LAPSE:2019.0610
Preprint
LAPSE:2019.0610
Data Science-Enabled Molecular-to-Systems Engineering for Sustainable Water Treatment
Elvis Eugene, William Phillip, Alexander Dowling*
October 11, 2019. Originally submitted on June 28, 2019
Growing social and economic pressures demand technological innovations that enable the widespread usage of unconventional sources of water. These challenges motivate the emerging fit-for-purpose paradigm, wherein water is provided at the precise quality level of the intended application. Unfortunately, to date, fundamental advances in materials and nanotechnology have been slow to advance this paradigm. Using examples from membrane science and engineering, we highlight the critical need to bridge research at the molecular and nano-scales with development at the device and systems-scales to fully realize sustainable fit-for-purpose water technology. Specifically, we present four opportunities for computing and data science to accelerate convergence of sustainable water research: materials informatics and inverse design, model-based design of experiments, superstructure optimization, and uncertainty quantification. As such, we highlight opportunities to collaboratively revolutionize molecular-to-systems engineering of sustainable water technologies, but emphasize open communication between data scientists and water-focused researchers using a common vocabulary as a significant hurdle.
Keywords
Bayesian optimization, design of experiments, fit-for-purpose water, inverse materials design, materials informatics, superstructure optimization, uncertainty quantification
Suggested Citation
Eugene E, Phillip W, Dowling A. Data Science-Enabled Molecular-to-Systems Engineering for Sustainable Water Treatment. (2019). LAPSE:2019.0610
Author Affiliations
Eugene E: University of Notre Dame
Phillip W: University of Notre Dame
Dowling A*: University of Notre Dame [ORCID] [Google Scholar]
* Corresponding Author
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Journal Name
Current Opinion in Chemical Engineering
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Revision of Version 2
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LAPSE:2019.0610
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doi:10.1016/j.coche.2019.10.002
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Oct 11, 2019
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[v3] (Revision of Version 2)
Oct 11, 2019
[v2] (Version 1 (added missing author))
Jun 28, 2019
[v1] (Original Submission)
Jun 28, 2019
 
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adowling
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