Helmholtz Institute Freiberg for Resource Technology
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Data publication: The spatial association of accessory minerals with biotite in granitic rocks from the South Mountain Batholith, Nova Scotia, Canada
No full textData publication: The spatial association of accessory minerals with biotite in granitic rocks from the South Mountain Batholith, Nova Scotia, Canada
D. Barrie Clarke; Axel D. Renno; David C. Hamilton; Sabine Gilbricht; Kai Bachmann
Related to publication Geosphere (2022) 18 (1): 1–18; https://doi.org/10.1130/GES02339.1
We use mineral liberation analysis (MLA) to quantify the spatial association of 15,118 grains of accessory apatite, monazite, xenotime, and zircon with essential biotite, and clustered with themselves, in a peraluminous biotite granodiorite from the South Mountain Batholith in Nova Scotia (Canada). A random distribution of accessory minerals demands that the proportion of accessory minerals in contact with biotite is identical to the proportion of biotite in the rock, and the binary touching factor (percentage of accessory mineral touching biotite divided by modal proportion of biotite) would be ~1.00. Instead, the mean binary touching factors for the four accessory minerals in relation to biotite are: apatite (5.06 for 11,168 grains), monazite (4.68 for 857 grains), xenotime (4.36 for 217 grains), and zircon (5.05 for 2876 grains). Shared perimeter factors give similar values. Accessory mineral grains that straddle biotite grain boundaries are larger than completely locked, or completely liberated, accessory grains. Only apatite-monazite clusters are significantly more abundant than expected for random distribution. The high, and statistically significant, binary touching factors and shared perimeter factors suggest a strong physical or chemical control on their spatial association. We evaluate random collisions in magma (synneusis), heterogeneous nucleation processes, induced nucleation in passively enriched boundary layers, and induced nucleation in actively enriched boundary layers to explain the significant touching factors. All processes operate during the crystallization history of the magma, but induced nucleation in passively and actively enriched boundary layers are most likely to explain the strong spatial association of phosphate accessories and zircon with biotite. In addition, at least some of the apatite and zircon may also enter the granitic magma as inclusions in grains of Ostwald-ripened xenocrystic biotite.
This data repository contains the complete set of the respective MLA – measurements (Reference) including the raw data and the data analysis.Explanation of the individual data files (in the zip directory).
Main Directory:
• Data_The spatial association of accessory minerals with biotite in granitic rocks
Subdirectories:
• Processed_Data
• Raw_Data
Processed_Data
• exported diagrams
o apatite grain size distribution
o monazite grain size distribution
o xenotime grain size distribution
o zircon grain size distribution
• exported excel tables
o All_Samples
o grain properties 2B3A
o grain properties all geometric data
o grain properties area px perimeter
o grain properties length and breadth
o mineral association
The Raw Data File directory contains the MLA raw data in the default saved form
Application of green solvents to remove ionomer-containing binder for PEM water electrolyzer recycling (RAW data of the Master Thesis)
No full textThe files contain the raw data of the following Master Thesis:
Förster, Wenzel
Application of green solvents to remove ionomer-containing binder for PEM water electrolyzer recycling
Master Thesis
TU Bergakademie Freiberg
Date of submission: 2024-12-10
The data contains two excel files and six zip-files
Hydrodynamics in a bubble column – Part 2: Three-phase flow
No full textMultiphase computational fluid dynamics (CFD) simulation is a useful tool to study the hydrodynamics in a bubble column, if appropriate closure models are known. Systematic assessment of different models is an ongoing venture that benefits from improved validation data. The present study accumulates a database on three-phase flow experiments in a bubble column. This is achieved by using a combination of Particle Image Velocimetry and Shadowgraphy to measure the liquid velocity, solid velocity, solid concentration and gas dispersion properties simultaneously. This methodology is applied for different needle diameters, gas flow rates and particle concentrations.
A detailed description of the experimental setup can be found in XXX.
