Experimental investigations of stress-gas pressure evolution rules of coal and gas outburst: A case study in Dingji coal mine, China

Coal and gas outburst is a potentially fatal risk during the mining of gassy coal seams, which seriously threatens the safe mining of collieries. To understand the outburst mechanism and evolution rules, a new apparatus (LSTT) was developed to conduct simulated experiment. In the context of an outburst accident in Dingji coal mine, the authors launched an authentic outburst experiment to replay the outburst accident. Experimental apparatus, similar criterion, coal‐like materials and gas sources, and experimental design were discussed systematically in this paper. Experimentally, the study analyzed the geo‐stress has significant influence on the outburst evolution. At the driving face, the stress concentration possibly caused gas outburst, under the influence of mining‐induced stress. After the outburst occurred, the stress balance of the coal changed, resulting in the instability of the coal. Furthermore, the elastic energy, gas enthalpy, and gravitational potential energy were released rapidly. The experimental result stated that outburst coal has the sorting characteristics, in line with the field outburst law. The intensity prediction model has been built based on the energy model. Moreover, the factors that impact outburst intensity were analyzed. In the process of coal and gas outburst, the gas enthalpy of gas and the elastic potential of coal are the main energy sources. This study provides guidance for the development of the outburst mechanism and outburst mine management

Tilting flat bands in an empty microcavity

Recently microcavities with anisotropic materials are shown to be able to create novel bands with non-zero local Berry curvature. The anisotropic refractive index of the cavity layer is believed to be critical in opening an energy gap at the tilted Dirac points. In this work, we show that an anticrossing between a cavity mode and a Bragg mode can also form within an empty microcavity without any birefringent materials. Flat bands are observed within the energy gap due to the particular refractive index distribution of the sample. The intrinsic TE-TM splitting and XY splitting induce the squeezing of the cavity modes in momentum space, so that the flat bands are spin-dependently tilted. Our results pave the way to investigate the spin orbit coupling of photons in a simple microcavity without anisotropic cavity layers

A dynamic learning method based on the Gaussian process for tunnel boring machine intelligent driving

Introduction: The application of intelligent learning methods to the mining of characteristics and rules of time-series data has gained increasing attention with the rapid development of deep learning. One critical application of such methods is the intelligent assistant driving of tunnel boring machines (TBMs), for which the optimization of driving parameters is essential to improve construction efficiency. However, existing prediction models for TBM parameters are “static” and cannot dynamically capture parameter evolution during real-time driving cycles.Methods: In this study, we propose a novel dynamic learning model for TBM parameters by introducing the Gaussian process to address this problem. The model can learn decision-making experiences from historical driving cycles, dynamically update the model based on small sample data from current driving cycles, and simultaneously achieve driving parameter prediction. We focused on real-time prediction of TBM parameters in a tunnel project in western China.Results: The results show that the average relative errors of predicted total thrust and torque values were 1.9% and 2.7%, respectively, and the prediction accuracy was higher than that of conventional models such as random forest and long short-term memory. The model fully exploited updating of small samples of parameters, reducing the average time cost of the model to 29.7 s, which satisfies the requirements of efficient application.Discussion: The dynamic learning strategy of time-series data adopted in this study provides a reference for other similar engineering applications. The proposed model can improve the prediction accuracy of TBM parameters, thus facilitating the optimization of driving parameters and enhancing the construction efficiency of tunnels.Conclusion: In summary, this study establishes a dynamic learning model of TBM parameters that can dynamically capture parameter evolution and achieve accurate real-time driving parameter prediction. The proposed model can contribute to the development of intelligent assistant driving of TBMs and similar engineering applications

Electrically controlling vortices in a neutral exciton polariton condensate at room temperature

