Browsing by Author "Kalita, R.D."

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Advanced Microscopic Visualization for Structural Characterization of Cellulose Extracted from Saccharum Spontaneum (Kohua Bon) of Assam, India
(Optica Publishing Group (formerly OSA), 2021) Chakraborty, I.; Kalita, R.D.; Singh, P.; Banik, S.; Govindaraju, I.; Mal, S.S.; Zhuo, G.-Y.; Mahato, K.K.; Mazumder, N.
Alpha, microcrystalline and nanocrystalline cellulose were sequentially extracted from stems and leaves of Saccharum spontaneum and were subjected to morphological and structural characterization using advanced microscopy techniques, including Scanning electron microscopy and nonlinear optical microscopy. Â© Optica Publishing Group 2021, Â© 2021 The Author (s)
An insight into microscopy and analytical techniques for morphological, structural, chemical, and thermal characterization of cellulose
(John Wiley and Sons Inc, 2022) Chakraborty, I.; Rongpipi, S.; Govindaraju, I.; Rakesh, B.; Mal, S.S.; Gomez, E.W.; Gomez, E.D.; Kalita, R.D.; Nath, Y.; Mazumder, N.
Cellulose obtained from plants is a bio-polysaccharide and the most abundant organic polymer on earth that has immense household and industrial applications. Hence, the characterization of cellulose is important for determining its appropriate applications. In this article, we review the characterization of cellulose morphology, surface topography using microscopic techniques including optical microscopy, transmission electron microscopy, scanning electron microscopy, and atomic force microscopy. Other physicochemical characteristics like crystallinity, chemical composition, and thermal properties are studied using techniques including X-ray diffraction, Fourier transform infrared, Raman spectroscopy, nuclear magnetic resonance, differential scanning calorimetry, and thermogravimetric analysis. This review may contribute to the development of using cellulose as a low-cost raw material with anticipated physicochemical properties. Highlights: Morphology and surface topography of cellulose structure is characterized using microscopy techniques including optical microscopy, transmission electron microscopy, scanning electron microscopy, and atomic force microscopy. Analytical techniques used for physicochemical characterization of cellulose include X-ray diffraction, Fourier transform infrared spectroscopy, Raman spectroscopy, nuclear magnetic resonance spectroscopy, differential scanning calorimetry, and thermogravimetric analysis. © 2022 Wiley Periodicals LLC.
Physicochemical characterization of microcrystalline cellulose extracted by sequential dual acid hydrolysis
(Elsevier, 2024) Kalita, R.D.; Chakraborty, I.; Singh, P.; Banik, S.; Mal, S.S.; Zhuo, G.-Y.; Mazumder, N.
Properties and applications of microcrystalline cellulose (MCC) differ based on its source and method of extraction. In this article, MCC was extracted from Saccharum spontaneum using single acid hydrolysis (MCC1) and sequential dual acid hydrolysis (MCC2). Scanning electron microscope (SEM) images exhibited that the dimension of MCC2 is much smaller compared to MCC1. X-ray diffraction (XRD) indicated that sequential dual acid hydrolysis results in decrease the crystallinity index (CI%) in case of MCC2 (34.45%). Fourier transform infrared spectroscopy (FTIR) spectra indicates the presence of characteristic bonds such as O–H stretching, C–H stretching, OH bending, and C–O–C stretching in both MCC1 and MCC2. Based on thermal analysis conducted using differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA), it was confirmed that MCC2 (275.0°C) melts at much lower temperature compared to MCC1 (342.04°C). MCC2 is also less thermally stable compared to MCC1 in terms of mass loss (%). In all, both MCC1 and MCC2 have different physicochemical properties based on the process of extraction and may have different applications. Based on their physicochemical characteristics, smaller MCC particles are known to be favored for wide variety of applications such as pharmaceutical excipients and impact factors such as tablet hardness, friability, and disintegration. © 2024 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.