The experimental data (Table 1) described in this repository is structured into different folders and files as follows:
Level 1: Folders classified by measurement configuration: TW_Jg_X_Di_YYY_C_ZZZ as outlined in Table 1
TW = Identifier
Jg_X = Superficial gas velocity in mm/s
Di_YYY = Inner diameter of the needle in µm
C_ZZZ = Particle concentration * 100 in %
Level 2: Folders classified by measurement height: Z_XXX
Z_XXX = Measurement height in mm
Level 3: csv files classified by their analysis parameter:
Gas_Eg_ub_over_x.csv: Each csv file consists of five columns, namely the x-coordinate (in m), the gas holdup, the uncertainty of the gas holdup, the averaged bubble rising velocity (in m/s) and the corresponding uncertainty (in m/s).
Liquid_v_z_over_x.csv: Each csv file consists of three columns, namely the x-coordinate (in m), the averaged liquid velocity (in m/s) and the corresponding uncertainty (in m/s).
Solid_alpha_over_z.csv: Each csv file consists of three columns, namely the z-coordinate (in m), the averaged solid fraction and the corresponding uncertainty .
Solid_v_z_over_x.csv: Each csv file consists of three columns, namely the x-coordinate (in m), the averaged solid velocity (in m/s) and the corresponding uncertainty (in m/s).
Table 1: Overview of the measurement cases in this repository.
| ID | Needle diameter [µm] | Superficial gas velocity [mm/s] | Particle concentration [vol%] |
|-----|----------------------|---------------------------------|-------------------------------|
| T1 | 200 | 2 | 0 |
| T2 | 200 | 4 | 0 |
| T3 | 200 | 6 | 0 |
| T4 | 600 | 2 | 0 |
| T5 | 600 | 4 | 0 |
| T6 | 600 | 6 | 0 |
| L1 | 200 | 2 | 0.05 |
| L2 | 600 | 2 | 0.05 |
| L3 | 200 | 2 | 0.1 |
| L4 | 600 | 2 | 0.1 |
| L5 | 200 | 2 | 0.15 |
| L6 | 600 | 2 | 0.15 |
| L7 | 200 | 4 | 0.05 |
| L8 | 600 | 4 | 0.05 |
| L9 | 200 | 4 | 0.1 |
| L10 | 600 | 4 | 0.1 |
| L11 | 200 | 4 | 0.15 |
| L12 | 600 | 4 | 0.15 |
| L13 | 200 | 6 | 0.05 |
| L14 | 600 | 6 | 0.05 |
| L15 | 200 | 6 | 0.1 |
| L16 | 600 | 6 | 0.1 |
| L17 | 200 | 6 | 0.15 |
| L18 | 600 | 6 | 0.15 |This project has received funding from the European Union's Horizon 2020 Marie Skłodowska-Curie Actions (MSCA), Innovative Training Networks (ITN), H2020-MSCA-ITN-2020 under grant agreement No. 955805, and the European Institute of Innovation and Technology (EIT). This body of the European Union receives support from the European Union's Horizon 2020 research and innovation programme
EPICS device backend for the ChimeraTK framework
No full textThe EPICS device backend implements a EPICS client, that allows to create an ChimeraTK device that communicates with an EPICS IOC via the EPICS Channel Access (CA) protocol
Correlated Widefield-confocal Microscopy Dataset
No full textHow to cite us
Li, R., Della Maggiora, G., Andriasyan, V., Petkidis, A., Yushkevich, A., Deshpande, N., ... & Yakimovich, A. (2024). Microscopy image reconstruction with physics-informed denoising diffusion probabilistic model. Communications Engineering, 3(1), 186.
@article{li2024microscopy,
title={Microscopy image reconstruction with physics-informed denoising diffusion probabilistic model},
author={Li, Rui and Della Maggiora, Gabriel and Andriasyan, Vardan and Petkidis, Anthony and Yushkevich, Artsemi and Deshpande, Nikita and Kudryashev, Mikhail and Yakimovich, Artur},
journal={Communications Engineering},
volume={3},
number={1},
pages={186},
year={2024},
publisher={Nature Publishing Group UK London}
}
Download Timeout Troubleshooting
Use "-C" flag of curl in case you experience timeout of the download:
curl -C - https://rodare...tar.gz_part1\?download\=1 --output spa.tar.gz_part1
Dataset
This dataset contains a sample of 600 fluorescently labelled nuclei of cultured cells imaged using widefield fluorescence microscopy and confocal fluorescence microscopy at different focal planes.
