Achenbach Bastian, Yurdusen Aysu, Stock Norbert, Maurin Guillaume, Serre Christian
Institut für Anorganische Chemie, Christian-Albrechts-Universität zu Kiel, Max-Eyth-Straße 2, 24118, Kiel, Germany.
Institut des Matériaux Poreux de Paris, Ecole Normale Supérieure, ESPCI Paris, CNRS, PSL University, Paris, 75005, France.
Adv Mater. 2025 Jan 7:e2411359. doi: 10.1002/adma.202411359.
Even if MOFs are recently developed for large-scale applications, the road to applications of MOFs is long and rocky. This requires to overcome challenges associated with phase discovery, synthesis optimization, basic and advanced characterization, and computational studies. Lab-scale results need to be transferred to large-scale processes, which is often not trivial, and life-cycle analyses and techno-economic analyses need to be performed to realistically assess their potential for industrial relevance. Based on the experience in the field of stable, functional MOFs combining advanced synthesis, characterization, and modeling, this mini-review gives recommendations especially for non-specialists, for example, from chemical engineers to medical doctors, to accelerate and facilitate knowledge transfer which will ultimately lead to the application of MOFs. The recommendations will include the reporting of synthesis and characterization data as well as standardization and detailed information required for the application of data mining and machine learning techniques, which are increasingly used to accelerate the discovery of new materials and data analysis. Once a suitable MOF is identified and its key properties determined, translational studies shall finally be carried out in collaboration with end-users to validate performance under real conditions and allow understanding of the processes involved.
即使金属有机框架材料（MOFs）最近才被开发用于大规模应用，但MOFs的应用之路漫长且崎岖。这需要克服与相发现、合成优化、基础和高级表征以及计算研究相关的挑战。实验室规模的结果需要转化为大规模工艺，这通常并非易事，并且需要进行生命周期分析和技术经济分析，以切实评估它们在工业相关性方面的潜力。基于在结合先进合成、表征和建模的稳定功能性MOFs领域的经验，本综述特别为非专业人士提供建议，例如从化学工程师到医生，以加速和促进知识转移，这最终将导致MOFs的应用。这些建议将包括合成和表征数据的报告，以及应用数据挖掘和机器学习技术所需的标准化和详细信息，这些技术越来越多地用于加速新材料的发现和数据分析。一旦确定了合适的MOF并确定了其关键特性，最终应与终端用户合作进行转化研究，以在实际条件下验证性能并了解其中涉及的过程。
