The Spectral Statistical Interpolation (SSI) analysis system of NCEP is used to assimilate meteorological data from the Global Positioning Satellite System (GPS/MET) refraction angles with the variational technique. V...The Spectral Statistical Interpolation (SSI) analysis system of NCEP is used to assimilate meteorological data from the Global Positioning Satellite System (GPS/MET) refraction angles with the variational technique. Verified by radiosonde, including GPS/MET observations into the analysis makes an overall improvement to the analysis variables of temperature, winds, and water vapor. However, the variational model with the ray-tracing method is quite expensive for numerical weather prediction and climate research. For example, about 4 000 GPS/MET refraction angles need to be assimilated to produce an ideal global analysis. Just one iteration of minimization will take more than 24 hours CPU time on the NCEP's Cray C90 computer. Although efforts have been taken to reduce the computational cost, it is still prohibitive for operational data assimilation. In this paper, a parallel version of the three-dimensional variational data assimilation model of GPS/MET occultation measurement suitable for massive parallel processors architectures is developed. The divide-and-conquer strategy is used to achieve parallelism and is implemented by message passing. The authors present the principles for the code's design and examine the performance on the state-of-the-art parallel computers in China. The results show that this parallel model scales favorably as the number of processors is increased. With the Memory-IO technique implemented by the author, the wall clock time per iteration used for assimilating 1420 refraction angles is reduced from 45 s to 12 s using 1420 processors. This suggests that the new parallelized code has the potential to be useful in numerical weather prediction (NWP) and climate studies.展开更多
The advancement of Large Language Models (LLMs) for domain applications in fields such as materials science and engineering depends on the development of fine-tuning strategies that adapt models for specialized, techn...The advancement of Large Language Models (LLMs) for domain applications in fields such as materials science and engineering depends on the development of fine-tuning strategies that adapt models for specialized, technical capabilities. In this work, we explore the effects of Continued Pretraining (CPT), Supervised Fine-Tuning (SFT), and various preference-based optimization approaches, including Direct Preference Optimization (DPO) and Odds Ratio Preference Optimization (ORPO), on fine-tuned LLM performance. Our analysis shows how these strategies influence model outcomes and reveals that the merging of multiple fine-tuned models can lead to the emergence of capabilities that surpass the individual contributions of the parent models. We find that model merging is not merely a process of aggregation, but a transformative method that can drive substantial advancements in model capabilities characterized by highly nonlinear interactions between model parameters, resulting in new functionalities that neither parent model could achieve alone, leading to improved performance in domain-specific assessments. We study critical factors that influence the success of model merging, such as the diversity between parent models and the fine-tuning techniques employed. The insights underscore the potential of strategic model merging to unlock novel capabilities in LLMs, offering an effective tool for advancing AI systems to meet complex challenges. Experiments with different model architectures are presented, including the Llama 3.1 8B and Mistral 7B family of models, where similar behaviors are observed. Exploring whether the results hold also for much smaller models, we use a tiny LLM with 1.7 billion parameters and show that very small LLMs do not necessarily feature emergent capabilities under model merging, suggesting that model scaling may be a key component. In open-ended yet consistent chat conversations between a human and AI models, our assessment reveals detailed insights into how different model variants perform, and shows that the smallest model achieves a high intelligence score across key criteria including reasoning depth, creativity, clarity, and quantitative precision. Other experiments include the development of image generation prompts that seek to reason over disparate biological material design concepts, to create new microstructures, architectural concepts, and urban design based on biological materials-inspired construction principles. We conclude with a series of questions about scaling and emergence that could be addressed in future research.展开更多
Sensitivity analysis in chaotic dynamical systems is a challenging task from a computational point of view.In this work,we present a numerical investigation of a novel approach,known as the space-split sensitivity or ...Sensitivity analysis in chaotic dynamical systems is a challenging task from a computational point of view.In this work,we present a numerical investigation of a novel approach,known as the space-split sensitivity or S3 algorithm.The S3 algorithm is an ergodic-averaging method to differentiate statistics in ergodic,chaotic systems,rigorously based on the theory of hyperbolic dynamics.We illustrate S3 on one-dimensional chaotic maps,revealing its computational advantage over na?ve finite difference computations of the same statistical response.In addition,we provide an intuitive explanation of the key components of the S3 algorithm,including the density gradient function.展开更多
Green hydrogen production is crucial for a sustainable future,but current catalysts for the oxygen evolution reaction(OER)suffer from slow kinetics,despite many efforts to produce optimal designs,particularly through ...Green hydrogen production is crucial for a sustainable future,but current catalysts for the oxygen evolution reaction(OER)suffer from slow kinetics,despite many efforts to produce optimal designs,particularly through the calculation of descriptors for activity.In this study,we develop a dataset of density functional theory calculations of bulk and surface perovskite oxides,and adsorption energies of OER intermediates,which includes compositions up to quaternary and facets up to(555).We demonstrate that per-site properties of perovskite oxides such as Bader charge or band center can be tuned through element substitution and faceting,and develop a machine learning model that accurately predicts these properties directly from the local chemical environment.We leverage these per-site properties to identify promising perovskites with high theoretical OER activity.The identified design principles and promising materials provide a roadmap for closing the gap between current artificial catalysts and biological enzymes such as photosystem II.展开更多
