Modeling and Optimization of Sensitivity and Creep for Multi-Component Sensing Materials.

ABSTRACT: Pressure sensors urgently need high-performance sensing materials in order to be developed 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-dominat

SUBMITTER: Bi G 

PROVIDER: S-EPMC9862774 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature