Abstract
Pervaporation, combined with other separation processes, can effectively remove water from fermentation product streams, making it highly suitable for purifying alcohols like 2,3-butanediol (BDO). In this study, a dense poly(vinylidene fluoride) (PVDF) hollow fiber membrane module prototype was fabricated for BDO dehydration, achieving >0.2 LMH total flux and >95% BDO rejection. With a Markov chain Monte Carlo (MCMC) approach, Bayesian inference was used to quantify the uncertainty of the permeance parameters. A membrane cascade model was developed to scale up a process that purifies a preconcentrated BDO feed (70 wt %) to high purity (90 wt %). Through propagation of the uncertainty of the parameters and sensitivity analyses of the process variables, a cascade design was recommended. Despite data and model limitations, the framework enabled a reliable system analysis and economic evaluation, validated through tight confidence intervals in key process metrics, establishing the foundation for future applications of Bayesian methods in membrane-based processes.
| Original language | English |
|---|---|
| Pages (from-to) | 16770-16785 |
| Number of pages | 16 |
| Journal | Industrial and Engineering Chemistry Research |
| Volume | 64 |
| Issue number | 34 |
| DOIs | |
| State | Published - Aug 27 2025 |
Funding
This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05–00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( https://www.energy.gov/doe-public-access-plan ). This work was supported by the Department of Energy, Bioenergy Technologies Office (BETO) under contract DE-EE-0009263. The ORNL team would like to acknowledge Lawrence Powell for his help monitoring ongoing experiments. The ORNL team would like to acknowledge Dr. Stephen Dewitt, Dr. Wei Wang, and Dr. Walt Kosar from Arkema, Inc. for their technical support with membrane coating.
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