Distinction of polished and unpolished sp2 carbons via principal component analysis

O. Maslova, M. Ammar, S. Barannikova
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Abstract

Mechanical polishing of graphite-like sp2 carbon structures is known to lead to the unpredictable increase in the defect-conducted (D) band (∼1350 cm−1) in their Raman spectra, whereas the G band (∼1580 cm−1) interpreted as an intrinsic characteristic of these materials remains visually unchanged. In this respect, special attention is paid to the characterization of polished carbon materials via Raman mapping that enables one to scan the area of interest within the sample surface and to evaluate the effect of polishing at the structural level. Data collected during the mapping can be processed via a simple analysis of spectroscopic parameters (intensity, width, and peak position) or through the multivariate statistical methods (principal component analysis). According to various studies, the latter has been widely used in the last years due to its simplicity and the possibility to substantially reduce the processing time, which is especially convenient when working with huge-volume data composed of thousands of spectra. In this work the principal component analysis (PCA) was applied to distinguish polished and unpolished sp2 carbons by the example of anthracene-based cokes (a variety of graphitizable sp2 carbon). For this purpose the Raman spectra were acquired on the samples pyrolized at temperatures of 1600, 2000 and 2900°C and exposed to polishing. According to the preliminary results, the difference between polished and unpolished specimens becomes more obvious as the temperature of pyrolysis increases (above 2000°C), leading to a pronounced distinction at a temperature of 2900°C. Thus, the method allows one to distinguish the specimens whose structural differences are due to pyrolysis or polishing.
通过主成分分析来区分抛光和未抛光的sp2碳
已知对类石墨sp2碳结构进行机械抛光会导致拉曼光谱中缺陷传导(D)带(~ 1350 cm−1)的不可预测的增加,而被解释为这些材料固有特征的G带(~ 1580 cm−1)在视觉上保持不变。在这方面,特别注意通过拉曼映射对抛光碳材料的表征,使人们能够扫描样品表面内感兴趣的区域,并在结构水平上评估抛光的效果。在制图过程中收集的数据可以通过简单的光谱参数分析(强度、宽度和峰位置)或通过多元统计方法(主成分分析)进行处理。根据各种研究,后者由于其简单且可以大大缩短处理时间,在处理由数千个光谱组成的大容量数据时尤其方便,近年来得到了广泛的应用。在这项工作中,主成分分析(PCA)应用于区分抛光和未抛光的sp2碳,以蒽基焦为例(各种石墨化的sp2碳)。为此,在1600、2000和2900°C的温度下,对暴露于抛光下的样品进行了拉曼光谱分析。初步结果表明,随着热解温度的升高(2000℃以上),抛光试样与未抛光试样的差异越来越明显,在2900℃时差异明显。因此,该方法允许人们区分由于热解或抛光而导致结构差异的样品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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