Architected materials can achieve enhanced properties compared to their plain counterparts.Specific architecting serves as a powerful design lever to achieve targeted behavior without changing the base material.Thus,t...Architected materials can achieve enhanced properties compared to their plain counterparts.Specific architecting serves as a powerful design lever to achieve targeted behavior without changing the base material.Thus,the connection between architected structure and resultant properties remains an open field of great interest to many fields,from aerospace to civil to automotive applications.Here,we focus on properties related to mechanical compression,and design hierarchical honeycomb structures to meet specific values of stiffness and compressive stress.To do so,we employ a combination of techniques in a singular workflow,starting with molecular dynamics simulation of the forward design problem,augmenting with data-driven artificial intelligence models to address the inverse design problem,and verifying the behavior of de novo structures with experimentation of additively manufactured samples.We thereby demonstrate an approach for architected design that is generalizable to multiple material properties and agnostic to the identity of the base material.展开更多
Non-equilibrium electronic quantum transport is crucial for existing and envisioned electronic,optoelectronic,and spintronic devices.Encompassing atomistic to mesoscopic length scales in the same nonequilibrium device...Non-equilibrium electronic quantum transport is crucial for existing and envisioned electronic,optoelectronic,and spintronic devices.Encompassing atomistic to mesoscopic length scales in the same nonequilibrium device simulations has been challenging due to the computational cost of high-fidelity coupled multiphysics and multiscale requirements.In this work,we present ELEQTRONeX(ELEctrostatic Quantum TRansport modeling Of Nanomaterials at eXascale),a massively parallel GPU-accelerated framework for self-consistently solving the nonequilibrium Green’s function formalism and electrostatics in complex device geometries.By customizing algorithms for GPU multithreading,we achieve significant improvement in computational time,and excellent scaling on up to 512 GPUs and billions of spatial grid cells.We validate our code by computing band structures,current-voltage characteristics,conductance,and drain-induced barrier lowering for various 3D configurations of carbon nanotube field-effect transistors,and demonstrate its suitability for complex device/material geometries where periodic approaches are not feasible,such as arrays of misaligned carbon nanotubes requiring fully 3D simulations.展开更多
Recent years have witnessed a surge of interest in topological semimetals due to their unique electronic band structures and exotic quantum phenomena[1].Among them,Weyl semimetals(WSMs)host massless chiral fermions as...Recent years have witnessed a surge of interest in topological semimetals due to their unique electronic band structures and exotic quantum phenomena[1].Among them,Weyl semimetals(WSMs)host massless chiral fermions as low-energy excitations[2],leading to novel transport phenomena,such as the chiral magnetic effect(CME)[3],which arises from the chiral anomaly and results in a nonequilibrium current parallel to an applied magnetic field when an electric field is also present.However,a static magnetic field alone cannot induce a current;that is,the CME in equilibrium is zero.展开更多
We present here a brief summary of a National Natural Science Foundation Major Project entitled "Theoretical study of the low-lying electronic excited state for molecular aggregates". The project focuses on ...We present here a brief summary of a National Natural Science Foundation Major Project entitled "Theoretical study of the low-lying electronic excited state for molecular aggregates". The project focuses on theoretical investigation of the electronic structures and dynamic processes upon photo-and electric-excitation for molecules and aggregates. We aim to develop reliable methodology to predict the optoelectronic properties of molecular materials related to the electronic excitations and to apply in the experiments. We identify two essential scientific challenges: (i) nature of intramolecular and intermolecular electronic excited states; (ii) theoretical description of the dynamic processes of the coupled motion of electronic excitations and nucleus. We propose the following four subjects of research: (i) linear scaling time-dependent density-functional theory and its application to open shell system; (ii) computational method development of electronic excited state for molecular aggregates; (iii) theoretical investigation of the time evolution of the excited state dynamics; (iv) methods to predict the optoelectronic properties starting from electronic excited state investigation for organic materials and experimental verifications.展开更多
The low-lying electronic states of Yb and YbO are investigated by using time-dependent relativistic density functional theory,which is based on the newly developed exact two-component Hamiltonian resulting from symmet...The low-lying electronic states of Yb and YbO are investigated by using time-dependent relativistic density functional theory,which is based on the newly developed exact two-component Hamiltonian resulting from symmetrized elimination of the small component.The nature of the excited states is analyzed by using the full molecular symmetry.The calculated results support the previous experimental assignment of the ground and excited states of YbO.展开更多
