Multiscale Characterization of Lignocellulosic Biomass Variability and Its Implications to Preprocessing and Conversion: A Case Study for Corn Stover

Allison E. Ray*, C. Luke Williams, Amber N. Hoover, Chenlin Li, Kenneth L. Sale, Rachel M. Emerson, Jordan Klinger, Ethan Oksen, Akash Narani, Jipeng Yan, Christine M. Beavers, Deepti Tanjore, Manal Yunes, Elizabeth Bose, Juan H. Leal, Julie L. Bowen, Edward J. Wolfrum, Michael G. Resch, Troy A. Semelsberger, Bryon S. Donohoe

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

Feedstock variability that originates from biomass production and field conditions propagates through the value chain, posing a significant challenge to the emerging biorefinery industry. Variability in feedstock properties impacts feeding, handling, equipment operations, and conversion performance. Feedstock quality attributes, and their variations, are often overlooked in assessing feedstock value and utilization for conversion to fuels, chemicals, and products. This study developed and employed a multiscale analytical characterization approach coupled with data analytic methods to better understand the sources and distribution of feedstock quality variability through evaluation of 24 corn stover bales collected in 4 counties of Iowa. In total, 216 core samples were generated by sampling nine positions on each bale using a reliable bale coring process. The samples were characterized for a broad suite of physicochemical properties ranging across field and bale, macro, micro, and molecular scales. Results demonstrated that feedstock quality attributes can vary at all spatial scales and that multiple sources of variability must be considered in order to establish and manage biomass quality for conversion processes.

Original languageEnglish
Pages (from-to)3218-3230
Number of pages13
JournalACS Sustainable Chemistry and Engineering
Volume8
Issue number8
DOIs
Publication statusPublished - 2 Mar 2020
Externally publishedYes

Keywords

  • Biomass variability
  • Corn stover
  • Emergent properties
  • Inorganic speciation
  • Material attributes
  • Multiscale characterization
  • k-means clustering

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