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Optimal Design of Carbon-Based Polymer Nanocomposites Preparation Based on Response Surface Methodology

Response surface methodology (RSM) and central composite design (CCD) were used to improve the preparation of carbon nanotube and graphene (CNT-GN)-sensing unit composite materials in this study. Four independent variable factors (CNT content, GN content, mixing time, and curing temperature) were co...

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Autores principales: Yan, Shaoqiu, Tang, Ying, Bi, Gangping, Xiao, Bowen, He, Guotian, Lin, Yuanchang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10052088/
https://www.ncbi.nlm.nih.gov/pubmed/36987274
http://dx.doi.org/10.3390/polym15061494
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author Yan, Shaoqiu
Tang, Ying
Bi, Gangping
Xiao, Bowen
He, Guotian
Lin, Yuanchang
author_facet Yan, Shaoqiu
Tang, Ying
Bi, Gangping
Xiao, Bowen
He, Guotian
Lin, Yuanchang
author_sort Yan, Shaoqiu
collection PubMed
description Response surface methodology (RSM) and central composite design (CCD) were used to improve the preparation of carbon nanotube and graphene (CNT-GN)-sensing unit composite materials in this study. Four independent variable factors (CNT content, GN content, mixing time, and curing temperature) were controlled at five levels, and 30 samples were generated using the multivariate control analysis technique. On the basis of the experimental design, semi-empirical equations were developed and utilized to predict the sensitivity and compression modulus of the generated samples. The results reveal a strong correlation between the experimental and expected values of sensitivity and the compression modulus for the CNT-GN/RTV (room-temperature-vulcanized silicone rubber) polymer nanocomposites fabricated using different design strategies. The correlation coefficients for the sensitivity and compression modulus are [Formula: see text] and [Formula: see text] respectively. The ideal preparation parameters of the composite in the experimental range include a CNT content of 1.1 g, a GN content of 1.0 g, a mixing time of 15 min, and a curing temperature of 68.6 °C, according to theoretical predictions and experimental findings. At 0~30 kPa, the CNT-GN/RTV-sensing unit composite materials may reach a sensitivity of 0.385 kPa(−1) and a compressive modulus of 601.567 kPa. This provides a new idea for the preparation of flexible sensor cells and reduces the time and economic cost of experiments.
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spelling pubmed-100520882023-03-30 Optimal Design of Carbon-Based Polymer Nanocomposites Preparation Based on Response Surface Methodology Yan, Shaoqiu Tang, Ying Bi, Gangping Xiao, Bowen He, Guotian Lin, Yuanchang Polymers (Basel) Article Response surface methodology (RSM) and central composite design (CCD) were used to improve the preparation of carbon nanotube and graphene (CNT-GN)-sensing unit composite materials in this study. Four independent variable factors (CNT content, GN content, mixing time, and curing temperature) were controlled at five levels, and 30 samples were generated using the multivariate control analysis technique. On the basis of the experimental design, semi-empirical equations were developed and utilized to predict the sensitivity and compression modulus of the generated samples. The results reveal a strong correlation between the experimental and expected values of sensitivity and the compression modulus for the CNT-GN/RTV (room-temperature-vulcanized silicone rubber) polymer nanocomposites fabricated using different design strategies. The correlation coefficients for the sensitivity and compression modulus are [Formula: see text] and [Formula: see text] respectively. The ideal preparation parameters of the composite in the experimental range include a CNT content of 1.1 g, a GN content of 1.0 g, a mixing time of 15 min, and a curing temperature of 68.6 °C, according to theoretical predictions and experimental findings. At 0~30 kPa, the CNT-GN/RTV-sensing unit composite materials may reach a sensitivity of 0.385 kPa(−1) and a compressive modulus of 601.567 kPa. This provides a new idea for the preparation of flexible sensor cells and reduces the time and economic cost of experiments. MDPI 2023-03-17 /pmc/articles/PMC10052088/ /pubmed/36987274 http://dx.doi.org/10.3390/polym15061494 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yan, Shaoqiu
Tang, Ying
Bi, Gangping
Xiao, Bowen
He, Guotian
Lin, Yuanchang
Optimal Design of Carbon-Based Polymer Nanocomposites Preparation Based on Response Surface Methodology
title Optimal Design of Carbon-Based Polymer Nanocomposites Preparation Based on Response Surface Methodology
title_full Optimal Design of Carbon-Based Polymer Nanocomposites Preparation Based on Response Surface Methodology
title_fullStr Optimal Design of Carbon-Based Polymer Nanocomposites Preparation Based on Response Surface Methodology
title_full_unstemmed Optimal Design of Carbon-Based Polymer Nanocomposites Preparation Based on Response Surface Methodology
title_short Optimal Design of Carbon-Based Polymer Nanocomposites Preparation Based on Response Surface Methodology
title_sort optimal design of carbon-based polymer nanocomposites preparation based on response surface methodology
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10052088/
https://www.ncbi.nlm.nih.gov/pubmed/36987274
http://dx.doi.org/10.3390/polym15061494
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