CSAC-Net: Fast Adaptive sEMG Recognition through Attention Convolution Network and Model-Agnostic Meta-Learning.

Gesture recognition through surface electromyography (sEMG) provides a new method for the control algorithm of bionic limbs, which is a promising technology in the field of human-computer interaction. However, subject specificity of sEMG along with the offset of the electrode makes it challenging to develop a model that can quickly adapt to new subjects. In view of this, we introduce a new deep neural network called CSAC-Net. Firstly, we extract the time-frequency feature from the raw signal, which contains rich information. Secondly, we design a convolutional neural network supplemented by an attention mechanism for further feature extraction. Additionally, we propose to utilize model-agnostic meta-learning to adapt to new subjects and this learning strategy achieves better results than the state-of-the-art methods. By the basic experiment on CapgMyo and three ablation studies, we demonstrate the advancement of CSAC-Net.

The identification of active N species in N-doped carbon carriers that improve the activity of Fe electrocatalysts towards the oxygen evolution reaction.

Nitrogen-doped carbon nanomaterials have become some of the most effective carriers for transition metal-based electrocatalysts towards the oxygen evolution reaction. However, the specific active nitrogen species in nitrogen-doped carriers remains unclear up to now. To identify the active nitrogen species, herein, we prepare nitrogen-doped carbon nanospheres containing different types of nitrogen species and a small amount of Fe atoms. Electrochemical tests demonstrate that the Fe/nitrogen-doped carbon nanospheres with more graphitic nitrogen exhibit much higher activity for the oxygen evolution reaction than those with more pyridinic nitrogens and pyrrolic nitrogens in alkaline media, revealing that the graphitic nitrogen is the active species that greatly improves the activity of Fe catalysts. Density functional theory calculations further reveal that the graphitic nitrogen enhances the activity and stability of Fe-based catalysts mainly through increasing the adsorption energy, charge and spin densities of the Fe atoms loaded around it. These findings provide a brand-new perspective for rationally designing more effective transition metal-based electrocatalysts for the oxygen evolution reaction through controlling the active graphitic nitrogen distribution in carbon carriers.

Reaction Kinetics of Hydrogen Atom Abstraction from C4-C6 Alkenes by the Hydrogen Atom and Methyl Radical.

Alkenes are important ingredients of realistic fuels and are also critical intermediates during the combustion of a series of other fuels including alkanes, cycloalkanes, and biofuels. To provide insights into the combustion behavior of alkenes, detailed quantum chemical studies for crucial reactions are desired. Hydrogen abstractions of alkenes play a very important role in determining the reactivity of fuel molecules. This work is motivated by previous experimental and modeling evidence that current literature rate coefficients for the abstraction reactions of alkenes are still in need of refinement and/or redetermination. In light of this, this work reports a theoretical and kinetic study of hydrogen atom abstraction reactions from C4-C6 alkenes by the hydrogen (H) atom and methyl (CH3) radical. A series of C4-C6 alkene molecules with enough structural diversity are taken into consideration. Geometry and vibrational properties are determined at the B3LYP/6-31G(2df,p) level implemented in the Gaussian-4 (G4) composite method. The G4 level of theory is used to calculate the electronic single point energies for all species to determine the energy barriers. Conventional transition state theory with Eckart tunneling corrections is used to determine the high-pressure-limit rate constants for 47 elementary reaction rate coefficients. To faciliate their applications in kinetic modeling, the obtained rate constants are given in the Arrhenius expression and rate coefficients for typical reaction classes are recommended. The overall rate coefficients for the reaction of H atom and CH3 radical with all the studied alkenes are also compared. Branching ratios of these reaction channels for certain alkenes have also been analyzed.

Fabrication of CeO2-MO x (M = Cu, Co, Ni) composite yolk-shell nanospheres with enhanced catalytic properties for CO oxidation.

CeO2-MO x (M = Cu, Co, Ni) composite yolk-shell nanospheres with uniform size were fabricated by a general wet-chemical approach. It involved a non-equilibrium heat-treatment of Ce coordination polymer colloidal spheres (Ce-CPCSs) with a proper heating rate to produce CeO2 yolk-shell nanospheres, followed by a solvothermal treatment of as-synthesized CeO2 with M(CH3COO)2 in ethanol solution. During the solvothermal process, highly dispersed MO x species were decorated on the surface of CeO2 yolk-shell nanospheres to form CeO2-MO x composites. As a CO oxidation catalyst, the CeO2-MO x composite yolk-shell nanospheres showed strikingly higher catalytic activity than naked CeO2 due to the strong synergistic interaction at the interface sites between MO x and CeO2. Cycling tests demonstrate the good cycle stability of these yolk-shell nanospheres. The initial concentration of M(CH3COO)2·xH2O in the synthesis process played a significant role in catalytic performance for CO oxidation. Impressively, complete CO conversion as reached at a relatively low temperature of 145 °C over the CeO2-CuO x -2 sample. Furthermore, the CeO2-CuO x catalyst is more active than the CeO2-CoO x and CeO2-NiO catalysts, indicating that the catalytic activity is correlates with the metal oxide. Additionally, this versatile synthesis approach can be expected to create other ceria-based composite oxide systems with various structures for a broad range of technical applications.