The synthesis of organoselenium compounds through C–Se bond-forming has attracted immense attention due to their biological values and extensive pharmaceutical applications. As a result, diverse ...selenating reagents have been developed over the past few decades for this purpose. In particular, elemental selenium (Se), with the advantages of being non-toxic, odorless and chemically stable, has gained numerous interests as it showed great potentials for the formation of variously valuable organoseleniums via direct incorporation of Se atom into target molecules in a simple way. Moreover, direct C–H bond selenation with elemental Se has been considered as a highly atom-economic method to C–Se bond formation because it avoided substrate pre-activation. In view of the importance of organoselenium compounds, this review highlights the recent advances in organic synthesis involving elemental Se since 2002, which would be useful for researchers in the learning of Se for organic reactions.
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•Threshold methods was used in forecasting outburst.•The methods were realized using multiple indices and logistic regression.•The algorithm is mainly concerned with LR model.•Forecasting accuracy of ...94% is obtained.
Precursor information of rock fracture is a prerequisite for rock dynamic disaster (RDD) prediction. To investigate the precursor information of rock fracture based on pressure stimulated current ...(PSC), progressive loading (PL) and step-like loading (SLL) experiments on sandstone samples were conducted. The response characteristics of PSCs from sandstone samples being actively loaded in the laboratory were analyzed and potential precursors to rock fracture based on PSCs are discussed. The results show that weak currents are generated instantaneously when a load is applied on sandstone samples and the PSCs correspond well to stress variations. In the PL experiments, the PSC responses are different in the different stages of deformation. In the compaction stage, the PSC first increases linearly and rapidly as the stress becomes greater but then decreases slowly a few seconds later; In the elastic stage, the current increases slowly and linearly with stress but it begins to rise with an increasing rate when the sample enters the plastic deformation stage, reaching the peak value of PSC the instant the final fracture occurs. In the SLL experiments, when stress is increased from a lower to a higher stress step, the PSCs increase rapidly and reach peak values the moment the stress stops increasing. In addition, the peak current increases exponentially with stress rate with a negative exponent. During stress maintenance, the PSCs decay slowly before finally reaching a stable value, and the PSC decaying process obeys the non-extensive statistical mechanics. The accumulated charge increases linearly with the relative stress, but the charge increasing rate are different in the three deformation stages. The variation rate of accumulated charge in plastic deformation stage is approximately eleven times as that in elastic deformation stage. The variation of current has a precursor response to rock fracture: the increase of PSC with an accelerative rate can be used as a precursor of rock failure during a progressive loading, the increasingly intensive abrupt drops during the PSCs decay are precursors for rock fracture during creep, and the rapid increase of accumulated charge variation rate can be used as a precursor of rock fracture both under progressive and step-like loadings. These research results are expected to provide new ideas and methods for RDD prediction.
For this study, microseismic (MS) and electromagnetic radiation (EMR) monitoring systems were installed in a coal mine to monitor rock bursts. The MS system monitors coal or rock mass ruptures in the ...whole mine, whereas the EMR equipment monitors the coal or rock stress in a small area. By analysing the MS energy, number of MS events, and EMR intensity with respect to rock bursts, it has been shown that the energy and number of MS events present a “quiet period” 1–3 days before the rock burst. The data also show that the EMR intensity reaches a peak before the rock burst and this EMR intensity peak generally corresponds to the MS “quiet period”. There is a positive correlation between stress and EMR intensity. Buckling failure of coal or rock depends on the rheological properties and occurs after the peak stress in the high-stress concentration areas in deep mines. The MS “quiet period” before the rock burst is caused by the heterogeneity of the coal and rock structures, the transfer of high stress into internal areas, locked patches, and self-organized criticality near the stress peak. This study increases our understanding of coal and rock instability in deep mines. Combining MS and EMR to monitor rock burst could improve prediction accuracy.
Abstract
During the deformation and fracture process, the acoustic emission (AE) signals can be produced for the of coal, rock and other solid materials, which revealing the damage localization ...evolution process. The effect of gas adsorption and pressure can change mechanical properties of coal mass and affect its damage development. Based on this, the experimental system for gas-bearing coal loading and AE monitoring was constructed, to analyze AE response characteristics under the joint action of loading stress and gas pressure on coal specimen. Afterwards, the damage localization evolution process of coal mass was studied with the moment tensor inversion method. Results showed that temporal response of AE signals was closely related to the damage degree and loading level of coal specimen, which could reveal its local severe damage and final failure characteristics. The spatial distribution and spread trend of AE fracture events inside coal specimen could be calculated through the moment tensor inversion method. It was basically consistent with the results of crack expansion on the specimen surface. The zones, where fracture events occurred intensively, gathered and spread in a continuous trend, were conductive to forming the macrocrack belt macroscopically. It could be regarded as the hazard zone with dynamic failure occurrence. Moreover, when the coal specimen faced the critical failure, the precursor characteristics of AE response appeared with the shear fracture events dominated markedly. The study results provide a new research idea for revealing the damaging localization evolution process under the coupling effect of stress and gas and lay the application foundation.
