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Updated: Aug 30, 2025
X-ray Powder Diffraction in Conservation Science: Towards Routine Crystal Structure Determination of Corrosion Products on Heritage Art Objects
Published on: June 8, 2016
Towards a machine-readable literature: finding relevant papers based on an uploaded powder diffraction pattern
Berrak Özer1, Martin A Karlsen2, Zachary Thatcher1
1Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, 10027, USA.
Abstract:
A prototype application for machine-readable literature is investigated. The program is called pyDataRecognition and serves as an example of a data-driven literature search, where the literature search query is an experimental data set provided by the user. The user uploads a powder pattern together with the radiation wavelength. The program compares the user data to a database of existing powder patterns associated with published papers and produces a rank ordered according to their similarity score. The program returns the digital object identifier and full reference of top-ranked papers together with a stack plot of the user data alongside the top-five database entries. The paper describes the approach and explores successes and challenges.
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