Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

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

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.

SUBMITTER: Teng C

PROVIDER: S-EPMC7199623 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

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

Teng Chaoyi C Gauvin Raynald R

Scanning 20200104

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 ma ...[more]

PMID: 32411314

Similar Datasets

Simple automation of SEM-EDS spectral maps analysis with Python and the edxia framework.

Project description:In a recent article, we described the edxia framework, a user-friendly framework to analyse the microstructure of cementitious materials using SEM-EDS hypermaps. The manual approach presented was shown to be efficient to answer the relevant scientific questions. However, it is limited for batch analysis and (semi-)automated treatments. In this article, we show how the framework can be used to customise the analysis to the problem at hand. We first present some possible extensions, and then we provide a simple example of automatic clustering, using the flexible Python scientific libraries which will allow to define more custom workflows in the future.

| S-EPMC9311694 | biostudies-literature

Liquid-Phase Synthesis of Highly Reactive Rare-Earth Metal Nanoparticles.

Project description:The first liquid-phase synthesis of high-quality, small-sized rare-earth metal nanoparticles (1-3 nm)-ranging from lanthanum as one of the largest (187 pm) to scandium as the smallest (161 pm) rare-earth metal-is shown. Size, oxidation state, and reactivity of the nanoparticles are examined (e.g., electron microscopy, electron spectroscopy, X-ray absorption spectroscopy, selected reactions). Whereas the nanoparticles are highly reactive (e.g. in contact to air and water), they are chemically stable as THF suspensions and powders under inert conditions. The reactivity can be controlled to obtain inorganic and metal-organic compounds at room temperature.

| S-EPMC8361762 | biostudies-literature

Probability-of-Superiority SEM (PS-SEM)-Detecting Probability-Based Multivariate Relationships in Behavioral Research.

Project description:In behavioral research, exploring bivariate relationships between variables X and Y based on the concept of probability-of-superiority (PS) has received increasing attention. Unlike the conventional, linear-based bivariate relationship (e.g., Pearson's correlation), PS defines that X and Y can be related based on their likelihood-e.g., a student who is above mean in SAT has 63% likelihood of achieving an above-mean college GPA. Despite its increasing attention, the concept of PS is restricted to a simple bivariate scenario (X-Y pair), which hinders the development and application of PS in popular multivariate modeling such as structural equation modeling (SEM). Therefore, this study addresses an empirical-based simulation study that explores the potential of detecting PS-based relationship in SEM, called PS-SEM. The simulation results showed that the proposed PS-SEM method can detect and identify PS-based when data follow PS-based relationships, thereby providing a useful method for researchers to explore PS-based SEM in their studies. Conclusions, implications, and future directions based on the findings are also discussed.

| S-EPMC6008517 | biostudies-literature

A multivariate statistical test for differential expression analysis.

Project description:Statistical tests of differential expression usually suffer from two problems. Firstly, their statistical power is often limited when applied to small and skewed data sets. Secondly, gene expression data are usually discretized by applying arbitrary criteria to limit the number of false positives. In this work, a new statistical test obtained from a convolution of multivariate hypergeometric distributions, the Hy-test, is proposed to address these issues. Hy-test has been carried out on transcriptomic data from breast and kidney cancer tissues, and it has been compared with other differential expression analysis methods. Hy-test allows implicit discretization of the expression profiles and is more selective in retrieving both differential expressed genes and terms of Gene Ontology. Hy-test can be adopted together with other tests to retrieve information that would remain hidden otherwise, e.g., terms of (1) cell cycle deregulation for breast cancer and (2) "programmed cell death" for kidney cancer.

| S-EPMC9117296 | biostudies-literature

Thermal Analysis of High-Entropy Rare Earth Oxides.

Project description:Phase transformations in multicomponent rare earth sesquioxides were studied by splat quenching from the melt, high-temperature differential thermal analysis and synchrotron X-ray diffraction on laser-heated samples. Three compositions were prepared by the solution combustion method: (La,Sm,Dy,Er,RE)2O3, where all oxides are in equimolar ratios and RE is Nd or Gd or Y. After annealing at 800 °C, all powders contained mainly a phase of C-type bixbyite structure. After laser melting, all samples were quenched in a single-phase monoclinic B-type structure. Thermal analysis indicated three reversible phase transitions in the range 1900-2400 °C, assigned as transformations into A, H, and X rare earth sesquioxides structure types. Unit cell volumes and volume changes on C-B, B-A, and H-X transformations were measured by X-ray diffraction and consistent with the trend in pure rare earth sesquioxides. The formation of single-phase solid solutions was predicted by Calphad calculations. The melting point was determined for the (La,Sm,Dy,Er,Nd)2O3 sample as 2456 ± 12 °C, which is higher than for any of constituent oxides. An increase in melting temperature is probably related to nonideal mixing in the solid and/or the melt and prompts future investigation of the liquidus surface in Sm2O3-Dy2O3, Sm2O3-Er2O3, and Dy2O3-Er2O3 systems.

| S-EPMC7412006 | biostudies-literature

Shedding New Light on Ancient Glass Beads by Synchrotron, SEM-EDS, and Raman Spectroscopy Techniques.