Integrated monitoring technology using acoustic emission (AE) and electromagnetic radiation (EMR) is a promising mean for monitoring coal and rock dynamic disasters. However, due to the complex ...underground environment, blasting, drilling and mechanical operations may generate interference signals that affect the accuracy of early warning. It is essential to study the automatic recognition of effective and interference signals for AE and EMR. For this reason, a field test of synchronous AE-EMR monitoring was conducted in a coal mine. Further, the time domain, frequency domain and fractal characteristics of effective and interference signals for AE and EMR were analyzed, and sensitive characteristics were obtained by the Relief algorithm. Based on this, automatic recognition models of effective and interference signals were established by Fisher's linear discriminant method, support vector machine and ensemble learning method, respectively. Field application showed that support vector machine performed higher recognition accuracy. The AE and EMR warning indicators were obtained based on the signal recognition model, and the results show that the indicators reflect the risk of rock burst more accurately and earlier than the original indicators before the removal of interference signals.
Previous studies indicate that an electric potential (EP) signal is generated during the loading process of coal and that the EP response is related to the damage evolution. When coupled with gas, EP ...changes the pore structure and mechanical properties of a coal mass, promoting crack generation and growth and accelerating damage evolution. To study the EP response characteristics and investigate the damage of gas-bearing coal, a triaxial test was carried out with a gas-controlled confining pressure, and multiple types of data were measured and analyzed. The results show that with the change in stress, the EP response increases and fluctuates. This response reflects the stress and reveals the damage evolution, which could be verified with the variation in the acoustic emission response. For the mechanism analyses, the failure of the sample is caused by crack expansion and propagation under the coupling action of stress and gas. Consequently, microscopic charge separation and electron emission are the dominant mechanisms controlling the EP response. Furthermore, the constitutive damage equation of gas-bearing coal is established based on the EP response in view of continuous damage theory and the stress intensity distribution hypothesis. The calculation results of damage and stress based on the EP response are utilized for verification; the results indicate that the damage expressed by the EP response is reasonable and useful. This finding is helpful for understanding the damage evolution mechanism of gas-bearing coal.
•AlGaN/GaN HEMT structures have been grown on Si (1 1 1) substrates with different AlN nucleation layers (NL) by MOCVD.•Effects of the growth temperature of AlN NL on properties of the AlGaN/GaN ...heterostructures are investigated.•Optimized growth temperature of AlN NL resulted in superior two-dimensional electron gas performance of the AlGaN/GaN heterostructure.
AlGaN/GaN heterostructures were grown on Si (1 1 1) substrates with different AlN nucleation layers (NL) by metal–organic chemical vapor deposition (MOCVD). The results indicate that the growth temperature of AlN NL has a noticeable influence on the structural, electronic and optical properties of the AlGaN/GaN heterostructures. Optimizing the growth temperature to 1040 °C led to quasi-2D smooth surface of the AlN NL with providing sufficient compressive stress to suppress cracking of the subsequent GaN layer during the cooling process, resulting in improved crystalline quality of GaN layer and superior two-dimensional electron gas (2DEG) performance of the AlGaN/GaN heterostructure.
Microseismic, acoustic emission, and electromagnetic radiation monitoring methods are often used to monitor rock burst disasters in coal mines. In the process of coal mining, the time series ...characteristics and amplitude characteristics of microseismic, acoustic emission, and electromagnetic radiation data are mainly used to identify rockburst risk, but the results of risk identification through the three monitoring methods are quite different. Consequently, the accurate and comprehensive early warning of rock burst risk is still an urgent problem to be solved. The development of deep learning provides a new means for intelligent early warning of rock burst risk. In this paper, a comprehensive early warning method of microseismic, acoustic emission, and electromagnetic radiation (MS-AE-EMR) signals of rock bursts was proposed based on a deep learning algorithm. This method uses long short-term memory recurrent neural networks (LSTM-RNNs) to intelligently identify the MS-AE-EMR precursor signal of rock burst risk, predicts the MS-AE-EMR signal by a convolution neural network (CNN), analyses the MS-AE-EMR precursor signal of rock burst risk through the data analysis method and obtains the risk coefficient of rock burst. Moreover, by using the MS-AE-EMR original signal and risk coefficient, it trains the multi-input CNN and inputs the predicted signal into the trained multi-input CNN to obtain the predicted risk coefficient of rock burst. Analysing the risk coefficient completes the comprehensive early warning of the MS-AE-EMR signal of rock burst. After field verification, the RNN-based comprehensive early warning method of the MS-AE-EMR signal can respond positively to rock burst risk and capture the information in advance. Therefore, this method is of great significance for accurate monitoring and early warning of rock burst in coal mines.
In this paper, the characteristics and mechanism of the surface potential of coal containing gas for different loading modes (uniaxial compression, cyclic and graded loading) are investigated using ...an experimental surface potential testing system. Coal can produce a surface potential signal during gas adsorption. This signal increases with the adsorption time and exhibits a memory effect; that is, when the adsorbed gas pressure is increased, the surface potential increases. The coal containing gas can produce a surface potential signal based on different loading modes (uniaxial, cyclic, and graded loading), and the surface potential increases with the load. The higher the gas pressure is, the lower the peak stress is but the higher the maximum surface potential is. The surface potential under cyclic loading exhibits a significant memory effect and is lower than that during the stress-holding stage during graded loading. The surface potential caused by the loading and failure of coal containing gas is the result of the joint actions of gas and stress, which induce a free charge, a frictional force and an electrokinetic effect. This study offers theoretically significant and practical results that reflect the microscale process and electrical precursors of coal fracturing.
•Coal can produce surface potential signal in the process of absorbing gas.•The higher the gas pressure, the higher the surface potential peak.•The surface potential of cyclic loading has a significant memory effect.
