Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distribu...Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distributed ranges of the superconductive transition temperature (Tc) for complex oxides, and Tc values for cuprate superconductors. The calculated results indicated that the adjusted ANN can be used to predict superconductive properties for unknown oxides.展开更多
An artificial localized corrosion system is assembled and some parameters related to the localized corrosion in active dissolution state (i.e., non-passive state) have been studied. The results showed that the develop...An artificial localized corrosion system is assembled and some parameters related to the localized corrosion in active dissolution state (i.e., non-passive state) have been studied. The results showed that the developed electrochemical system can satisfactorily imitate a naturally formed localized corrosion and the coupling current can indicate the maximum localized propagating rate. In this artificial system, the anodic dissolution reaction followed the auto-catalytic mechanism. The localized corrosion current density was dependent on the area ratio R of the cathode to the occluded anode. While R was equal to or more than 6, the coupling current reached at a maximum value and did not alter with the increase in R-value. Therefore, R=7 is chosen as one of these optimum parameters used in constructing the system, with which the biggest galvanic current might be obtained. In contrast, the thickness of the polymer filler separating the occluded anode area from the bulk electrolyte solution and the volume of the occluded anode area did not affect the corrosion current obviously. They might affect the response time to approach a steady state.展开更多
The Delta-perturbation expansion method, a kind of new perturbation technique depending upon an artificial parameter Delta was studied. The study reveals that the method exits some advantages, but also exits some limi...The Delta-perturbation expansion method, a kind of new perturbation technique depending upon an artificial parameter Delta was studied. The study reveals that the method exits some advantages, but also exits some limitations. To overcome the limitations, the so-called linearized perturbation method proposed by HE Ji-huan can be powerfully applied.展开更多
A longstanding challenge in materials science has been the computational modeling of interfaces between materials with different lattice parameters.Traditional approaches using plane-wave basis sets require either int...A longstanding challenge in materials science has been the computational modeling of interfaces between materials with different lattice parameters.Traditional approaches using plane-wave basis sets require either introducing artificial strain through unified lattice parameters or constructing prohibitively large supercells to accommodate the mismatch.These limitations have often deterred researchers from investigating large,mismatched interfaces,creating a gap in the understanding of these important systems.This work introduces an innovative algorithm that adaptively tunes the plane-wave basis sets to match the periodic structure of each material across the interface.By eliminating the need for extensive supercells or compromised lattice parameters,this new method reduces computational costs while retaining reliable results.The ability to efficiently calculate the eigen-energies of such mismatched systems,a crucial step for full density functional theory(DFT)calculations,is demonstrated with two dimensional versions of InAs/Si and SiC/Si interface potentials.展开更多
文摘Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distributed ranges of the superconductive transition temperature (Tc) for complex oxides, and Tc values for cuprate superconductors. The calculated results indicated that the adjusted ANN can be used to predict superconductive properties for unknown oxides.
文摘An artificial localized corrosion system is assembled and some parameters related to the localized corrosion in active dissolution state (i.e., non-passive state) have been studied. The results showed that the developed electrochemical system can satisfactorily imitate a naturally formed localized corrosion and the coupling current can indicate the maximum localized propagating rate. In this artificial system, the anodic dissolution reaction followed the auto-catalytic mechanism. The localized corrosion current density was dependent on the area ratio R of the cathode to the occluded anode. While R was equal to or more than 6, the coupling current reached at a maximum value and did not alter with the increase in R-value. Therefore, R=7 is chosen as one of these optimum parameters used in constructing the system, with which the biggest galvanic current might be obtained. In contrast, the thickness of the polymer filler separating the occluded anode area from the bulk electrolyte solution and the volume of the occluded anode area did not affect the corrosion current obviously. They might affect the response time to approach a steady state.
文摘The Delta-perturbation expansion method, a kind of new perturbation technique depending upon an artificial parameter Delta was studied. The study reveals that the method exits some advantages, but also exits some limitations. To overcome the limitations, the so-called linearized perturbation method proposed by HE Ji-huan can be powerfully applied.
基金support of The Boeing Company,as part of the Boeing-Technion Sustainable Aviation Fuel Innovation CenterWe sincerely thank Boeing for their valuable support and collaboration.This project was also conducted within the framework of the Guy Sella Memorial Project at Technion,established by SolarEdge Technologies LTD.Partial funding from The Israeli Sustainable Aviation Fuel Knowledge Center–iSAF,supported by The Israeli Ministry of Innovation,Science,and Technology,is gratefully acknowledgedThis article is based upon work from COST IG18234(NanoCatML),supported by COST(European Cooperation in Science and Technology)http://www.cost.eu.
文摘A longstanding challenge in materials science has been the computational modeling of interfaces between materials with different lattice parameters.Traditional approaches using plane-wave basis sets require either introducing artificial strain through unified lattice parameters or constructing prohibitively large supercells to accommodate the mismatch.These limitations have often deterred researchers from investigating large,mismatched interfaces,creating a gap in the understanding of these important systems.This work introduces an innovative algorithm that adaptively tunes the plane-wave basis sets to match the periodic structure of each material across the interface.By eliminating the need for extensive supercells or compromised lattice parameters,this new method reduces computational costs while retaining reliable results.The ability to efficiently calculate the eigen-energies of such mismatched systems,a crucial step for full density functional theory(DFT)calculations,is demonstrated with two dimensional versions of InAs/Si and SiC/Si interface potentials.
