使用傅立叶变换红外光谱和拉曼光谱对粉色口红进行比较鉴别

IF 2.7 3区 化学 Q2 CHEMISTRY, ANALYTICAL Vibrational Spectroscopy Pub Date : 2023-12-13 DOI:10.1016/j.vibspec.2023.103640
Rowdha Abdulla Alblooshi , Rashed Humaid Alremeithi , Abdulrahman Hussain Aljannahi , Ayssar Nahlé
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引用次数: 0

摘要

口红是女性的日常用品,很容易转移到衣服、杯子、纸巾和其他物品上。口红分析是法医学中一个相对较新且令人兴奋的领域,它有助于在犯罪现场留下口红证据的刑事案件中识别嫌疑人。通过将特定品牌的口红与样本进行比对,调查人员可以肯定地将某些人与地点或人物联系起来,从而有助于调查和后续诉讼。在本研究中,使用真空傅立叶变换红外光谱和拉曼光谱对同一制造商生产的 20 种不同的粉红色口红进行了分析,结果显示样本之间的区分度为 95.8%。利用数据挖掘技术对傅立叶变换红外光谱进行了数据分析。数据挖掘模型采用主成分分析法(PCA)进行分类,并能根据傅立叶变换红外光谱对口红样品进行区分。
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Comparative forensic discrimination of pink lipsticks using fourier transform infra-red and Raman spectroscopy

As a routine, lipstick is daily used by females and can easily be transferred to clothes, cups, tissue papers, and other objects. The analysis of lipsticks is a relatively new and exciting field in forensics, helping to identify suspects in criminal cases where lipstick evidence has been left at crime scenes. By matching a specific brand of lipstick to a sample, investigators can positively connect certain individuals to locations or people, helping to aid in their investigation and subsequent proceedings. In this present study, 20 different pink shade lipsticks of the same manufacturer were analyzed using Vacuum FT-IR, and Raman spectroscopy to show a differentiation percentage of 95.8% between the samples. Data analysis using data mining techniques was performed on FT-IR spectra. Principle Component Analysis (PCA) was used as a data mining model for classification purposes, and it was able to distinguish between lipsticks samples based on their FT-IR spectra.

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来源期刊
Vibrational Spectroscopy
Vibrational Spectroscopy 化学-分析化学
CiteScore
4.70
自引率
4.00%
发文量
103
审稿时长
52 days
期刊介绍: Vibrational Spectroscopy provides a vehicle for the publication of original research that focuses on vibrational spectroscopy. This covers infrared, near-infrared and Raman spectroscopies and publishes papers dealing with developments in applications, theory, techniques and instrumentation. The topics covered by the journal include: Sampling techniques, Vibrational spectroscopy coupled with separation techniques, Instrumentation (Fourier transform, conventional and laser based), Data manipulation, Spectra-structure correlation and group frequencies. The application areas covered include: Analytical chemistry, Bio-organic and bio-inorganic chemistry, Organic chemistry, Inorganic chemistry, Catalysis, Environmental science, Industrial chemistry, Materials science, Physical chemistry, Polymer science, Process control, Specialized problem solving.
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