Reconstructed Water Oxidation Electrocatalysts: The Impact of Surface Dynamics on Intrinsic Activities

Electroreduction of small molecules such as H₂O, CO₂, and N₂ for producing clean fuels or valuable chemicals provides a sustainable approach to meet the increasing global energy demands and to alleviate the concern on climate change resulting from fossil fuel consumption. On the path to implement this purpose, however, several scientific hurdles remain, one of which is the low energy efficiency due to the sluggish kinetics of the paired oxygen evolution reaction (OER). In response, it is highly desirable to synthesize high-performance and cost-effective OER electrocatalysts. Recent advances have witnessed surface reconstruction engineering as a salient tool to significantly improve the catalytic performance of OER electrocatalysts. In this review, recent progress on the reconstructed OER electrocatalysts and future opportunities are discussed. A brief introduction of the fundamentals of OER and the experimental approaches for generating and characterizing the reconstructed active sites in OER nanocatalysts are given first, followed by an expanded discussion of recent advances on the reconstructed OER electrocatalysts with improved activities, with a particular emphasis on understanding the correlation between surface dynamics and activities. Finally, a prospect for clean future energy communities harnessing surface reconstruction-promoted electrochemical water oxidation will be provided.     

Review on synthesis of porous TiO2-based catalysts for energy conversion systems

Porous TiO₂-based catalysts have recently received remarkable attention in the field of energy conversion systems, including hydrogen/oxygen evolution reaction, oxygen/nitrogen reduction reaction, and photodegradation of pollutants owing to their unique structure, large surface area, and good chemical stability. In this report, we review existing research on porous TiO₂-based catalysts for energy conversion systems during the past four years. First, the advantages of porous TiO₂-based catalysts are introduced. Next, the synthetic approaches in developing porous TiO₂-based catalysts are summarized. The different types of energy conversion systems based on porous TiO₂-based catalysts are then presented. Finally, the challenges and future perspectives in synthesizing porous TiO₂-based catalysts are discussed.     

致密砂岩油藏能量补充方式评价及优化

针对致密砂岩油藏大规模体积压裂开发后能量补充困难的问题,利用自主设计制作的大型人造三维岩心物理模型和物理模拟实验舱,开展致密砂岩油藏能量补充方式优化研究。实验结果表明:致密砂岩油藏压裂开发过程中,地层能量损耗严重,采取注水或注气的方式可有效进行能量补充;地层中裂缝规模越大,越有利于原油渗流,后续补充能量的传播范围越广,有助于进一步提高原油采收率;从提高驱油效率和扩大波及系数方面优选吞吐渗吸介质,CO₂均优于活性水,CO₂吞吐开发在矿场试验中取得了显著的增油效果,因此,CO₂吞吐作为一种有效的能量补充方式在致密油开发中展现了良好的应用前景。该文分析了致密砂岩储层水平井压裂开发的渗流规律,优选出致密砂岩储层大规模压裂开发后最佳渗吸介质,可为致密砂岩油藏开发设计提供重要的理论依据。     

煤泥燃烧过程中汞的迁移行为研究

采用在线汞测试方法，以山西省低热值煤电厂中掺烧的煤泥为研究对象，利用实验室小型流化床，研究煤泥中汞的热转化行为差异及共性特征、影响煤泥热转化过程中汞迁移的关键因素，以揭示煤泥热转化过程中汞污染物的迁移机理。结果表明，同一种煤泥，相同气氛，800、900、1 000 ℃下，燃烧温度对煤泥中的汞的释放比例没有变化；相同温度，汞的释放比例为氮气>空气>氧气。3种煤泥在相同燃烧条件下，汞的释放特征相似，元素汞的释放量和释放比例差异较大。释放量与煤泥中的汞含量正相关，释放比例与煤泥中汞的赋存形态有一定关系。     

Dynamic energy and mass balance model for an industrial alkaline water electrolyzer plant process

This paper proposes a parameter adjustable dynamic mass and energy balance simulation model for an industrial alkaline water electrolyzer plant that enables cost and energy efficiency optimization by means of system dimensioning and control. Thus, the simulation model is based on mathematical models and white box coding, and it uses a practicable number of fixed parameters. Zero-dimensional energy and mass balances of each unit operation of a 3 MW, and 16 bar plant process were solved in MATLAB functions connected via a Simulink environment. Verification of the model was accomplished using an analogous industrial plant of the same power and pressure range having the same operational systems design. The electrochemical, mass flow and thermal behavior of the simulation and the industrial plant were compared to ascertain the accuracy of the model and to enable modification and detailed representation of real case scenarios so that the model is suitable for use in future plant optimization studies. The thermal model dynamically predicted the real case with 98.7 % accuracy. Shunt currents were the main contributor to relative low Faraday efficiency of 86 % at nominal load and steady-state operation and heat loss to ambient from stack was only 2.6 % of the total power loss.     

