Raman Quantitative Models of Silicate Ternary Mixtures: Factoring in the Effect of Glass Content

ABSTRACT Raman spectroscopy is a powerful nondestructive tool for analyzing the mineral composition of planetary surface soils. However, quantifying the modal mineralogy remains a challenge, especially for lunar regolith due to the low Raman scattering cross sections of key silicate minerals and the interference from glass components. This study developed quantitative models for determining the mineral modes of lunar soil simulants, factoring in the effect of glass content on Raman‐based mineral quantification. The simulant materials, including feldspar, olivine, augite, and glass, were mixed in varying mass fractions to create 24 different mixtures. A Gaussian–Lorentzian fitting method was employed to analyze the Raman spectra and extract peak areas, which were quantitatively correlated with the mineral proportions in the mixtures. The quantitative models were built using the linear relationship between Raman peak areas and mineral proportions. These models demonstrated high accuracy with correlation coefficients ( R 2 ) exceeding 0.94 and root mean square errors (RMSEs) less than 5.16 wt.% for the glass‐free samples. Further analyses showed that the inclusion of up to 40 wt.% glass reduced only the area of Raman peaks, particularly for augite, but the models remained reliable for predicting mineral content. This work provides a reliable approach for quantitative mineral analysis of lunar soils, offering valuable insights for future planetary exploration missions.

Authors

Institutions

Publication Details

Journal
Journal of Raman Spectroscopy
Published
2026-01-15
DOI
https://doi.org/10.1002/jrs.70110
Primary Topic
Planetary Science and Exploration
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Raman Quantitative Models of Silicate Ternary Mixtures: Factoring in the Effect of Glass Content

Qi Zou, Ping Liu, Haijun Cao, Changqing Liu et al.
Journal of Raman Spectroscopy
Planetary Science and Exploration
article

Raman Quantitative Models of Silicate Ternary Mixtures: Factoring in the Effect of Glass Content

Qi Zou, Ping Liu, Haijun Cao, Changqing Liu, Zongcheng Ling, Chenyu Wang, Hongkun Quincy Qu
article en

Abstract

ABSTRACT Raman spectroscopy is a powerful nondestructive tool for analyzing the mineral composition of planetary surface soils. However, quantifying the modal mineralogy remains a challenge, especially for lunar regolith due to the low Raman scattering cross sections of key silicate minerals and the interference from glass components. This study developed quantitative models for determining the mineral modes of lunar soil simulants, factoring in the effect of glass content on Raman‐based mineral quantification. The simulant materials, including feldspar, olivine, augite, and glass, were mixed in varying mass fractions to create 24 different mixtures. A Gaussian–Lorentzian fitting method was employed to analyze the Raman spectra and extract peak areas, which were quantitatively correlated with the mineral proportions in the mixtures. The quantitative models were built using the linear relationship between Raman peak areas and mineral proportions. These models demonstrated high accuracy with correlation coefficients ( R 2 ) exceeding 0.94 and root mean square errors (RMSEs) less than 5.16 wt.% for the glass‐free samples. Further analyses showed that the inclusion of up to 40 wt.% glass reduced only the area of Raman peaks, particularly for augite, but the models remained reliable for predicting mineral content. This work provides a reliable approach for quantitative mineral analysis of lunar soils, offering valuable insights for future planetary exploration missions.

Journal of Raman Spectroscopy
China Academy of Space Technology (CN), Shandong Jiaotong University (CN), Applied Photonics (United Kingdom) (GB), Institute of Space Sciences (ES), Photonic Science (United Kingdom) (GB)
Shandong University, National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Shandong Province
Life in Land
Openalex Percentile: Top 85%
Planetary Science and Exploration
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.