The role of carbon in microstructure evolution of SiBCO ceramics

The composition of polymer derived ceramics could be readily tuned through controlling the structure and element content of the polymer precursors, and investigation on the effect of the element on microstructure evolution is important to the design of advanced ceramics. In this article, the effect of carbon content in SiBCO polymer precursors was systematically investigated. The polymer network and thermal stability of polymer precursors and the carbon content of pyrolyzed SiBCO ceramic could be readily tuned by controlling the DVB amount used. Carbon contributed to the formation of graphitic carbon in SiBC_xO ceramics and inhibited the growth of β–SiC and SiO₂ crystals at 1600 °C, but lead to an increase in the graphitic carbon phase at 1800 °C.     

Amorphous-crystalline cobalt-molybdenum bimetallic phosphide heterostructured nanosheets as Janus electrocatalyst for efficient water splitting

Efficient and sustainable Janus catalysts toward hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) are highly desirable for future hydrogen production via water electrolysis. Herein we report an active Janus electrocatalyst of amorphous-crystalline cobalt-molybdenum bimetallic phosphide heterostructured nanosheets on nickel foam (CoMoP/CoP/NF) for efficient electrolysis of alkaline water. As-reported CoMoP/CoP/NF consists of amorphous bimetal phosphide nanosheets doped with crystalline CoMoP/CoP heterostructured nanoparticles on NF. It can efficiently catalyze both HER (η = 127 mV@100 mA cm^?2) and OER (η = 308 mV@100 mA cm^?2) in alkaline electrolyte with long-term durability. Serving as anode and cathode of water electrolyzer, CoMoP/CoP/NF generates electrolytic current of 10, 50 and 100 mA cm^?2 at low voltage of 1.50, 1.59, and 1.67 V, respectively.     

Zeolitic-imidazolate frameworks-derived Co3S4/NiS@Ni foam heterostructure as highly efficient electrocatalyst for oxygen evolution reaction

Transition metals sulfide-based nanomaterials have recently received significant attention as a promising cathode electrode for the oxygen evolution reaction (OER) due to their easily tunable electronic, chemical, and physical properties. However, the poor electrical conductivity of metal-sulfide materials impedes their practical application in energy devices. Herein, firstly nano-sized crystals of cobalt-based zeolitic-imidazolate framework (Co-ZIF) arrays were fabricated on nickel-form (NF) as the sacrificial template by a facile solution method to enhance the electrical conductivity of the electrocatalyst. Then, the Co₃S₄/NiS@NF heterostructured arrays were synthesized by a simple hydrothermal route. The Co-ZIFs derived Co₃S₄ nanosheets are grown successfully on NiS nanorods during the hydrothermal sulfurization process. The bimetallic sulfide-based Co₃S₄/NiS@NF-12 electrocatalyst demonstrated a very low overpotential of 119 mV at 10 mA cm^?2 for OER, which is much lower than that of mono-metal sulfide NiS@NF (201 mV) and ruthenium-oxide (RuO₂) on NF (440 mV) electrocatalysts. Furthermore, the Co₃S₄/NiS@NF-12 electrocatalyst showed high stability during cyclic voltammetry and chronoamperometry measurements. This research work offers an effective strategy for fabricating high-performance non-precious OER electrocatalysts.     

Density functional theory study of the hydrogen evolution reaction in haeckelite boron nitride quantum dots

To satisfy arising energy needs and to handle the forthcoming worldwide climate transformation, the major research attention has been drawn to environmentally friendly, renewable and abundant energy resources. Hydrogen plays an ideal and significant role is such resources, due to its non-carbon based energy and production through clean energy. In this work, we have explored catalytic activity of a newly predicted haeckelite boron nitride quantum dot (haeck-BNQD), constructed from the infinite BN sheet, for its utilization in hydrogen production. Density functional theory calculations are employed to investigate geometry optimization, electronic and adsorption mechanism of haeck-BNQD using Gaussian16 package, employing the hybrid B3LYP and wB97XD functionals, along with 6–31G(d,p) basis set. A number of physical quantities such as HOMO/LUMO energies, density of states, hydrogen atom adsorption energies, Mulliken populations, Gibbs free energy, work functions, overpotentials, etc., have been computed and analysed in the context of the catalytic performance of haeck-BNQD for the hydrogen-evolution reaction (HER). Based on our calculations, we predict that the best catalytic performance will be obtained for H adsorption on top of the squares or the octagons of haeck-BNQD. We hope that our prediction of most active catalytic sites on haeck-BNQD for HER will be put to test in future experiments.     

