Applications and Perspectives for the Use of Fibers via Machine Learning Assisted Data Mining - Part II

Aug 5, 2026

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This paper examines the substitution and enhancement of vegetable fibers as additives in polymeric matrices, emphasizing nanoparticle-assisted modification and its characterization and applications over 2011–2021. A machine-learning based artificial intelligence workflow using Vosviewer analyzes 3,000 articles from SCOPUS and ScienceDirect. Bibliometric and network results highlight trends in the expanding use of fibers from synthetic and vegetable origins, with growing attention in recent years toward health-related applications.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages11

Reading Time28 min

AccessFree to download

Introduction

Materials and Equipment

Methodology for Data Mining

Results and Discussion

Technical Notes Received 20/11/2023 . Revised 30/11/2023 . Accepted 15/12/2023 . Published 29/12/2023 . APPLICATIONS AND PERSPECTIVES FOR THE USE OF FIBERS VIA MACHINE LEARNING ASSISTED DATA MINING-part II Johny Chantre da Silvaa, Sérgio Thode Filhob, Juliano Elvis de Oliveirac and Fernando Gomes de Souza Jra a Institute of Macromolecules Professor Eloísa mano- IMA, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil, b Federal Institute of Rio de Janeiro, Rio de Janeiro, Brazil, c Department of Agriculture, Federal University of Lavras, Lavras, Brazil. Abstract: The use of vegetable fibers in place of synthetic fibers has been valued due to the wide applicability of these materials in the automotive, textile, packaging and construction industries This is due to the fact that they have properties such as: biodegradation, less abrasive, low density and excellent thermal, mechanical and acoustic properties. Thus, this document discusses the use of plant fibers as additives in polymeric matrices from a prospective analysis, via data mining, specific on the use of nanoparticles as additives in plant fibers and their characterizations and applications in the last 10 years (2011 to 2021) based on 3,000 articles made available in the SCOPUS and SCIENCE DIRECT databases. For this, an artificial intelligence algorithm, based on machine learning, implemented in the Vosviewer software was used. With it, it was observed the advance of the use of fibers of synthetic and vegetable origin, in recent years, focused on the field of health. Keywords: Modification of plant fibers. Machine learning. Nanoscale modification. Data mining. Artificial intelligence. aRio de Janeiro, RJ. , Brazil, e-mail: [ojopedroza@gmail.com](ojopedroza@gmail.com) bUniversidade Federal do Rio de Janeiro (UFRJ) Instituto de Macromoléculas Professora. Eloisa Mano (IMA), Rio de Janeiro, RJ. , Brazil, [e-mail:](e-mail: mldias@ima.ufrj.br)[ ](e-mail: mldias@ima.ufrj.br)[mldias@ima.ufrj.br](e-mail: mldias@ima.ufrj.br) 1. INTRODUCTION Due to the costs of producing synthetic fibers, related to reagents and their disposal in nature, studies on the use and application of natural fibers have grown in recent years6. Coconut fibers2 , coffee6 and sisal4,5 , among others, are used for various applications, due to their natural characteristics such as: thermal, mechanical resistance, low cost and density, besides the fact that they are biodegradable. With the studies of these fibers, some deficiencies related to the nature of these materials were observed as loss of their properties by contact with water and by low chemical support with polymeric matrices4,5,6 . These deficiencies stimulated scientists to improve the biochemical and physicochemical characteristics of these materials. Currently, such fibers can undergo varied modifications in order to ensure new properties to the material. An example for example is the surface modification of these fibers with nanoparticles, potentiating or adding new properties to these materials3. The natural fiber market has expanded in recent years to $121.42 billion in 2017, with a trend of reaching $398.00 billion in 20261. Based on this information, a bibliometric survey was carried out based on 3,000 articles associated with plant fibers and nanoparticles, specifically taken from a collection totaling 25,000 articles associated with fibers and nanoparticles. 2. MATERIALS AND EQUIPMENT Computer with internet access, access to Science Direct and Scopus databases , via intranet UFRJ / CAFe, Vosviewer Software and Microsoft Excel for table preparation. 1. METHODOLOGY FOR DATA MINING The articles used were obtained from the Science Direct and Scopus database, following the same methodology performed in part 1 of this article. In this work, the keywords "vegetable fibers and nanoparticles" were used in both databases in order to obtain the maximum number of articles (3,000) related to keywords in the period 20

FAQs

Why are researchers interested in using vegetable fibers instead of synthetic fibers?

Vegetable fibers are valued for biodegradability, low density, reduced abrasiveness, and strong thermal, mechanical, and acoustic properties. They are also used across automotive, textile, packaging, and construction industries.

How does the study perform data mining and analysis?

It retrieves articles from ScienceDirect and Scopus using the keywords “vegetable fibers and nanoparticles,” targeting 2011–2021 and a set of 3,000 articles. A machine-learning based AI approach in Vosviewer is used to analyze bibliometric patterns and networks.

What do the results suggest about research trends from 2011 to 2021?

The bibliometric network shows stronger interactions among several keyword clusters and identifies main “nodes” such as reinforcement- and model-related terms. The temporal overlay further reflects the evolution of the most recent keyword occurrences by cluster.

Aug 5, 2026

Upload by Maeve