AIMC Topic: X-Ray Diffraction

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Integrating machine learning with -SAS for enhanced structural analysis in small-angle scattering: applications in biological and artificial macromolecular complexes.

The European physical journal. E, Soft matter Jun 3, 2024
Small-Angle Scattering (SAS), encompassing both X-ray (SAXS) and Neutron (SANS) techniques, is a crucial tool for structural analysis at the nanoscale, particularly in the realm of biological macromolecules. This paper explores the intricacies of SAS...
Machine Learning Macromolecular Substances Scattering, Small Angle Neutron Diffraction X-Ray Diffraction Monte Carlo Method
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BioSAXS at European Synchrotron Radiation Facility - Extremely Brilliant Source: BM29 with an upgraded source, detector, robot, sample environment, data collection and analysis software.

Journal of synchrotron radiation Jan 1, 2023
As part of its Extremely Brilliant Source (EBS) upgrade project, the ESRF's BM29 BioSAXS beamline was subject to a significant upgrade and refurbishment. In addition to the replacement of the beamline's original bending magnet source by a two-pole wi...
Software Scattering, Small Angle Data Collection Robotics Synchrotrons X-Ray Diffraction Humans
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Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models.

Methods in enzymology Dec 8, 2022
Antibodies are an established class of human therapeutics. Epitope characterization is an important part of therapeutic antibody discovery. However, structural characterization of antibody-antigen complexes remains challenging. On the one hand, X-ray...
Models, Molecular Epitopes Deep Learning Proteins Cryoelectron Microscopy Proprotein Convertase 9 X-Ray Diffraction Protein Conformation Humans Scattering, Small Angle Antigen-Antibody Complex
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Single-Image Super-Resolution Improvement of X-ray Single-Particle Diffraction Images Using a Convolutional Neural Network.

Journal of chemical information and modeling Jul 12, 2022
Femtosecond X-ray pulse lasers are promising probes for the elucidation of the multiconformational states of biomolecules because they enable snapshots of single biomolecules to be observed as coherent diffraction images. Multi-image processing using...
Image Processing, Computer-Assisted Lasers X-Ray Diffraction Neural Networks, Computer
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Hybrid Deep Learning Crystallographic Mapping of Polymorphic Phases in Polycrystalline Hf Zr O Thin Films.

Small (Weinheim an der Bergstrasse, Germany) Apr 3, 2022
By controlling the configuration of polymorphic phases in high-k Hf Zr O thin films, new functionalities such as persistent ferroelectricity at an extremely small scale can be exploited. To bolster the technological progress and fundamental understan...
X-Ray Diffraction Deep Learning Humans
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Application of machine learning classifiers to X-ray diffraction imaging with medically relevant phantoms.

Medical physics Dec 1, 2021
PURPOSE: Recent studies have demonstrated the ability to rapidly produce large field of view X-ray diffraction (XRD) images, which provide rich new data relevant to the understanding and analysis of disease. However, work has only just begun on devel...
Support Vector Machine X-Ray Diffraction Machine Learning Phantoms, Imaging Algorithms
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[A giant step towards elucidating the function of proteins].

Medecine sciences : M/S Feb 16, 2021
X-Ray Diffraction Caspase 1 Protein Folding Protein Structure, Tertiary Artificial Intelligence Proteins Myoglobin Deep Learning Algorithms Caspases Crystallography
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High-Throughput and Autonomous Grazing Incidence X-ray Diffraction Mapping of Organic Combinatorial Thin-Film Library Driven by Machine Learning.

ACS combinatorial science Jun 17, 2020
High-throughput X-ray diffraction (XRD) is one of the most indispensable techniques to accelerate materials research. However, the conventional XRD analysis with a large beam spot size may not best appropriate in a case for characterizing organic mat...
Semiconductors High-Throughput Screening Assays Machine Learning Organic Chemicals X-Ray Diffraction Combinatorial Chemistry Techniques
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Classification of grazing-incidence small-angle X-ray scattering patterns by convolutional neural network.

Journal of synchrotron radiation May 20, 2020
Grazing-incidence small-angle X-ray scattering (GISAXS) patterns have multiple superimposed contributions from the shape of the nanoscale structure, the coupling between the particles, the partial pair correlation, and the layer geometry. Therefore, ...
Nanoparticles Neural Networks, Computer Scattering, Small Angle X-Ray Diffraction
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Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks.

Journal of chemical information and modeling Apr 6, 2020
Large volumes of data from material characterizations call for rapid and automatic data analysis to accelerate materials discovery. Herein, we report a convolutional neural network (CNN) that was trained based on theoretical data and very limited exp...
Neural Networks, Computer X-Ray Diffraction
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