MANTiS: a program for the analysis of X-ray spectromicroscopy data

Abstract

Spectromicroscopy combines spectral data with microscopy, where typical datasets consist of a stack of images taken across a range of energies over a microscopic region of the sample. Manual analysis of these complex datasets can be time-consuming, and can miss the important traits in the data. With this in mind we have developed MANTiS, an open-source tool developed in Python for spectromicroscopy data analysis. The backbone of the package involves principal component analysis and cluster analysis, classifying pixels according to spectral similarity. Our goal is to provide a data analysis tool which is comprehensive, yet intuitive and easy to use. MANTiS is designed to lead the user through the analysis using story boards that describe each step in detail so that both experienced users and beginners are able to analyze their own data independently. These capabilities are illustrated through analysis of hard X-ray imaging of iron in Roman ceramics, and soft X-ray imaging of a malaria-infected red blood cell.

Chemical imaging of Fischer-Tropsch catalysts under operating conditions

“…The XRD-CT reconstructions were then processed further by (i) fitting a linear baseline across the diffraction peaks of interest to map the location and intensity of the phases of interest and (ii) fitting Gaussian functions to determine the intensity, area, position, and FWHM of the peaks, thereby facilitating the determination of average crystallite size by Scherrer analysis and also any changes in lattice parameters. Principal components analysis and cluster analysis were performed on the reconstructed XRD-CT data using MANTiS ( 61 ); the resultant patterns from each cluster were then used as the experimental inputs for simulation of the phases present.…”

Phase transformation mechanism in lithium manganese nickel oxide revealed by single-crystal hard X-ray microscopy

“…Newer development in FF-TXM-XANES capability has enabled spectroscopic data acquisition rate several orders of magnitude faster than what was possible a few years ago202223. Research on scientific big data mining methods aiming for more effective analysis and better interpretation of the X-ray spectro-microscopic data has also been actively pursued24252627. Recent studies successfully utilized these advances in FF-TXM-XANES, and revealed the nucleation and growth process of new phases as a function of Li content in conventional secondary cathode particles, including LFP28293031, LiMn 2 O 4 (ref.…”

Non-negative matrix analysis in x-ray spectromicroscopy: Choosing regularizers

“…An exploratory version of the NNMA analysis approach described here is implemented in a Python open-source code 1 called MANTiS [6], developed by 2nd Look Consulting; a more refined interface to NNMA analysis is planned for an upcoming release of MANTiS. For the data shown here, the combined cost function converged to a minimum over about 10,000 iterations, taking about 10 minutes on a laptop computer.…”