Dataset for publication ``A bin-resolved statistical framework for comparing particle size distributions''

Mitra, Rahul

Dataset for publication ``A bin-resolved statistical framework for comparing particle size distributions''

Type of the data datacite.resourceTypeGeneral	Dataset
Total size of the dataset datacite.size	3240654
Author dc.contributor.author	Mitra, Rahul
Upload date dc.date.accessioned	2026-07-23T13:06:30Z
Publication date dc.date.available	2026-07-23T13:06:30Z
Publication date dc.date.issued	2026-07-23
Abstract of the dataset dc.description.abstract	This dataset accompanies the study introducing the Difference Significance Profile (DSP), a statistically rigorous framework for bin-resolved comparison of particle size distributions (PSDs). It contains particle-level size measurements obtained by in-line SOPAT imaging of spray-dried alumina powders, together with all processed data required to reproduce the statistical analyses presented in the associated publication. The repository includes raw particle-size data, common binned PSDs, probability differences, bin-wise DSP statistics, bootstrap calibration results, covariance matrices, and comparison-level summary statistics for two experimental scenarios: (i) powders produced under different spray-drying temperatures (120 °C and 145 °C) and (ii) repeated experiments under identical conditions (120 °C) to assess repeatability. Additionally, mercury intrusion porosimetry measurements for the two temperature conditions are provided to support the physical interpretation of the observed PSD differences. The dataset enables complete reproduction of the DSP analysis, facilitates benchmarking against alternative PSD comparison methods, and provides a reusable resource for statistical analysis of particle size distributions in particle technology and related fields.
Public reference to this page dc.identifier.uri	https://opara.zih.tu-dresden.de/handle/123456789/2197
Public reference to this page dc.identifier.uri	https://doi.org/10.25532/OPARA-1165
Publisher dc.publisher	Technische Universität Bergakademie Freiberg
Licence dc.rights	Attribution-NonCommercial-ShareAlike 4.0 International	en
URI of the licence text dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/4.0/
Specification of the discipline(s) dc.subject.classification	4::42
Title of the dataset dc.title	Dataset for publication ``A bin-resolved statistical framework for comparing particle size distributions''
Software opara.descriptionSoftware.ResourceProcessing	Python
Software opara.descriptionSoftware.ResourceProduction	Python
Software opara.descriptionSoftware.ResourceViewing	Python
Project abstract opara.project.description	The priority program 2364 funded by the German Research Foundation (DFG) investigates and tests methods for autonomous process control in particle technology. It integrates material and data flows with measurement technology, process dynamics, and control to create a closed-loop autonomous process. Initially, it focuses on controlling single unit operations before expanding to entire process chains. The program develops scientific tools - methods, algorithms, and models - for reliable process control and process transformation. It investigates multiphase processes involving solids and fluid particles across synthesis, handling, and formulation operations.
Funding Acknowledgement opara.project.fundingAcknowledgement	The authors appreciate funding by the German Research Foundation (DFG) within SPP 2364 ``Autonomous Processes in Particle Technology'' under grants 504580586 and 504954383.
Public project website(s) opara.project.publicReference	https://www.mvm.kit.edu/SPP2364_APP.php
Project title opara.project.title	SPP 2364 Autonomous Processes in Particle Technology