The appropriate theoretical picture of describing the ferroelectric order in hybrid organic-inorganic perovskite remains attractive and under intense debate.We rationalize the interaction between organic molecule subl...The appropriate theoretical picture of describing the ferroelectric order in hybrid organic-inorganic perovskite remains attractive and under intense debate.We rationalize the interaction between organic molecule sublattice and inorganic frame from first-principles.Through systematic investigations on the NH_(4)PbI_(3),we show that the non-polar octahedral rotation dominates the process of stabilizing of the lattice with small value of tolerance factor.The direct coupling between molecules is negligible.With the help of hydrogen bonding to the inorganic cage,molecule sublattice will eventually build long-range ferroelectric or anti-ferroelectric order under the constrain of the inorganic cage and further polarize the inorganic frame as the feedback.These results also clarify that to build ferroelectricity the polar molecule is helpful but not crucial.As the general rule for hybrid organic-inorganic perovskite,we identified the fundamental mechanism that can be considered as a critical pre-step forward to further controlling the related physics in functional materials.展开更多
In this paper,we study numerically quantized vortex dynamics and their interaction in the two-dimensional(2D)Ginzburg-Landau equation(GLE)with a dimensionless parameter#>0 on bounded domains under either Dirichlet ...In this paper,we study numerically quantized vortex dynamics and their interaction in the two-dimensional(2D)Ginzburg-Landau equation(GLE)with a dimensionless parameter#>0 on bounded domains under either Dirichlet or homogeneous Neumann boundary condition.We begin with a reviewof the reduced dynamical laws for time evolution of quantized vortex centers in GLE and show how to solve these nonlinear ordinary differential equations numerically.Then we present efficient and accurate numerical methods for discretizing the GLE on either a rectangular or a disk domain under either Dirichlet or homogeneous Neumann boundary condition.Based on these efficient and accurate numerical methods for GLE and the reduced dynamical laws,we simulate quantized vortex interaction of GLE with different#and under different initial setups including single vortex,vortex pair,vortex dipole and vortex lattice,compare them with those obtained from the corresponding reduced dynamical laws,and identify the cases where the reduced dynamical laws agree qualitatively and/or quantitatively as well as fail to agree with those from GLE on vortex interaction.Finally,we also obtain numerically different patterns of the steady states for quantized vortex lattices under the GLE dynamics on bounded domains.展开更多
Amulti-timescale algorithmis proposed for simulating time-dependent problems in micro-and nano-fluidics.The total simulation domain is spatially decomposed into two regions.Molecular dynamics is employed in the crucia...Amulti-timescale algorithmis proposed for simulating time-dependent problems in micro-and nano-fluidics.The total simulation domain is spatially decomposed into two regions.Molecular dynamics is employed in the crucial interfacial regions and continuum hydrodynamics is adopted in the remaining bulk regions.The coupling is through“constrained dynamics”in an overlap region.Our time scheme is based on the time scale separation between the continuum macro time step and molecular micro time step.This allows the molecular dynamics during one macro time step to be treated as in quasi-steady state.Therefore,molecular simulation is only performed in two shorter time intervals.Through linear extrapolation of macroscopic velocities and re-initialization of particle configurations,we can significantly reduce the total computational cost.We demonstrate and discuss our time algorithm through hybrid simulation of channel flow driven by a sinusoidally moving top wall.Converging results are achieved for cases of large separation of time scale with much less computational cost than with the original hybrid simulation without time extrapolation.展开更多
In this paper we propose a uniformly convergent numerical method for discretizing singularly perturbed nonlinear eigenvalue problems under constraints with applications in Bose-Einstein condensation and quantum chemis...In this paper we propose a uniformly convergent numerical method for discretizing singularly perturbed nonlinear eigenvalue problems under constraints with applications in Bose-Einstein condensation and quantum chemistry.We begin with the time-independent Gross-Pitaevskii equation and show how to reformulate it into a singularly perturbed nonlinear eigenvalue problem under a constraint.Matched asymptotic approximations for the problem are presented to locate the positions and characterize the widths of boundary layers and/or interior layers in the solution.A uniformly convergent numerical method is proposed by using the normalized gradient flow and piecewise uniform mesh techniques based on the asymptotic approximations for the problem.Extensive numerical results are reported to demonstrate the effectiveness of our numerical method for the problems.Finally,the method is applied to compute ground and excited states of Bose-Einstein condensation in the semiclassical regime and some conclusive findings are reported.展开更多
The project aims to develop an integrated linear-scaling time-dependent density functional theory (TD-DFT) for studying low-lying excited states of luminescent molecular materials, especially those fluorescence and ph...The project aims to develop an integrated linear-scaling time-dependent density functional theory (TD-DFT) for studying low-lying excited states of luminescent molecular materials, especially those fluorescence and phosphorescence co-emitting systems. The central idea will be "from fragments to molecule" (FF2M). That is, the fragmental information will be employed to synthesize the molecular wave function, such that the locality (transferability) of the fragments (functional groups) is directly built into the algorithms. Both relativistic and spin-adapted open-shell TD-DFT will be considered. Use of the renormalized exciton method will also be made to further enhance the efficiency and accuracy of TD-DFT. Solvent effects are to be targeted with the fragment-based solvent model. It is expected that the integrated TD-DFT and program will be of great value in rational design of luminescent molecular materials.展开更多
