Numerical Simulation of Nonlinear Response of Nanodielectrics and Non-Destructive Evaluation of Agglomeration Degree
Qiu Yonglin1, Zhang Shuo1, Cheng Li1, Wang Hanqing1,2
1. State Key Laboratory of Power Transmission Equipment Technology Chongqing University Chongqing 400044 China; 2. Contemporary Amperex Future Energy Research Institute (Shanghai) Limited Shanghai 201109 China
Abstract：Doped nanoparticles can effectively enhance the electrical properties of nanodielectrics; however, the degree of agglomeration of particles in the matrix significantly influences the modification effect. At present, microscopic imaging is predominantly employed to evaluate the degree of nanodielectric particle agglomeration; however, this method is time-consuming and costly for a single measurement, offers a highly limited observation area, and may damage the material under investigation. Nonlinear ultrasound enables the detection of micro- and nano-defects in materials by detecting nonlinear changes in stress-strain and is a potential technique for assessing the degree of particle agglomeration. This paper investigates the origin of the nonlinear response of nanodielectrics and employ nonlinear ultrasound technology for assessing nanodielectric particle dispersion. The findings indicate that the equivalent particle size inversion results obtained through nonlinear ultrasound technology exhibit an error margin of 3%~6% compared to the particle size statistical results from the scanning electron microscope (SEM). Furthermore, nonlinear ultrasound technology facilitates a rapid, comprehensive, and nondestructive evaluation of the degree of nanodielectric particle agglomeration. An agglomerated interfacial mismatch model was initially developed, employing the interfacial mismatch coefficient δ to analogously describe the degree of particle agglomeration. On this basis, an ontological model of the nonlinear response of nanodielectrics is derived by combining the nonlinear ultrasonic wave motion equation to quantitatively solve the nonlinear response of nanodielectrics introduced due to the particle agglomeration interface. Subsequently, a simplified two-dimensional acoustic model for SiO2/epoxy resin (EP) featuring varying degrees of agglomeration was created using COMSOL software's partial differential equation module, to validate the nanodielectric nonlinear response model, and the simulation results demonstrate that the second-order nonlinear coefficient β escalates with the degree of particle agglomeration. Combined with the simulation model, the optimal interval of ultrasonic excitation signal frequency parameter is 0.1~5 MHz, and the optimal amplitude parameter is 70 nm, which provides a theoretical basis for the construction of the subsequent experimental platform. Ultimately, three SiO2/EP samples with different dispersibility were prepared by controlling the ultrasonic dispersion treatment time. The nonlinear ultrasound experimental setup was established, and the samples underwent testing using in atomic force microscopy (AFM), SEM, and nonlinear ultrasound. The AFM test results indicate that the stress-strain hysteresis in the dispersed particle-substrate interface region is negligible, with no additional nonlinearity introduced. In the agglomerated particle-substrate interface region, the stress-strain hysteresis is significant, with a notable increase in the nonlinear coefficient, highlighting the agglomeration interface as the primary source of nonlinearity in nanodielectrics. SEM and nonlinear ultrasound test outcomes reveal that the degree of agglomeration in the three samples escalates as the ultrasonic dispersion treatment time decreases, with a concurrent increase in the nonlinear coefficient. Utilizing the nonlinear coefficient and in conjunction with the nanodielectrics' nonlinear response model, the equivalent particle size of agglomerates can be quantitatively determined. The test outcomes demonstrate that the equivalent particle size determined by nonlinear ultrasound technology exhibits an error margin of 2.75% to 5.2% compared to SEM particle size statistics. Furthermore, this method offers the benefits of speed, comprehensiveness, and non-destructive evaluation, presenting a novel approach for assessing nanodielectric dispersion.
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2025, Vol. 40 
