L. Breitenfeld, M. Dyar, Leif Tokle, Kevin Robertson
{"title":"Raman Spectroscopy of the Ilmentite — Geikielite Solid Solution","authors":"L. Breitenfeld, M. Dyar, Leif Tokle, Kevin Robertson","doi":"10.2138/am-2023-9262","DOIUrl":null,"url":null,"abstract":"\n Ilmenite (Fe2+TiO3) and geikielite (MgTiO3) are important terrestrial minerals relevant to the geology of the Earth, the Moon, Mars, and meteorite samples. Raman spectroscopy is a powerful technique that allows for mineral cation determination for the ilmenite — geikielite solid solution. We report on a sample suite of nine samples within the ilmenite — geikielite solid solution and provide context for their quantitative interpretation. We compare a univariate Raman peak position model for predicting ilmenite composition with a multivariate machine learning model. The univariate model is currently recommended, though the multivariate model may become superior if the data set size is increased. This study lays the groundwork for quantifying Fe (ilmenite) and Mg (geikielite) within oxides minerals using a cheap, portable, and efficient technology like Raman spectroscopy.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":"101 7","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.2138/am-2023-9262","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
Ilmenite (Fe2+TiO3) and geikielite (MgTiO3) are important terrestrial minerals relevant to the geology of the Earth, the Moon, Mars, and meteorite samples. Raman spectroscopy is a powerful technique that allows for mineral cation determination for the ilmenite — geikielite solid solution. We report on a sample suite of nine samples within the ilmenite — geikielite solid solution and provide context for their quantitative interpretation. We compare a univariate Raman peak position model for predicting ilmenite composition with a multivariate machine learning model. The univariate model is currently recommended, though the multivariate model may become superior if the data set size is increased. This study lays the groundwork for quantifying Fe (ilmenite) and Mg (geikielite) within oxides minerals using a cheap, portable, and efficient technology like Raman spectroscopy.
期刊介绍:
ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications.
The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.