Rice adulteration is a severe problem in agro-products and food regulatory agencies, suppliers, and consumers. In this study, to effectively distinguish whether high-quality rice is mixed with low-quality rice, detection and analysis of adulterated rice in five levels with different mixing proportions was conducted via terahertz spectroscopy and pattern recognition algorithms. Initially, samples were prepared and spectral data were acquired by using the terahertz transmission mode, and a principal component analysis (PCA) algorithm was applied to extract features from original spectrum information and reduce data dimensions. Subsequently, partial least squares-discriminant analysis (PLS-DA), support vector machine (SVM), and a back propagation neural network (BPNN) combined with the absorption spectra after different pretreatments, including standard normal variate (SNV) transformation, baseline correction (BC), and first derivative (1st derivative), were applied to establish the classification models. Results indicate that an SVM model employing the absorption spectra with a 1st derivative pretreatment exhibits the best discrimination ability, with an accuracy up to 97.33% in the prediction set. This result proves that terahertz spectroscopy combined with chemometric methods can be an effective tool to identify rice adulteration levels.

The doubly clamped microelectromechanical system (MEMS) beam resonators exhibit extremely high sensitivity to tiny changes in the resonance frequency owing to their high quality (Q-) factors, even at room temperature. Such a sensitive frequency-shift scheme is very attractive for fast and highly sensitive terahertz (THz) detection. The MEMS resonator absorbs THz radiation and induces a temperature rise, leading to a shift in its resonance frequency. This frequency shift is proportional to the amount of THz radiation absorbed by the resonator and can be detected and quantified, thereby allowing the THz radiation to be measured. In this review, we present an overview of the THz bolometer based on the doubly clamped MEMS beam resonators in the aspects of working principle, readout, detection speed, sensitivity, and attempts at improving the performance. This allows one to have a comprehensive view of such a novel THz detector.

We theoretically clarify the mechanism of the strain-tuning effect for control of the mechanical nonlinearity in doubly clamped MEMS beam resonators and experimentally demonstrate that nonlinearity can be effectively suppressed with a preloaded lattice-mismatch strain in the MEMS beam. Mechanical nonlinearity arises from the hardening- and softening-nonlinearity terms in the Duffing motion equation of the MEMS beam. By approaching the buckling condition of the MEMS beam, the substantially increased softening nonlinearity greatly compensates for the hardening nonlinearity, resulting in suppression of the total nonlinearity. Utilizing this knowledge, we fabricate ${\mathrm{In}}_x{\mathrm{Ga}}_{1-x}\mathrm{As}$ MEMS beams with a preloaded lattice-mismatch strain, which is achieved by adding a small amount (x = ∼0.4%) of indium to the $\mathrm{Ga}\mathrm{As}$ MEMS beam during wafer growth. The buckling condition in the experiment is achieved by carefully modulating the length of the ${\mathrm{In}}_x{\mathrm{Ga}}_{1-x}\mathrm{As}$ MEMS beams. As a result, mechanical nonlinearity is largely modulated from hardening to softening and reaches a quasizero value near the buckling condition, demonstrating the effectiveness of using lattice mismatch for controlling the mechanical nonlinearity of MEMS resonators.

Cantilever enhanced photoacoustic spectroscopy (CEPAS) technology improves the detection ability of weak gas photoacoustic signal effectively utilizing a micro-cantilever acoustic sensor instead of capacitive microphone, which can achieve highly sensitive detection of CO₂ and has great significance for environmental monitoring, industrial production control and regional carbon emission monitoring and other applications. A fiber-optic Fabry-Perot (F-P) sensor with a cantilever structure is designed in this work to overcome the disadvantage of the complication of traditional mechanical cantilever photoacoustic spectroscopy system. The photoacoustic spectroscopy system is established based on the resonance enhancement of the fiber cantilever acoustic sensor with a 2.0 μm distributed feedback (DFB) laser, which combines the technologies of wavelength modulation and second-harmonic detection for measuring CO₂ concentration. The experimental results show that the concentration calibration curve has a good correlation of 0.9765, and the detection limit of CO₂ concentration reaches 0.044×10^-6, which verifies the feasibility of the system for detecting atmospheric CO₂ concentration.