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Abstract
Zeolites play numerous important roles in modern petroleum refineries and have the potential to advance the production of fuels and chemical feedstocks from renewable resources. The performance of a zeolite as separation medium and catalyst depends on its framework structure. To date, 213 framework types have been synthesized and >330,000 thermodynamically accessible zeolite structures have been predicted. Hence, identification of optimal zeolites for a given application from the large pool of candidate structures is attractive for accelerating the pace of materials discovery. Here we identify, through a large-scale, multi-step computational screening process, promising zeolite structures for two energy-related applications: the purification of ethanol from fermentation broths and the hydroisomerization of alkanes with 18-30 carbon atoms encountered in petroleum refining. These results demonstrate that predictive modelling and data-driven science can now be applied to solve some of the most challenging separation problems involving highly non-ideal mixtures and highly articulated compounds.
Original language | English (US) |
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Article number | 5912 |
Journal | Nature communications |
Volume | 6 |
DOIs | |
State | Published - Jan 21 2015 |
Bibliographical note
Publisher Copyright:© 2015 Macmillan Publishers Limited. All rights reserved.
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- 1 Finished
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NMGC: Nanoporous Materials Genome: Methods and Software to Optimize Gas Storage, Separations, and Catalysis (Phase 1)
Siepmann, I. (PI), Cramer, C. (CoI), Gagliardi, L. (CoI), Truhlar, D. G. (CoI), Tsapatsis, M. (CoI) & Goodpaster, J. D. (CoI)
9/1/12 → 8/31/17
Project: Research project