Structural defects are abundant in solids,and vital to the macroscopic materials properties.However,a defect-property linkage typically requires significant efforts from experiments or simulations,and often contains l...Structural defects are abundant in solids,and vital to the macroscopic materials properties.However,a defect-property linkage typically requires significant efforts from experiments or simulations,and often contains limited information due to the breadth of nanoscopic design space.Here we report a graph neural network(GNN)-based approach to achieve direct translation between mesoscale crystalline structures and atom-level properties,emphasizing the effects of structural defects.Our end-to-end method offers great performance and generality in predicting both atomic stress and potential energy of multiple systems with different defects.Furthermore,the approach also precisely captures derivative properties which strictly observe physical laws and reproduces evolution of properties with varying boundary conditions.By incorporating a genetic algorithm,we then design de novo atomic structures with optimum global properties and target local patterns.The method would significantly enhance the efficiency of evaluating atomic behaviors given structural imperfections and accelerates the design process at the meso-level.展开更多
We investigate several robust preconditioners for solving the saddle-point linear systems that arise from spatial discretization of unsteady and steady variablecoefficient Stokes equations on a uniform staggered grid....We investigate several robust preconditioners for solving the saddle-point linear systems that arise from spatial discretization of unsteady and steady variablecoefficient Stokes equations on a uniform staggered grid.Building on the success of using the classical projection method as a preconditioner for the coupled velocitypressure system[B.E.Griffith,J.Comp.Phys.,228(2009),pp.7565–7595],as well as established techniques for steady and unsteady Stokes flow in the finite-element literature,we construct preconditioners that employ independent generalized Helmholtz and Poisson solvers for the velocity and pressure subproblems.We demonstrate that only a single cycle of a standard geometric multigrid algorithm serves as an effective inexact solver for each of these subproblems.Contrary to traditional wisdom,we find that the Stokes problem can be solved nearly as efficiently as the independent pressure and velocity subproblems,making the overall cost of solving the Stokes system comparable to the cost of classical projection or fractional step methods for incompressible flow,even for steady flow and in the presence of large density and viscosity contrasts.Two of the five preconditioners considered here are found to be robust to GMRES restarts and to increasing problem size,making them suitable for large-scale problems.Our work opens many possibilities for constructing novel unsplit temporal integrators for finite-volume spatial discretizations of the equations of low Mach and incompressible flow dynamics.展开更多
Methylammonium lead iodide,as related organometal halide perovskites,emerged recently as a particularly attractive material for photovoltaic applications.The origin of its appealing properties is sometimes assigned to...Methylammonium lead iodide,as related organometal halide perovskites,emerged recently as a particularly attractive material for photovoltaic applications.The origin of its appealing properties is sometimes assigned to its potential ferroelectric character,which remains however a topic of intense debate.Here,we rationalize from first-principles calculations how the spatial arrangement of methylammonium polar molecules is progressively constrained by the subtle interplay between their tendency to bond with the inorganic framework and the appearance of iodine octahedra rotations inherent to the perovskite structure.The disordered tetragonal phase observed at room temperature is paraelectric.We show that it should a priori become ferroelectric but that iodine octahedra rotations drive the system toward an antipolar orthorhombic ground state,making it a missed ferroelectric.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supported by the National Natural Science Eoundation of China under Grant No.40221503the China National Key Programme for Development Basic Sciences (Abbreviation:973 Project,Grant No.G1999032801)
文摘The Spectral Statistical Interpolation (SSI) analysis system of NCEP is used to assimilate meteorological data from the Global Positioning Satellite System (GPS/MET) refraction angles with the variational technique. Verified by radiosonde, including GPS/MET observations into the analysis makes an overall improvement to the analysis variables of temperature, winds, and water vapor. However, the variational model with the ray-tracing method is quite expensive for numerical weather prediction and climate research. For example, about 4 000 GPS/MET refraction angles need to be assimilated to produce an ideal global analysis. Just one iteration of minimization will take more than 24 hours CPU time on the NCEP's Cray C90 computer. Although efforts have been taken to reduce the computational cost, it is still prohibitive for operational data assimilation. In this paper, a parallel version of the three-dimensional variational data assimilation model of GPS/MET occultation measurement suitable for massive parallel processors architectures is developed. The divide-and-conquer strategy is used to achieve parallelism and is implemented by message passing. The authors present the principles for the code's design and examine the performance on the state-of-the-art parallel computers in China. The results show that this parallel model scales favorably as the number of processors is increased. With the Memory-IO technique implemented by the author, the wall clock time per iteration used for assimilating 1420 refraction angles is reduced from 45 s to 12 s using 1420 processors. This suggests that the new parallelized code has the potential to be useful in numerical weather prediction (NWP) and climate studies.
