During X-ray diffraction experiments, bright lasers shine on a sample, producing diffracted images that contain important information about the material’s structure and properties. But conventional methods of analyzing these images can be contentious, time-consuming, and often ineffective, so scientists are developing deep learning models to better leverage the data.
During X-ray diffraction experiments, bright lasers shine on a sample, producing diffracted images that contain important information about the material’s structure and properties. But conventional methods of analyzing these images can be contentious, time-consuming, and often ineffective, so scientists are developing deep learning models to better leverage the data. During X-ray diffraction experiments, bright lasers shine on a sample, producing diffracted images that contain important information about the material’s structure and properties. But conventional methods of analyzing these images can be contentious, time-consuming, and often ineffective, so scientists are developing deep learning models to better leverage the data.