activity
20192026
most citedUsing a machine learning approach to determine the space group of a structure from the atomic pair distribution function (PDF)

73 citations · 81 across the 8 of their papers we have counts for

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7 papers · 1 filter

cond-mat.mtrl-sci2022★ 5 cited

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).…

cond-mat.mtrl-sci2021

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…

cond-mat.mtrl-sci2021

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…

cond-mat.mtrl-sci2020★ 1 cited

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…

cond-mat.mtrl-sci2019

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…

cond-mat.mtrl-sci2019★ 73 cited

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…

cond-mat.mtrl-sci2019★ 2 cited

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…