To reduce global warming,many countries are shifting to sustainable energy production systems.Solid oxide electrolysis cells(SOECs)are being considered due to their high hydrogen generation efficiency.However,low fara...To reduce global warming,many countries are shifting to sustainable energy production systems.Solid oxide electrolysis cells(SOECs)are being considered due to their high hydrogen generation efficiency.However,low faradaic efficiency in scaling SOEC technology affects costs and limits large-scale adoption of hydrogen as fuel.This review covers SOECs’critical aspects:current state-of-the-art anode,cathode,and electrolyte materials,operational and materials parameters affecting faradaic efficiency,and computational modeling techniques to resolve bottlenecks affecting SOEC faradaic efficiency.展开更多
Reproducible wafer-scale growth of two-dimensional(2D)materials using the Chemical Vapor Deposition(CVD)process with precise control over their properties is challenging due to a lack of understanding of the growth me...Reproducible wafer-scale growth of two-dimensional(2D)materials using the Chemical Vapor Deposition(CVD)process with precise control over their properties is challenging due to a lack of understanding of the growth mechanisms spanning over several length scales and sensitivity of the synthesis to subtle changes in growth conditions.A multiscale computational framework coupling Computational Fluid Dynamics(CFD),Phase-Field(PF),and reactive Molecular Dynamics(MD)was developed–called the CPM model–and experimentally verified.Correlation between theoretical predictions and thorough experimental measurements for a Metal-Organic CVD(MOCVD)-grown WSe_(2)model material revealed the full power of this computational approach.Large-area uniform 2D materials are synthesized via MOCVD,guided by computational analyses.The developed computational framework provides the foundation for guiding the synthesis of wafer-scale 2D materials with precise control over the coverage,morphology,and properties,a critical capability for fabricating electronic,optoelectronic,and quantum computing devices.展开更多
Empirical interatomic potentials require optimization of force field parameters to tune interatomic interactions to mimic ones obtained by quantum chemistry-based methods.The optimization of the parameters is complex ...Empirical interatomic potentials require optimization of force field parameters to tune interatomic interactions to mimic ones obtained by quantum chemistry-based methods.The optimization of the parameters is complex and requires the development of new techniques.Here,we propose an INitial-DEsign Enhanced Deep learning-based OPTimization(INDEEDopt)framework to accelerate and improve the quality of the ReaxFF parameterization.The procedure starts with a Latin Hypercube Design(LHD)algorithm that is used to explore the parameter landscape extensively.The LHD passes the information about explored regions to a deep learning model,which finds the minimum discrepancy regions and eliminates unfeasible regions,and constructs a more comprehensive understanding of physically meaningful parameter space.We demonstrate the procedure here for the parameterization of a nickel–chromium binary force field and a tungsten–sulfide–carbon–oxygen–hydrogen quinary force field.We show that INDEEDopt produces improved accuracies in shorter development time compared to the conventional optimization method.展开更多
Graphite has achieved widespread recognition as an effective solid lubricant due to its high functionality across diverse environmental conditions.Although superlubricity or ultra-low friction is readily observed at t...Graphite has achieved widespread recognition as an effective solid lubricant due to its high functionality across diverse environmental conditions.Although superlubricity or ultra-low friction is readily observed at the graphite basal plane,it has been reported that certain adsorbates from the surrounding environment can deteriorate this friction regime.Here,we conducted a fundamental analysis on the effect of phenol,pentanol,and water adsorbates on the friction of graphite-silica interfaces using molecular dynamics simulations with the reactive force field ReaxFF.First,we evaluated three ReaxFF parameter sets optimized using friction-pertinent properties.It was observed that the force field optimization objective played a major role in the calculated tribological properties.Secondly,parameters such as normal load and motion directionality were investigated.Additionally,adsorption,and binding energy calculations were performed to expand upon the hypothesis that friction may be directly correlated to the interfacial molecular structure rather than binding energy and adsorbate commensuration with graphene.By quantitatively representing the interfacial roughness of each adsorbate,the hypothesis was confirmed by unequivocally explaining the calculated friction coefficients.展开更多
基金Work supported through the INL Laboratory Directed Research&Development(LDRD)Program under DOE Idaho Operations Office Contract DE-AC07-05ID14517.
