Recent advancements have established machine learning's utility in predicting nonlinear fluid dynamics,with predictive accuracy being a central motivation for employing neural networks.However,the pattern recognit...Recent advancements have established machine learning's utility in predicting nonlinear fluid dynamics,with predictive accuracy being a central motivation for employing neural networks.However,the pattern recognition central to the networks function is equally valuable for enhancing our dynamical insight into the complex fluid dynamics.In this paper,a single-layer convolutional neural network(CNN)was trained to recognize three qualitatively different subsonic buffet flows(periodic,quasi-periodic and chaotic)over a high-incidence airfoil,and a near-perfect accuracy was obtained with only a small training dataset.The convolutional kernels and corresponding feature maps,developed by the model with no temporal information provided,identified large-scale coherent structures in agreement with those known to be associated with buffet flows.Sensitivity to hyperparameters including network architecture and convolutional kernel size was also explored.The coherent structures identified by these models enhance our dynamical understanding of subsonic buffet over high-incidence airfoils over a wide range of Reynolds numbers.展开更多
Single-atom catalysts with precise structure and tunable coordination nature provide opportunities for developing novel catalytic centers and understanding reaction mechanisms.Herein,hollow Co_(9)S_(8)polyhedrons with...Single-atom catalysts with precise structure and tunable coordination nature provide opportunities for developing novel catalytic centers and understanding reaction mechanisms.Herein,hollow Co_(9)S_(8)polyhedrons with lattice-confined Ru single atoms(Ru-Co_(9)S_(8))are fabricated.Aberration-corrected scanning transmission electron microscopy and X-ray absorption spectroscopy verify the isolated Ru atoms are confined in Co_(9)S_(8)to form Co-S-Ru catalytic centers.Theoretical calculations indicate that the oxygen evolution reaction(OER)and oxygen reduction reaction(ORR)energy barriers are extensively reduced,the d-band center of Co_(9)S_(8)downshifts from the Fermi level,therefore boosting the desorption of O-containing intermediates.Consequently,the Ru-Co_(9)S_(8)exhibits an ultralow overpotential of 163 mV at 10 mA·cm^(−2)for OER and could catalyze a rechargeable Zn-air battery with a high-power density of 92.0 mW·cm^(−2).This work provides a promising approach for designing novel bifunctional catalytic active centers for energy conversion.展开更多
文摘Recent advancements have established machine learning's utility in predicting nonlinear fluid dynamics,with predictive accuracy being a central motivation for employing neural networks.However,the pattern recognition central to the networks function is equally valuable for enhancing our dynamical insight into the complex fluid dynamics.In this paper,a single-layer convolutional neural network(CNN)was trained to recognize three qualitatively different subsonic buffet flows(periodic,quasi-periodic and chaotic)over a high-incidence airfoil,and a near-perfect accuracy was obtained with only a small training dataset.The convolutional kernels and corresponding feature maps,developed by the model with no temporal information provided,identified large-scale coherent structures in agreement with those known to be associated with buffet flows.Sensitivity to hyperparameters including network architecture and convolutional kernel size was also explored.The coherent structures identified by these models enhance our dynamical understanding of subsonic buffet over high-incidence airfoils over a wide range of Reynolds numbers.
基金the National Natural Science Foundation of China(No.21902189)Key Scientific Research Projects of Universities in Henan Province(No.21A150062)+1 种基金Young Backbone Teacher of Zhongyuan University of Technology(No.2020XQG09)the Fundamental Research Funds of Zhongyuan University of Technology(No.K2020YY003).
文摘Single-atom catalysts with precise structure and tunable coordination nature provide opportunities for developing novel catalytic centers and understanding reaction mechanisms.Herein,hollow Co_(9)S_(8)polyhedrons with lattice-confined Ru single atoms(Ru-Co_(9)S_(8))are fabricated.Aberration-corrected scanning transmission electron microscopy and X-ray absorption spectroscopy verify the isolated Ru atoms are confined in Co_(9)S_(8)to form Co-S-Ru catalytic centers.Theoretical calculations indicate that the oxygen evolution reaction(OER)and oxygen reduction reaction(ORR)energy barriers are extensively reduced,the d-band center of Co_(9)S_(8)downshifts from the Fermi level,therefore boosting the desorption of O-containing intermediates.Consequently,the Ru-Co_(9)S_(8)exhibits an ultralow overpotential of 163 mV at 10 mA·cm^(−2)for OER and could catalyze a rechargeable Zn-air battery with a high-power density of 92.0 mW·cm^(−2).This work provides a promising approach for designing novel bifunctional catalytic active centers for energy conversion.