Manipulating bosonic condensates with electric fields is very challenging as the electric fields do not directly interact with the neutral particles of the condensate. Here we demonstrate a simple electric method to tune the vorticity of exciton polariton condensates in a strong coupling liquid crystal (LC) microcavity with CsPbBr$_3$ microplates as active material at room temperature. In such a microcavity, the LC molecular director can be electrically modulated giving control over the polariton condensation in different modes. For isotropic non-resonant optical pumping we demonstrate the spontaneous formation of vortices with topological charges of +1, +2, -2, and -1. The topological vortex charge is controlled by a voltage in the range of 1 to 10 V applied to the microcavity sample. This control is achieved by the interplay of a built-in potential gradient, the anisotropy of the optically active perovskite microplates, and the electrically controllable LC molecular director in our system with intentionally broken rotational symmetry. Besides the fundamental interest in the achieved electric polariton vortex control at room temperature, our work paves the way to micron-sized emitters with electric control over the emitted light's phase profile and quantized orbital angular momentum for information processing and integration into photonic circuits

High-mobility graphene on liquid p-block elements by ultra-low-loss CVD growth

The high-quality and low-cost of the graphene preparation method decide whether graphene is put into the applications finally. Enormous efforts have been devoted to understand and optimize the CVD process of graphene over various d-block transition metals (e.g. Cu, Ni and Pt). Here we report the growth of uniform high-quality single-layer, single-crystalline graphene flakes and their continuous films over p-block elements (e.g. Ga) liquid films using ambient-pressure chemical vapor deposition. The graphene shows high crystalline quality with electron mobility reaching levels as high as 7400 cm2 V−1s−1 under ambient conditions. Our employed growth strategy is ultra-low-loss. Only trace amounts of Ga are consumed in the production and transfer of the graphene and expensive film deposition or vacuum systems are not needed. We believe that our research will open up new territory in the field of graphene growth and thus promote its practical application

CeO2 Nanowires Inserted into Reduced Graphene Oxide as Active Electrocatalyst for Oxygen Reduction Reaction

Fabrication of an interconnected and conductive nano-architecture is a prospective strategy to design a high-performance and low cost electrocatalyst for oxygen reduction reaction (ORR). Herein, a novel nano-architecture assembled by graphene nanosheets and CeO2 nanowires (NWs) with a hierarchical structure was developed by a facile hydrothermal process using ethanol/water as solvents without any organic additives. In this framework, graphene oxide (GO) was reduced to graphene and chemical bonding formed between the GO and CeO2 NWs in a hydrothermal process. The imbedded CeO2 NWs could prevent the restacking of the graphene sheets and improved the electrical conductivity of the hybrid catalyst. The effect of different ratios of GO to CeO2 NWs in the hybrid were studied. The GO3-CeO2 NWs composite exhibited better catalytic performance with slow attenuation and high limiting current density 3.55 and 1.99 times higher than CeO2 NWs and pure GO. The onset potential of GO3-CeO2 NWs is 0.13 V and 0.05 V positive shift from that of CeO2 NWs and pure GO, respectively, suggesting that the GO3-CeO2 NWs hybrid had an excellent stability and activity for ORR. It was found that CeO2 NWs served not only as an effective catalyst but also as an “oxygen buffer” to relieve oxygen insufficiency for ORR

Single-shot spatial instability and electric control of polariton condensates at room temperature

In planar microcavities, the transverse-electric and transverse-magnetic (TE-TM) mode splitting of cavity photons arises due to their different penetration into the Bragg mirrors and can result in optical spin-orbit coupling (SOC). In this work, we find that in a liquid crystal (LC) microcavity filled with perovskite microplates, the pronounced TE-TM splitting gives rise to a strong SOC that leads to the spatial instability of microcavity polariton condensates under single-shot excitation. Spatially varying hole burning and mode competition occurs between polarization components leading to different condensate profiles from shot to shot. The single-shot polariton condensates become stable when the SOC vanishes as the TE and TM modes are spectrally well separated from each other, which can be achieved by application of an electric field to our LC microcavity with electrically tunable anisotropy. Our findings are well reproduced and traced back to their physical origin by our detailed numerical simulations. With the electrical manipulation our work reveals how the shot-to-shot spatial instability of spatial polariton profiles can be engineered in anisotropic microcavities at room temperature, which will benefit the development of stable polariton-based optoeletronic and light-emitting devices