python API for Scientific I/O with openPMD
openPMD is an open metadata format for open data workflows in open science. This library provides a common high-level API for openPMD writing and reading. It provides a common interface to I/O libraries and file formats such as HDF5 and ADIOS. Where supported, openPMD-api implements both serial and MPI parallel I/O capabilities.Supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration). Supported by the Consortium for Advanced Modeling of Particles Accelerators (CAMPA), funded by the U.S. DOE Office of Science under Contract No. DE-AC02-05CH11231. This work was partially funded by the Center of Advanced Systems Understanding (CASUS), which is financed by Germany's Federal Ministry of Education and Research (BMBF) and by the Saxon Ministry for Science, Culture and Tourism (SMWK) with tax funds on the basis of the budget approved by the Saxon State Parliament
Dataset for Inversion of 1D SAXS grating signal
This simulated dataset consists of 48k train, 6k validation and 6k test data in the h5py file format. A small example on how to access the data is located in the python script "load_data_example.py". "all_params.h5" are the three parameters of each grating in the order sigma, g, b. "all_dist.h5" are the gratings and "all_endproduct.h5" are the 2048D lineouts of the SAXS diffraction pattern. Besides the |FFT|^2 SAXS propagator a number of pertubations were implemented in order to close the domain gap between simulation and experiment
Three-dimensional, km-scale hyperspectral data of a well-exposed Zn-Pb mineral exploration target at Black Angel Mountain, Greenland
Hyperspectral imaging is a most promising innovative technology for non-invasive material mapping and is starting to be adapted in a wide range of applications, including geosciences, ag-riculture, and food quality control. Novel processing workflows have revolutionized the way we can correct, interpret, and integrate hyperspectral data in the past decade. The reprojection of planar hyperspectral scans to real 3D point cloud representations (“hyperclouds”) has opened up new possibilities for the mapping of large and topographically complex targets. So far, only a few tools have been developed to process and visualize this kind of data. In this contribution we pre-sent an open-source hypercloud dataset capturing complex but spectacularly well exposed geolo-gy from the Black Angel Mountain in Maarmorilik, West Greenland, alongside a detailed and interactive tutorial documenting the workflow that was used to create it
Data publication: Lanmodulin Peptides – Unravelling the Binding of the EF-Hand Loop Sequences Stripped from the Structural Corset
The data on which the findings in the publication are based
Link to the publilcation:
https://doi.org/10.1039/D2QI00933
Data and Scripts for "Accelerating Equilibration in First-Principles Molecular Dynamics with Orbital-Free Density Functional Theory"
# Data and Scripts for "Accelerating Equilibration in First-Principles Molecular Dynamics with Orbital-Free Density Functional Theory"
This dataset contains data and calculation scripts for the publication "Boosting first-principles molecular dynamics with orbital-free density functional theory".
Its goal is to enable interested parties to reproduce the experiments we have carried out.
## Prerequesites
The following software versions are needed for the python scripts:
- `python`: 3.8.x
- `mala`: 1.1.0 (with `dftpy` installed)
Further, make sure you have a working `Quantum ESPRESSO` and `VASP` installation and have downloaded additional
data such as local pseudopotentials and ML models (for references, see publication).
## Contents
- `scripts/`: Example scripts for the three principal python tasks associated with out work: ML inference, trajectory
analysis and OF-DFT-MD runs (via DFTPy). The scripts are general blueprints for these experiments and can be adjusted
to perform all of the calculations given in the publication.
- `data/`: Contains raw calculation data for the three investigated systems (hydrogen, beryllium and aluminium).
Since the main goal of this work is to compare OF-DFT-MD initialized and ideal crystal structure initialized
trajectories and inferences, each of the three system-folders contains a `MD_ideal_crystal_structure` and
`MD_ofdft_init` folder, with ideal crystal structure and OF-DFT-MD initialized data, respectively. Therein, contents
may differ; e.g. aluminium contains DFT calculation data, for beryllium data is divided by system size and Nosé mass,
while for hydrogen data for different temperatures is given
Software for Bubble identification from images with machine learning methods
This package contains the software and the trained models described in the publication "Bubble identification from images with machine learning methods". Please refer to the README.md for installation instructions and to the Prediction_demo.ipynb for usage demonstration
Software publication: Estimating cross-border mobility from the difference in peak-timing: A case study in Poland-Germany border regions
Codes for reproducing the results in the research article "Estimating cross-border mobility from the difference in peak-timing: A case study in Poland-Germany border regions
HZDR Data Management Strategy — Top-Level Architecture
Top-Level Architecture of the proposed HZDR Data Management Strategy with additional description of the various systems and services