Abstract It is of great significance to realize the rapid, nondestructive and accurate identification of tire rubber particles in forensic science. However, there are no relevant reports. This study collected and tested infrared spectroscopy data of 240 samples from 15 brands. Baseline correction, multivariate scatter correction, standard normal variables and Savitzky-Golay smoothing were adopted to preprocess the infrared spectra. The comparison of the fingerprint region and full infrared spectrum was explored. The identification models were established by principal component analysis and discriminant analysis. The results showed that there is no significant discrimination in the peak position and shape; instead the peak intensity and relative height were slightly different. The cumulative variance contribution rate of principal components 1 through 12 reached 98.3690% demonstrating 98.3690% of the details in the original measurements. The 39-dimensional principal components of infrared fingerprint region accurately differentiated sample brands and employed computational complexity. Styrene butadiene samples from six brands were accurately identified based on the three discriminant functions Za1, Zb1, and Zc1. Butadiene samples from five brands were differentiated using discriminant functions Za2, Zb2, and Zc2. Isoprene samples from brands were separated using the discriminant functions Za3, Zb3, and Zc3. All samples were precisely identified by this rapid and nondestructive protocol. The results of this study demonstrate the potential of attenuated total reflectance-Fourier transform infrared spectroscopy in combination with principal component analysis and discriminant analysis as a new method for the identification of tire rubber particles.

中文翻译：

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通过衰减全反射快速无损地鉴定轮胎颗粒 - 傅里叶变换红外光谱和化学计量学

摘要 在法医学中实现轮胎橡胶颗粒的快速、无损、准确识别具有重要意义。但是，没有相关报道。本研究收集并测试了来自 15 个品牌的 240 个样品的红外光谱数据。采用基线校正、多元散射校正、标准正态变量和Savitzky-Golay平滑对红外光谱进行预处理。探索了指纹区域和全红外光谱的比较。通过主成分分析和判别分析建立识别模型。结果表明，峰位和峰形没有明显区别；相反，峰强度和相对高度略有不同。主成分 1 到 12 的累积方差贡献率达到 98.3690%，显示原始测量中细节的 98.3690%。红外指纹区域的 39 维主成分准确区分了样本品牌，并采用了计算复杂度。基于三个判别函数 Za1、Zb1 和 Zc1，准确识别了来自六个品牌的苯乙烯丁二烯样品。使用判别函数 Za2、Zb2 和 Zc2 区分来自五个品牌的丁二烯样品。使用判别函数 Za3、Zb3 和 Zc3 分离来自品牌的异戊二烯样品。所有样品均通过这种快速且无损的方案进行精确鉴定。