Porous CoNiOOH nanosheets derived from the well-mixed MOFs as stable and highly efficient electrocatalysts for water oxidation

The development of efficient and stable electrocatalysts is of great significance for improving water splitting. Among them, transition metal oxyhydroxides show excellent performance in oxygen evolution reactions (OER), but there are certain difficulties in direct preparation. Recently, Metal–organic frameworks (MOFs) as precatalysts or precursors have shown promising catalytic performance in OER and can be decomposed under alkaline conditions. Therefore, using a mild and controllable way to convert MOFs into oxyhydroxides and retaining the original structural advantages is crucial for improving the catalytic activity. Herein, a rapid electrochemical strategy is used to activate well-mixed MOFs to prepare Co/Ni oxyhydroxide nanosheets for efficient OER catalysts, and the structural transformation in this process was investigated in detail by using scanning electron microscope, X-ray diffraction, Raman, X-ray photoelectron spectroscopy and electrochemical methods. It is discovered that electrochemical activation can promote ligand substitution of well-mixed MOFs to form porous oxyhydroxide nanosheets and tune the electronic structure of the metal (Co and Ni), which can lead to more active site exposure and accelerate charge transfer. In addition, the change of structure also improves hydrophilicity, as well as benefiting from the strong synergistic effect between multiple species, the optimal a-MCoNi–MOF/NF has excellent OER performance and long-term stability. More obviously, the porous CoNiOOH nanosheets are formed in situ during electrochemical activation process through structural transformation and acts as the active centers. This work provides new insights for mild synthesis of MOFs derivatives and also provides ideas for the preparation of highly efficient catalysts.     

Self-construction of pea-like Cu/Cu2S Mott-Schottky electrocatalyst for the oxygen evolution reaction

The speed of the oxygen evolution reaction seriously affects the hydrogen production efficiency of water electrolysis. Hence it is crucial to develop efficient and durable OER electrocatalysts. Construction of heterojunction catalysts is also one of the strategies to develop efficient catalysts. In this paper, a pea-like Cu/Cu₂S–C3 Mott?Schottky electrocatalyst was self-constructed by vapor deposition, while CF (copper foam) was used as substrate material and copper source, and thiourea was served as sulfur source. The built-in electric field is formed at the metal-semiconductor interface, which endows it with promising electrocatalytic performance. As the working electrode, the overpotentials of Cu/Cu₂S–C3 required to reach the current density of 10 and 50 mA cm^?2 were about 170 and 335 mV. The impact of the Mott-Schottky structure on the catalyst was also reflected in stability. The i-t tests of the sample Cu/Cu₂S–C3 were carried out under 10 and 60 mA cm^?2 and performed well.     

疫情下电磁场理论课程的网络教学

本文主要总结了新冠疫情期间作者的电磁场理论课程在线教学经验。对比分析了录播和直播的优缺点后,选择录播教学方式。基于超星网络教学平台,展示了录播网络教学的具体措施,包括网上答疑和学习效果检查以及在线批改作业等。给出了网络教学可以为线下教学继续使用的方法和手段,为疫情结束后的正常教学提供了新的网络教学补充措施。     

Pristine and cobalt doped copper sulfide microsphere particles for seawater splitting

In this work, copper sulfide particles are synthesized with different Co doping concentrations such as 0, 1 and 5% at 80 °C by optimizing synthesis times from 1 to 3 h. Copper sulfide particles possess two structural phases of covellite CuS and digenite Cu₉S₅. The increase in synthesis time from 1 to 3 h increases the Cu₉S₅ phase growth and changes the morphology from flower to microsphere. The CuS synthesized with 0, 1 and 5% Co dopant concentrations demonstrate flower consisting of agglomerated nanosheets, microsphere and flower like microsphere. The elemental investigation substantiates Co ions presence in CuS microspheres. The A_1g (LO) mode intensity is decreased with increase in Co dopant concentration confirming Co incorporation into CuS microsphere. The CuS synthesized with 0, 1, 5% Co dopants exhibit 322 mV, 305 mV and 289 mV to attain 100 mA/cm² in 1 M KOH seawater. The CuS synthesized with 5% Co dopant demonstrates higher double layer capacitance (C_dl) of 173.9 mFcm^?2 and lower charge transfer resistance (R_ct) of 6.07 Ω with 78.84% retention after 10 h continuous stability than that of the other pristine (118.3 mFcm^?2, 13.72 Ω) and 1% Co doped CuS microsphere (165.7 mFcm^?2, 8.55 Ω) indicating more surface active site and rapid charge carrier transport, respectively.     

Machine fault diagnosis with small sample based on variational information constrained generative adversarial network

In actual engineering scenarios, limited fault data leads to insufficient model training and over-fitting, which negatively affects the diagnostic performance of intelligent diagnostic models. To solve the problem, this paper proposes a variational information constrained generative adversarial network (VICGAN) for effective machine fault diagnosis. Firstly, by incorporating the encoder into the discriminator to map the deep features, an improved generative adversarial network with stronger data synthesis capability is established. Secondly, to promote the stable training of the model and guarantee better convergence, a variational information constraint technique is utilized, which constrains the input signals and deep features of the discriminator using the information bottleneck method. In addition, a representation matching module is added to impose restrictions on the generator, avoiding the mode collapse problem and boosting the sample diversity. Two rolling bearing datasets are utilized to verify the effectiveness and stability of the presented network, which demonstrates that the presented network has an admirable ability in processing fault diagnosis with few samples, and performs better than state-of-the-art approaches.