Search results for " Computational"

showing 10 items of 661 documents

Nuclear quantum effects in liquid water from path-integral simulations using anab initioforce-matching approach

2014

We have applied path integral simulations, in combination with new ab initio based water potentials, to investigate nuclear quantum effects in liquid water. Because direct ab initio path integral simulations are computationally expensive, a flexible water model is parameterized by force-matching to density functional theory-based molecular dynamics simulations. The resulting effective potentials provide an inexpensive replacement for direct ab inito molecular dynamics simulations and allow efficient simulation of nuclear quantum effects. Static and dynamic properties of liquid water at ambient conditions are presented and the role of nuclear quantum effects, exchange-correlation functionals…

Chemical Physics (physics.chem-ph)PhysicsStatistical Mechanics (cond-mat.stat-mech)Liquid waterBiophysicsAb initioFOS: Physical sciencesComputational Physics (physics.comp-ph)Condensed Matter - Soft Condensed MatterCondensed Matter PhysicsMolecular dynamicsForce matchingPhysics - Chemical PhysicsQuantum mechanicsDispersion (optics)Path integral formulationWater modelSoft Condensed Matter (cond-mat.soft)Density functional theoryPhysical and Theoretical ChemistryPhysics - Computational PhysicsMolecular BiologyCondensed Matter - Statistical MechanicsMolecular Physics
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Recent achievements in ab initio modelling of liquid water

2013

The application of newly developed first-principle modeling techniques to liquid water deepens our understanding of the microscopic origins of its unusual macroscopic properties and behaviour. Here, we review two novel ab initio computational methods: second-generation Car-Parrinello molecular dynamics and decomposition analysis based on absolutely localized molecular orbitals. We show that these two methods in combination not only enable ab initio molecular dynamics simulations on previously inaccessible time and length scales, but also provide unprecedented insights into the nature of hydrogen bonding between water molecules. We discuss recent applications of these methods to water cluste…

Chemical Physics (physics.chem-ph)Statistical Mechanics (cond-mat.stat-mech)Biological Physics (physics.bio-ph)Physics - Chemical PhysicsSoft Condensed Matter (cond-mat.soft)FOS: Physical sciencesPhysics - Biological PhysicsComputational Physics (physics.comp-ph)Condensed Matter - Soft Condensed MatterPhysics - Computational PhysicsCondensed Matter - Statistical Mechanics
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Adversarial reverse mapping of equilibrated condensed-phase molecular structures

2020

A tight and consistent link between resolutions is crucial to further expand the impact of multiscale modeling for complex materials. We herein tackle the generation of condensed molecular structures as a refinement -- backmapping -- of a coarse-grained structure. Traditional schemes start from a rough coarse-to-fine mapping and perform further energy minimization and molecular dynamics simulations to equilibrate the system. In this study we introduce DeepBackmap: A deep neural network based approach to directly predict equilibrated molecular structures for condensed-phase systems. We use generative adversarial networks to learn the Boltzmann distribution from training data and realize reve…

Chemical Physics (physics.chem-ph)Structure (mathematical logic)Artificial neural networkComputer sciencePhase (waves)FOS: Physical sciencesLink (geometry)Condensed Matter - Soft Condensed MatterComputational Physics (physics.comp-ph)Energy minimizationMultiscale modelingBoltzmann distributionHuman-Computer InteractionMolecular dynamicsArtificial IntelligencePhysics - Chemical PhysicsSoft Condensed Matter (cond-mat.soft)Physics - Computational PhysicsAlgorithmSoftwareMachine Learning: Science and Technology
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Adversarial reverse mapping of condensed-phase molecular structures: Chemical transferability

2021

Switching between different levels of resolution is essential for multiscale modeling, but restoring details at higher resolution remains challenging. In our previous study we have introduced deepBackmap: a deep neural-network-based approach to reverse-map equilibrated molecular structures for condensed-phase systems. Our method combines data-driven and physics-based aspects, leading to high-quality reconstructed structures. In this work, we expand the scope of our model and examine its chemical transferability. To this end, we train deepBackmap solely on homogeneous molecular liquids of small molecules, and apply it to a more challenging polymer melt. We augment the generator's objective w…

Chemical Physics (physics.chem-ph)Work (thermodynamics)Materials sciencelcsh:BiotechnologyTransferabilityGeneral EngineeringPhase (waves)FOS: Physical sciencesComputational Physics (physics.comp-ph)Resolution (logic)Multiscale modelinglcsh:QC1-999Physics - Chemical Physicslcsh:TP248.13-248.65General Materials ScienceRepresentation (mathematics)Reverse mappingBiological systemPhysics - Computational Physicslcsh:PhysicsGenerator (mathematics)APL Materials
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Short hydrogen bonds enhance nonaromatic protein-related fluorescence

2021

Significance Intrinsic fluorescence of nonaromatic amino acids is a puzzling phenomenon with an enormous potential in biophotonic applications. The physical origins of this effect, however, remain elusive. Herein, we demonstrate how specific hydrogen bond networks can modulate fluorescence. We highlight the key role played by short hydrogen bonds, present in the protein structure, on the ensuing fluorescence. We provide detailed experimental and molecular evidence to explain these unusual nonaromatic optical properties. Our findings should benefit the design of novel optically active biomaterials for applications in biosensing and imaging.

