Catalytic pyrolysis presents a promising avenue for mitigating plastic waste accumulation by converting it into valuable products. In this study, we investigate the application of computational methods integrating molecular similarities and the Kovats retention index to enhance the accuracy of qualitative analysis in catalytic pyrolysis processes. Utilizing gas-chromatography data and high-level measurement results, molecular compositions of pyrolysis products are determined and the consistency of molecular composition across various experimental conditions is evaluated. Despite encountering challenges such as algorithm failures due to high computational costs, our analysis reveals significant insights into the molecular composition of pyrolysis products. Through the utilization of molecular similarity methods, the potential to refine the estimation of molecular compositions is also demonstrated, particularly in scenarios in which retention index database accuracy is uncertain. Our findings underscore the importance of further refining computational methods and formulating additional constraints based on high-level measurements to enhance the accuracy of molecular composition estimates.

中文翻译：

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催化热解的计算见解：使用 Kovats 保留指数和分子相似性改进分子组成估计


催化热解通过将塑料废物转化为有价值的产品来减少塑料废物的积累，为减少塑料废物的积累提供了一种有前途的途径。在这项研究中，我们研究了整合分子相似性和 Kovats 保留指数的计算方法的应用，以提高催化热解过程中定性分析的准确性。利用气相色谱数据和高级测量结果，确定热解产物的分子组成，并评估各种实验条件下分子组成的一致性。尽管由于计算成本高而遇到了算法失败等挑战，但我们的分析揭示了对热解产物分子组成的重要见解。通过利用分子相似性方法，还展示了改进分子组成估计的潜力，特别是在保留指数数据库准确性不确定的情况下。我们的研究结果强调了进一步改进计算方法和根据高级测量制定额外约束以提高分子组成估计的准确性的重要性。