基金supported in part by Google,the MIT Generative AI Initiative,USDA(grant number 2021-69012-35978)with additional support from NIH.This material is partially based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant number 2141064.
文摘The advancement of Large Language Models (LLMs) for domain applications in fields such as materials science and engineering depends on the development of fine-tuning strategies that adapt models for specialized, technical capabilities. In this work, we explore the effects of Continued Pretraining (CPT), Supervised Fine-Tuning (SFT), and various preference-based optimization approaches, including Direct Preference Optimization (DPO) and Odds Ratio Preference Optimization (ORPO), on fine-tuned LLM performance. Our analysis shows how these strategies influence model outcomes and reveals that the merging of multiple fine-tuned models can lead to the emergence of capabilities that surpass the individual contributions of the parent models. We find that model merging is not merely a process of aggregation, but a transformative method that can drive substantial advancements in model capabilities characterized by highly nonlinear interactions between model parameters, resulting in new functionalities that neither parent model could achieve alone, leading to improved performance in domain-specific assessments. We study critical factors that influence the success of model merging, such as the diversity between parent models and the fine-tuning techniques employed. The insights underscore the potential of strategic model merging to unlock novel capabilities in LLMs, offering an effective tool for advancing AI systems to meet complex challenges. Experiments with different model architectures are presented, including the Llama 3.1 8B and Mistral 7B family of models, where similar behaviors are observed. Exploring whether the results hold also for much smaller models, we use a tiny LLM with 1.7 billion parameters and show that very small LLMs do not necessarily feature emergent capabilities under model merging, suggesting that model scaling may be a key component. In open-ended yet consistent chat conversations between a human and AI models, our assessment reveals detailed insights into how different model variants perform, and shows that the smallest model achieves a high intelligence score across key criteria including reasoning depth, creativity, clarity, and quantitative precision. Other experiments include the development of image generation prompts that seek to reason over disparate biological material design concepts, to create new microstructures, architectural concepts, and urban design based on biological materials-inspired construction principles. We conclude with a series of questions about scaling and emergence that could be addressed in future research.
基金supported by the Air Force Office of Scientific Research(Grant FA8650-19-C-2207)。
文摘Sensitivity analysis in chaotic dynamical systems is a challenging task from a computational point of view.In this work,we present a numerical investigation of a novel approach,known as the space-split sensitivity or S3 algorithm.The S3 algorithm is an ergodic-averaging method to differentiate statistics in ergodic,chaotic systems,rigorously based on the theory of hyperbolic dynamics.We illustrate S3 on one-dimensional chaotic maps,revealing its computational advantage over na?ve finite difference computations of the same statistical response.In addition,we provide an intuitive explanation of the key components of the S3 algorithm,including the density gradient function.
基金supported by the Advanced Research Projects Agency-Energy(ARPA-E),US Department of Energy under award number DE-AR0001220.
文摘Green hydrogen production is crucial for a sustainable future,but current catalysts for the oxygen evolution reaction(OER)suffer from slow kinetics,despite many efforts to produce optimal designs,particularly through the calculation of descriptors for activity.In this study,we develop a dataset of density functional theory calculations of bulk and surface perovskite oxides,and adsorption energies of OER intermediates,which includes compositions up to quaternary and facets up to(555).We demonstrate that per-site properties of perovskite oxides such as Bader charge or band center can be tuned through element substitution and faceting,and develop a machine learning model that accurately predicts these properties directly from the local chemical environment.We leverage these per-site properties to identify promising perovskites with high theoretical OER activity.The identified design principles and promising materials provide a roadmap for closing the gap between current artificial catalysts and biological enzymes such as photosystem II.
