Selectively converting CO_(2) to HCOOH on Cu-alloys integrated in hematite-driven artificial photosynthetic cells

The integration of electrochemical CO_(2)reduction(CO_(2)RR) and photoelectrochemical water oxidation offers a sustainable access to valuable chemicals and fuels. Here, we develop a rapidly annealed hematite photoanode with a photocurrent density of 2.83 mA cm^(-2)at 1.7 VRHEto drive the full-reaction. We also present Cu-alloys electrocatalysis extended from CuInSnS4, which are superior in both activity and selectivity for CO_(2)RR. Specifically, the screened CuInSn achieves a CO_(2)to HCOOH Faradaic efficiency of 93% at a cell voltage of-2.0 V by assembling into artificial photosynthesis cell. The stability test of IT exhibits less than 3% degradation over 24 h. Furthermore, in-situ Raman spectroscopy reveals that both CO_(3)^(-2)and CO_(2)are involved in CO_(2)RR as reactants. The preferential affinity of C for H in the ^(*)HCO_(2)intermediate enables an improved HCOOH-selectivity, highlighting the role of multifunctional Cu in reducing the cell voltage and enhancing the photocurrent density.

Strategic comparison of membrane-assisted and membrane-less water electrolyzers and their potential application in direct seawater splitting(DSS)

Electrocatalytic splitting of water by means of renewable energy as the electricity supply is one of the most promising methods for storing green renewable energy as hydrogen. Although two-thirds of the earth’s surface is covered with water, there is inadequacy of freshwater in most parts of the world. Hence, splitting seawater instead of freshwater could be a truly sustainable alternative. However, direct seawater splitting faces challenges because of the complex composition of seawater. The composition, and hence, the local chemistry of seawater may vary depending on its origin, and in most cases, tracking of the side reactions and standardizing and customizing the catalytic process will be an extra challenge. The corrosion of catalysts and competitive side reactions due to the presence of various inorganic and organic pollutants create challenges for developing stable electro-catalysts. Hence, seawater splitting generally involves a two-step process, i.e., purification of seawater using reverse osmosis and then subsequent fresh water splitting. However, this demands two separate chambers and larger space, and increases complexity of the reactor design. Recently, there have been efforts to directly split seawater without the reverse osmosis step. Herein, we represent the most recent innovative approaches to avoid the two-step process, and compare the potential application of membrane-assisted and membrane-less electrolyzers in direct seawater splitting(DSS). We particularly discuss the device engineering, and propose a novel electrolyzer design strategies for concentration gradient based membrane-less microfluidic electrolyzer.

A techno-economic and life cycle assessment for the production of green methanol from CO_(2): catalyst and process bottlenecks

The success of catalytic schemes for the large-scale valorization of CO_(2) does not only depend on the development of active,selective and stable catalytic materials but also on the overall process design.Here we present a multidisciplinary study(from catalyst to plant and techno-economic/lifecycle analysis)for the production of green methanol from renewable H2 and CO_(2).We combine an in-depth kinetic analysis of one of the most promising recently reported methanol-synthesis catalysts(InCo)with a thorough process simulation and techno-economic assessment.We then perform a life cycle assessment of the simulated process to gauge the real environmental impact of green methanol production from CO_(2).Our results indicate that up to 1.75 ton of CO_(2) can be abated per ton of produced methanol only if renewable energy is used to run the process,while the sensitivity analysis suggest that either rock-bottom H2 prices(1.5$kg1)or severe CO_(2) taxation(300$per ton)are needed for a profitable methanol plant.Besides,we herein highlight and analyze some critical bottlenecks of the process.Especial attention has been paid to the contribution of H2 to the overall plant costs,CH4 trace formation,and purity and costs of raw gases.In addition to providing important information for policy makers and industrialists,directions for catalyst(and therefore process)improvements are outlined.

