Suzhen Liu

The continuous monitoring of polymer gelation kinetics is important in engineering. As traditional characterization techniques inevitably disturb the fragile architectures of evolving matrices, high-frequency ultrasonic spectroscopy as a non-destructive alternative is increasing exploited to conduct perfect monitoring. This review establishes a comprehensive mathematical and physical framework that maps raw, experimental acoustic parameters directly onto dynamic macromolecular network topologies. (1) It evaluates the theoretical foundations bridging wave propagation mechanics and polymer rheology, analyzing how longitudinal moduli (M*) diverge from low-frequency shear parameters (G*) due to solvent compressibility and frequency-dependent observation windows. (2) It decodes how structural relaxation timescales and interfacial boundary dynamics dictate acoustic velocity curves and asymmetric attenuation anomalies by analyzing the acoustic signatures across covalent, physical and organic–inorganic hybrid networks. (3) It evaluates the state of multiscale computational modeling, from the principle of molecular dynamics theorems and finite volume element bonds to a method for extracting real-time mesh dimensions. (4) It discusses the technical barriers including the high-attenuation barrier as well as the emerging engineering breakthroughs like coded signal excitation. Finally, it outlines a predictive pipeline intended to change ultrasonic monitoring from a laboratory characterization method to an automated monitoring framework for gel manufacturing.

State of Health (SOH) serves as a key metric in assessing the performance of lithium-ion batteries. It is challenging for a single sensing signal to fully characterize the multi-physics evolution characteristics during battery degradation, which limits the accuracy and robustness of SOH estimates. Therefore, a lithium-ion battery SOH estimate method combining electrical and ultrasonic features with a frequency-enhanced decomposed Transformer (FEDformer) is proposed. To begin with, a multi-condition battery aging dataset is constructed through experiments, comprising electrical and ultrasonic signal data from 7828 cycles. Subsequently, 20 electrical and ultrasonic features are extracted from multiple perspectives, and 12 strongly correlated features are selected via the Spearman correlation coefficient. Finally, the FEDformer is employed to establish the SOH estimate model, where the accuracy, robustness, and generalization of the SOH estimates are comparatively analyzed across different input features, models, and cross-aging conditions. The results demonstrate that, compared to using electrical features alone, the combined ultrasonic features improve the estimation performance by more than 40% on average. Furthermore, in the cross-aging datasets, the mean absolute error and root mean square error of the SOH estimates are 0.52% and 0.63%, respectively, validating the robustness and generalization capability of the proposed method.

State-of-charge (SOC) and state-of-health (SOH) of lithium-ion batteries are critical parameters in battery management systems, directly impacting the driving range, performance stability, and safety of electric vehicles. To improve the accuracy and stability of SOC and SOH estimation simultaneously, this paper proposes a joint estimation method with constant-current bias compensation. First, based on a second-order RC equivalent circuit model, a constant-current bias compensation term is introduced into the Kalman filter framework. The estimation accuracy and robustness of SOC are validated under multiple operating conditions and noise levels. Then, a model integrating Transformer and gated recurrent unit is constructed. The fata morgana algorithm (FATA) is adopted for hyperparameter optimization. Ablation studies and multi-model comparative experiments are conducted to verify the model’s accuracy. Finally, capacity correction is performed using SOH results. By combining current bias compensation and precise temporal features extracted from aging data, joint estimation of SOC and SOH is achieved. Results show that after introducing current bias compensation and aging-based capacity correction, the accumulated SOC estimation error is reduced by more than 10%, while SOH estimation achieves a MAPE below 0.90% and an RMSPE below 1.10%. The proposed joint method is thus verified to be accurate and practical.

A novel multi-modal sensitivity analysis framework is proposed for electrochemical models of lithium-ion battery, integrating time-domain constant-current discharge data with linear and second-order nonlinear impedance spectroscopy data to improve battery model parameter identifiability. By analyzing 26 parameters of a commercial NMC 811 cell (NMC/graphite), we demonstrate that frequency-domain analysis, particularly through the first-ever implementation of second-order nonlinear electrochemical impedance spectroscopy in battery parameter studies, significantly enhances sensitivity quantification capabilities. The framework extends the Doyle-Fuller-Newman pseudo-two-dimensional model deriving frequency-dependent governing equations via Maclaurin/Fourier expansions, which are validated with impedance spectroscopy. Parameter ranges were constrained by experimental calibration, rather than arbitrary intervals, to prevent misleading sensitivity conclusions. The results show that while time-domain methods captured only capacity-related parameters, the frequency-domain approaches improved the identifiability of 14 critical parameters, such as solid-phase diffusion coefficients, double-layer capacitances, and reaction rate constants. Moreover, low-sensitivity parameters such as electrode area and Bruggeman coefficients achieve measurable sensitivity through the nonlinear impedance analysis. The proposed methodology not only quantifies parameter sensitivity but also provides a guideline for developing advanced, multi-modal parameter identification frameworks.

