Citation: Bi, G.; Xiao, B.; Lin, Y.; Yan,
S.; Tang, Y.; He, S.; Shang, M.; He, G.
Modeling and Optimization of
Sensitivity and Creep for
Multi-Component Sensing Materials.
Nanomaterials 2023, 13, 298. https://
doi.org/10.3390/nano13020298
Academic Editors: Antonios
Kelarakis and Mikhael Bechelany
Received: 11 November 2022
Revised: 28 December 2022
Accepted: 4 January 2023
Published: 11 January 2023
Copyright: © 2023 by the authors.
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/).
Article
Modeling and Optimization of Sensitivity and Creep for
Multi-Component Sensing Materials
Gangping Bi
1,2,3,†
, Bowen Xiao
1,3,4,†
, Yuanchang Lin
1,3,
*, Shaoqiu Yan
1,2,3
, Ying Tang
1,2,3
, Songxiying He
3
,
Mingsheng Shang
1
and Guotian He
1,3,
*
1
Chongqing Institute of Green Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
2
College of Mechanical Engineering, Chongqing University of Technology, Chongqing 400054, China
3
Chongqing Key Laboratory of Artificial Intelligence and Service Robot Control Technology,
Chongqing Institute of Green Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
4
Chongqing School, College of Artificial Intelligence, University of Chinese Academy of Sciences,
Chongqing 400020, China
* Correspondence: lyc@cigit.ac.cn (Y.L.); heguotian@cigit.ac.cn (G.H.)
† These authors contributed equally to this work.
Abstract:
Pressure sensors urgently need high-performance sensing materials in order to be de-
veloped further. Sensitivity and creep are regarded as two key indices for assessing a sensor’s
performance. For the design and optimization of sensing materials, an accurate estimation of the
impact of several parameters on sensitivity and creep is essential. In this study, sensitivity and creep
were predicted using the response surface methodology (RSM) and support vector regression (SVR),
respectively. The input parameters were the concentrations of nickel (Ni) particles, multiwalled
carbon nanotubes (MWCNTs), and multilayer graphene (MLG), as well as the magnetic field intensity
(B). According to statistical measures, the SVR model exhibited a greater level of predictability and
accuracy. The non-dominated sorting genetic-II algorithm (NSGA-II) was used to generate the Pareto-
optimal fronts, and decision-making was used to determine the final optimal solution. With these
conditions, the optimized results revealed an improved performance compared to the earlier study,
with an average sensitivity of 0.059 kPa
−1
in the pressure range of 0–16 kPa and a creep of 0.0325,
which showed better sensitivity in a wider range compared to previous work. The theoretical sensi-
tivity and creep were relatively similar to the actual values, with relative deviations of 0.317% and
0.307% after simulation and experimental verification. Future research for transducer performance
optimization can make use of the provided methodology because it is representative.
Keywords: RSM; SVR; NSGA-II; MWCNTs; MLG; Ni; magnetic field; sensitivity; creep
1. Introduction
Due to their potential applications in a variety of industries, including the aviation,
space, chemical, automotive, and biomedicine industries [
1
–
4
], polymer nanocomposites
have become a hot topic of study. Conducting polymer nanocomposites are used in nu-
merous sensor applications to achieve intelligence, informationalization, and the future
networks [
5
]. Performance characteristics of sensors include sensitivity, creep, repeatability,
hysteresis [
6
], etc. Sensitivity and creep have become the two key metrics affecting the per-
formance of sensors, since they influence measurement accuracy and stability, respectively.
However, the fabrication of materials for outstanding sensitivity and creep resistance is
heavily constrained by the complexity of the sensing system.
A promising method for enhancing the sensitivity and creep resistance has been identified
as properly adjusting the choice of materials and the reasonable ratio. For a piezo-resistive tactile
sensor, conductive filler particles are typically chosen from materials with the same dimensions,
such as Ni (zero dimensions), CNT (one dimension), MLG (two dimensions), and others. High
sensitivity and creep resistance for sensors have been the focus of an intense research effort.
Nanomaterials 2023, 13, 298. https://doi.org/10.3390/nano13020298 https://www.mdpi.com/journal/nanomaterials
