73 citations · 81 across the 8 of their papers we have counts for
8 papers
diffpy.morph: Python tools for model independent comparisons between sets of 1D functions
Andrew Yang, Christopher L. Farrow, Pavol Juhás +22
diffpymorph addresses a need to gain scientific insights from 1D scientific spectra in model independent ways. A powerful approach for this is to take differences between pairs…
Robustness test of the spacegroupMining model for determining space groups from atomic pair distribution function data
Ling Lan, Chia-Hao Liu, Qiang Du +1
Machine learning models based on convolutional neural networks have been used for predicting space groups of crystal structures from their atomic pair distribution function (PDF).…
nmfMapping: a cloud-based web application for non-negative matrix factorization of powder diffraction and pair distribution function datasets
Zachary Thatcher, Chia-Hao Liu, Long Yang +7
A cloud-hosted web-based software application, nmfMapping, for carrying out a nonnegative matrix factorization of a set of powder diffraction or atomic pair distribution function d…
Towards scanning nanostructure x-ray microscopy
Anton Kovyakh, Soham Banerjee, Chia-Hao Liu +5
We demonstrate spatial mapping of the local and nano-scale structure of thin film objects using spatially resolved PDF analysis of synchrotron x-ray diffraction data. This is demon…
Validation of non-negative matrix factorization for assessment of atomic pair-distribution function (PDF) data in a real-time streaming context
Chia-Hao Liu, Christopher J. Wright, Ran Gu +9
We validate the use of matrix factorization for the automatic identification of relevant components from atomic pair distribution function (PDF) data. We also present a newly devel…
sasPDF: pair distribution function analysis of nanoparticle assemblies from small-angle-scattering data
Chia-Hao Liu, Eric M. Janke, Ruipen Li +4
We extends pair distribution function (PDF) analysis into the small-angle scattering (SAS) regime and describe the data collection protocol for optimum data quality. We also presen…
Using a machine learning approach to determine the space group of a structure from the atomic pair distribution function (PDF)
Chia-Hao Liu, Yunzhe Tao, Daniel Hsu +2
We present a method for predicting the space group of a structure given a calculated or measured atomic pair distribution function (PDF) from that structure. The method utilizes ma…
Cluster-mining: An approach for determining core structures of metallic nanoparticles from atomic pair distribution function data
Soham Banerjee, Chia-Hao Liu, Kirsten M. O. Jensen +6
We present a novel approach for finding and evaluating structural models of small metallic nanoparticles. Rather than fitting a single model with many degrees of freedom, the appro…