Evidence map›Paper›PMID 36501592›Full record

ArticlePolymers2022

Use of Fourier Series in X-ray Diffraction (XRD) Analysis and Fourier-Transform Infrared Spectroscopy (FTIR) for Estimation of Crystallinity in Cellulose from Different Sources.

Nicolás Montoya-Escobar, Daniel Ospina-Acero, Jorge Andrés Velásquez-Cock, Catalina Gómez-Hoyos, Angélica Serpa Guerra, Piedad Felisinda Gañan Rojo, Lina Maria Vélez Acosta, Juan Pablo Escobar, Natalia Correa-Hincapié, Omar Triana-Chávez and 2 more

Abstract read
In one paragraph

Article in Polymers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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  12. Enhancing Jabon (Polymers · 2025
    Article
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  18. Article
  19. Complexities related to the amorphous content of lactose carriers.International journal of pharmaceutics: X · 2023
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Nicolás Montoya-EscobarPrograma de Ingeniería en Nanotecnología, Universidad Pontificia Bolivariana, Circular 1_N_70-01, Medellín 050031, Colombia.ORCID 0000-0002-6451-3759
Daniel Ospina-AceroElectro Science Laboratory, Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH 43210, USA.
Jorge Andrés Velásquez-CockPrograma de Ingeniería en Nanotecnología, Universidad Pontificia Bolivariana, Circular 1_N_70-01, Medellín 050031, Colombia.
Catalina Gómez-HoyosPrograma de Ingeniería en Nanotecnología, Universidad Pontificia Bolivariana, Circular 1_N_70-01, Medellín 050031, Colombia.ORCID 0000-0003-3308-3722
Angélica Serpa GuerraFacultad de Ingeniería Agroindustrial, Universidad Pontificia Bolivariana, Circular 1_N_70-01, Medellín 050031, Colombia.
Piedad Felisinda Gañan RojoFacultad de Ingeniería Química, Universidad Pontificia Bolivariana, Circular 1_N_70-01, Medellín 050031, Colombia.ORCID 0000-0003-2596-2591
Lina Maria Vélez AcostaFacultad de Ingeniería Agroindustrial, Universidad Pontificia Bolivariana, Circular 1_N_70-01, Medellín 050031, Colombia.ORCID 0000-0002-7774-7378
Juan Pablo EscobarFacultad de Ingeniería de Sistemas, Universidad Pontificia Bolivariana, Circular 1_N_70-01, Medellín 050031, Colombia.
Natalia Correa-HincapiéGrupo Calidad, Metrología y Producción, Instituto Tecnológico Metropolitano, Medellín 050013, Colombia.ORCID 0000-0002-0967-3952
Omar Triana-ChávezGrupo de Biología y Control de Enfermedades Infecciosas (BCEI), Sede de Investigación Universitaria, Universidad de Antioquia, Medellín 050010, Colombia.ORCID 0000-0001-8031-0225
Robin Zuluaga GallegoFacultad de Ingeniería Agroindustrial, Universidad Pontificia Bolivariana, Circular 1_N_70-01, Medellín 050031, Colombia.ORCID 0000-0002-7039-0038
Pablo M StefaniInstituto de Investigaciones en Ciencia y Tecnología de Materiales (INTEMA), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Mar del Plata (UNMdP), Av. Colón 10850, Mar del Plata 7600, Argentina.ORCID 0000-0002-8140-4415

Funding

FONCYT PICT-2019-2672FONCYT PICT-2020-1003Gobernación de Antioquia 617-09/20-49Instituto Tecnológico Metropolitano 617-09/20-49Pontifical Bolivarian University 617-09/20-49University of Antioquia 617-09/20-49
6 · The paper itself

Abstract

Cellulose crystallinity can be described according to the crystal size and the crystallinity index (CI). In this research, using Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) methods, we studied the crystallinity of three different types of cellulose: banana rachis (BR), commercial cellulose (CS), and bacterial cellulose (BC). For each type of cellulose, we analyzed three different crystallization grades. These variations were obtained using three milling conditions: 6.5 h, 10 min, and unmilled (films). We developed a code in MATLAB software to perform deconvolution of the XRD data to estimate CI and full width at half-maximum (FWHM). For deconvolution, crystalline peaks were represented with Voigt functions, and a Fourier series fitted to the amorphous profile was used as the amorphous contribution, which allowed the contribution of the amorphous profile to be more effectively modeled. Comparisons based on the FTIR spectra and XRD results showed there were no compositional differences between the amorphous samples. However, changes associated with crystallinity were observed when the milling time was 10 min. The obtained CI (%) values show agreement with values reported in the literature and confirm the effectiveness of the method used in this work in predicting the crystallization aspects of cellulose samples.

Indexed as

cellulosecrystallinitycrystallinity indexFourier seriesinfrared spectroscopypeak deconvolutionX-ray diffraction

Identifiers

PMID36501592
PMCPMC9736003

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