nmfMapping: a cloud-based web application for non-negative matrix factorization of powder diffraction and pair distribution function datasets

Abstract

A cloud-hosted web-based software application, nmfMapping, for carrying out a non-negative matrix factorization of a set of powder diffraction or atomic pair distribution function datasets is described. This application allows structure scientists to find trends rapidly in sets of related data such as from in situ and operando diffraction experiments. The application is easy to use and does not require any programming expertise. It is available at https://pdfitc.org/.

Correlating the structural transformation and properties of ZIF-67 during pyrolysis, towards electrocatalytic oxygen evolution

“…Data modelling was performed with DiffPy-CMI 65 and NMF analysis with the nmfMapping application on the PDFitc platform. 66,67…”

“…Data modelling was performed with DiffPy-CMI 65 and NMF analysis with the nmfMapping application on the PDFitc platform. 66,67 4.5 Powder X-ray diffraction PXRD data were measured at room temperature on a Rigaku Smartlab diffractometer using Co Ka 1 and Co Ka 2 radiation (l = 1.79 Å). Parallel beam optics were used, and data were collected in an angular 2q range of 5-90°on a D/TEX 250 strip detector.…”

Structural transitions during Ni nanoparticle formation by decomposition of a Ni-containing metal–organic framework using in situ total scattering

“…Non-negative matrix factorization breaks down the whole PDF pattern into its components and proved to be a useful tool for in situ experiments with multiple phases. 46,47 In the case of MOF decomposition, the main components are the MOF, the formed Ni nanoparticles and possibly secondary phases. From the NMF weights of these components, we can conclude the course of decomposition to further support the sequential PDF refinements.…”

“…Thatcher et al showed that the NMF weights are in good agreement with the molar phase fractions from Rietveld refinements. 46 The NMF mapping is also not dependent on any structural information, like a crystal structure, which is especially helpful in our case of amorphization of the framework and evolution of nanoparticles. To validate the significance of the NMF mapping, we compared the NMF weights with the molar contents found by sequential PDF refinements, which match well.…”

A fast two-stage algorithm for non-negative matrix factorization in smoothly varying data

“…It has become one of the most popular multi-dimensional data processing tools in various applications such as signal processing (Buciu, 2008), biomedical engineering (Sra & Dhillon, 2006), pattern recognition , computer vision and image engineering (Buciu, 2008). More recently it has been applied in the realm of crystallography, for example, to in situ timedependent diffraction measurements of synthesis (Liu et al, 2021;Thatcher et al, 2022) and spatially resolved electron diffraction maps (Rakita et al, 2023). Lee & Seung (1999) initiated the study of NMF and presented a method.…”