基金This material is based upon work supported by the NSF GRFP under Grant No.1122374We acknowledge support by NIH(5R01AR077793-03)+1 种基金the Office of Naval Research(N000141612333 and N000141912375)AFOSR-MURI(FA9550-15-1-0514)and the Army Research Office(W911NF1920098).Related support from the MIT-IBM Watson AI Lab,MIT Quest,and Google Cloud Computing,is acknowledged.
文摘Architected materials can achieve enhanced properties compared to their plain counterparts.Specific architecting serves as a powerful design lever to achieve targeted behavior without changing the base material.Thus,the connection between architected structure and resultant properties remains an open field of great interest to many fields,from aerospace to civil to automotive applications.Here,we focus on properties related to mechanical compression,and design hierarchical honeycomb structures to meet specific values of stiffness and compressive stress.To do so,we employ a combination of techniques in a singular workflow,starting with molecular dynamics simulation of the forward design problem,augmenting with data-driven artificial intelligence models to address the inverse design problem,and verifying the behavior of de novo structures with experimentation of additively manufactured samples.We thereby demonstrate an approach for architected design that is generalizable to multiple material properties and agnostic to the identity of the base material.
基金supported by the U.S.Department of Energy,Office of Science,under the Microelectronics Co-Design Research Program(Co-Design and Integration of Nano-sensors on CMOS)the Microelectronics Science Research Centers(Nanoscale hybrids:a new paradigm for energy-efficient optoelectronics)+3 种基金Accelerate Innovations in Emerging Technologies Program(Phonon Control for Next-Generation Superconducting Systems and Sensors)under Contract DE-AC02-05-CH11231supported by the same programs under Contract DE-NA-0003525Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia,LLC.,a wholly owned subsidiary of Honeywell International,Inc.,for the U.S.Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525the National Energy Research Scientific Computing Center(NERSC),a Department of Energy Office of Science User Facility using NERSC award ASCR-ERCAP0026882.
文摘Non-equilibrium electronic quantum transport is crucial for existing and envisioned electronic,optoelectronic,and spintronic devices.Encompassing atomistic to mesoscopic length scales in the same nonequilibrium device simulations has been challenging due to the computational cost of high-fidelity coupled multiphysics and multiscale requirements.In this work,we present ELEQTRONeX(ELEctrostatic Quantum TRansport modeling Of Nanomaterials at eXascale),a massively parallel GPU-accelerated framework for self-consistently solving the nonequilibrium Green’s function formalism and electrostatics in complex device geometries.By customizing algorithms for GPU multithreading,we achieve significant improvement in computational time,and excellent scaling on up to 512 GPUs and billions of spatial grid cells.We validate our code by computing band structures,current-voltage characteristics,conductance,and drain-induced barrier lowering for various 3D configurations of carbon nanotube field-effect transistors,and demonstrate its suitability for complex device/material geometries where periodic approaches are not feasible,such as arrays of misaligned carbon nanotubes requiring fully 3D simulations.
基金supported by the National Natural Science Foundation of China(12204074,12222402,92365101,12347101,12074108,12447141,12404045,and 12474151)the Natural Science Foundation of Chongqing(2023NSCQ-JQX0024 and CSTB2022NSCQ-MSX0568)+3 种基金the Beijing National Laboratory for Condensed Matter Physics(2024BNLCMPKF025)the Postdoctoral Fellowship Program of CPSF(GZC20252254)the Special Funding for Postdoctoral Research Projects in Chongqing(2024CQBSHTB2036)the Science and Technology Research Program of Chongqing Municipal Education Commission(KJZDK202500512 and KJQN-202400553)。
文摘Recent years have witnessed a surge of interest in topological semimetals due to their unique electronic band structures and exotic quantum phenomena[1].Among them,Weyl semimetals(WSMs)host massless chiral fermions as low-energy excitations[2],leading to novel transport phenomena,such as the chiral magnetic effect(CME)[3],which arises from the chiral anomaly and results in a nonequilibrium current parallel to an applied magnetic field when an electric field is also present.However,a static magnetic field alone cannot induce a current;that is,the CME in equilibrium is zero.
基金the National Natural Science Foundation of China (21290190)
文摘We present here a brief summary of a National Natural Science Foundation Major Project entitled "Theoretical study of the low-lying electronic excited state for molecular aggregates". The project focuses on theoretical investigation of the electronic structures and dynamic processes upon photo-and electric-excitation for molecules and aggregates. We aim to develop reliable methodology to predict the optoelectronic properties of molecular materials related to the electronic excitations and to apply in the experiments. We identify two essential scientific challenges: (i) nature of intramolecular and intermolecular electronic excited states; (ii) theoretical description of the dynamic processes of the coupled motion of electronic excitations and nucleus. We propose the following four subjects of research: (i) linear scaling time-dependent density-functional theory and its application to open shell system; (ii) computational method development of electronic excited state for molecular aggregates; (iii) theoretical investigation of the time evolution of the excited state dynamics; (iv) methods to predict the optoelectronic properties starting from electronic excited state investigation for organic materials and experimental verifications.
