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Sökning: L773:2190 6815 OR L773:2190 6823 > Predictive models e...

Predictive models enhance feedstock quality of corn stover via air classification

Cousins, Dylan S. (författare)
Department of Chemical and Biological Engineering, Montana State University, 306 Cobleigh Hall, PO Box 173920, Bozeman, MT, 59717-3920, USA
Rony, Asif Hasan (författare)
Idaho National Laboratory, Idaho Falls, ID, USA
Otto, William G. (författare)
Department of Chemical and Biological Engineering, Montana State University, 306 Cobleigh Hall, PO Box 173920, Bozeman, MT, 59717-3920, USA
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Pedersen, Kristian P. (författare)
Department of Chemical and Biological Engineering, Montana State University, 306 Cobleigh Hall, PO Box 173920, Bozeman, MT, 59717-3920, USA
Hernandez, Sergio (författare)
Idaho National Laboratory, Idaho Falls, ID, USA
Lacey, Jeffrey A. (författare)
Idaho National Laboratory, Idaho Falls, ID, USA
Aston, John E. (författare)
Idaho National Laboratory, Idaho Falls, ID, USA
Hodge, David B. (författare)
Luleå tekniska universitet,Kemiteknik,Department of Chemical and Biological Engineering, Montana State University, 306 Cobleigh Hall, PO Box 173920, Bozeman, MT, 59717-3920, USA
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 (creator_code:org_t)
2022
2022
Engelska.
Ingår i: Biomass Conversion and Biorefinery. - : Springer Nature. - 2190-6815 .- 2190-6823.
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Feedstock heterogeneity is a fundamental obstacle to cost-competitive biobased products. Agricultural products like corn stover have anatomical components that vary in their chemical composition, mechanical properties, structure, and response to chemical and biological treatments. A technique that can enrich streams in select anatomical fractions would allow a tailored deconstruction approach to increase overall process efficiency. Air classification can be leveraged for such refining; however, fundamental characterization and understanding of the particle properties that underly the physics of air classification are only modestly documented. Here, we determine fundamental particle properties including mass-to-area ratio, drag coefficient, and partition velocity that describe how anatomical tissues of corn stover behave during air classification. Mass-to-area ratios of anatomical tissues vary by nearly two orders of magnitude from 2.3 mg/mm2 for cob to 0.04 mg/mm2 for leaf. Drag coefficients of longer, fibrous materials (i.e., rind, husk, and sheath) are shown to correlate with particle area (p-value < 0.001) whereas granular tissues (i.e., cob, pith, and leaf) correlate better with mass-to-area ratio (p-values < 0.001). When compared to experimental observations, a simulated two-stage air classification and size reduction scenario predicts the overall partitioning of anatomical tissues within 15% for pith, husk, rind, and cob tissues. The model predicts an air-classified fraction preferentially enriched in cob (purity = 20%), rind (purity = 74%), and pith (purity = 4.5%) with a mass yield of 47%. Empirical relations for these properties can be used to predict the partitioning of corn stover during air classification based on anatomical type and size.

Ämnesord

NATURVETENSKAP  -- Biologi -- Biokemi och molekylärbiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Biochemistry and Molecular Biology (hsv//eng)

Nyckelord

Air classification
Feedstock enhancement
Feedstock enhancement
Biorefnery
Particle image analysis
Comminution
Biomass separation
Biokemisk processteknik
Biochemical Process Engineering

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