Eulerian-Lagranigan simulation of aerosol evolution in turbulent mixing layer

The formation and evolution of aerosol in turbulent flows are ubiquitous in both industrial processes and nature. The intricate interaction of turbulent mixing and aerosol evolution in a canonical turbulent mixing layer was investigated by a direct numerical simulation （DNS） in a recent study （Zhou, K., Attili, A., Alshaarawi, A., and Bisetti, F. Simulation of aerosol nucleation and growth in a turbulent mixing layer. Physics of Fluids, 26, 065106 （2014））. In this work, Monte Carlo （MC） simulation of aerosol evolution is carried out along Lagrangian trajectories obtained in the previous simulation, in order to quantify the error of the moment method used in the previous simulation. Moreover, the particle size distribution （PSD）, not available in the previous works, is also investigated. Along a fluid parcel moving through the turbulent flow, temperature and vapor concentration exhibit complex fluctuations, triggering complicate aerosol processes and rendering complex PSD. However, the mean PSD is found to be bi-modal in most of the mixing layer except that a tri-modal distribution is found in the turbulent transition region. The simulated PSDs agree with the experiment observations available in the literature. A different explanation on the formation of such PSDs is provided.

A New Method of Simulating Fiber Suspensions and Applications to Channel Flows

A successive iteration method is proposed to numerically simulate fiber suspensions.The computational field is discretized with the collocated finite volume method,and an ergodic hypothesis is adopted to gready accelerate the solution to the Fokker-Planck equation.The method is employed in channel flows with different fiber volume fractions and aspect ratios,and its effectiveness is proved.The numerical results show that the existence of fibers significantly changes the pressure distribution,and the fiber aspect ratio has a greater effect on the velocity profile than on the volume faction.At the center of the channel,the velocity increases along the streamwise direction,while the velocity near the wall decreases slightly.The uncoupling and coupling solutions of the additional stress of the fiber suspensions are quite different.

A Lagrangian-based flame index for the transported probability density function method

We propose a new flame index for the transported probability density function(PDF) method. The flame index uses mixing flux projections of Lagrangian particles on mixture fraction and progress variable directions as the metrics to identify the combustion mode, with the Burke-Schumann solution as a reference. A priori validation of the flame index is conducted with a series of constructed turbulent partially premixed reactors. It indicates that the proposed flame index is able to identify the combustion mode based on the subgrid mixing information. The flame index is then applied the large eddy simulation/PDF datasets of turbulent partially premixed jet flames. Results show that the flame index separate different combustion modes and extinction correctly. The proposed flame index provides a promising tool to analyze and model the partially premixed flames adaptively.

Numerical Simulation of the High-Boosting Influence on Mixing,Combustion and Emissions of High-Power-Density Engine

Future high-power-density engines require high level of intake boost.However,the effects of boosting on mixing,combustion and emissions in existing studies are inconsistent.In this paper,the mixing,combustion and emission characteristics with intake pressures of 100-400 kPa at low,medium and high loads are studied.The results show that the increase of intake pressures is conducive to the enhancement of air entrainment,while the air utilization ratios are reduced,thus requiring injection pressure to be optimized to effectively improve the mixing.For the intake pressures of 100 kPa,the average chemical reaction path is low-temperature reaction route,while the path of higher intake pressures is dominated by high-temperature pyrolysis.For soot emissions,when the equivalence ratio is lower than 0.175,the oxygen in the cylinder is suficient,so the effect of temperature decrease is more significant,which leads to the increase of soot emissions with the increase of intake pressures.Otherwise,the effect of increasing oxygen concentration is more significant,so soot decreases accordingly.When the peak of global temperature is lower than 1800 K,the effect of the increase of oxygen concentration is more dominant,so the NO_(x)emission increases with the increase of intake pressures.Otherwise,the rule of NOxemissions is consistent with temperature changes.

基于双进度变量的非预混火焰NO生成大涡模拟研究

本文基于火焰面/进度变量(FPV)模型框架,提出了一种双进度变量NO输运修正模型。将该模型与大涡模拟相结合,对Sandia非预混甲烷射流火焰开展了数值模拟。结果表明,该模型对于NO浓度的预测精度相比于文献中结果显著提升。进一步详细分析了具有火焰不稳定性的Sandia火焰F的NO生成特性,当雷诺数从22400升高至44800时,火焰F相比于火焰D,中心轴线处的NO峰值下降约28%。模拟结果成功捕捉到了雷诺数升高导致的强局部熄火现象,以及该条件下火焰温度降低,NO生成受到抑制的趋势。

