Development of functionalized nanocrystalline cellulose-based polyelectrolytes with high water uptake

Rahman, Mohammad Motiur; Howlader, A. Hasan; Rahman, Ehsanur; Roy, Hridoy; Hosen, Mohammad Mozammal; Rahman, Md. Mahbubur; Sarkar, Stephen Don; Roy, Chanchal K.; Imran, Abu Bin; Firoz, Shakhawat H.

doi:10.1038/s41428-021-00483-1

Cited by 5 publications

(5 citation statements)

References 48 publications

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“…The surfaces often form topological features (holes and voids), while persistence diagrams and “barcodes” show how topological invariants depend on spatial resolution over varying length scales. Horizontal and vertical features a prevalent in images over features inclined under arbitrary angles. ,, The randomly oriented brightness gradient leads to the “primary circle” in the data space. In contrast, the vertical and horizontal features lead to two nonintersecting secondary circles being equivalent topologically to the Klein bottle surface.…”

Section: Resultsmentioning

confidence: 99%

“…As opposed to that, short barcode lines or points close to the diagonal at the persistence diagram represent features that only exist for a short range of the proximity radii and are likely caused by noise. 29,36 The 3 × 3 submatrices or patches of the roughness profiles for samples were investigated to study anisotropy. Statistics of the locations of the minimum and maximum values are presented in Figures S8−S10.…”

Section: Many Surfaces Have An Exponentially Decaying Acf C( ) Exp( ) =mentioning

confidence: 99%

“…Horizontal and vertical features a prevalent in images over features inclined under arbitrary angles. 29,36,37 The randomly oriented brightness gradient leads to the "primary circle" in the data space. In contrast, the vertical and horizontal features lead to two nonintersecting secondary circles being equivalent topologically to the Klein bottle surface.…”

Section: Many Surfaces Have An Exponentially Decaying Acf C( ) Exp( ) =mentioning

confidence: 99%

“…Long lines at barcode diagrams (H 1 and H 2 ) or points away from the diagonal at persistence diagrams represent stable features at a significant range of the proximity radii, so they more objectively characterize the data set. As opposed to that, short barcode lines or points close to the diagonal at the persistence diagram represent features that only exist for a short range of the proximity radii and are likely caused by noise.29,36 The 3 × 3 submatrices or patches of the roughness profiles for samples were investigated to study anisotropy. Statistics of the locations of the minimum and maximum values are presented in Figures S8−S10.…”

mentioning

confidence: 99%

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Topological Data Analysis of Nanoscale Roughness of Layer-by-Layer Polyelectrolyte Samples Using Machine Learning

Aglikov,

Aliev,

Zhukov

et al. 2023

ACS Appl. Electron. Mater.

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The surface roughness of layer-by-layer (LbL) polyelectrolytes is studied by atomic force microscopy (AFM) and analyzed with novel methods including topological data analysis (TDA) and machine learning (ML) to correlate multiscale roughness with the number of bilayers and to recognize the types of polyelectrolytes (PEs). LbL PEs composed of one to four bilayers of ( 1) polyethylenimine (PEI)/poly(sodium 4-styrenesulfonate) (PSS), (2) PEI/poly(acrylic acid) (PAA), and (3) PEI/ MXene rigid flakes are deposited on a smooth silicon wafer. With a growing number of bilayers, the roughness changes from a smooth surface to an equilibrium rough profile. The AFM study of the surface morphology demonstrates that surface roughness is multiscale, with smaller features imposed on larger ones. Roughness data is filtered from measurement resolution artifacts, and several methods are applied: correlation length, statistics of the distribution of extremes in trimmed images, and TDA barcodes and persistence diagrams of simplexes in 8D data space. An ML algorithm is used to determine the number of bilayers in a PE. Roughness analysis indicates a gradual transition from a smooth to a rough surface with saturation at three to four bilayers and the existence of multiscale roughness invariance.

