Terahertz optical properties of wood-plastic composites

Opal-based terahertz optical elements fabricated by self-assembly of porous SiO2 nanoparticles

In this paper, we study artificial opals as a promising material platform for terahertz (THz) optics. Materials were synthesized using self-assembly of porous SiO₂ nanoparticles and annealing at different temperatures to further tune their optical properties. Two distinct approaches for the fabrication of bulk THz optics from these novel materials were considered. First, THz cylindrical lenses of identical geometry but different refractive indices and focal lengths were produced using standard mechanical processing of opals, in order to highlight their compatibility with conventional technologies of bulk optics fabrication. Second, a THz axicone was made via direct sedimentation of aqueous colloidal suspension of SiO₂ nanoparticles in the mold of geometry inverse to that of a desired optical shape, followed by annealing and polishing. The second approach has an advantage of being considerably less labor intensive, while capable of obtaining optical elements of complex geometries. Thus fabricated bulk THz optical elements were studied experimentally using continuous-wave THz imaging, and the results were compared with 2D and 3D numerical predictions based on the finite-difference time-domain and finite-element frequency-domain methods. Our findings highlight technological robustness of the developed THz optical material platform and, thus, open the door for creating a variety of bulk THz optical elements of complex shapes and widely-tunable optical performance.

Thin thermally grown oxide thickness detection in thermal barrier coatings based on SWT-BP neural network algorithm and terahertz technology

Terahertz time-domain spectroscopy is a contactless and nondestructive testing technique that is often used to measure the thickness of layered materials. However, the technique presents limited thickness detection resolution, especially in the thin thermally grown oxide (TGO) of thermal barrier coatings whose thickness is below 30 µm. In this study, an SWT-BP algorithm combining a stationary wavelet transform (SWT) and a backpropagation (BP) neural network was proposed, and the regression coefficient of SWT-detailed results was 0.92. The prediction results were in good agreement with the real-time results; it demonstrated that the proposed algorithm was able to achieve a thickness prediction of up to 1-29 µm of the TGO. The proposed algorithm is suitable for thin thickness detection of the TGO.