Mechanical and morphological characterization of basalt/Cissus quadrangularis hybrid fiber reinforced polylactic acid composites

Author(s):  
A Arul Jeya Kumar ◽  
M Prakash

In today's scenario, most of the research works are carried out on the replacement of synthetic fibers using eco-friendly materials called natural fibers. Although there are many research findings in connection with natural fibers, in this work, a new combination of natural fiber having high biomedical potential is reinforced in the polymer composite. Three different weight fractions of polylactic acid, basalt, and Cissus quadrangularis fibers were melt mixed using twin-screw extruder named as PBCQ 1, PBCQ 2, and PBCQ 3. The mechanical, physical, and thermomechanical properties were studied by testing tensile, flexural, impact, hardness, water absorption, Fourier-transform infrared spectroscopy, and dynamic mechanical analysis of the injection-molded biomedical composite specimens prepared as per ASTM standards. It was noticed that the PBCQ 2 composite has the maximum elongation strength, bending strength, shear strength, and shore D hardness compared to other composites taken in this study. Water absorption of PBCQ 1 and PBCQ 2 composites are relatively less than PBCQ 3. The scanning electron microscopy micrograph of PBCQ composites shows tight bonding between the matrix and fibers. The adhesion of matrix and fibers was confirmed by Fourier-transform infrared spectroscopy graph, which indicates the stretching of molecular structure for the occurrence of O–H, C=O, and C–H links. The dynamic mechanical analysis curve of the PBCQ 2 composite indicates high storage modulus and less loss modulus compared to PBCQ 1 and PBCQ 3 due to the low weight percentage of basalt fiber in these composites.

2021 ◽  
Author(s):  
Shreyas Patankar ◽  
Ekaterina Vassilenko ◽  
Mathew Watkins ◽  
Anna Posacka ◽  
Peter Ross

<p>Microplastic pollution in oceans is among the global environmental concerns of our time. Emerging research on ocean environments indicates that microfibers, such as those originating from textiles, are some of the most commonly occurring type of microplastic contaminants. While Fourier-transform infrared spectroscopy (FTIR) is commonly used to identify and characterize pollutant samples obtained from the environment, this identification is challenging because infrared spectra of materials can be modified by exposure to the ocean, air, UV light, and other ambient conditions, in a process referred to as “weathering”. We report preliminary efforts in improving FTIR characterization of microplastics by building a library of infrared spectra of common textile fibers weathered under a selection of ambient conditions. Consumer textile materials including polyester, nylon, cotton, and other, were exposed to a selection of ambient conditions: ocean, air, and wastewater treatment stages, in a controlled weathering experiment. Infrared spectra were monitored for up to 52 weeks, with the resulting data illuminating on the environmental fate and longevity of synthetic and natural fibers. Spectral changes caused by weathering were found to depend strongly on both the composition of the material and the specific ambient conditions. This library of weathered material spectra is useful not only in easier identification of environmental microfibers, but also in helping us estimate the duration and manner of weathering that a given environmental microfiber may have experienced.</p>


2017 ◽  
Vol 24 (2) ◽  
pp. 299-309 ◽  
Author(s):  
Ludmila Vanharova ◽  
Marketa Julinova ◽  
Roman Slavik

AbstractThe research deals with biodegradation of films prepared from polyvinylpyrrolidone and polylactic acid (PVP/PLA). Biodegradation of PVP/PLA films was supported by the following additives: 1-methyl-2-pyrrolidone, 1-octyl-2-pyrrolidone, acrylamide and N-acetyl-L-phenylalanine according to the previous study. The films were prepared by a solvent casting technique. Biodegradation was observed using the respirometric method in different environments. The films subjected to biodegradation were analyzed by scanning electron microscopy and Fourier transform infrared spectroscopy. It was found that the films are substantially degraded, but not in the biological way; PVP was quickly removed in presence of water because of its easy solubility. In contrast, this fact could support biodegradation of PLA, which becomes more available for microorganisms when PVP leaves PLA matrix.


2018 ◽  
Vol 157 ◽  
pp. 07002
Author(s):  
Marcel Kohutiar ◽  
Mariana Pajtášová ◽  
Róbert Janík ◽  
Iveta Papučová ◽  
Jana Pagáčová ◽  
...  

The aim of given paper is to study selected polymers using dynamic mechanical analysis method (DMA). DMA is one of the most useful techniques for the study of the viscoelastic behaviour of thermoplastic polymers. In relation to DMA, an oscillatory stress and strain is applied to the material at specific frequencies and temperatures and based on this mentioned fact hereinbefore, the resulting changes after the loading in the material are measured. This technique allows detecting the melting temperature and the glass transition temperature of the thermoplastic materials. Furthermore, some spectroscopy techniques, such as energy dispersive X-ray spectroscopy (EDX) and infrared spectroscopy (IR), were also used for the investigation of the thermoplastics. The thermoplastics used for examination, namely polyethylene, polystyrene, polypropylene and polyethylene terephthalate, were gained from the waste of the packaging.


2020 ◽  
Vol 10 (21) ◽  
pp. 7470
Author(s):  
Sung-Uk Zhang

Polylactic acid (PLA) is the most common polymeric material in the 3D printing industry but degrades under harsh environmental conditions such as under exposure to sunlight, high-temperatures, water, soil, and bacteria. An understanding of degradation phenomena of PLA materials is critical to manufacturing robust products by using 3D printing technologies. The objective of this study is to evaluate four machine learning algorithms to classify the degree of thermal degradation of heat-treated PLA materials based on Fourier transform infrared spectroscopy (FTIR) data. In this study, 3D printed PLA specimens were subjected to high-temperatures for extended periods of time to simulate thermal degradation and subsequently examined by using two types of FTIR spectrometers: desktop and portable spectrometers. Classifiers created by multi-class logistic regression and multi-class neural networks were appropriate prediction models for these datasets.


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