Akbari Lakeh Mahsa, Gerritsen Floris, Aronds Tycho, Jansen Jeroen J, Tinnevelt Gerjen H
Radboud University, Institute for Molecules and Materials (Analytical Chemistry), P.O. Box 9010, 6500 GL, Nijmegen, The Netherlands.
Veridis Technologies B.V., High Tech Campus 27, 5656 AE Eindhoven, Netherlands.
ACS Sustain Chem Eng. 2025 May 7;13(19):7179-7188. doi: 10.1021/acssuschemeng.5c01544. eCollection 2025 May 19.
A crucial issue in the plastic recycling industry is the loss of quality in recycled materials due to cross-contamination, which leads to excessive material losses. Determining cross-contamination levels in recyclate batches fills a crucial gap in quality control, helping to identify suitable applications and enhance the value of the material stream. A key challenge lies in selecting a sample size that accurately represents the large variability within the tons of batches processed daily. This work presents a data analysis framework to accurately estimate cross-contamination levels in plastic recyclate batches and determine the sample size required to meet industry demands while accounting for both analytical and sampling errors. Additionally, this work introduces MADSCAN, a novel, scale-free thermal analysis technique that allows for the analysis of the sample sizes identified by the framework. Objectives include providing crucial information to industry stakeholders, assisting regulators in establishing quality control processes, and guiding technology providers in advancing measurement techniques for the circular economy, with a focus on meeting sample size and accuracy requirements.
塑料回收行业的一个关键问题是，由于交叉污染导致回收材料质量下降，进而造成大量材料损失。确定回收批次中的交叉污染水平填补了质量控制方面的关键空白，有助于确定合适的应用并提高物料流的价值。一个关键挑战在于选择一个能准确代表每日处理的数吨批次中巨大变异性的样本量。这项工作提出了一个数据分析框架，以准确估计塑料回收批次中的交叉污染水平，并确定在考虑分析误差和采样误差的情况下满足行业需求所需的样本量。此外，这项工作还引入了MADSCAN，这是一种新颖的、无标度热分析技术，可用于分析该框架确定的样本量。目标包括为行业利益相关者提供关键信息，协助监管机构建立质量控制流程，并指导技术供应商推进循环经济的测量技术，重点是满足样本量和准确性要求。
