The past two decades have seen an exponential growth of interest in one of the least explored region of the electromagnetic spectrum, the terahertz (THz) frequency band, ranging from to 0.1 to 10 THz. Once only the realm of astrophysicists studying the background radiation of the universe, THz waves have become little by little relevant in the most diverse fields, such as medical imaging, industrial inspection, remote sensing, fundamental science, and so on. Remarkably, THz wave radiation can be generated and detected by using ambient air as the source and the sensor. This is accomplished by creating plasma under the illumination of intense femtosecond laser fields. The integration of such a plasma source and sensor in THz time-domain techniques allows spectral measurements covering the whole THz gap (0.1 to 10 THz), further increasing the impact of this scientific tool in the study of the four states of matter.
In this review, the authors introduce a new paradigm for implementing THz plasma techniques. Specifically, we replaced the use of elongated plasmas, ranging from few mm to several cm, with sub-mm plasmas, which will be referred to as microplasmas, obtained by focusing ultrafast laser pulses with high numerical aperture optics (NA from 0.1 to 0.9).
The experimental study of the THz emission and detection from laser-induced plasmas of submillimeter size are presented. Regarding the microplasma source, one of the interesting phenomena is that the main direction of THz wave emission is almost orthogonal to the laser propagation direction, unlike that of elongated plasmas. Perhaps the most important achievement is the demonstration that laser pulse energies lower than 1 mJ are sufficient to generate measurable THz pulses from ambient air, thus reducing the required laser energy requirement of two orders of magnitude compared to the state of art. This significant decrease in the required laser energy will make plasma-based THz techniques more accessible to the scientific community, as well as opening new potential industrial applications.
Finally, experimental observations of THz radiation detection with microplasmas are also presented. As fully coherent detection was not achieved in this work, the results presented herein are to be considered a first step to understand the peculiarities involved in using the microplasma as a THz sensor.
Longitudinal twinning α-In2Se3 nanowires with the (10
Particulate matter with the diameter of less than 2.5 mm (PM2.5) is the most important causation of air pollution. In this study, PM2.5 samples were collected in three different environment including ordinary atmospheric environment, lampblack environment and the environment with an air conditioning exhaust fan, and analyzed by using terahertz time-domain spectroscopy (THz-TDS). The linear regression analysis and the principal component analysis (PCA) are used to identify PM2.5 samples collected in different environment. The results indicate that combining THz-TDS with statistical methods can serve as a contactless and efficient approach to identify air pollutants in different environment.
The plasma characteristics of carbon-doped glycidyl azide polymer (GAP) are investigated ablation by nanosecond laser pulses. For the GAP energetic liquid, a specific impulse of 840 s and an ablation efficiency up to 98% are obtained, which can be attributed to the low mass loss owing to the carbon doping. A comparison between the chemical energies shows that the carbon-doped GAP provides better propulsion than pure GAP. This indicates that even for an energetic liquid, an efficient approach to enhance the thrust performance is to reduce the splashing. High ablation thrust could be achieved at a low laser fluence and high carbon content.
Terahertz imaging is one of the forefront topics of imaging technology today. Denoising process is the key for improving the resolution of the terahertz holographic reconstructed image. Based on the fact that the weighted nuclear norm minimization (WNNM) method preserves the details of the reconstructed image well and the non-local mean (NLM) algorithm performs better in the removal of background noise, this paper proposes a new method in which the NLM algorithm is used to improve the WNNM method. The experimental observation and quantitative analysis of the denoising results prove that the new method has better denoising effect for the terahertz holographic reconstructed image.
Detection of small ships from an optical remote sensing image plays an essential role in military and civilian fields. However, it becomes more difficult if noise dominates. To solve this issue, a method based on a low-level vision model is proposed in this paper. A global channel, high-frequency channel, and low-frequency channel are introduced before applying discrete wavelet transform, and the improved extended contrast sensitivity function is constructed by self-adaptive center-surround contrast energy and a proposed function. The saliency image is achieved by the three-channel process after inverse discrete wavelet transform, whose coefficients are weighted by the improved extended contrast sensitivity function. Experimental results show that the proposed method outperforms all competing methods with higher precision, higher recall, and higher F-score, which are 100.00%, 90.59%, and 97.96%, respectively. Furthermore, our method is robust against noise and has great potential for providing more accurate target detection in engineering applications.
In this paper, ZnO/Nb2O5 core/shell nanorod arrays were synthesized and used as photoanodes for dye-sensitized solar cells (DSSCs). We first synthesized ZnO nanorod array on fluorine-doped tin oxide (FTO) glasses by a hydrothermal method, and then ZnO/Nb2O5 core/shell nanorod array was directly obtained via solvothermal reaction in NbCl5 solution. The scanning electron microscope (SEM) and transmission electron microscope (TEM) images revealed that the ZnO nanorods were uniformly wrapped by Nb2O5 shell layers with a thickness of 30–40 nm. Photovoltaic characterization showed that the device based on ZnO/Nb2O5 core/shell nanorod photoanode exhibited an improved efficiency of 1.995%, which was much higher than the efficiency of 0.856% for the DSSC based on bare ZnO nanorod photoanode. This proved that the photovoltaic performance of ZnO nanorods could be improved by wrapping with Nb2O5 shells.
The Er3+/Yb3+ co-doped phosphate (EYDP) glass waveguides operated at 1539 nm have been manufactured by using the implantation technique of carbon ions under the condition of 6.0 MeV energy and 5.0 × 1013 ions/cm2 fluence in this work. The ion implantation process was computed by means of the stopping and range of ions in matter. The dark-mode spectrum at 1539 nm of the waveguide was recorded by the method of the prism coupling measurement. The microscopic image of the fabricated structure was photographed by an optical microscope. It is the first step for the application of the waveguides on the base of EYDP glasses in optical-integrated photonic devices at near-infrared band.
A wavelength selection method for discrete wavelength combinations was developed based on equidistant combination-partial least squares (EC-PLS) and applied to a near-infrared (NIR) spectroscopic analysis of hemoglobin (Hb) in human peripheral blood samples. An allowable model set was established through EC-PLS on the basis of the sequence of the predicted error values. Then, the wavelengths that appeared in the allowable models were sorted, combined, and utilized for modeling, and the optimal number of wavelengths in the combinations was determined. The ideal discrete combination models were obtained by traversing the number of allowable models. The obtained optimal EC-PLS and discrete wavelength models contained 71 and 42 wavelengths, respectively. A simple and high-performance discrete model with 35 wavelengths was also established. The validation samples excluded from modeling were used to validate the three models. The root-mean-square errors for the NIR-predicted and clinically measured Hb values were 3.29, 2.86, and 2.90 g·L−1, respectively; the correlation coefficients, relative RMSEP, and ratios of performance to deviation were 0.980, 0.983, and 0.981; 2.7%, 2.3%, and 2.4%; and 4.6, 5.3, and 5.2, respectively. The three models achieved high prediction accuracy. Among them, the optimal discrete combination model performed the best and was the most effective in enhancing prediction performance and removing redundant wavelengths. The proposed optimization method for discrete wavelength combinations is applicable to NIR spectroscopic analyses of complex samples and can improve prediction performance. The proposed wavelength models can be utilized to design dedicated spectrometers for Hb and can provide a valuable reference for non-invasive Hb detection.