Faster quantum chemistry calculations with dual basis sets
Faster quantum chemistry calculations with dual basis sets
批准号:
7325244
负责人:
JING KONG
金额:
$40.28万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-09-01 至 2010-05-31
关键词:
AddressAdoptedAlgorithmsBase PairingClassCodeComputer SimulationComputer softwareDevelopmentElectronicsElectronsEmpiricismEvaluationFailureGoalsHybridsMethodsModelingOne-Step dentin bonding systemPerformancePhaseProductivityPublishingQuantum MechanicsRangeReactionRecommendationResearchResearch PersonnelSavingsStructureSystemTechniquesTestingTimeWorkbasebiological researchchemical bondcostdensitydrug discoveryimprovedmolecular modelingnovelquantum chemistryresearch and developmentsizetheoriesyeast two hybrid system
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): Electronic structure methods permit the computational modeling of biomolecular systems from first principles of quantum mechanics without any experimental input or empiricism. This predictive capability comes at high computational cost, which restricts their use to key classes of problems where simpler empirical methods fail, such as making and breaking chemical bonds in reactions, or providing the first principles input to calibrate empirical force fields. This proposal aims to significantly enhance the performance of the most widely used electronic structure methods, such as second order perturbation theory, density functional theory, novel hybrids of the two, and some more advanced correlation methods. The opportunity is to gain a speedup of between 5 and 10 or more by developing dual basis approximations, a promising perturbative approach whose feasibility was established in the preliminary research. Its capabilities will be fully developed to permit force evaluation in addition to energies themselves. Other complementary algorithms that accelerate large-basis calculations on large molecules will also be formulated and implemented. This project aims to improve the efficiency of the most-widely used quantum chemistry models, namely density-functional theory and second-order perturbation theory. These methods are at the core of molecular modeling and applied widely in biological research/development and in drug discovery. The improvement will significantly increase researchers' productivity and extend its application scope.
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资助金额:$9.52万
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New Numerical Solutions for Density Functional Theory
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资助金额:$10.74万
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New Numerical Solutions for Density Functional Theory
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资助金额:$38.97万
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Faster quantum chemistry calculations with dual basis sets
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批准号:7482973
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资助金额:$35.2万
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Parallel Linear Scaling Algorithms
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Ab-Initio Geometry Optimization of Large Molecules
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资助金额:$38.98万
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Ab-Initio Geometry Optimization of Large Molecules
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批准号:6484828
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资助金额:$10.96万
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财政年份:2002
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负责人:JING KONG
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Local Quantum Theory for Large Molecular Systems
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批准号:6948578
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资助金额:$37.65万
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海外基金