基金Supported by the National Natural Science Foundation of China (Grant Nos. 20573003, 20625311 and 20773003)MOST of China (Grant Nos. 2006CB601103 and 2006AA01A119)
文摘The low-lying electronic states of Yb and YbO are investigated by using time-dependent relativistic density functional theory,which is based on the newly developed exact two-component Hamiltonian resulting from symmetrized elimination of the small component.The nature of the excited states is analyzed by using the full molecular symmetry.The calculated results support the previous experimental assignment of the ground and excited states of YbO.
基金This work was financially supported by the National Natural Science Foundation of China(Grant Nos.12274145,12174121,11974062,12222402)Guangdong Basic and Applied Basic Research Foundation,China(Grand Nos.2023A1515010672,2021A1515010369,2020A1515110627).J.-Z.Z.acknowledges the startup funding from South China Normal University.
文摘The appropriate theoretical picture of describing the ferroelectric order in hybrid organic-inorganic perovskite remains attractive and under intense debate.We rationalize the interaction between organic molecule sublattice and inorganic frame from first-principles.Through systematic investigations on the NH_(4)PbI_(3),we show that the non-polar octahedral rotation dominates the process of stabilizing of the lattice with small value of tolerance factor.The direct coupling between molecules is negligible.With the help of hydrogen bonding to the inorganic cage,molecule sublattice will eventually build long-range ferroelectric or anti-ferroelectric order under the constrain of the inorganic cage and further polarize the inorganic frame as the feedback.These results also clarify that to build ferroelectricity the polar molecule is helpful but not crucial.As the general rule for hybrid organic-inorganic perovskite,we identified the fundamental mechanism that can be considered as a critical pre-step forward to further controlling the related physics in functional materials.
基金supported by the Singapore A*STAR SERC“Complex Systems”Research Programme grant 1224504056the Academic Research Fund of Ministry of Education of Singapore grant R-146-000-120-112。
文摘In this paper,we study numerically quantized vortex dynamics and their interaction in the two-dimensional(2D)Ginzburg-Landau equation(GLE)with a dimensionless parameter#>0 on bounded domains under either Dirichlet or homogeneous Neumann boundary condition.We begin with a reviewof the reduced dynamical laws for time evolution of quantized vortex centers in GLE and show how to solve these nonlinear ordinary differential equations numerically.Then we present efficient and accurate numerical methods for discretizing the GLE on either a rectangular or a disk domain under either Dirichlet or homogeneous Neumann boundary condition.Based on these efficient and accurate numerical methods for GLE and the reduced dynamical laws,we simulate quantized vortex interaction of GLE with different#and under different initial setups including single vortex,vortex pair,vortex dipole and vortex lattice,compare them with those obtained from the corresponding reduced dynamical laws,and identify the cases where the reduced dynamical laws agree qualitatively and/or quantitatively as well as fail to agree with those from GLE on vortex interaction.Finally,we also obtain numerically different patterns of the steady states for quantized vortex lattices under the GLE dynamics on bounded domains.
基金This material is based upon work supported by the National Science Foundation under Grant No.CMMI-0709187.
文摘Amulti-timescale algorithmis proposed for simulating time-dependent problems in micro-and nano-fluidics.The total simulation domain is spatially decomposed into two regions.Molecular dynamics is employed in the crucial interfacial regions and continuum hydrodynamics is adopted in the remaining bulk regions.The coupling is through“constrained dynamics”in an overlap region.Our time scheme is based on the time scale separation between the continuum macro time step and molecular micro time step.This allows the molecular dynamics during one macro time step to be treated as in quasi-steady state.Therefore,molecular simulation is only performed in two shorter time intervals.Through linear extrapolation of macroscopic velocities and re-initialization of particle configurations,we can significantly reduce the total computational cost.We demonstrate and discuss our time algorithm through hybrid simulation of channel flow driven by a sinusoidally moving top wall.Converging results are achieved for cases of large separation of time scale with much less computational cost than with the original hybrid simulation without time extrapolation.
基金Singapore Ministry of Education grant No.R-146-000-083-112 and would like to thank Professor Tao Tang for very helpful discussion on the subject.
