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Scientific Article details

Title Discovering Circular Process Solutions through Automated Reaction Network Optimization
ID_Doc 6406
Authors Weber, JM; Guo, Z; Lapkin, AA
Title Discovering Circular Process Solutions through Automated Reaction Network Optimization
Year 2022
Published Acs Engineering Au, 2, 4
DOI 10.1021/acsengineeringau.2c00002
Abstract The transition toward a circular and biobased chemical industry is needed to cut global CO2 emissions and limit the chemical industry's overall impact on the environment. However, the development of circular chemical reaction systems is challenging as it requires symbiotic sets of novel chemical reaction pathways and involves unconventional processing steps. We present a methodological pipeline for automated reaction network optimization. The tools can guide the development of circular processes on the reaction pathway level. Chemical big data combined with energetic assessment metrics and state-of-the-art decision-making has the potential to efficiently identify the most promising reaction systems. We mine large-scale chemical reaction data from Reaxys database and automate the screening of pathways based on chemical rules. We then approximate thermodynamic properties for exergy calculations of the prescreened pathways and formulate the optimization problem as linear programming and mixed-integer linear programming problem. The methodological workflow is illustrated in a case study on the conversion of ss pinene to citral. Our results show that the tools are well suited to model circular process interactions within different environment scenarios.
Author Keywords systems thinking; network optimization; data mining; circular economy; exergy analysis; chemical supply chain
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Emerging Sources Citation Index (ESCI)
EID WOS:001124788200001
WoS Category Engineering, Chemical
Research Area Engineering
PDF https://pubs.acs.org/doi/pdf/10.1021/acsengineeringau.2c00002
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