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PyDSC: a simple tool to treat differential scanning calorimetry data

Aline Cisse, Judith Peters, Giuseppe Lazzara, Leonardo Chiappisi

2020Journal of Thermal Analysis and Calorimetry21 citationsDOIOpen Access PDF

Abstract

Abstract Herein, we describe an open-source, Python-based, script to treat the output of differential scanning calorimetry (DSC) experiments, called pyDSC , available free of charge for download at https://github.com/leonardo-chiappisi/pyDSC under a GNU General Public License v3.0. The main aim of this program is to provide the community with a simple program to analyze raw DSC data. Key features include the correction from spurious signals, and, most importantly, the baseline is computed with a robust, physically consistent approach. We also show that the baseline correction routine implemented in the script is significantly more reproducible than different standard ones proposed by proprietary instrument control software provided with the microcalorimeter used in this work. Finally, the program can be easily applied to large amount of data, improving the reliability and reproducibility of DSC experiments.

Topics & Concepts

Python (programming language)Differential scanning calorimetryComputer scienceSpurious relationshipReproducibilitySoftwareMIT LicenseScannerProgramming languageArtificial intelligenceStatisticsMathematicsPhysicsMachine learningThermodynamicsthermodynamics and calorimetric analysesSpectroscopy and Quantum Chemical StudiesChemical and Physical Properties in Aqueous Solutions