液氢无损储存回热式热驱动制冷机的数值模拟

本文针对液氢储罐零蒸发需求,利用SAGE软件对300 W@20 K回热式热驱动制冷机系统开展了模拟计算和优化设计,验证了双效自由活塞斯特林制冷机和热声驱动脉管制冷机两种方案用于液氢无损储存系统的可行性。结果表明,在平均压力5 MPa,工作频率50 Hz,加热温度500℃的工况下,双效自由活塞斯特林制冷机的整机[火用]效率可达到19.4%,而热声驱动脉管制冷机为14.3%。但斯特林系统由于采用定参数谐振活塞耦合,难以实现多工况匹配,导致其对平均压力、加热温度等运行参数的变化十分敏感。相比之下,热声系统完全无运动部件,具有极佳的工况适应性,因此热声驱动脉管制冷机系统在液氢无损储存应用领域将是一种颇具潜力的解决方案。

Development of a simplified n-heptane/methane model for high-pressure direct-injection natural gas marine engines

High-pressure direct-injection (HPDI) of natu- ral gas is one of the most promising solutions for future ship engines, in which the combustion process is mainly controlled by the chemical kinetics. However, the employment of detailed chemical models for the multi-dimensional combustion simulation is significantly expensive due to the large scale of the marine engine. In the present paper, a reduced n-heptane/methane model consisting of 35-step reactions was constructed using multiple reduction approaches. Then this model was further reduced to include only 27 reactions by utilizing the HyChem (Hybrid Chemistry) method. An overall good agreement with the experimentally measured ignition delay data of both n-heptane and methane for these two reduced models was achieved and reasonable predictions for the measured laminar flame speeds were obtained for the 35-step model. But the 27-step model cannot predict the laminar flame speed very well. In addition, these two reduced models were both able to reproduce the experimentally measured in-cylinder pressure and heat release rate profiles for a HPDI natural gas marine engine, the highest error of predicted combustion phase being 6.5%. However, the engine-out CO emission was over-predicted and the highest error of predicted NOx emission was less than 12.9%. The predicted distributions of temperature and equivalence ratio by the 35-step and 27-step models are similar to those of the 334-step model. However, the predicted distributions of OH and CH2O are significantly different from those of the 334-step model. In short, the reduced chemical kinetic models developed provide a high-efficient and dependable method to simulate the characteristics of combustion and emissions in HPDI natural gas marine engines.

非预混旋流火焰中部熄火及重新稳燃机理研究

本文利用5kHz同步PIV/OH-PLIF实验装置,结合大涡模拟(LES)耦合PDF燃烧模型,系统研究燃料中心喷射下非预混旋流火焰中部熄火及再次稳燃机理,对比了两种旋流器出口结构的影响。结果表明,LES-PDF模型可以准确地捕捉到旋流流场分布及火焰形态,包括中部熄火及火焰重新稳定。相比于直燃道的结构,扩张燃道的存在引导了更宽的回流区,改善了中部熄火现象,两种结构对其下游的主火焰再次稳燃高度影响不大。中央燃气射流带来的高标量耗散率使得热损失变大,从而引起中部熄火。同时进一步促进了CH_(4)与空气的预先混合及部分反应前置物(CH_(2)O),为非预混旋流火焰在下游重新稳燃提供了有利条件。通过对火焰再次稳燃处OH反应项及扩散项的分析,发现反应项占据主导地位,部分预混火焰传播为再次稳燃的主要机理。

Predicting entropy and heat capacity of hydrocarbons using machine learning

Chemical substances are essential in all aspects of human life,and understanding their properties is essential for developing chemical systems.The properties of chemical species can be accurately obtained by experiments or ab initio computational calculations;however,these are time-consuming and costly.In this work,machine learning models(ML)for estimating entropy,S,and constant pressure heat capacity,Cp,at 298.15 K,are developed for alkanes,alkenes,and alkynes.The training data for entropy and heat capacity are collected from the literature.Molecular descriptors generated using alvaDesc software are used as input features for the ML models.Support vector regression(SVR),v-support vector regression(v-SVR),and random forest regression(RFR)algorithms were trained with K-fold cross-validation on two levels.The first level assessed the models’performance,and the second level generated the final models.Between the three ML models chosen,SVR shows better performance on the test dataset.The SVR model was then compared against traditional Benson’s group additivity to illustrate the advantages of using the ML model.Finally,a sensitivity analysis is performed to find the most critical descriptors in the property estimations.