文摘In this paper we propose a uniformly convergent numerical method for discretizing singularly perturbed nonlinear eigenvalue problems under constraints with applications in Bose-Einstein condensation and quantum chemistry.We begin with the time-independent Gross-Pitaevskii equation and show how to reformulate it into a singularly perturbed nonlinear eigenvalue problem under a constraint.Matched asymptotic approximations for the problem are presented to locate the positions and characterize the widths of boundary layers and/or interior layers in the solution.A uniformly convergent numerical method is proposed by using the normalized gradient flow and piecewise uniform mesh techniques based on the asymptotic approximations for the problem.Extensive numerical results are reported to demonstrate the effectiveness of our numerical method for the problems.Finally,the method is applied to compute ground and excited states of Bose-Einstein condensation in the semiclassical regime and some conclusive findings are reported.
基金the National Natural Science Foundation of China (21290192)
文摘The project aims to develop an integrated linear-scaling time-dependent density functional theory (TD-DFT) for studying low-lying excited states of luminescent molecular materials, especially those fluorescence and phosphorescence co-emitting systems. The central idea will be "from fragments to molecule" (FF2M). That is, the fragmental information will be employed to synthesize the molecular wave function, such that the locality (transferability) of the fragments (functional groups) is directly built into the algorithms. Both relativistic and spin-adapted open-shell TD-DFT will be considered. Use of the renormalized exciton method will also be made to further enhance the efficiency and accuracy of TD-DFT. Solvent effects are to be targeted with the fragment-based solvent model. It is expected that the integrated TD-DFT and program will be of great value in rational design of luminescent molecular materials.
基金We acknowledge support from the Army Research Office(W911NF1920098)AFOSR-MURI(FA9550-15-1-0514).
文摘Structural defects are abundant in solids,and vital to the macroscopic materials properties.However,a defect-property linkage typically requires significant efforts from experiments or simulations,and often contains limited information due to the breadth of nanoscopic design space.Here we report a graph neural network(GNN)-based approach to achieve direct translation between mesoscale crystalline structures and atom-level properties,emphasizing the effects of structural defects.Our end-to-end method offers great performance and generality in predicting both atomic stress and potential energy of multiple systems with different defects.Furthermore,the approach also precisely captures derivative properties which strictly observe physical laws and reproduces evolution of properties with varying boundary conditions.By incorporating a genetic algorithm,we then design de novo atomic structures with optimum global properties and target local patterns.The method would significantly enhance the efficiency of evaluating atomic behaviors given structural imperfections and accelerates the design process at the meso-level.
文摘We investigate several robust preconditioners for solving the saddle-point linear systems that arise from spatial discretization of unsteady and steady variablecoefficient Stokes equations on a uniform staggered grid.Building on the success of using the classical projection method as a preconditioner for the coupled velocitypressure system[B.E.Griffith,J.Comp.Phys.,228(2009),pp.7565–7595],as well as established techniques for steady and unsteady Stokes flow in the finite-element literature,we construct preconditioners that employ independent generalized Helmholtz and Poisson solvers for the velocity and pressure subproblems.We demonstrate that only a single cycle of a standard geometric multigrid algorithm serves as an effective inexact solver for each of these subproblems.Contrary to traditional wisdom,we find that the Stokes problem can be solved nearly as efficiently as the independent pressure and velocity subproblems,making the overall cost of solving the Stokes system comparable to the cost of classical projection or fractional step methods for incompressible flow,even for steady flow and in the presence of large density and viscosity contrasts.Two of the five preconditioners considered here are found to be robust to GMRES restarts and to increasing problem size,making them suitable for large-scale problems.Our work opens many possibilities for constructing novel unsplit temporal integrators for finite-volume spatial discretizations of the equations of low Mach and incompressible flow dynamics.
基金W.-Y.T.acknowledges the support from F.R.S.-FNRS Belgium.J.-Z.Z.acknowledges the support from the Startup Funding for Outstanding Young Scientist of South China Normal University and the financial support of China Scholarship Council(Grant No.202006755025)The authors acknowledge access to the CECI supercomputer facilities funded by the F.R.S-FNRS(Grant No.2.5020.1)the Tier-1 supercomputer of the Federation Wallonie-Bruxelles funded by the Walloon Region(Grant No.1117545).
文摘Methylammonium lead iodide,as related organometal halide perovskites,emerged recently as a particularly attractive material for photovoltaic applications.The origin of its appealing properties is sometimes assigned to its potential ferroelectric character,which remains however a topic of intense debate.Here,we rationalize from first-principles calculations how the spatial arrangement of methylammonium polar molecules is progressively constrained by the subtle interplay between their tendency to bond with the inorganic framework and the appearance of iodine octahedra rotations inherent to the perovskite structure.The disordered tetragonal phase observed at room temperature is paraelectric.We show that it should a priori become ferroelectric but that iodine octahedra rotations drive the system toward an antipolar orthorhombic ground state,making it a missed ferroelectric.
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.
