External stakeholders: CIC energiGUNE and ALBA Synchrotron
BIG-MAP partners: Institut Laue Langevin and ICMAB-CSIC, Institute of Materials Science of Barcelona
The huge amount of diffraction data generated by high throughput screening (HTS) experiments as well as by in situ and operando studies at large user facilities, such as Synchrotron and Neutron sources, calls for new software tools able to radically accelerate the analysis and process data in real time.
The project FullProfAPP will develop an automated Rietveld analysis tool for powder diffraction patterns of battery materials using FullProf, an open-science free tool for diffraction-based materials characterization, as the refinement engine. It will include new routines and machine learning (ML) algorithms to enable the automatization the complex refinement process and designed in a flexible and extensible way to be fully compatible with the BIG-MAP infrastructure.
To go beyond the state of the art, FullprofAPP will develop and implement an autonomous system that is able to handle several dozens to hundreds of patterns in batches as well as analyze them from the phase identification (indexation) step to the full refinement, providing structural data and quantitative phase analysis as output information.
This tool will be very beneficial for the field of battery materials research, which will be pioneering such programs and methods. This breakthrough could give visibility to the project as the technologies used could be used in many other fields.