文摘To reduce global warming,many countries are shifting to sustainable energy production systems.Solid oxide electrolysis cells(SOECs)are being considered due to their high hydrogen generation efficiency.However,low faradaic efficiency in scaling SOEC technology affects costs and limits large-scale adoption of hydrogen as fuel.This review covers SOECs’critical aspects:current state-of-the-art anode,cathode,and electrolyte materials,operational and materials parameters affecting faradaic efficiency,and computational modeling techniques to resolve bottlenecks affecting SOEC faradaic efficiency.
基金This project is partly supported by the University of Alabama,the NSF-CAREER under the NSF cooperative agreement CBET-20426832D Crystal Consortium–Material Innovation Platform(2DCC-MIP)under NSF cooperative agreements DMR-1539916 and DMR-2039351+1 种基金the I/UCRC Center for Atomically Thin Multifunctional Coatings(ATOMIC)seed project SP001-17Y.Z.J.and L.Q.C.also acknowledge the generous support by the Hamer Foundation through a Hamer Professorship.
文摘Reproducible wafer-scale growth of two-dimensional(2D)materials using the Chemical Vapor Deposition(CVD)process with precise control over their properties is challenging due to a lack of understanding of the growth mechanisms spanning over several length scales and sensitivity of the synthesis to subtle changes in growth conditions.A multiscale computational framework coupling Computational Fluid Dynamics(CFD),Phase-Field(PF),and reactive Molecular Dynamics(MD)was developed–called the CPM model–and experimentally verified.Correlation between theoretical predictions and thorough experimental measurements for a Metal-Organic CVD(MOCVD)-grown WSe_(2)model material revealed the full power of this computational approach.Large-area uniform 2D materials are synthesized via MOCVD,guided by computational analyses.The developed computational framework provides the foundation for guiding the synthesis of wafer-scale 2D materials with precise control over the coverage,morphology,and properties,a critical capability for fabricating electronic,optoelectronic,and quantum computing devices.
基金The authors acknowledge partial funding support from U.S.National Science Foundation under Award No.DMR-1842922,DMR-1842952,DMR-1539916,and MRI-1626251.
文摘Empirical interatomic potentials require optimization of force field parameters to tune interatomic interactions to mimic ones obtained by quantum chemistry-based methods.The optimization of the parameters is complex and requires the development of new techniques.Here,we propose an INitial-DEsign Enhanced Deep learning-based OPTimization(INDEEDopt)framework to accelerate and improve the quality of the ReaxFF parameterization.The procedure starts with a Latin Hypercube Design(LHD)algorithm that is used to explore the parameter landscape extensively.The LHD passes the information about explored regions to a deep learning model,which finds the minimum discrepancy regions and eliminates unfeasible regions,and constructs a more comprehensive understanding of physically meaningful parameter space.We demonstrate the procedure here for the parameterization of a nickel–chromium binary force field and a tungsten–sulfide–carbon–oxygen–hydrogen quinary force field.We show that INDEEDopt produces improved accuracies in shorter development time compared to the conventional optimization method.
基金funded by PPG Industries through a project under Cooperative Agreement 2021072-142118 from The National Center for Manufacturing Sciences(NCMS)and the US DoD。
文摘Graphite has achieved widespread recognition as an effective solid lubricant due to its high functionality across diverse environmental conditions.Although superlubricity or ultra-low friction is readily observed at the graphite basal plane,it has been reported that certain adsorbates from the surrounding environment can deteriorate this friction regime.Here,we conducted a fundamental analysis on the effect of phenol,pentanol,and water adsorbates on the friction of graphite-silica interfaces using molecular dynamics simulations with the reactive force field ReaxFF.First,we evaluated three ReaxFF parameter sets optimized using friction-pertinent properties.It was observed that the force field optimization objective played a major role in the calculated tribological properties.Secondly,parameters such as normal load and motion directionality were investigated.Additionally,adsorption,and binding energy calculations were performed to expand upon the hypothesis that friction may be directly correlated to the interfacial molecular structure rather than binding energy and adsorbate commensuration with graphene.By quantitatively representing the interfacial roughness of each adsorbate,the hypothesis was confirmed by unequivocally explaining the calculated friction coefficients.
