This article delivers a robust overview of potential electrode materials for use in symmetrical solid oxide fuel cells(S-SOFCs),a relatively new SOFC technology.To this end,this article provides a comprehensive review...This article delivers a robust overview of potential electrode materials for use in symmetrical solid oxide fuel cells(S-SOFCs),a relatively new SOFC technology.To this end,this article provides a comprehensive review of recent advances and progress in electrode materials for S-SOFC,discussing both the selection of materials and the challenges that come with making that choice.This article discussed the relevant factors involved in developing electrodes with nano/microstructure.Nanocomposites,e.g.,non-cobalt and lithiated materials,are only a few of the electrode types now being researched.Furthermore,the phase structure and microstructure of the produced materials are heavily influenced by the synthesis procedure.Insights into the possibilities and difficulties of the material are discussed.To achieve the desired microstructural features,this article focuses on a synthesis technique that is either the most recent or a better iteration of an existing process.The portion of this analysis that addresses the risks associated with manufacturing and the challenges posed by materials when fabricating S-SOFCs is the most critical.This article also provides important and useful recommendations for the strategic design of electrode materials researchers.展开更多
1.Why hydrogen?The concept of the“hydrogen economy”was first coined by Prof.John Bockris during a talk he gave in 1970 at the General Motors Technical Center.Bockris’s talk introduced the vision of a world economy ...1.Why hydrogen?The concept of the“hydrogen economy”was first coined by Prof.John Bockris during a talk he gave in 1970 at the General Motors Technical Center.Bockris’s talk introduced the vision of a world economy in which energy was carried in the form of hydrogen.展开更多
Increasing electrode thickness can substantially enhance the specific energy of lithium-ion batteries;however,ionic transport,electronic conductivity,and ink rheology are current barriers to adoption.Here,a novel appr...Increasing electrode thickness can substantially enhance the specific energy of lithium-ion batteries;however,ionic transport,electronic conductivity,and ink rheology are current barriers to adoption.Here,a novel approach using a mixed xanthan gum and locust bean gum binder to construct ultrathick electrodes is proposed to address above issues.After combining aqueous binder with single-walled carbon nanotubes(SWCNT),active material(LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)) and subsequent vacuum freeze-drying,highly aligned,and low-tortuosity structures with a porosity of ca.50%can be achieved with an average pore size of 10μm,whereby the gum binder-SWCNT-NMC811 forms vertical structures supported by tissue-like binder/SWCNT networks allowing for excellent electronic conducting phase percolation.As a result,ultra-thick electrodes with a mass loading of about 511 mg cm^(−2) and 99.5 wt%active materials have been demonstrated with a remarkable areal capacity of 79.3 mAh cm^(−2),which is the highest value reported so far.This represents a>25×improvement compared with conventional electrodes with an areal capacity of about 3 mAh cm^(−2).This route also can be expanded to other electrode materials,such as LiFePO_(4) and Li_(4)Ti_(5)O_(12),and thus opens the possibility for low-cost and sustainable ultra-thick electrodes with increased specific energy for future lithium-ion batteries.展开更多
Mixed ionic electronic conductors(MIECs)have attracted increasing attention as anode materials for solid oxide fuel cells(SOFCs)and they hold great promise for lowering the operation temperature of SOFCs.However,there...Mixed ionic electronic conductors(MIECs)have attracted increasing attention as anode materials for solid oxide fuel cells(SOFCs)and they hold great promise for lowering the operation temperature of SOFCs.However,there has been a lack of understanding of the performance-limiting factors and guidelines for rational design of composite metal-MIEC electrodes.Using a newly-developed approach based on 3 D-tomography and electrochemical impedance spectroscopy,here for the first time we quantify the contribution of the dual-phase boundary(DPB)relative to the three-phase boundary(TPB)reaction pathway on real MIEC electrodes.A new design strategy is developed for Ni/gadolinium doped ceria(CGO)electrodes(a typical MIEC electrode)based on the quantitative analyses and a novel Ni/CGO fiber-matrix structure is proposed and fabricated by combining electrospinning and tape-casting methods using commercial powders.With only 11.5 vol%nickel,the designer Ni/CGO fiber-matrix electrode shows 32%and 67%lower polarization resistance than a nano-Ni impregnated CGO scaffold electrode and conventional cermet electrode respectively.The results in this paper demonstrate quantitatively using real electrode structures that enhancing DPB and hydrogen kinetics are more efficient strategies to enhance electrode performance than simply increasing TPB.展开更多