Image preprocessing
Notably, the hardware precision of the sectioning process led to variations in the step size when shifting the focal plane between the two devices. This resulted in distinct z-dimensions between the datasets obtained from the two microscopy techniques. The confocal stacks in raw data comprised 92 focal planes, whereas the widefield stacks consisted of only 40 slices. Each focal plane image had a shape [2048, 2048, 1]. Assuming the central slice of each stack to be the in-focus, we performed z-direction registration by downsampling the confocal stacks from the central slice (46th) to match the 40 slices of the widefield stacks. Due to the instrumental limitations, a slight drift was noticeable between images. To address this, we used the phase cross-correlation algorithm [2] to compensate for the offsets on the x-y plane for the z-dimension registered image stacks. Having completed the registration and alignment along three dimensions, we then partitioned the original images into non-overlapping patches with dimensions of [128, 128, 1] in the xy plane. This partitioned dataset serves as the test dataset for validating our blind-deconvolution model, conducted without the specific Point Spread Function (PSF) parameters [3].
Files description
The Widefield-confocal Microscopy Dataset is stored in the '*.npz' format, encompassing the variables 'c_img' and 'w_img.' These handles respectively denote the confocal images and their corresponding widefield microscopy images. Both types of data undergo registration, alignment, and normalization, with values scaled to range between [0.0, 1.0]. For each category, the data has a shape of [600, 128, 128, 40], where the first dimension denotes the individual field of view and the last dimension signifies the z-dimension representing changes in the focal plane for virtual sectioning. The first dimension corresponds to the patch number, each with a patch size of [128, 128].
Sample preparation and microscopy
A549 lung carcinoma cell line cells were seeded in 96-well imaging plates a night prior to imaging, then fixed with 4% paraformaldehyde (Sigma) and stained for DNA with Hoechst 33342 fluorescent dye (Sigma). Cell culture was maintained similarly to the procedures described in [1]. Next, stained cell nuclei were imaged using ImageXpress Confocal system (Molecular Devices) in either confocal or widefield mode employing Nikon 20X Plan Apo Lambda objective. To obtain 3D information images in both modes were acquired as Z-stacks with 0.3 µm and 0.7 µm for confocal and widefield modes respectively. Confocal z-stack was Nyquist sampled. The excitation wavelength was 405 nm and the emission was 452 nm. Using these settings, we obtained individual stacks for both modalities, with each stack covering 2048 by 2048 pixels or 699 by 699 µm.
References
Yakimovich, Artur, et al. "Plaque2. 0—a high-throughput analysis framework to score virus-cell transmission and clonal cell expansion." PloS one 10.9 (2015): e0138760.
Alink, Mark S. Oude, et al. "Lowering the SNR wall for energy detection using cross-correlation." IEEE transactions on vehicular technology 60.8 (2011): 3748-3757.
Li, Rui, et al. "Microscopy image reconstruction with physics-informed denoising diffusion probabilistic model." arXiv preprint arXiv:2306.02929 (2023)
Retrained Models and Scripts for Aluminum at 298K and 933K
No full textRetrained Models and Scripts for Aluminum at 298K and 933K
Authors
- Fiedler, Lenz (HZDR/CASUS)
- Cangi, Attila (HZDR/CASUS)
Affiliations:
HZDR - Helmholtz-Zentrum Dresden-Rossendorf
CASUS - Center for Advanced Systems Understanding
Data set description
This data sets contains models, scripts and inference results for aluminum at room temperature and the melting point. Training data, hyperparameters and general methodology follow Ref. [1]. The models here are retrained versions of the ones discussed in this publication, and therefore retrained versions of the models contained in Ref. [2]. As such, data from Ref. [2] has been used. Only a subset of models contained in Ref. [1] have been retrained, namely the room temperature model, one liquid and one solid melting point model with four training snapshot each, and the final melting point hybrid model (six training snapshots per phase). Furthermore, for both the hybrid melting temperature model and the room temperature model, multiple models with different initializations were trained.
