The identification of microplastics becomes increasingly challenging with decreasing particle size and increasing sample heterogeneity. The analysis of microplastic samples by Fourier transform infrared (FTIR) spectroscopy is a versatile, bias-free tool to succeed at this task. In this study, we provide an adaptable reference database, which can be applied to single-particle identification as well as methods like chemical imaging based on FTIR microscopy. The large datasets generated by chemical imaging can be further investigated by automated analysis, which does, however, require a carefully designed database. The novel database design is based on the hierarchical cluster analysis of reference spectra in the spectral range from 3600 to 1250 cm⁻¹. The hereby generated database entries were optimized for the automated analysis software with defined reference datasets. The design was further tested for its customizability with additional entries. The final reference database was extensively tested on reference datasets and environmental samples. Data quality by means of correct particle identification and depiction significantly increased compared to that of previous databases, proving the applicability of the concept and highlighting the importance of this work. Our novel database provides a reference point for data comparison with future and previous microplastic studies that are based on different databases.

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随着粒径的减小和样品异质性的提高，微塑料的鉴定变得越来越具有挑战性。通过傅立叶变换红外（FTIR）光谱分析微量塑料样品是一种通用的，无偏差的工具，可以成功地完成此任务。在这项研究中，我们提供了一个适应性强的参考数据库，该数据库可应用于单颗粒识别以及基于FTIR显微镜的化学成像等方法。化学成像生成的大型数据集可以通过自动分析进行进一步研究，但是，这需要精心设计的数据库。新颖的数据库设计基于光谱范围为3600至1250 cm ^-1的参考光谱的层次聚类分析。由此生成的数据库条目已针对具有定义参考数据集的自动化分析软件进行了优化。对该设计的其他条目进行了可定制性的进一步测试。最终参考数据库已在参考数据集和环境样本上进行了广泛测试。与以前的数据库相比，通过正确的粒子识别和描述获得的数据质量显着提高，证明了该概念的适用性并突出了这项工作的重要性。我们新颖的数据库为与基于不同数据库的未来和以前的微塑性研究进行数据比较提供了参考点。

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