The development of material science in the manufacturing industry has resulted in a huge
amount of material data, which are often from different sources and vary in data format and …

Profiling data by plotting distributions and analyzing summary statistics is a critical step
throughout data analysis. Currently, this process is manual and tedious since analysts must …

Autonomous experimentation (AE) is an emerging paradigm that seeks to automate the
entire workflow of an experiment, including—crucially—the decision-making step. Beyond …

Visual inspection of x-ray scattering images is a powerful technique for probing the physical
structure of materials at the molecular scale. In this paper, we explore the use of deep …

Nano-structured thin films have a variety of applications from waveguides, gaseous sensors
to piezoelectric devices. Grazing Incidence Small Angle x-ray Scattering images enable …

In this work, contrast-variation small-angle and ultra-small-angle neutron scattering are used
together with wide-angle X-ray scattering (WAXS) to characterize the bulk molecular …

DLSIA (Deep Learning for Scientific Image Analysis) is a Python-based machine learning
library that empowers scientists and researchers across diverse scientific domains with a …

In this paper, we summarize briefly some of the future trends in synchrotron science as seen
at the National Synchrotron Light Source II, a new, low emittance source recently …

This work describes a proof of concept demonstrating that convolutional neural networks
(CNNs) can be used to invert x-ray diffraction (XRD) data, so as to, for instance, retrieve …

X-ray scattering is a key technique towards material analysis and discovery. Modern x-ray
facilities are producing x-ray scattering images at such an unprecedented rate that machine …