Published June 6, 2024 | Version v1
Dataset Open

Predicting particle quality attributes of organic crystalline materials using Particle Informatics

  • 1. Politecnico di Torino
  • 2. Imperial College London
  • 3. Cambridge Crystallographic Data Centre

Description

Dataset related to the publication: "Predicting particle quality attributes of organic crystalline materials using Particle Informatics" published in Powder Technology (Volume 443, 1 July 2024, 119927Volume 443, 1 July 2024, 119927). In this work, a novel quercetin solvate of dimethylformamide (QDMF) was studied. The crystal structure was solved using single crystal X-ray diffraction and analysed using synthon analysis and other particle informatics tools (e.g., solvate analyser). The thermal behaviour and thermodynamic stability of QDMF were studied experimentally using Raman spectroscopy, ATR-FTIR spectroscopy, differential scanning calorimetry, and thermogravimetric analysis. A clear relationship between the two-step desolvation behaviour of QDMF and the type, strength, and directionality of the main bulk synthons characterizing the QDMF structure was observed. Additionally, the attachment energy model was used to predict the QDMF morphology, together with facet-specific topology and chemical nature of each of the dominant {001}, {110}, and {200} facets. The {200} facet was found to be significantly rougher than the other two; whereas, the {110} was characterized by a higher percentage of exposed DMF molecules compared to the other two facets. Specific scanning electron microscopy and contact angle measurements were used to experimentally detect differences among the three facets and validate the modelling results.

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Additional details

Related works

Is published in
Publication: 10.1016/j.powtec.2024.119927 (DOI)

Funding

European Commission
CryForm - Crystal Engineering the New Generation of Sustainable, Biocompatible and Stimuli Responsive Formulations for the Delivery of Active Ingredients 949229