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Section: Resultsmentioning

confidence: 99%

Section: Many Surfaces Have An Exponentially Decaying Acf C( ) Exp( ) =mentioning

confidence: 99%

Section: Many Surfaces Have An Exponentially Decaying Acf C( ) Exp( ) =mentioning

confidence: 99%

mentioning

confidence: 99%

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Topological Data Analysis of Nanoscale Roughness of Layer-by-Layer Polyelectrolyte Samples Using Machine Learning

Aglikov,

Aliev,

Zhukov

et al. 2023

ACS Appl. Electron. Mater.

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“…The DCNC was prepared by the two-step selective oxidation, according to a method described earlier [7]. Briefly, 100 mL of 63.5 % (w/w) H2SO4 was poured in a 500 mL round bottom flask and MCC was mixed with the solution.…”

Section: Preparation Of the Adsorbentsmentioning

confidence: 99%

Encapsulation of Industrial Cationic Pollutants from Aqueous Solution by Nanocrystalline Cellulose and It’s Modified Forms

Roy¹,

Rahman²,

Tarek³

et al. 2021

Proceedings of International Exchange and Innovation Conference on Engineering &Amp; Sciences (IEICES)

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Adsorbents based on nanocrystalline cellulose (NCC) were synthesized by two steps selective functionalization at C-2, C-3 position of glucose moiety/structure resulting in an intermediate product, di-aldehyde nanocrystalline cellulose (DANC) and final product, di-carboxylate nanocrystalline cellulose (DCNC). The success of functionalization reaction was confirmed by FTIR and SEM. The removal of basic blue 41 was then investigated by varying process parameters such as initial solution pH, contact time and initial dye concentration. The adsorption kinetics were investigated using pseudo 1 st and pseudo 2 nd -order model; which fitted well to the later one. Meanwhile, adsorption isotherm study predicted monolayer adsorption mechanism following the Langmuir model with a calculated maximum adsorption capacity of 446.19 mg/L for DCNC, which was much higher compared to DANC and NCC. The reusability studies configured that DCNC can be reused at least 5 cycles without losing significant efficiency. These findings prefigure that DCNC is an excellent biodegradable adsorbent.

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Characterization of sodium carboxymethyl cellulose/calcium alginate scaffold loaded with curcumin in skin tissue engineering

Rezaei

Nemati

Mehrabani

et al. 2022

J of Applied Polymer Sci

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Applying biological macromolecule like curcumin (CUC) has gained considerable attention for the anti-inflammatory, antioxidant, antimicrobial and antitumor properties. Therefore, this study was carried out to characterize carboxymethylcellulose/ calcium alginate (CMC/CA) scaffold loaded with CUC in skin tissue engineering. To observe the structural, mechanical, degradability, biological and antibacterial effect of CUC, it was loaded in a cellulose-based electrospinning scaffold of sodium CMC (SCMC) with CA. The addition of CUC increased the fiber diameter to 504 ± 83, and 522 ± 25 nm in 3% and 5% of CUC concentrations, respectively. The elasticity of the scaffold was enhanced, while the scaffold strength was decreased slightly. The inhibitory zone in the scaffold containing CUC denoted to its antibacterial properties. In addition, the cell viability, proliferation and attachment to the electrospun scaffolds were increased. Utilization of CUC-loaded materials can play an important role in anti-bacterial performance of the scaffold. Although mechanical properties of SCMC may slightly decreased during the loading process, but the morphological, chemical, and biological properties were improved. It seems that applying electrospinning technique and CUC incorporation in fabricated scaffolds can be a promising choice in skin tissue engineering when antibacterial properties are also targeted in conjunction with the tensile strength.

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Development of functionalized nanocrystalline cellulose-based polyelectrolytes with high water uptake

Cited by 5 publications

References 48 publications

Topological Data Analysis of Nanoscale Roughness of Layer-by-Layer Polyelectrolyte Samples Using Machine Learning

Topological Data Analysis of Nanoscale Roughness of Layer-by-Layer Polyelectrolyte Samples Using Machine Learning

Encapsulation of Industrial Cationic Pollutants from Aqueous Solution by Nanocrystalline Cellulose and It’s Modified Forms

Characterization of sodium carboxymethyl cellulose/calcium alginate scaffold loaded with curcumin in skin tissue engineering

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