Avendano Marco, Trusty Blake, Dangwal Shailesh, Coin Zachary, Islam Syed, Nair Sankar, Bhave Ramesh, Realff Matthew J
School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
Oak Ridge National Laboratory, Chemical Sciences Division, Oak Ridge, Tennessee 37830, United States.
Ind Eng Chem Res. 2025 Aug 12;64(34):16770-16785. doi: 10.1021/acs.iecr.5c01198. eCollection 2025 Aug 27.
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.
渗透蒸发与其他分离过程相结合,能够有效地从发酵产物流中去除水分,使其非常适合用于纯化2,3-丁二醇(BDO)等醇类物质。在本研究中,制备了一种用于BDO脱水的致密聚偏氟乙烯(PVDF)中空纤维膜组件原型,实现了总通量>0.2 LMH以及BDO截留率>95%。采用马尔可夫链蒙特卡罗(MCMC)方法,利用贝叶斯推理对渗透参数的不确定性进行量化。开发了一种膜级联模型,以扩大将预浓缩的BDO进料(70 wt%)纯化至高纯度(90 wt%)的过程。通过参数不确定性的传播和过程变量的敏感性分析,推荐了一种级联设计。尽管存在数据和模型限制,但该框架实现了可靠的系统分析和经济评估,并通过关键过程指标的紧密置信区间得到验证,为贝叶斯方法在基于膜的过程中的未来应用奠定了基础。