Project description:The oxidation states of colouring elements and the pigments in ancient rare glasses have been investigated in this study. Synchrotron X-ray, SEM-EDS, and Raman techniques revealed that Cu2+plays a major role in blue and green glasses. The lead stannate pigment gives glasses a yellow colour. Copper and lead stannate can cause the green colour in glasses, and iron gives rise to the colour of black glasses. Microcomputed tomography reveals the distribution of the heavy elements, pigments, and inclusions in the glasses. The Dvaravati glasses in Southeast Asia may have been imported or technologically transferred to domestic manufacturers during trading on the Silk Road that connected the East and the West.

| S-EPMC6831571 | biostudies-literature

Enhanced quantification for 3D SEM-EDS: using the full set of available X-ray lines.

Project description:An enhanced method to quantify energy dispersive spectra recorded in 3D with a scanning electron microscope (3D SEM-EDS) has been previously demonstrated. This paper presents an extension of this method using all the available X-ray lines generated by the beam. The extended method benefits from using high energy lines, that are more accurately quantified, and from using soft X-rays that are highly absorbed and thus more surface sensitive. The data used to assess the method are acquired with a dual beam FIB/SEM investigating a multi-element Ni-based superalloy. A high accelerating voltage, needed to excite the highest energy X-ray line, results in two available X-ray lines for several elements. The method shows an improved compositional quantification as well as an improved spatial resolution.

| S-EPMC4266451 | biostudies-literature

Arsenopyrite Bio-Oxidization Behavior in Bioleaching Process: Evidence From Laser Microscopy, SEM-EDS, and XPS.

Project description:In arsenopyrite bioleaching, the interfacial reaction between mineral and cells is one of the most important factors. The energy of the interface is influenced by the mineralogical and microbiological characteristics. In this paper, the interfacial energy was calculated, and the surface of arsenopyrite during the bioleaching process was characterized by 3D laser microscopy, scanning electron microscopy with energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy, in order to assess the dissolution and oxidation behavior of arsenopyrite during bioleaching. The results showed that the contact angles of arsenopyrite were 22 ± 2° when covered with biofilms, but the reaction surface of arsenopyrite turned 103 ± 2°. However, the angle was 45-50° when covered by passive layer, which was half as that of arsenopyrite surface. The interfacial energy of arsenopyrite without biofilms increased from 45 to 62 mJ/m2, while it decreased to 5 ± 1 mJ/m2 when covered by biofilms during the leaching process. The surface was separated into fresh surface, oxidized surface, and (corrosion) pits. The interfacial energy was influenced by the fresh and oxidized surfaces. Surface roughness increased from 0.03 ± 0.01 to 5.89 ± 1.97 μm, and dissolution volume increased from 6.31 ± 0.47 × 104 to 2.72 ± 0.49 × 106 μm3. The dissolution kinetics of arsenopyrite followed the model of Kt = lnX, and the dissolution mechanisms were mixed controlled: surface reaction control and diffusion through sulfur layer. On the surface of arsenopyrite crystal, the oxidation steps of each element can be described as: for Fe, Fe(II)-(AsS)→Fe(III)-(AsS)→Fe(III)-OH or Fe(III)-SO; for S, As-S(-1) or Fe-S(-1)→polysulfide S→intermediate S-O→sulfate; and for As, As-1-S→As0→As+1-O→As+3-O→As+5-O.

| S-EPMC7417448 | biostudies-literature

Phase Transformation and Thermal Decomposition Kinetics of a Mixed Rare Earth Concentrate.

Project description:The Bayan Obo rare earth (BORE) concentrate is the largest light rare earth mineral resource in the world. The decomposition of the BORE concentrate is a principal step to develop new technologies to recover useful elements and is therefore of much importance. In this paper, the phase transformation and thermal decomposition kinetics of the BORE concentrate in air were investigated. The results showed that bastnaesite decomposed upon air roasting. The roasted solid was recovered by sulfuric acid leaching. The activation energy and pre-exponential factor of the roasting reaction of the BORE concentrate were calculated through the isoconversional methods of Flynn-Wall-Ozawa and Kissinger, and the probable mechanism function was estimated through the Coats-Redfern method. The kinetic model that best describes the thermal decomposition reaction for the BORE concentrate is the A2 (Avrami-Erofeev 2) model, and the corresponding probable mechanism function is f(α) = 2(1 - α)[-ln(1 - α)]1/2 and G(α) = [-ln(1 - α)]1/2.

| S-EPMC6643672 | biostudies-literature

A mechanism for the strange metal phase in rare-earth intermetallic compounds.

Project description:SignificanceThe elusive strange metal phase (ground state) was observed in a variety of quantum materials, notably in f-electron-based rare-earth intermetallic compounds. Its emergence has remained unclear. Here, we propose a generic mechanism for this phenomenon driven by the interplay of the gapless fermionic short-ranged antiferromagnetic spin correlation and critical bosonic charge fluctuations near a Kondo breakdown quantum phase transition. It is manifested as a fluctuating Kondo-scattering-stabilized critical (gapless) fermionic spin liquid. It shows [Formula: see text] scaling in dynamical electron scattering rate, a signature of quantum criticality. Our results on quasilinear-in-temperature scattering rate and logarithmic-in-temperature divergence in specific heat coefficient as temperature vanishes were recently seen in CePd[Formula: see text]NixAl.

| S-EPMC8915960 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data