The computational demands of 3D continuum models for proton exchange membrane fuel cells remain substantial. One prevalent approach is the hierarchical model combining a 2D/3D flow field with a 1D sub-model for the ca...The computational demands of 3D continuum models for proton exchange membrane fuel cells remain substantial. One prevalent approach is the hierarchical model combining a 2D/3D flow field with a 1D sub-model for the catalyst layers and membrane. However, existing studies often simplify the 1D domain to a linearized 0D lumped model, potentially resulting in significant errors at high loads. In this study, we present a computationally efficient neural network driven 3D+1D model for proton exchange membrane fuel cells. The 3D sub-model captures transport in the gas channels and gas diffusion layers and is coupled with a 1D electrochemical sub-model for microporous layers, membrane, and catalyst layers. To reduce computational intensity of the full 1D description, a neural network surrogates the 1D electrochemical sub-model for coupling with the 3D domain. Trained by model-generated large synthetic datasets, the neural network achieves root mean square errors of less than 0.2%. The model is validated against experimental results under various relative humidities. It is then employed to investigate the nonlinear distribution of internal states under different operating conditions. With the neural network operating at 0.5% of the computing cost of the 1D sub-model, the hybrid model preserves a detailed and nonlinear representation of the internal fuel cell states while maintaining computational costs comparable to conventional 3D+0D models. The presented hybrid data-driven and physical modeling framework offers high accuracy and computing speed across a broad spectrum of operating conditions, potentially aiding the rapid optimization of both the membrane electrode assembly and the gas channel geometry.展开更多
The generation of multiphase porous electrode microstructures is a critical step in the optimisation of electrochemical energy storage devices.This work implements a deep convolutional generative adversarial network(D...The generation of multiphase porous electrode microstructures is a critical step in the optimisation of electrochemical energy storage devices.This work implements a deep convolutional generative adversarial network(DC-GAN)for generating realistic nphase microstructural data.The same network architecture is successfully applied to two very different three-phase microstructures:A lithium-ion battery cathode and a solid oxide fuel cell anode.A comparison between the real and synthetic data is performed in terms of the morphological properties(volume fraction,specific surface area,triple-phase boundary)and transport properties(relative diffusivity),as well as the two-point correlation function.The results show excellent agreement between datasets and they are also visually indistinguishable.By modifying the input to the generator,we show that it is possible to generate microstructure with periodic boundaries in all three directions.This has the potential to significantly reduce the simulated volume required to be considered“representative”and therefore massively reduce the computational cost of the electrochemical simulations necessary to predict the performance of a particular microstructure during optimisation.展开更多
基金the Fundamental Research Grant Scheme (FRGS),grant No.FRGS/1/2021/TK0/UKM/01/5 funded by the Ministry of Higher Education (MOHE)。
文摘This article delivers a robust overview of potential electrode materials for use in symmetrical solid oxide fuel cells(S-SOFCs),a relatively new SOFC technology.To this end,this article provides a comprehensive review of recent advances and progress in electrode materials for S-SOFC,discussing both the selection of materials and the challenges that come with making that choice.This article discussed the relevant factors involved in developing electrodes with nano/microstructure.Nanocomposites,e.g.,non-cobalt and lithiated materials,are only a few of the electrode types now being researched.Furthermore,the phase structure and microstructure of the produced materials are heavily influenced by the synthesis procedure.Insights into the possibilities and difficulties of the material are discussed.To achieve the desired microstructural features,this article focuses on a synthesis technique that is either the most recent or a better iteration of an existing process.The portion of this analysis that addresses the risks associated with manufacturing and the challenges posed by materials when fabricating S-SOFCs is the most critical.This article also provides important and useful recommendations for the strategic design of electrode materials researchers.
文摘1.Why hydrogen?The concept of the“hydrogen economy”was first coined by Prof.John Bockris during a talk he gave in 1970 at the General Motors Technical Center.Bockris’s talk introduced the vision of a world economy in which energy was carried in the form of hydrogen.
基金supported by the National Key Research and Development Program of China(2016YFB0100300)National Nature Science Foundation of China(no.U1864213)+2 种基金the EPSRC Joint UK-India Clean Energy Centre(JUICE)(EP/P003605/1)the EPSRC Multi-Scale Modelling project(EP/S003053/1)the UK Engineering and Physical Council(EPSRC)for funding under EP/S000933/1.
文摘Increasing electrode thickness can substantially enhance the specific energy of lithium-ion batteries;however,ionic transport,electronic conductivity,and ink rheology are current barriers to adoption.Here,a novel approach using a mixed xanthan gum and locust bean gum binder to construct ultrathick electrodes is proposed to address above issues.After combining aqueous binder with single-walled carbon nanotubes(SWCNT),active material(LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)) and subsequent vacuum freeze-drying,highly aligned,and low-tortuosity structures with a porosity of ca.50%can be achieved with an average pore size of 10μm,whereby the gum binder-SWCNT-NMC811 forms vertical structures supported by tissue-like binder/SWCNT networks allowing for excellent electronic conducting phase percolation.As a result,ultra-thick electrodes with a mass loading of about 511 mg cm^(−2) and 99.5 wt%active materials have been demonstrated with a remarkable areal capacity of 79.3 mAh cm^(−2),which is the highest value reported so far.This represents a>25×improvement compared with conventional electrodes with an areal capacity of about 3 mAh cm^(−2).This route also can be expanded to other electrode materials,such as LiFePO_(4) and Li_(4)Ti_(5)O_(12),and thus opens the possibility for low-cost and sustainable ultra-thick electrodes with increased specific energy for future lithium-ion batteries.
