Amorphous and non-stoichiometric hafnium oxide(a-HfO_(x))systems are essential for advanced electronic applications due to their superior electrical properties.Simulating their atomic behaviors under electric fields(E...Amorphous and non-stoichiometric hafnium oxide(a-HfO_(x))systems are essential for advanced electronic applications due to their superior electrical properties.Simulating their atomic behaviors under electric fields(Efield)is critical but challenging.Ab-initio molecular dynamics(AIMD)offer high accuracy but is computationally expensive,while classical MD lacks precision.To address this,we develop a charge equilibration integrated graph neural network(CIGNN)model that predicts atomic charge,energy,and force under Efield conditions.Using the CIGNN model and AIMD datasets,we develop a CIGNN-based machine learning potential(CNMP)optimized for a-HfO_(x)systems.The CNMP achieves quantum mechanical accuracy and effectively captures the atomic behaviors and dynamic properties of these systems across varying temperatures,densities,and E_(field)conditions.We expect the CNMP to serve as a valuable tool for studying field-induced phenomena in complex systems and to provide a foundation for advancing innovations in electronic applications.展开更多
In recent years,rumors have been shown to have a significant impact on individual and societal activities.As renewables play an increasingly significant role in electricity markets,certain rumors may deviate the biddi...In recent years,rumors have been shown to have a significant impact on individual and societal activities.As renewables play an increasingly significant role in electricity markets,certain rumors may deviate the bidding behavior of market entities and eventually affect the performance of market operations.In this study,we attempt to reveal the general threats caused by rumors in the context of day-ahead electricity markets considering the integration of volatile renewables.First,we model the propagation of rumors in the societal system considering the weight of propagation resistance,which principally reflects the communication accessibility of market entities.Second,we develop an integrated two-layer network model to uncover the inherent coupling mechanism between market operations and rumor propagation.In particular,the role of electricity market operations on rumor propagation is characterized by changes in the truthfulness of rumors associated with electricity prices.The rumors,in turn,affect the bidding quantities of market entities in electricity market operations.Finally,numerical experiments are conducted on modified IEEE 6-bus and 118-bus systems.The results demonstrate the potential threats of rumors to electricity market operations with different penetration levels of renewables.展开更多
基金supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning No. NRF-2020R1A6C101A202 and NRF-2024M3A7C2045166 and NRF-2021M3I3A1084940 and RS-2023-00257666 and RS-2024-00446683 and RS-2024-00450836.
文摘Amorphous and non-stoichiometric hafnium oxide(a-HfO_(x))systems are essential for advanced electronic applications due to their superior electrical properties.Simulating their atomic behaviors under electric fields(Efield)is critical but challenging.Ab-initio molecular dynamics(AIMD)offer high accuracy but is computationally expensive,while classical MD lacks precision.To address this,we develop a charge equilibration integrated graph neural network(CIGNN)model that predicts atomic charge,energy,and force under Efield conditions.Using the CIGNN model and AIMD datasets,we develop a CIGNN-based machine learning potential(CNMP)optimized for a-HfO_(x)systems.The CNMP achieves quantum mechanical accuracy and effectively captures the atomic behaviors and dynamic properties of these systems across varying temperatures,densities,and E_(field)conditions.We expect the CNMP to serve as a valuable tool for studying field-induced phenomena in complex systems and to provide a foundation for advancing innovations in electronic applications.
基金supported by the Fundamental Research Funds for the Central Universities(Zhejiang University NGICS Platform)the Zhejiang Provincial Public Welfare Technology Application Research Project(No.LGJ21E070001)。
文摘In recent years,rumors have been shown to have a significant impact on individual and societal activities.As renewables play an increasingly significant role in electricity markets,certain rumors may deviate the bidding behavior of market entities and eventually affect the performance of market operations.In this study,we attempt to reveal the general threats caused by rumors in the context of day-ahead electricity markets considering the integration of volatile renewables.First,we model the propagation of rumors in the societal system considering the weight of propagation resistance,which principally reflects the communication accessibility of market entities.Second,we develop an integrated two-layer network model to uncover the inherent coupling mechanism between market operations and rumor propagation.In particular,the role of electricity market operations on rumor propagation is characterized by changes in the truthfulness of rumors associated with electricity prices.The rumors,in turn,affect the bidding quantities of market entities in electricity market operations.Finally,numerical experiments are conducted on modified IEEE 6-bus and 118-bus systems.The results demonstrate the potential threats of rumors to electricity market operations with different penetration levels of renewables.
