Speaker
Description
X-ray scattering is one of the main techniques used to characterise the structure of nanomaterials. Extraction of real-space structures from X-ray scattering patterns needs to be carried out through the use of scattering formulae fitting, which has the disadvantages of being time-consuming, requiring specialised knowledge, and initial parameter estimation. In the face of a large amount of experimental data, especially synchrotron radiation experimental data dealing with increasing luminous flux, the existing frontal analysis methods are not able to tone track the challenges of real-time analysis. We Use machine learning methods, relevant structural information can be quickly obtained from scattering experimental data without the introduction of the relevant scattering knowledge.