Chemical transformationOptics and PhotonicsGlutamineIntrinsic fluorescenceMolecular Dynamics SimulationPhotochemistryFluorescenceAb initio molecular dynamicsAmmoniaHumansSingle amino acidshort hydrogen bondDensity Functional TheoryMultidisciplinaryHydrogen bondChemistryintrinsic fluorescenceultraviolet fluorescenceHydrogen BondingConical intersectionFluorescenceBiophysics and Computational BiologyExcited statePhysical Sciences408PeptidesProceedings of the National Academy of Sciences of the United States of America
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Spectroscopic signatures of the carbon buckyonions C60@C180 and C60@C240: a dispersion-corrected DFT study

2013

We have investigated, using dispersion corrected DFT methods, the structure and the spectroscopic properties of carbon buckyonions C-60@C-180 and C-60@C-240. C-60, C-180 and C-240 showed a noticeable variation of their geometries in C-60@C-180 and C-60@C-240, upon encapsulation. Inclusion of the dispersion correction term in the calculations has a significant effect on the geometry. C-60@C-180 has a large positive interaction energy, while for C-60@C-240 a negative value is found indicating that only C-240 can easily accommodate C-60. In both cases dispersion interactions strongly contribute to the stabilization of the complexes. Vibrational frequencies, electronic transitions and NMR prope…

ChemistryDispersion Correctionfullerenes; computational chemistryAnalytical chemistryfullerenesGeneral Physics and AstronomyPositive interactioncomputational chemistryDFTEncapsulated buckyonionSpectroscopic.Atomic electron transitionChemical physicsPhysical and Theoretical ChemistrySettore CHIM/02 - Chimica Fisica
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A gallery of Chua's Attractors - Part VI

2007

Chua oscillator chaos n-scroll hyperchaotic and synchronized attractors computational approach
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Functional Type Error Control for Stabilised Space-Time IgA Approximations to Parabolic Problems

2018

The paper is concerned with reliable space-time IgA schemes for parabolic initial-boundary value problems. We deduce a posteriori error estimates and investigate their applicability to space-time IgA approximations. Since the derivation is based on purely functional arguments, the estimates do not contain mesh dependent constants and are valid for any approximation from the admissible (energy) class. In particular, they imply estimates for discrete norms associated with stabilised space-time IgA approximations. Finally, we illustrate the reliability and efficiency of presented error estimates for the approximate solutions recovered with IgA techniques on a model example.

Class (set theory)Computer scienceReliability (computer networking)Space timeFunctional typeParabolaValue (computer science)010103 numerical & computational mathematicsComputer Science::Numerical Analysis01 natural sciences010101 applied mathematicsApplied mathematics0101 mathematicsError detection and correctionEnergy (signal processing)
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Guaranteed error bounds and local indicators for adaptive solvers using stabilised space–time IgA approximations to parabolic problems

2019

Abstract The paper is concerned with space–time IgA approximations to parabolic initial–boundary value problems. We deduce guaranteed and fully computable error bounds adapted to special features of such type of approximations and investigate their efficiency. The derivation of error estimates is based on the analysis of the corresponding integral identity and exploits purely functional arguments in the maximal parabolic regularity setting. The estimates are valid for any approximation from the admissible (energy) class and do not contain mesh-dependent constants. They provide computable and fully guaranteed error bounds for the norms arising in stabilised space–time approximations. Further…

Class (set theory)Series (mathematics)Space timeContext (language use)010103 numerical & computational mathematicsType (model theory)01 natural sciencesIdentity (music)010101 applied mathematicsComputational MathematicsComputational Theory and MathematicsModeling and SimulationApplied mathematicsA priori and a posteriori0101 mathematicsEnergy (signal processing)MathematicsComputers & Mathematics with Applications
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Collocation Method for Linear BVPs via B-spline Based Fuzzy Transform

2018

The paper is devoted to an application of a modified F-transform technique based on B-splines in solving linear boundary value problems via the collocation method. An approximate solution is sought as a composite F-transform of a discrete function (which allows the solution to be compactly stored as the values of this discrete function). We demonstrate the effectiveness of the described technique with numerical examples, compare it with other methods and propose theoretical results on the order of approximation when the fuzzy partition is based on cubic B-splines.

CollocationB-spline010103 numerical & computational mathematics02 engineering and technologyFunction (mathematics)01 natural sciencesFuzzy logicCollocation method0202 electrical engineering electronic engineering information engineeringOrder (group theory)Applied mathematics020201 artificial intelligence & image processingBoundary value problem0101 mathematicsApproximate solutionMathematics
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