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Updated: Feb 21, 2026

Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering

Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering

Published on: November 5, 2018

DeepFit: Physically and Chemically Informed XAS-Structure Fitting Made Simple.

Kirill Kulaev¹, Bogdan Protsenko¹, Weiren Cheng²

¹The Smart Materials Research Institute, Southern Federal University, Rostov-on-Don 344090, Russian Federation.

The Journal of Physical Chemistry Letters

|February 19, 2026

Summary

This summary is machine-generated.

DeepFit, a new deep learning tool, simplifies X-ray absorption spectroscopy (XAS) analysis. It accurately refines material structures by combining machine learning with quantum chemistry, making complex data analysis routine.

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Area of Science:

Materials Science
Computational Chemistry
Spectroscopy

Background:

X-ray absorption spectroscopy (XAS) is crucial for understanding material structures under operating conditions.
Traditional XAS analysis faces challenges like high computational costs and ambiguous results.

Purpose of the Study:

To develop a deep learning approach, DeepFit, to overcome the limitations of conventional XAS analysis.
To enable accurate and efficient refinement of 3D structures from XAS data.

Main Methods:

Developed DeepFit, an E(3)-equivariant neural network model.
Trained the model on a large database of theoretical XAS spectra.
Integrated spectral mismatch minimization with quantum-chemical energy constraints.

Main Results:

DeepFit accurately refines bond lengths, showing good agreement with experimental data (e.g., XRD/EXAFS).
Achieved high selectivity in identifying local structural motifs.
Demonstrated successful application in experimental studies of homogeneous catalysts.

Conclusions:

DeepFit offers a universal, deep learning-based solution for quantitative XAS analysis.
The method transforms complex XAS data interpretation into a routine, black-box process.
Combines machine learning with quantum chemistry for robust structural refinement.