Helmholtz Institute Freiberg for Resource Technology
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Data publication: An integrative approach towards bio-inspired sequestration of rare earth elements
No full textThe dataset comprises the experimental data that form the basis of the conclusions presented in the paper, including spectroscopic, calorimetric, and microscopic data
NEXT Plant data: Results of Quality Assurance and Quality Control - Supplementary material for publications based on this data set
No full textFormat: HTML document (bookdown format)
Purpose: This file provides a detailed description of the quality assurance and quality control (QA/QC) procedures applied to the plant concentration data collected during the study. It includes statistical analysis of reference materials, drift correction, uncertainty modeling, and evaluation of laboratory and field precision.
Description of the File Content
This file is part of a larger data publication and serves as a supplementary document to the main dataset. It outlines the QA/QC procedures used to ensure the accuracy, precision, and reliability of the plant element concentration data. The file includes:
Reference Material (RM) Analysis:
Statistical summaries of standard reference materials (SRMs) such as UPDEEP_SPRU_BARK_DRY, UPDEEP_SPRU_TWIG_DRY, and UPDEEP_SPRU_NEED_DRY.
Comparison of pre-analyzed SRM values with actual measurements.
X-charts showing the performance of SRMs over time and across different batches.
Drift and Offset Correction:
Visualizations of raw and corrected data for routine samples, laboratory, and field replicates.
Analysis of data trends and correction of analytical drift and offsets.
Uncertainty Modeling:
Calculation of relative standard deviation (RSD) from laboratory replicates.
Identification of elements with high uncertainty (RSD > 10%) that may be excluded from further analysis.
Tables and visualizations showing the distribution of uncertainties across different plant tissues.
Field Precision Assessment:
Evaluation of field replicate data to assess variability in field sampling.
Identification of elements with poor field precision (RSD > 20%).
Data Preparation and Processing:
R code for data loading, cleaning, and transformation.
Use of packages such as data.table, ggplot2, dplyr, and kableExtra for data manipulation and visualization.
Summary of Key Findings and Data Included
Reference Materials: The file provides statistical summaries (mean, median, SD, RMAD) of SRMs used to monitor analytical performance. These are compared with actual measurements to assess accuracy and precision.
Drift Correction: The data shows the effect of drift correction on plant concentration measurements, improving the consistency of results across different batches.
Uncertainty Analysis: The RSD of laboratory replicates is calculated, and elements with high variability are flagged for exclusion.
Field Precision: Field replicates are used to assess the variability of sampling and analysis in the field, with some elements showing poor precision.
Visualizations: The file includes numerous plots (e.g., X-charts, scatter plots) to illustrate data trends, comparisons, and uncertainty levels
Multiphase Python Repository by HZDR
No full textThe python package provides several routines and scripts required to operate the code and cases repositories containing additional code and setups for the open-source software released by the OpenFOAM Foundation. This includes, among other things, utilities for pre- and post-processing of simulation cases, utilities to launch virtual environments containing the source code, and utilities to operate the continuous integration and development environment in a self-hosted Gitlab instance
Densitometric scans on a LOHC Reactor
No full textThis data archive contains the pulse height spectra recorded with the MCA-527 (GBS) multichannel analyser and the corresponding history files. The pulse height spectra were recorded continuously throughout the day with an integration time of 300 s. The scintillation detector was operated at +800 V. The data is used for quantitative liquid holdup determination
Data publication: Let's get cyclic – Influence of Head-to-Tail Cyclisation of Lanmodulin-inspired peptides on the Lanthanide Affinity and Structure
No full textThe dataset comprises the experimental data that form the basis of the conclusions presented in the paper, including spectroscopic, calorimetric, and microscopic data. This repository will become openly accessible upon publication of the manuscript. Until then, please contact the author, Björn Drobot
Multiphase Cases Repository by HZDR for OpenFOAM Foundation Software
No full textThis repository contains simulation setups for the Multiphase Code Repository by HZDR for OpenFOAM Foundation Software. The simulation setups are separated into mono- and polydisperse bubbly flows utilising the Baseline model by HZDR set, setups for a morphology-adaptive multifield two-fluid model (disperse and resolved interfaces) and miscellaneous cases.Acknowledgement: OpenFOAM(R) is a registered trade mark of OpenCFD Limited, producer and distributor of the OpenFOAM(R) software via www.openfoam.com. The Multiphase Cases Repository by HZDR for OpenFOAM Foundation Software is not compatible with the software released by OpenCFD Limited, but is based on the software released by the OpenFOAM Foundation via www.openfoam.or
Data publication: Generating structured foam via flowing through a wire array
No full textThe structure of liquid foam is generally considered random and isotropic. However, when foam flows past a set of wires, an inhomogeneous liquid fraction distribution, or layering, can be observed within the bulk. This dataset presents neutron radiography data of foam flowing past a set of thin metal wires. During the experiments, the gas flow rate and bubble size were varied. Additionally, a dataset for foam flow past a single wire is included for reference.
The folder includes initial data for the manuscript "Generating structured foam via flowing through a wire array".
Folder includes:
01_scripts scripts used for the data processing
02_rawdata Initial neutron imaging data (.tif images)
03_evaluation folder with MATLAB scripts used for data analysis
LABBOOK Experimental labbook explaining the experimental sequence.
Protocol The Neutron imaging protocol with the data of neutron source and image resolution
The data processing is shown for the O1 bubble generator. It includes:
1. MASK_... script used to define the cell walls and determine the mask, used further for the liquid fraction calculation.
2. N13_INIT... scritps to define normalised image, which further used to determine liquid fraction distribution
3. POST_BOT... scripts used to postprocess the data: define Liquid fraction distribution and DFT of those distributions.
Note:
1. The data were analysed at two positions: bottom (0) and top (100), meaining at the wire grid and 100 mm downstream the grid. To this end, mask should be calculated also for the top part of the nozzle, if needed, as shown in the presented examples.
2. The data for the empty cell were calculated for the foam flow through the cell with a single thin wire. The data were extracted
in the ROI before the wire (run 553-557).
3. Data processing was performed as suggested in https://doi.org/10.1371/journal.pone.0210300The authors gratefully acknowledge the financial support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, under grant number HE 7529/3-1, project number 431077191). This work is based on experiments (beam-time proposal number 20240273) performed at the NEUTRA instrument of the Swiss spallation neutron source SINQ, Paul Scherrer Institute, Villigen, Switzerland
Data publication: Free volume and nonlinear viscoelasticity in supercrystalline nanocomposites: A nanoindentation driven modelling analysis
No full textThis data set consists of positron annihilation lifetime measurements generated at a conventional measuring station with a Na-22 source
Data to "Minterpy: Multivariate polynomial interpolation in Python"
No full textThis release includes the dataset used to generate the convergence plot featured in the paper "Minterpy: Multivariate Polynomial Interpolation in Python," submitted to the Journal of Open Source Software (JOSS). It also provides instructions for reproducing both the data from scratch and the plot derived from that data.
This is the second release of the dataset, prepared following feedback from the JOSS review process
mspacman
No full textmspacman is an open-source Python package for 3D particle characterization in CT images. It is specifically developed to address partial volume blur (PVB). The software models PVB using a linear mixing approach to individual particles' grey value histograms. It supports samples with up to 11 mineral phases and can quantify particles containing up to 5 distinct phases. mspacman semi-automates the entire analysis pipeline. This includes image upload, geometrical and intensity properties extraction, histogram computation, phase quantification, and bootstrapped uncertainty estimation. The package provides a scalable framework for high-resolution mineral characterization