Multivariate Statistical Analysis on a SEM/EDS Phase Map of Rare Earth Minerals.

Chaoyi Teng,Raynald Gauvin

doi:10.1155/2020/2134516

Abstract

The scanning electron microscope/X-ray energy dispersive spectrometer (SEM/EDS) system is widely applied to rare earth minerals (REMs) to qualitatively describe their mineralogy and quantitatively determine their composition. The performance of multivariate statistical analysis on the EDS raw dataset can enhance the efficiency and the accuracy of phase identification. In this work, the principal component analysis (PCA) and the blind source separation (BSS) algorithms were performed on an EDS map of a REM sample, assisting to achieve an efficient phase map analysis. The PCA significantly denoised the phase map and was used as a preprocessing step for the following BSS. The BSS separated the mixed EDS signals into a set of physically interpretable components, bringing convenience to the phase separation and identification. Through the comparison between the independent component analysis (ICA) and the nonnegative matrix factorization (NMF) algorithms, the NMF was confirmed to be more suitable for the EDS mapping analysis.

Highlights

Industrial demands for rare earth elements (REEs) keep rising as a result of their increasing application in hightechnology electronic devices
This study investigates an alternative method, which applies the multivariate statistical analysis (MSA) on a map dataset to extract REE intensities and effectively shortens the data acquisition time
In the three rare earth minerals (REMs), the main REEs are La, Ce, Pr, and Nd, so these elements were used for the phase identification in this work

Summary

Introduction

Industrial demands for rare earth elements (REEs) keep rising as a result of their increasing application in hightechnology electronic devices. The small proportion of REMs in the ores and the low concentration of REEs in the REMs may cause the problem of insufficient X-ray intensities for distinct peaks in the sum spectrum, resulting in omissions of rare earth phases in an EDS mapping analysis. To settle this issue, the simplest way is to extend the acquisition time to overwhelm the spectrum background, but the trade-off is the analytical efficiency

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