Comparison of crystallinity index computational methods based on lignocellulose X-ray diffractogram
CHEAH Yong Sing, MASAHARU Komiyama
download PDFAbstract. Crystallinity index (CrI) obtained from X-ray diffraction (XRD) technique is often utilized as a characterization parameter of lignocellulosic biomass. There exist a few methodologies to calculate CrI but the respective merit as lignocellulose characterization parameter is not very clear. Here four commonly employed CrI computational methods were applied to raw and torrefied biomasses (palm kernel shell and sugarcane bagasse), cellulose- and lignin-added raw biomasses and artificial mixtures of cellulose, hemicellulose and lignin in order to compare the effect of the composition of lignocellulosic biomass toward CrI calculated from X-ray diffractogram. Calculated CrI systematically showed larger value than the weight percentage of cellulose contained in the samples. Among the four computational methods compared, Segal (single peak height ratio) method and Ruland-Vonk (two-peak area ratio) method appeared to give reasonable CrI numbers although they are still overestimating the cellulose weight ratio. The Ruland-Vonk method consistently gave the lowest CrI values among the methods examined.
Keywords
Lignocellulosic Biomass, Crystallinity Index, Computational Methods, Comparison, Torrefaction, Artificial Lignocellulose
Published online 5/20/2023, 7 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: CHEAH Yong Sing, MASAHARU Komiyama, Comparison of crystallinity index computational methods based on lignocellulose X-ray diffractogram, Materials Research Proceedings, Vol. 29, pp 128-134, 2023
DOI: https://doi.org/10.21741/9781644902516-16
The article was published as article 16 of the book Sustainable Processes and Clean Energy Transition
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
References
[1] M. Hall, P. Bansal, J.H. Lee, M.J. Realff, A.S. Bommarius, Cellulose crystallinity – a key predictor of the enzymatic hydrolysis rate, FEBS J. 277 (2010) 1571-1582. https://doi.org/10.1111/j.1742-4658.2010.07585.x
[2] I. Siró, D. Plackett, Microfibrillated cellulose and new nanocomposite materials: a review, Cellulose, 17 (2010) 459-494. https://doi.org/10.1007/s10570-010-9405-y
[3] U. Rofiqah, A. Safitri, Fadhilah, Study of delignification process and crystallinity index on lignocellulose components of corn cob in different pretreatments: a combination of pretreatment (ionic cholineacetate and NaOH) and NaOH pretreatment, IOP Conf. Ser.: Mater. Sci. Eng. 625 (2019) 012029. https://doi.org/10.1088/1757-899X/625/1/012029
[4] R. Abu Darim, A. Azizan, J. Salihon, Study of crystallinity index (CrI) of oil palm frond pretreatment using aqueous [EMIM][OAc] in a closed system, IOP Conf. Ser.: Mater. Sci. Eng. 358 (2018) 012007. https://doi.org/10.1088/1757-899X/358/1/012007
[5] A.A.N. Gunny, D. Arbain, P. Jamal, Effect of structural changes of lignocelluloses material upon pre-treatment using green solvents, AIP Conf. Proc. 1835 (2017) 020022. https://doi.org/10.1063/1.4981844
[6] Y. Pu, F. Hu, F. Huang, B.H. Davison, A.J. Ragauskas, Assessing the molecular structure basis for biomass recalcitrance during dilute acid and hydrothermal pretreatments, Biotechnol. Biofuels, 6 (2013) 15. https://doi.org/10.1186/1754-6834-6-15
[7] K. Karimi, M.J. Taherzadeh, A critical review of analytical methods in pretreatment of lignocelluloses: composition, imaging, and crystallinity, Bioresour. Technol. 200 (2016) 1008-1018. https://doi.org/10.1016/j.biortech.2015.11.022
[8] L. Segal, J.J. Creely, A.E. Martin Jr., C.M. Conrad, An empirical method for estimating the degree of crystallinity of native cellulose using the x-ray diffractometer, Text. Res. J. 29 (1959) 786-794. https://doi.org/10.1177/004051755902901003
[9] G. Jayme, H. Knolle, Introduction into empirical X-ray determination of crystallinity of cellulose materials, Das Papier, 18 (1964) 249-255.
[10] W. Ruland, X-ray determination of crystallinity and diffuse disorder scattering, Acta Crystallogr. 14 (1961) 1180-1185. https://doi.org/10.1107/S0365110X61003429
[11] C.G. Vonk, Computerization of Ruland’s X-ray method for determination of the crystallinity in polymers, J. Appl. Crystallogr. 6 (1973) 148-152. https://doi.org/10.1107/S0021889873008332
[12] R. Ibbett, D. Domvoglou, D.A.S. Phillips, The hydrolysis and recrystallisation of lyocell and comparative cellulosic fibres in solutions of mineral acid, Cellulose, 15 (2008) 241-254. https://doi.org/10.1007/s10570-007-9157-5
[13] S. Park, J.O. Baker, M.E. Himmel, P.A. Parilla, D.K. Johnson, Cellulose crystallinity index: measurement techniques and their impact on interpreting cellulase performance, Biotechnol. Biofuels, 3 (2010) 10. https://doi.org/10.1186/1754-6834-3-10
[14] N. Terinte, R. Ibbett, K.C. Schuster, Overview on native cellulose and microcrystalline cellulose I structure studied by X-ray diffraction (WAXD): comparison between measurement techniques, Lenzinger Ber. 89 (2011) 118-131.
[15] H. Yang, R. Yan, H. Chen, C. Zheng, D.H. Lee, D.T. Liang, In-depth investigation of biomass pyrolysis based on three major components: hemicellulose, cellulose and lignin, Ener. Fuels, 20 (2006) 388-393. https://doi.org/10.1021/ef0580117
