Membrane technologies are becoming increasingly versatile and helpful today for sustainable development.Machine Learning(ML),an essential branch of artificial intelligence(AI),has substantially impacted the research an...Membrane technologies are becoming increasingly versatile and helpful today for sustainable development.Machine Learning(ML),an essential branch of artificial intelligence(AI),has substantially impacted the research and development norm of new materials for energy and environment.This review provides an overview and perspectives on ML methodologies and their applications in membrane design and dis-covery.A brief overview of membrane technologies isfirst provided with the current bottlenecks and potential solutions.Through an appli-cations-based perspective of AI-aided membrane design and discovery,we further show how ML strategies are applied to the membrane discovery cycle(including membrane material design,membrane application,membrane process design,and knowledge extraction),in various membrane systems,ranging from gas,liquid,and fuel cell separation membranes.Furthermore,the best practices of integrating ML methods and specific application targets in membrane design and discovery are presented with an ideal paradigm proposed.The challenges to be addressed and prospects of AI applications in membrane discovery are also highlighted in the end.展开更多
Recent experimental data for anomalous magnetic moments strongly indicates the existence of new physics beyond the Standard Model.Energetic μ^(+) bunches are relevant to μ^(+) rare decay,spin rotation,resonance and ...Recent experimental data for anomalous magnetic moments strongly indicates the existence of new physics beyond the Standard Model.Energetic μ^(+) bunches are relevant to μ^(+) rare decay,spin rotation,resonance and relaxation(μSR)technology,future muon colliders,and neutrino factories.In this paper,we propose prompt μ^(+) acceleration in a nonlinear toroidal wakefield driven by a shaped steep-rising-front Laguerre–Gaussian(LG)laser pulse.An analytical model is described,which shows that a μ^(+) beam can be focused by an electron cylinder at the centerline of a toroidal bubble and accelerated by the front part of the longitudinal wakefield.A shaped LG laser with a short rise time can push plasma electrons,generating a higher-density electron sheath at the front of the bubble,which can enhance the acceleration field.The acceleration field driven by the shaped steep-rising-front LG laser pulse is about four times greater than that driven by a normal LG laser pulse.Our simulation results show that a 300 MeV μ^(+) bunch can be accelerated to 2 GeV and its transverse size is focused from an initial value of w_(0)=5μm to w=2μm in the toroidal bubble driven by the shaped steep-rising-front LG laser pulse with a normalized amplitude of a=22.展开更多
基金This work is supported by the National Key R&D Program of China(No.2022ZD0117501)the Singapore RIE2020 Advanced Manufacturing and Engineering Programmatic Grant by the Agency for Science,Technology and Research(A*STAR)under grant no.A1898b0043Tsinghua University Initiative Scientific Research Program and Low Carbon En-ergy Research Funding Initiative by A*STAR under grant number A-8000182-00-00.
文摘Membrane technologies are becoming increasingly versatile and helpful today for sustainable development.Machine Learning(ML),an essential branch of artificial intelligence(AI),has substantially impacted the research and development norm of new materials for energy and environment.This review provides an overview and perspectives on ML methodologies and their applications in membrane design and dis-covery.A brief overview of membrane technologies isfirst provided with the current bottlenecks and potential solutions.Through an appli-cations-based perspective of AI-aided membrane design and discovery,we further show how ML strategies are applied to the membrane discovery cycle(including membrane material design,membrane application,membrane process design,and knowledge extraction),in various membrane systems,ranging from gas,liquid,and fuel cell separation membranes.Furthermore,the best practices of integrating ML methods and specific application targets in membrane design and discovery are presented with an ideal paradigm proposed.The challenges to be addressed and prospects of AI applications in membrane discovery are also highlighted in the end.
基金supported in part by the National Key R&D Program of China(No.2018YFA0404802)National Natural Science Foundation of China(No.11875319)+2 种基金the Hunan Provincial Science and Technology Program(No.2020RC4020)Innovation Project of IHEP(Nos.542017IHEPZZBS11820,542018IHEPZZBS12427)the CAS Center for Excellence in Particle Physics(CCEPP),the Meritocracy Research Funds of China West Normal University(No.17YC504)。
文摘Recent experimental data for anomalous magnetic moments strongly indicates the existence of new physics beyond the Standard Model.Energetic μ^(+) bunches are relevant to μ^(+) rare decay,spin rotation,resonance and relaxation(μSR)technology,future muon colliders,and neutrino factories.In this paper,we propose prompt μ^(+) acceleration in a nonlinear toroidal wakefield driven by a shaped steep-rising-front Laguerre–Gaussian(LG)laser pulse.An analytical model is described,which shows that a μ^(+) beam can be focused by an electron cylinder at the centerline of a toroidal bubble and accelerated by the front part of the longitudinal wakefield.A shaped LG laser with a short rise time can push plasma electrons,generating a higher-density electron sheath at the front of the bubble,which can enhance the acceleration field.The acceleration field driven by the shaped steep-rising-front LG laser pulse is about four times greater than that driven by a normal LG laser pulse.Our simulation results show that a 300 MeV μ^(+) bunch can be accelerated to 2 GeV and its transverse size is focused from an initial value of w_(0)=5μm to w=2μm in the toroidal bubble driven by the shaped steep-rising-front LG laser pulse with a normalized amplitude of a=22.
