Environmental barrier coatings(EBC)are crucial for the use of SiC-based ceramic matrix composites in high-temperature combustion environments,yet knowledge of oxygen diffusion in these coatings is limited.This study i...Environmental barrier coatings(EBC)are crucial for the use of SiC-based ceramic matrix composites in high-temperature combustion environments,yet knowledge of oxygen diffusion in these coatings is limited.This study investigates oxygen diffusion dynamics in theβ-RE_(2)Si_(2)O_(7)system to minimize oxygen penetration in rare earth disilicates.We analyze defect formation energy under varying oxygen conditions,identifying key diffusion mechanisms.In oxygen-rich environments,the most favorable neutral interstitial oxygen diffuses along the[110]direction.In oxygen-poor conditions,neutral oxygen vacancies rotate around Y and Si atoms,exhibiting a diffusivity of 6.59×10^(−22)m^(2)/s at 1500 K forβ-Yb_(2)Si_(2)O_(7).Under intermediate oxygen levels,charged interstitial oxygen diffuses via concerted interstitialcy along the[001]direction with a diffusivity of 6.21×10^(−17)m^(2)/s.Additionally,alloying rare earth Y with Er and Yb increases diffusion barriers,contributing to improved EBC performance in extreme environments.The insights gained provides valuable guidance for designing robust coatings tailored to withstand extreme operational environments.展开更多
Ni-Co-Cr-Al-Fe-based high-entropy alloys(HEAs)have been demonstrated to possess exceptional oxidation resistance,rendering them promising candidates as bond coats to protect critical components in turbine power system...Ni-Co-Cr-Al-Fe-based high-entropy alloys(HEAs)have been demonstrated to possess exceptional oxidation resistance,rendering them promising candidates as bond coats to protect critical components in turbine power systems.However,with the conventional time-consuming alloy design approach,only a small fraction of Ni-Co-Cr-Al-Fe-based HEAs,focusing on equiatomic compositions,has been explored to date.In this study,we developed an effective design framework with the aid of machine learning(ML)and high throughput computations,enabling the rapid exploration of high-temperature oxidation-resistant non-equiatomic HEAs.This innovative approach leverages ML techniques to swiftly select candidates with superior oxidation resistance within the expansive high-entropy composition landscape.Complemented by a thermodynamic-informed ranking-based selection process,several novel non-equiatomic Ni-Co-Cr-Al-Fe HEA candidates surpassing the oxidation resistance of the state-of-the-art bond coat material MCrAlY have been identified and further experimentally demonstrated.Our findings offer a pathway for the development of advanced bond coats in the realm of next-generation turbine engine technology.展开更多
The n-body instability is investigated with the soft-sphere discrete element method.The divergence of nearby trajectories is quantifed by the dynamical memory time.Using the inverse proportionality between the dynamic...The n-body instability is investigated with the soft-sphere discrete element method.The divergence of nearby trajectories is quantifed by the dynamical memory time.Using the inverse proportionality between the dynamical memory time and the largest Lyapunov exponent,the soft-sphere discrete ele-ment method results are compared to previous hard-sphere molecular dynamics data for the first time.Good agreement is observed at low concentrations and the degree of instability is shown to increase asymptotically with increasing spring sifness.At particle concentrations above 30%,the soft-sphere Lya-punov exponents increase faster than the corresponding hard-sphere data.This paper concludes with a demonstration of how this case study may be used in conjunction with regression testing and code verification activities.展开更多
基金support of the U.S.Department of Energy’s(DOE)Fossil Energy and Carbon Management Advanced Energy Materials Research Program.The research was executed through the National Energy Technology Laboratory’s(NETL)Research and Innovation Center’s Advanced Materials Development Field Work ProposalThis research used resources of the National Energy Research Scientific Computing Center(NERSC),a U.S.DOE Office of Science User Facility supported by the Office of Science under Contract No.DE-AC02-05CH11231 using NERSC awards ALCC-ERCAP0022624 and ALCC-ERCAP0029917.
文摘Environmental barrier coatings(EBC)are crucial for the use of SiC-based ceramic matrix composites in high-temperature combustion environments,yet knowledge of oxygen diffusion in these coatings is limited.This study investigates oxygen diffusion dynamics in theβ-RE_(2)Si_(2)O_(7)system to minimize oxygen penetration in rare earth disilicates.We analyze defect formation energy under varying oxygen conditions,identifying key diffusion mechanisms.In oxygen-rich environments,the most favorable neutral interstitial oxygen diffuses along the[110]direction.In oxygen-poor conditions,neutral oxygen vacancies rotate around Y and Si atoms,exhibiting a diffusivity of 6.59×10^(−22)m^(2)/s at 1500 K forβ-Yb_(2)Si_(2)O_(7).Under intermediate oxygen levels,charged interstitial oxygen diffuses via concerted interstitialcy along the[001]direction with a diffusivity of 6.21×10^(−17)m^(2)/s.Additionally,alloying rare earth Y with Er and Yb increases diffusion barriers,contributing to improved EBC performance in extreme environments.The insights gained provides valuable guidance for designing robust coatings tailored to withstand extreme operational environments.
基金supported by the U.S.Department of Energy through the award#DE-EE0010214We would like to thank the Technology Manager Christian Rawson and Project manager Nick Lalena for the technical guidance and financial support.The computational time provided by the Thorny Flat High-Performance Computer Cluster is highly acknowledged.
文摘Ni-Co-Cr-Al-Fe-based high-entropy alloys(HEAs)have been demonstrated to possess exceptional oxidation resistance,rendering them promising candidates as bond coats to protect critical components in turbine power systems.However,with the conventional time-consuming alloy design approach,only a small fraction of Ni-Co-Cr-Al-Fe-based HEAs,focusing on equiatomic compositions,has been explored to date.In this study,we developed an effective design framework with the aid of machine learning(ML)and high throughput computations,enabling the rapid exploration of high-temperature oxidation-resistant non-equiatomic HEAs.This innovative approach leverages ML techniques to swiftly select candidates with superior oxidation resistance within the expansive high-entropy composition landscape.Complemented by a thermodynamic-informed ranking-based selection process,several novel non-equiatomic Ni-Co-Cr-Al-Fe HEA candidates surpassing the oxidation resistance of the state-of-the-art bond coat material MCrAlY have been identified and further experimentally demonstrated.Our findings offer a pathway for the development of advanced bond coats in the realm of next-generation turbine engine technology.
文摘The n-body instability is investigated with the soft-sphere discrete element method.The divergence of nearby trajectories is quantifed by the dynamical memory time.Using the inverse proportionality between the dynamical memory time and the largest Lyapunov exponent,the soft-sphere discrete ele-ment method results are compared to previous hard-sphere molecular dynamics data for the first time.Good agreement is observed at low concentrations and the degree of instability is shown to increase asymptotically with increasing spring sifness.At particle concentrations above 30%,the soft-sphere Lya-punov exponents increase faster than the corresponding hard-sphere data.This paper concludes with a demonstration of how this case study may be used in conjunction with regression testing and code verification activities.
