一种高效稳定的高熵合金电催化剂用于析氢反应

水分解是一种利用可再生能源驱动的绿色制氢方法,零碳排放特性使其成为解决氢能源生产的重要途径.在电化学水分解中,制备高活性和稳定性的催化剂至关重要.高熵合金(HEAs)由于独特的结构和性能使其成为理想的催化剂材料,其多元成分和可调组成提供了丰富的表面活性位点和灵活的催化特性,有望提高水分解的效率并降低成本.然而,简易高效地制备HEAs仍面临挑战,且目前对HEA催化剂的结构-活性关系的了解存在不足.因此,探索一种简便有效的方法用以制备高性能HEAs催化剂,并深入理解其在水分解反应中的作用机制和结构演变,能够为未来绿色制氢技术的发展提供重要的科学基础和技术支持.本文采用了电化学测量、CuK-边和PtL3-边的原位同步辐射X射线吸收光谱(XAS)测试以及密度泛函理论(DFT)计算相结合的方法,系统地研究了高熵合金电催化剂PtPdRhRuCu/C的析氢反应(HER)活性、反应机制以及结构演变规律.PtPdRhRuCu HEAs纳米颗粒由简便的一步溶剂热法制备,直径约为6.7±0.6 nm,其合金结构和元素分布通过多种表征手段(扫描透射电子显微镜、X射线衍射和能量色散X射线光谱等)得到确认.XAS对Cu K-边和PtL3-边的分析结果显示,HEAs纳米颗粒表面的少量铜氧化物在HER过程中被还原至金属态.扩展X射线吸收精细结构的拟合结果表明,HEAs在工况HER中保持了金属态和无序的原子排列,没有新的分离相形成.电化学测试结果表明,得益于多金属活性位点,PtPdRhRuCu/C催化剂在酸性和碱性条件下均表现出较好的HER活性和耐久性.在10 m Acm^(-2)的电流密度下,该催化剂在1molL^(-1)KOH中具有23.3 m V的极低过电位,优于商业Pt/C催化剂(50.3 m V),其质量活性是Pt/C的7.9倍,达到3.0 Amg^(-1)Pt.PtPdRhRuCu的高熵效应显著提升了催化剂在HER中的长期稳定性,在稳定性测试中,PtPdRhRuCu/C催化剂在10000次循环伏安测试后几乎无性能衰减,而Pt/C的过电位增加了约24 m V.在-55 m V过电位下的30 h的HER测试中,PtPdRhRuCu/C保持95.7%的初始电流密度,而Pt/C衰减了53.6%.在酸性条件下,PtPdRhRuCu/C的循环稳定性和耐久性也优于Pt/C.DFT计算结果表明,PtPdRhRuCu/C较好的HER性能和稳定性归因于高熵合金的协同效应,多金属成分提供了多样的活性位点,优化了HER反应路径,特别是在Volmer步骤中降低了水裂解的反应能垒.PtPdRhRuCu/C上的HER过程遵循Volmer-Tafel机理,水分子优先吸附在Ru位点,促进HO-H键的解离,解离出的质子迁移到Pt上,而OH通过Ru和Rh的桥接作用而稳定,最终在Cu上释放H2.综上,本文展示了高熵合金在HER中较好的性能,并通过详细的表征深入理解了其构-效关系.研究成果为高熵合金催化剂的合理设计和应用提供理论支持,为未来高效、耐久和低成本的绿色制氢技术提供重要的科学依据和技术支持.

Review of dynamic gesture recognition

In recent years,gesture recognition has been widely used in the fields of intelligent driving,virtual reality,and human-computer interaction.With the development of artificial intelligence,deep learning has achieved remarkable success in computer vision.To help researchers better understanding the development status of gesture recognition in video,this article provides a detailed survey of the latest developments in gesture recognition technology for videos based on deep learning.The reviewed methods are broadly categorized into three groups based on the type of neural networks used for recognition:two stream convolutional neural networks,3D convolutional neural networks,and Long-short Term Memory(LSTM)networks.In this review,we discuss the advantages and limitations of existing technologies,focusing on the feature extraction method of the spatiotemporal structure information in a video sequence,and consider future research directions.

Apple Inc.Analysis and Forecast Evaluation

Apple has been an American success story for quite a long time.After igniting the personal computer(PC)revolution in the 1970s and reinventing PC in the 1980s,it again brought various innovative and game-changing products,including smartphones,computers,and wearables in recent years.Its dominant product,iPhone,sparked years of massive growth and has become the biggest drive of the company's success.Besides,with a market capitalization of more than$2T,Apple is currently the world's most valuable company.This makes many investors interested in AAPL stock.Hence,this paper will explore whether the APPL stock is worth investing based on the analysis of its business model,SWOT analysis,and relative valuation in hope to provide some recommendations and predictions for investors.

Self-healing superhydrophobic polyvinylidene fluoride/ Fe3O4@polypyrrole fiber with core-sheath structures for superior microwave absorption

Self-healing superhydrophobic polyvinylidene fluoride/Fe3O4@polypyrrole （F- PVDF/FeBO4@PPyx） fibers with core-sheath structure were successfully fabricated by electrospinning of a PVDF/Fe3O4 mixture and in situ chemical oxidative polymerization of pyrrole, followed by chemical vapor deposition with fluoroalkyl silane. The F-PVDF/Fe3O4@PPy0.075 fiber film produces a superhydrophobic surface with self-healing behavior, which can repetitively and automatically restore superhydrophobicity when the surface is chemically damaged. Moreover, the maximum refection loss （Ru） of the F-PVDF/Fe304@PPy0.075 fiber film reaches -21.5 dB at 16.8 GHz and the RL below -10 dB is in the frequency range of 10.6-16.5 GHz with a thickness of 2.5 mm. The microwave absorption performance is attributed to the synergetic effect between dielectric loss and magnetic loss originating from PPy, PVDF and Fe3O4. As a consequence, preparing such F-PVDF/Fe3O4@PPyx fibers in this manner provides a simple and effective route to develop multi-functional microwave absorbing materials for practical applications.

