AIMC Topic: Powder Diffraction

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Machine Learning Tackles the Challenge of Powder X-ray Diffraction Indexing for All Crystal Systems.

Journal of chemical information and modeling Sep 22, 2025
The indexing of powder X-ray diffraction (PXRD) in unknown structure determinations is a critical yet challenging step in crystallography, particularly for low-symmetry systems (e.g., monoclinic, triclinic) and/or large unit cell systems ( > 1000 Å)...
Machine Learning Algorithms X-Ray Diffraction Powder Diffraction
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Combining High-Throughput Screening and Machine Learning to Predict the Formation of Both Binary and Ternary Amorphous Solid Dispersion Formulations for Early Drug Discovery and Development.

Pharmaceutical research Apr 3, 2025
OBJECTIVE: Amorphous solid dispersion (ASD) is widely utilized to enhance the solubility and bioavailability of water-insoluble drugs. However, conventional experimental approaches for ASD development are often resource-intensive and time-consuming. ...
Machine Learning Algorithms Drug Discovery Drug Development Support Vector Machine Solubility High-Throughput Screening Assays Drug Compounding Crystallization X-Ray Diffraction Chemistry, Pharmaceutical Powder Diffraction
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Data fusion strategies for performance improvement of a Process Analytical Technology platform consisting of four instruments: An electrospinning case study.

International journal of pharmaceutics Jun 26, 2019
The aim of this work was to develop a PAT platform consisting of four complementary instruments for the characterization of electrospun amorphous solid dispersions with meloxicam. The investigated methods, namely NIR spectroscopy, Raman spectroscopy,...
Neural Networks, Computer Spectroscopy, Near-Infrared Colorimetry Spectrum Analysis, Raman Microscopy Technology, Pharmaceutical X-Ray Diffraction Photography Meloxicam Powder Diffraction
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