基金the financial support from EPSRC(EP/P024807/1,EP/M014045/1,EP/S000933/1 and EP/N009924/1)by the EPSRC energy storage for low carbon grids project(EP/K002252/1)+3 种基金the EPSRC Joint UK-India Clean Energy center(JUICE)(EP/P003605/1)the Integrated Development of Low-Carbon Energy Systems(IDLES)project(EP/R045518/1)the Innovate UK BAFTA project,the Innovate UK for Advanced Battery Lifetime Extension(ABLE)project for funding underthe China Scholarship Council。
文摘Mixed ionic electronic conductors(MIECs)have attracted increasing attention as anode materials for solid oxide fuel cells(SOFCs)and they hold great promise for lowering the operation temperature of SOFCs.However,there has been a lack of understanding of the performance-limiting factors and guidelines for rational design of composite metal-MIEC electrodes.Using a newly-developed approach based on 3 D-tomography and electrochemical impedance spectroscopy,here for the first time we quantify the contribution of the dual-phase boundary(DPB)relative to the three-phase boundary(TPB)reaction pathway on real MIEC electrodes.A new design strategy is developed for Ni/gadolinium doped ceria(CGO)electrodes(a typical MIEC electrode)based on the quantitative analyses and a novel Ni/CGO fiber-matrix structure is proposed and fabricated by combining electrospinning and tape-casting methods using commercial powders.With only 11.5 vol%nickel,the designer Ni/CGO fiber-matrix electrode shows 32%and 67%lower polarization resistance than a nano-Ni impregnated CGO scaffold electrode and conventional cermet electrode respectively.The results in this paper demonstrate quantitatively using real electrode structures that enhancing DPB and hydrogen kinetics are more efficient strategies to enhance electrode performance than simply increasing TPB.
基金support of the Henry Royce Institute for advanced materials through the Materials Challenge Accelerator Programme(MCAP)funded from a grant provided by the Engineering and Physical Sciences Research Council(EP/X527257/1).
文摘The computational demands of 3D continuum models for proton exchange membrane fuel cells remain substantial. One prevalent approach is the hierarchical model combining a 2D/3D flow field with a 1D sub-model for the catalyst layers and membrane. However, existing studies often simplify the 1D domain to a linearized 0D lumped model, potentially resulting in significant errors at high loads. In this study, we present a computationally efficient neural network driven 3D+1D model for proton exchange membrane fuel cells. The 3D sub-model captures transport in the gas channels and gas diffusion layers and is coupled with a 1D electrochemical sub-model for microporous layers, membrane, and catalyst layers. To reduce computational intensity of the full 1D description, a neural network surrogates the 1D electrochemical sub-model for coupling with the 3D domain. Trained by model-generated large synthetic datasets, the neural network achieves root mean square errors of less than 0.2%. The model is validated against experimental results under various relative humidities. It is then employed to investigate the nonlinear distribution of internal states under different operating conditions. With the neural network operating at 0.5% of the computing cost of the 1D sub-model, the hybrid model preserves a detailed and nonlinear representation of the internal fuel cell states while maintaining computational costs comparable to conventional 3D+0D models. The presented hybrid data-driven and physical modeling framework offers high accuracy and computing speed across a broad spectrum of operating conditions, potentially aiding the rapid optimization of both the membrane electrode assembly and the gas channel geometry.
基金This work was supported by funding from both the CONACYT-SENER fund and the EPSRC Faraday Institution Multi-Scale Modelling project(https://faraday.ac.uk/,EP/S003053/1,grant number FIRG003).
文摘The generation of multiphase porous electrode microstructures is a critical step in the optimisation of electrochemical energy storage devices.This work implements a deep convolutional generative adversarial network(DC-GAN)for generating realistic nphase microstructural data.The same network architecture is successfully applied to two very different three-phase microstructures:A lithium-ion battery cathode and a solid oxide fuel cell anode.A comparison between the real and synthetic data is performed in terms of the morphological properties(volume fraction,specific surface area,triple-phase boundary)and transport properties(relative diffusivity),as well as the two-point correlation function.The results show excellent agreement between datasets and they are also visually indistinguishable.By modifying the input to the generator,we show that it is possible to generate microstructure with periodic boundaries in all three directions.This has the potential to significantly reduce the simulated volume required to be considered“representative”and therefore massively reduce the computational cost of the electrochemical simulations necessary to predict the performance of a particular microstructure during optimisation.