A bio-inspired Co304-polypyrrole-graphene complex as an efficient oxygen reduction catalyst in one-step ball milling

The development of non-precious metal-based electrocatalysts has attracted much research attention because of their high oxygen reduction reaction （ORR） activities, low cost, and good durability. By one-step in-situ ball milling of graphite, pyrrole, and cobalt salt without resorting to high-temperature annealing, we developed a general and facile strategy to synthesize bio-inspired cobalt oxide and polypyrrole coupled with a graphene nanosheet （Co3O4-PPy/GN） complex. Herein, the exfoliation of graphite and polymerization of pyrrole occurred simultaneously during the ball milling process. Meanwhile, the Co3O4 and Co-Nx ORR active sites were generated from the oxidized cobalt ion, cobalt-PPy, and the newly exfoliated graphene nanosheets via strong π-π stacking interactions. The resultant Co3O4-PPy/GN catalysts showed efficient electrocatalytic performances for ORRs in an alkaline medium with a positive onset and reduction potentials of -0.102 and -0.196 V （vs. Ag/AgCl）, as well as a high diffusion-limited current density （4.471 mA·cm^-2）, which was comparable to that of a Pt/C catalyst （4.941 mA·cm^-2）. Compared to Pt/C, Co3O4-PPy/GN catalysts displayed better long-term stability, methanol tolerance, and anti-CO-poisoning effects, which are of great significance for the design and development of advanced non-precious metal electrocatalysts.

Research on remote intelligent control technology of throttling and back pressure in managed pressure drilling

In order to reduce the non production time of drilling,improve the efficiency and safety of drilling,improve the economic effect of managed pressure drilling(MPD),and realize the intelligent control construction of digital oilfield.Based on the pressure control in MPD,this paper analyzes the pressure control drilling system,takes the wellhead back pressure as the controlled parameter,calculates the mathematical model of the throttle valve according to the characteristics of the throttle valve,the basic parameters and boundary conditions of pressure control drilling,and puts forward an improved particle swarm Optimization PID neural network(IPSO-PIDNN)model.By means of remote communication,VR technology can realize remote control of field control equipment.The real-time control results of IPSO-PIDNN are compared with those of traditional PID neural network(PIDNN)and traditional Particle Swarm Optimization PID neural network(PSO-PIDNN).The results show that IPSO-PIDNN model has good self-learning characteristics,high optimization quality,high control accuracy,no overshoot,fast response and short regulation time.Thus,the advanced automatic control of bottom hole pressure in the process of MPD is realized,which provides technical guarantee for the well control safety of MPD.

Metal-free porous nitrogen-doped carbon nanotubes for enhanced oxygen reduction and evolution reactions

Developing efficient metal-free bi-functional electrocatalysts is required to reduce costs and improve the slow oxygen reduction reaction （ORR） and oxygen evo- lution reaction （OER） kinetics in electrochemical systems. Porous N-doped carbon nanotubes （NCNTs） were fabri- cated by KOH activation and pyrolysis of polypyrrole nanotubes. The NCNTs possessed a large surface area of more than 1,000 m2 g-1. NCNT electrocatalysts, particu- larly those annealed at 900 ℃, exhibited excellent ORR electrocatalytic performance. Specifically, they yielded a more positive onset potential, higher current density, and long-term operation stability in alkaline media, when compared with a commercially available 20 wt% Pt/C catalyst. This resulted from the synergetic effect between the dominant pyridinic/graphitic-N species and the porous tube structures. The NCNT electrocatalyst also exhibited good performance for the OER. The metal-free porous nitrogen-doped carbon nanomaterials were prepared from low cost and environmentally friendly precursors. They are potential alternatives to Pt/C catalysts, for electrochemical energy conversion and storage.

Risk Assessment of Multi‑Hazards in Hangzhou:A Socioeconomic and Risk Mapping Approach Using the CatBoost‑SHAP Model

As the global push for sustainable urban development progresses, this study, set against the backdrop of Hangzhou City,one of China's megacities, addressed the conflict between urban expansion and the occurrence of urban geological hazards.Focusing on the predominant geological hazards troubling Hangzhou-urban road collapse, land subsidence, and karst collapse-we introduced a Categorical Boosting-SHapley Additive exPlanations(CatBoost-SHAP) model. This model not only demonstrates strong performance in predicting the selected typical urban hazards, with area under the curve(AUC) values reaching 0.92, 0.92, and 0.94, respectively, but also, through the incorporation of the explainable model SHAP, visually presents the prediction process, the interrelations between evaluation factors, and the weight of each factor. Additionally, the study undertook a multi-hazard evaluation, producing a susceptibility zoning map for multiple hazards, while performing tailored analysis by integrating economic and population density factors of Hangzhou. This research enables urban decision makers to transcend the “black box” limitations of machine learning, facilitating informed decision making through strategic resource allocation and scheduling based on economic and demographic factors of the study area. This approach holds the potential to offer valuable insights for the sustainable development of cities worldwide.