Energy conversion performances during biomass air gasification process under microwave irradiation

Biomass gasification technology under microwave irradiation is a new and novel method, and the energy conversion performances during the process play a guiding role in improving the energy conversion efficiencies and developing the gasification simulation models. In order to improve the energy utilization efficiency of microwave biomass gasification system, this study investigated and presented the energy conversion performances during biomass gasification process under microwave irradiation, and these were materialized through detailing (a) the energy conversion performance in the microwave heating stage, and (b) the energy conversion performance in the microwave assisted biomass gasification stage. Different forms of energies in the biomass microwave gasification process were calculated by the method given in this study based on the experimental data. The results showed that the useful energy (energy in silicon carbide (SiC), 18.73 kJ) accounted for 31.22% of the total energy input (electrical energy, 60.00 kJ) in the heating stage, and the useful energy (energy in the products, 758.55 kJ) accounted for 63.41% of the total energy input (electrical and biomass energy, 1196.28 kJ) in the gasification stage. During the whole biomass gasification process under microwave irradiation, the useful energy output (energy in the products, 758.55 kJ) accounted for 60.38% of the total energy input (electrical and biomass energy, 1256.28 kJ), and the energy in the gas (523.40 kJ) product played a dominate role in product energy (758.55 kJ). The energy loss mainly included the heat loss in the gas flow (89.20 kJ), magnetron loss (191.80 kJ) and microwave dissipation loss (198.00 kJ), which accounted for 7.10%, 15.27% and 15.76% of the total energy, respectively. The contents detailed in this study not only presented the energy conversion performances during microwave assisted gasification process but also supplied important data for developing gasification simulation models.     

Performance enhancement of methanol reforming reactor through finned surfaces and diffused entry for on-board hydrogen generation

Hydrogen-rich combustion in engines helps in reducing pollutants significantly. But hydrogen usage on a moving vehicle is not getting large-scale user acceptance mainly due to its poor energy storage density resulting in shorter driving ranges. This storage issue led to the hunt for mediums that can efficiently produce on-board hydrogen. Methanol proves to be an efficient alcohol fuel for producing hydrogen through steam reforming reaction. The heat energy required for such endothermic reaction is obtained through exhaust engine waste energy and this process is collectively known as thermochemical recuperation. However, the conventional reactor used for this process faces a lot of problems in terms of efficiency and methanol conversion. In this study, an attempt has been made to improve the design of the reactor for on-board hydrogen generation using engine exhaust heat for addressing the challenges related to performance and hydrogen yield. For enhancing the heat transfer, a finned surface (straight & wavy) was introduced in the reactor which resulted in an increment in methanol conversion significantly. It was found that wavy fin improved the methanol conversion up to 96.8% at an exhaust inlet temperature of 673 K. Also, a diffusing inlet section was introduced to increase the residence time of reactant gases while passing through the catalyst zone. Under given inlet conditions, the methanol conversion for 6° diffuse inlet reactor goes up to 87.9% as compared to 75.4% for the conventional reactor.     

磨矿动力学研究现状及应用

磨矿动力学是描述被磨物料的磨碎速率与磨矿时间之间关系规律的一种数学模型，对分析物料在磨矿过程中的粒级及能量变化具有重要作用。为充分发挥磨矿动力学在磨矿过程中的作用，论文在分析国内外研究现状的基础上，系统介绍了两种典型的磨矿动力学模型：m阶磨矿动力学模型和磨矿总体平衡动力学模型，分析了模型中各参数的含义；以磨矿总体平衡动力学模型为重点，分析了破碎速率函数和破碎分布函数的求解方式，包括零阶产出率法、奥-勒理论简算法、卡普尔G-H算法以及经验公式法等；从物料性质、磨矿介质及配比、磨矿方式及参数、化学添加剂等几个方面分析了影响磨矿动力学模型的因素；指出了磨矿动力学模型在矿物加工工程领域的应用现状并对其未来的研究方向提出展望。研究表明磨矿动力学在矿物加工领域具有广泛而重要的应用，为进一步改善磨矿工艺提供了理论依据。     

Statistical optimization of operating parameters of microbial electrolysis cell treating dairy industry wastewater using quadratic model to enhance energy generation

The performance of Microbial electrolysis cell (MEC) is affected by several operating conditions. Therefore, in the present study, an optimization study was done to determine the working efficiency of MEC in terms of COD (chemical oxygen demand) removal, hydrogen and current generation. Optimization was carried out using a quadratic mathematical model of response surface methodology (RSM). Thirteen sets of experimental runs were performed to optimize the applied voltage and hydraulic retention time (HRT) of single chambered batch fed MEC operated with dairy industry wastewater. The operating conditions (i.e) an applied voltage of 0.8 V and HRT of 2 days that showed a maximum COD removal response was chosen for further studies. The MEC operated at optimized condition (HRT- 2 days and applied voltage- 0.8 V) showed a COD removal efficiency of 95 ± 2%, hydrogen generation of 32 ± 5 mL/L/d, Power density of 152 mW/cm² and current generation of 19 mA. The results of the study implied that RSM, with its high degree of accuracy can be a reliable tool for optimizing the process of wastewater treatment. Also, dairy industry wastewater can be considered to be a potential source to generate hydrogen and energy through MEC at short HRT.     

Optimization of PEMFC system operating conditions based on neural network and PSO to achieve the best system performance

PEMFC system is a complex new clean power system. Based on MATLAB/Simulink, this paper develops a system-level dynamic model of PEMFC, including the gas supply system, hydrogen supply system, hydrothermal management system, and electric stack. The neural network fits the electric stack model to the simulation data. The effects of different operating conditions on the PEMFC stack power and system efficiency are analyzed. Combining the power of the reactor and the system efficiency to define the integrated performance index, the particle swarm optimization (PSO) algorithm is introduced to optimize the power density and system efficiency of the PEMFC with multiple objectives. The final optimal operating point increases the power density and system efficiency by 1.33% and 12.8%, respectively, which maximizes the output performance and reduces the parasitic power.