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 photoanod...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.展开更多
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 surfa...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.展开更多
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 pre...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.展开更多
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 lay...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.展开更多
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 accele...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.展开更多
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 t...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.展开更多
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 emis...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.展开更多
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 employ...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.展开更多
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 experimen...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.展开更多
基金financially supported by the National Key R&D Program of China (2018YFE0208500)the National Natural Science Foundation of China (Grants No. 22072022)funded by King Abdullah University of Science and Technology (KAUST) through the baseline funding (BAS/1/1413-01-01)。
文摘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.
基金King Abdullah University of Science and Technology for funding through the funding grant (BAS/1/1413-01-01)the Engineering and Physical Sciences Research Council (EPSRC,EP/V027433/1)+1 种基金the Royal Society (RGSR1211080IESR2212115)。
文摘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.
基金support from the King Abdullah University of Science and Technology(KAUST).T.Cordero-Lanzac and A.T.Aguayo acknowledge the financial support received from the Spanish Ministry of Science and Innovation with some ERDF funds(CTQ2016-77812-R)the Basque Government(IT1218-19)+2 种基金T.Cordero-Lanzac also acknowledges the Spanish Ministry of Education,Culture and Sport for the award of his FPU grant(FPU15-01666)A.Navajas and L.M.Gandía gratefully acknowledge the financial support from Spanish Ministerio de Ciencia,Innovación y Universidades,and the European Regional Development Fund(ERDF/FEDER)(grant RTI2018-096294-B-C31)L.M.Gandía also thanks Banco de Santander and Universidad Pública de Navarra for their financial support under“Programa de Intensificación de la Investigación 2018”initiative.
文摘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.
基金Project supported by the National Natural Science Foundation of China(Nos.11402179 and11572274)
文摘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.
基金Supported by the National Natural Science Foundation of China under Grant No 11132008.
文摘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.
基金sponsored by King Abdullah University of Science and Technology(KAUST)the National Natural Science Foundation of China(Grant No.91841302)。
文摘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.
基金supported by the Natural Science Foundation of China(No.51921004 and U2241262)。
文摘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.
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.91941102 and 51922076).
文摘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.
基金This work was supported by King Abdullah University of Science and Technology(KAUST)Office of Sponsored Research under the award number OSR-2019-CRG7-4077the KAUST Clean Fuels Consortium(KCFC)and its member companies.
文摘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.