The paper presents the possibilities to estimate 304 steel plate’s plastic deformation using spectral analysis of the amplitude of difference and sum frequencies resulting from mixing of two Lamb waves with different frequencies. An electromagnetic acoustic transducer (EMAT) is used for the excitation of Lamb waves. The numerical modelling of the results of Lamb wave interference in a plate under tensile deformation is carried out; a comprehensive nonlinear factor is proposed and its sensitivity to the tensile deformation has been evaluated. Experimental verification of the modelling results is carried out. The experimental results show that this factor can be used to evaluate 304 steel plate’s tensile deformation quantitatively. This evaluation can eliminate the redundancy between difference frequency nonlinear parameter and sum frequency nonlinear parameter, as well as, improve the complementarity between the two parameters.

Due to the high magnetic flux density at the edge of the magnet, the narrow-magnet Electromagnetic Acoustic Transducer can excite the ultrasonic wave with a larger amplitude than the conventional EMAT, but the waveform of the former is distorted. This paper presents a new focused EMAT design with a narrow magnet, which can both enhance the ultrasonic A0-Lamb signal and correct the distorted waveform. A synthesis equation of the ultrasonic signals based on the contribution of the in-plane (IP) and out-of-plane (OP) components of the magnet field is proposed to analyze the mechanism of the waveform distortion. The distorted wave is corrected by an uneven split-wires arrangement strategy. The EMAT employs a sector-shaped narrow magnet and a set of focused meander-line coils containing uneven split wires, for generating a 1MHz focused A0-Lamb wave in an aluminum plate. A three-dimensional finite element model of the EMAT is established using COMSOL Multiphysics to perform numerical simulations, and the effectiveness of the EMAT design is verified. The experimental results show that the EMAT not only corrects the signal distortion due to the narrow magnet and suppresses its side lobes, but also enlarges the amplitude of the A0-Lamb wave by 55.6% under the same magnetic flux density when compared with conventional EMAT.

A plate with varying thickness (PWVT) is a common structure in engineering and the demand for its early damage detection is strong. In this paper, the distribution of plastic strain in PWVT subjected to uniaxial tension was studied and it proposed that the nonlinear parameter distributed linearly. Based on this assumption the wave equation in damaged PWVT was solved and the model of ultrasonic nonlinear response was established. The model showed that when the plastic deformation kept constant, A ₂ / A ₁ ² increased quadratically with propagation and when the propagation distance kept constant, A ₂ / A ₁ ² was proportional to the plastic deformation level. A ₂ / A ₁ ² carried the damage information of PWVT. A detection platform was built in simulation and laboratory respectively to investigate the ultrasonic nonlinearity in damaged PWVT. The simulation and experimental results were in good agreement with the model, which indicated that the model could accurately describe the behavior of ultrasound propagating in PWVT.

In ultrasonic non-destructive testing technology, the method to detect the stress of metal plates using longitudinal critically refracted waves (LCR) is increasingly developing, in which the calculation of acoustoelastic coefficient of the metal plate is indispensable. However, due to the influence of the metallic material’s in-service environment on acoustoelastic coefficient, the existing calculation method of the acoustoelastic coefficient cannot meet the engineering requirements. Therefore, an inline measurement method based on electromagnetic loading is proposed in this paper. The calculation formula for the inline measurement of acoustoelastic coefficient is derived. An electromagnetic loading experimental platform is designed, including an electromagnetic loading module, an ultrasonic detecting module, and a delay control module. The loading test of a 1060 aluminum plate is carried out using the designed platform. The flight time of LCR waves is measured experimentally and used in the calculation formula of acoustoelastic coefficient. The experimental results of acoustoelastic coefficient meet the accuracy requirement of less than 5%, which can be used for stress measurement. So, the inline measurement method of acoustoelastic coefficient proposed in this paper is feasible.