Components Analysis of Biochar Based on Near Infrared Spectroscopy Technology

Rapid assessment of residual solvent content in the TEGDN dual-base propellants by near-infrared reflectance spectroscopy

Excessive residual solvent (RS) levels in triethyleneglycol dinitrate (TEGDN) dual-base propellants can significantly impair combustion performance. This work aimed to develop a rapid and accurate model for detecting the RS content in the TEGDN dual-base propellants using near-infrared (NIR) spectroscopy in the reflectance mode. The optimal wavelength range for modelling, spanning from 1124.9-1230.2 nm and 1335.5-1527.5 nm, was identified based on absorption peaks characteristic of TEGDN dual-base propellant samples and RS. To enhance the quality of the data, we determined optimal window sizes for pre-processing methods: derivative pre-processing and Savitzky-Golay (S-G) smoothing pre-processing. After evaluating the performance of different pre-treatment methods, we found that the model employing multiple scattering corrections (MSC) in conjunction with first-order derivative (FD) pre-processing demonstrated superior results. The partial least squares (PLS) method was used to build the RS model with an optimal number of factors of 6. For the developed RS model, the root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) were 0.019 and 0.024, respectively. The determination coefficient of calibration (Rc2) and the determination coefficient of cross-validation (Rcv2) were 0.968 and 0.952, respectively. In assessing the validation set using the developed model, we observed a root mean square error of prediction (RMSEP) of 0.025 and a determination coefficient of prediction (Rp2) of 0.958. Importantly, the relative error between the predicted values obtained through the NIR method and the measured values from the reference method consistently remained below 2 % under all circumstances. Consequently, the NIR-based RS model developed in this study offers a rapid and efficient means of detecting RS content in TEGDN dual-base propellants, facilitating judgment regarding the qualification of RS content.

Quantitative Inversion of Fixed Carbon Content in Coal Gangue by Thermal Infrared Spectral Data

Fixed carbon content is an important factor in measuring the carbon content of gangue, which is important for monitoring the spontaneous combustion of gangue and reusing coal gangue resources. Although traditional measurement methods of fixed carbon content, such as chemical tests, can achieve high accuracy, meeting the actual needs of mines via these tests is difficult because the measurement process is time consuming and costly and requires professional input. In this paper, we obtained the thermal infrared spectrum of coal gangue and developed a new spectral index to achieve the automated quantification of fixed carbon content. Thermal infrared spectroscopy analyses of 42 gangue and three coal samples were performed using a Turbo FT thermal infrared spectrometer. Then, the ratio index (RI), difference index (DI) and normalized difference index (NDI) were defined based on the spectral characteristics. The correlation coefficient between the spectral index and the thermal infrared spectrum was calculated, and a regression model was established by selecting the optimal spectral DI. The model prediction results were verified by a ten times 5-fold cross-validation method. The results showed that the mean error of the proposed method is 5.00%, and the root mean square error is 6.70. For comparison, the fixed carbon content was further predicted by another four methods, according to the spectral depth H, spectral area A, the random forest and support vector machine algorithms. The predicted accuracy calculated by the proposed method was the best among the five methods. Therefore, this model can be applied to predict the fixed carbon content of coal gangue in coal mines and can help guide mine safety and environmental protection, and it presents the advantages of being economic, rapid and efficient.

A Trace C₂H₂ Sensor Based on an Absorption Spectrum Technique Using a Mid-Infrared Interband Cascade Laser

In this study, tunable diode laser absorption spectroscopy (TDLAS) combined with wavelength modulation spectroscopy (WMS) was used to develop a trace C₂H₂ sensor based on the principle of gas absorption spectroscopy. The core of this sensor is an interband cascade laser that releases wavelength locks to the best absorption line of C₂H₂ at 3305 cm⁻¹ (3026 nm) using a driving current and a working temperature control. As the detected result was influenced by 1/f noise caused by the laser or external environmental factors, the TDLAS-WMS technology was used to suppress the 1/f noise effectively, to obtain a better minimum detection limit (MDL) performance. The experimental results using C₂H₂ gas with five different concentrations show a good linear relationship between the peak value of the second harmonic signal and the gas concentration, with a linearity of 0.9987 and detection accuracy of 0.4%. In total, 1 ppmv of C₂H₂ gas sample was used for a 2 h observation experiment. The data show that the MDL is low as 1 ppbv at an integration time of 63 s. In addition, the sensor can be realized by changing the wavelength of the laser to detect a variety of gases, which shows the flexibility and practicability of the proposed sensor.