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Extraction of cellulose nanocrystals from millet (Eleusine coracana) husk waste: optimization using Box Behnken design in response surface methodology (RSM)

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Abstract

Cellulose nanocrystals (CNCs) and their applications have attracted growing interest in both research and industry due to their appealing properties, such as excellent mechanical properties, high surface area, rich hydroxyl groups for modification, and natural properties that are 100% environmentally friendly. Cellulose nanocrystals were extracted from millet husk residue waste using a homogenized acid hydrolysis method. The effects of the process variables homogenization speed (A), acid concentration (B), and acid to cellulose ratio (C) on the yield and swelling capacity were investigated and optimized using the Box Behnken design (BBD) method in response surface methodology. The cellulose and nano-cellulose obtained were characterized using transform infrared microscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM). The numerical optimization analysis results showed that the maximum yield of CNCs and swelling capacity from cellulose was 93.12% and 2.81% obtained at homogenization speed, acid concentration, and acid to cellulose ratio of 7464.0 rpm, 63.40 wt%, and 18.83 wt%, respectively. ANOVA revealed that the most influential parameter in the model was homogenization speed for Yield and acid concentration for swelling capacity. The mathematical models to predict cellulose nanocrystals’ yield and swelling capacity were developed with R2 of 98.9% and 97.9%, respectively. The TGA showed that the thermal stability of cellulose was higher than that of CNCs. FTIR results showed that functional groups of CNCs and cellulose were similar. SEM image of CNCs is porous and displayed narrow particle size with needle-like morphology compared to cellulose. The XRD pattern presented an increase in the intensity of CNCs.

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Abbreviations

CNCs:

Cellulose nanocrystals

FTIR:

Fourier transform infrared

SEM:

Scanning electron microscopy

XRD:

X-ray diffraction

TGA:

Thermogravimetric analysis

CNCs:

Cellulose nanocrystals

ANOVA:

Analysis of variance

BBD:

Box Benkhen Design

SWC:

Swelling capacity

R 2 :

Regression coefficient

Y :

Is the predicted response

γ 0 :

Is the model constant

A, B, and C :

Are independent variables.

γ a, γ b and γ c :

Are linear coefficients

γ ab , γ ac and γ bc :

Are cross-product coefficients

γ aa, γ bb and γ cc :

Are the quadratic coefficients

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Acknowledgements

The authors acknowledge the financial support provided by the Paper Manufacturers Association of South Africa (PAMSA) and the Department of Science and Innovation (South Africa).

Funding

Paper Manufacturers Association of South Africa (PAMSA) and Department of Science and Innovation (South Africa) (Grant 2021).

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Authors and Affiliations

  1. Clean Technology and Applied Materials Research Group, Department of Chemical and Metallurgical Engineering, Vaal University of Technology, Vanderbijlpark, Private Bag X021, South Africa

    Musamba Banza & Hilary Rutto

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  1. Musamba Banza
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  2. Hilary Rutto
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Contributions

MB—conceptualization, data collection, investigation, and writing the original draft. HR—supervision, review, validation, and editing.

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Correspondence to Musamba Banza.

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Banza, M., Rutto, H. Extraction of cellulose nanocrystals from millet (Eleusine coracana) husk waste: optimization using Box Behnken design in response surface methodology (RSM). Int Nano Lett 12, 257–272 (2022). https://doi.org/10.1007/s40089-022-00369-x

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