Accelerating manufacturing for biomass conversion via integrated process and bench digitalization: a perspective
| Author(s) | Batchu, Sai Praneet | |
| Author(s) | Hernandez, Borja | |
| Author(s) | Malhotra, Abhinav | |
| Author(s) | Fang, Hui | |
| Author(s) | Ierapetritou, Marianthi | |
| Author(s) | Vlachos, Dionisios G. | |
| Date Accessioned | 2022-03-23T19:21:45Z | |
| Date Available | 2022-03-23T19:21:45Z | |
| Publication Date | 2022-01-25 | |
| Description | This article was originally published in Reaction Chemistry and Engineering. The version of record is available at: https://doi.org/10.1039/D1RE00560J. This article will be embargoed until 01/25/2023. | en_US |
| Abstract | We present a perspective for accelerating biomass manufacturing via digitalization. We summarize the challenges for manufacturing and identify areas where digitalization can help. A profound potential in using lignocellulosic biomass and renewable feedstocks, in general, is to produce new molecules and products with unmatched properties that have no analog in traditional refineries. Discovering such performance-advantaged molecules and the paths and processes to make them rapidly and systematically can transform manufacturing practices. We discuss retrosynthetic approaches, text mining, natural language processing, and modern machine learning methods to enable digitalization. Laboratory and multiscale computation automation via active learning are crucial to complement existing literature and expedite discovery and valuable data collection without a human in the loop. Such data can help process simulation and optimization select the most promising processes and molecules according to economic, environmental, and societal metrics. We propose the close integration between bench and process scale models and data to exploit the low dimensionality of the data and transform the manufacturing for renewable feedstocks. | en_US |
| Sponsor | The biomass chemistry concepts were supported as part of the Catalysis Center for Energy Innovation, an Energy Frontier Research Center funded by the US Dept. of Energy, Office of Science, Office of Basic Energy Sciences under award number DE-SC0001004. The data science concepts were supported from the Department of Energy's Office of Energy Efficient and Renewable Energy's Advanced Manufacturing Office under Award Number DE-EE0007888-9.5. The Delaware Energy Institute gratefully acknowledges the support and partnership of the State of Delaware toward the RAPID projects. The National Science Foundation (Award number CBET-213447) supported the manufacturing digitalization concepts. | en_US |
| Citation | Batchu, Sai Praneet, Borja Hernandez, Abhinav Malhotra, Hui Fang, Marianthi Ierapetritou, and Dionisios G. Vlachos. “Accelerating Manufacturing for Biomass Conversion via Integrated Process and Bench Digitalization: A Perspective.” Reaction Chemistry & Engineering, January 25, 2022. https://doi.org/10.1039/D1RE00560J. | en_US |
| ISSN | 2058-9883 | |
| URL | https://udspace.udel.edu/handle/19716/30702 | |
| Language | en_US | en_US |
| Publisher | Reaction Chemistry and Engineering | en_US |
| Title | Accelerating manufacturing for biomass conversion via integrated process and bench digitalization: a perspective | en_US |
| Type | Article | en_US |
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