All models were trained with the MALA code [3] version 1.2.1. They show better accuracy than their original counterparts, as they were trained using the inter-snapshot shuffling algorithm first discussed for the MALA code in Ref. [4].
[1] - "Accelerating finite-temperature Kohn-Sham density functional theory with deep neural networks", Physical Review B, doi.org/10.1103/PhysRevB.104.035120
[2] - "RODARE", doi.org/10.14278/rodare.2485 (v1.0.0)
[3] - "MALA", Zenodo, doi.org/10.5281/zenodo.5557254
[4] - "Machine learning the electronic structure of matter across temperatures", Physical Review B, doi.org/10.1103/PhysRevB.108.125146
Contents
- The models themselves, labeled as either Al298K or Al933K, given as one .zip file per model
- For 933K, additionally "liquid", "solid" and "hybrid" denotes the training data set
- For ensembles, a running index denotes the number in the ensemble
- Inference results, given as a single .zip file
- For all models, band energy and total free energy results are given in the .csv format
- The columns in these files correspond to "Calculated via DFT LDOS", "Calculated via ML-DFT LDOS", "Calculated via Kohn-Sham system", respectively
- For some models, additionally the predicted electronic density and density of states on select snapshots is given
- Shuffling, training and testing scripts, given as a single .zip file
- Scripts are ready-to-use with suitable MALA installation, however, correct data paths have to be filled i
Data publication: Hybrid star phenomenology from the properties of the special point
No full textThe columns of files EOS_TOV_etaV_etaD.TXT include central values of the baryonic chemical potential [MeV], pressure [MeV/fm^3], baryonic density [1/fm^3], radius [km] and mass [M_solar] of neutron stars modelled with hybrid quark-hadron equations of state constructed for the vector and diquark couplings etaV and etaD specified in the titles. The corresponding mass-radius diagrams are presented in Figs. 6-8 of the paper. The columns of the file etaV-etaD.TXT include diquark coupling and values of the vector coupling corresponding to the boundaries of the region providing the conditions of having the onset of deconfinement above the saturation density and stability of the quark branch of the mass-radius curve obtained as a solution of the TOV equation (see Fig. 7 of the paper)
Data publication: In-depth Surface Studies of p-GaN:Cs Photocathodes by Combining Ex-Situ Analytical Methods with In-Situ X-Ray Photoelectron Spectroscopy
No full textAll datasets that were generated during the PhD period and evaluated for the PhD thesis. The data contains .txt files, fotos (.jpeg, .png, .tiff, etc.), SEM and AFM images of p-GaN, p-GaAs and Cs2Te semiconductor sample sets. The files are sorted by sample names and the sample files contain different datasets of each sample. The whole uploaded file contains original data of XPS and heating experiments as well as evaluated data of the original files. Experiments were done to study the surface cleanness by different solvents, thermal cleaning experiments in vacuum, cesium deposition, measurement of quantum efficiencies, and the lifetime of photocathodes. The Cs2Te experiments contain the deposition parameters of the cesium and tellurium deposition on copper and the preparation steps of the Cu substrate
Data publication - Danielle Maass and BioKollekt article 2024: Identification of yttrium oxide-specific peptides for future recycling of rare earth elements from electronic scrap
No full textDieser Datensatz enthält die experimentell erworbenen und ausgewerteten Daten der Phagendisplayexperimente auf Y2O3
Inverting the Kohn-Sham equations with physics-informed machine learning
No full textThis data repository contains the datasets used in the paper "Inverting the Kohn-Sham equations with physics-informed machine learning".
It contains the data generation scripts, datasets for the systems used in the paper (Single Well - 1D atom, Double Well - 1D diatomic molecule) and output potentials generated by the physics-informed machine learning models (physics-informed neural networks and Fourier neural operators)