<i>PRINSAS 2.0</i>: a Python-based graphical user interface tool for fitting polydisperse spherical pore models in small-angle scattering analysis of porous materials

Despite the growing use of small- and ultra-small-angle scattering (SAS/USAS) across various fields, data processing remains challenging due to the complexity of SAS analysis and the limited accessibility of existing analysis software. These issues are addressed with <i>PRINSAS 2.0</i>, a portable Python-based tool with an intuitive graphical user interface. It enables efficient fitting of the polydisperse spherical pore model to SAS data and is specifically designed for porous materials often encountered in geoscience. This paper outlines the scientific and mathematical foundations of the software, along with its numerical implementation, to provide users with theoretical context and to support future development. The software was tested and validated using data from a range of geological and engineered porous samples measured at various neutron scattering facilities, ensuring broad compatibility. Additional validation using synthetic data sets, along with comparisons with existing pore size distribution fitting tools, confirmed its robustness in recovering predefined pore size distributions. <i>PRINSAS 2.0</i> offers wide accessibility while ensuring that the fit results adhere closely to the underlying theoretical model, making it a practical tool for non-specialist users of SAS techniques. It also integrates seamlessly with larger Python-based SAS analysis frameworks, while remaining fully functional as a standalone application.

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Publication Details

Journal
Journal of Applied Crystallography
Published
2025-06-16
DOI
https://doi.org/10.1107/s1600576725004315
Citations
1
Primary Topic
Enhanced Oil Recovery Techniques
Type
article
Field-Weighted Citation Impact
1.15

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article

PRINSAS 2.0: a Python-based graphical user interface tool for fitting polydisperse spherical pore models in small-angle scattering analysis of porous materials

Klaus Regenauer‐Lieb, Phung Vu, Andrzej P. Radliński, Tomasz Blach et al.
1 citations
Journal of Applied Crystallography
Enhanced Oil Recovery Techniques
1.15
article

PRINSAS 2.0: a Python-based graphical user interface tool for fitting polydisperse spherical pore models in small-angle scattering analysis of porous materials

Klaus Regenauer‐Lieb, Phung Vu, Andrzej P. Radliński, Tomasz Blach, John R. Daniels
article en
1 citations

Abstract

Despite the growing use of small- and ultra-small-angle scattering (SAS/USAS) across various fields, data processing remains challenging due to the complexity of SAS analysis and the limited accessibility of existing analysis software. These issues are addressed with <i>PRINSAS 2.0</i>, a portable Python-based tool with an intuitive graphical user interface. It enables efficient fitting of the polydisperse spherical pore model to SAS data and is specifically designed for porous materials often encountered in geoscience. This paper outlines the scientific and mathematical foundations of the software, along with its numerical implementation, to provide users with theoretical context and to support future development. The software was tested and validated using data from a range of geological and engineered porous samples measured at various neutron scattering facilities, ensuring broad compatibility. Additional validation using synthetic data sets, along with comparisons with existing pore size distribution fitting tools, confirmed its robustness in recovering predefined pore size distributions. <i>PRINSAS 2.0</i> offers wide accessibility while ensuring that the fit results adhere closely to the underlying theoretical model, making it a practical tool for non-specialist users of SAS techniques. It also integrates seamlessly with larger Python-based SAS analysis frameworks, while remaining fully functional as a standalone application.

Journal of Applied CrystallographyVol. 58(4)
Griffith University (AU), Curtin University (AU), Department of Mines and Petroleum (AU), UNSW Sydney (AU)
Australian Research Council
Openalex Percentile: Top 21%
Enhanced Oil Recovery Techniques
1.15
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