Towards Materials Ageing A Case Study in Navigating Energy Landscapes Sidney Yip

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Institute for Pure and Applied Mathematics, UCLA Navigating Chemical Compound Space for Materials and Bio Design Workshop III: Materials Design in Chemical Compound Space May 2 - 6, 2011 Towards Materials Ageing A Case Study in Navigating Energy Landscapes Sidney Yip Nuclear Science and Engineering/Materials Science and Engineering MIT

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Institute for Pure and Applied Mathematics, UCLA Navigating Chemical Compound Space for Materials and Bio Design Workshop III: Materials Design in Chemical Compound Space May 2 - 6, 2011. Towards Materials Ageing A Case Study in Navigating Energy Landscapes Sidney Yip - PowerPoint PPT Presentation

Transcript of Towards Materials Ageing A Case Study in Navigating Energy Landscapes Sidney Yip

Page 1: Towards Materials Ageing A Case Study in Navigating Energy Landscapes Sidney Yip

Institute for Pure and Applied Mathematics, UCLANavigating Chemical Compound Space for Materials and Bio Design

Workshop III: Materials Design in Chemical Compound SpaceMay 2 - 6, 2011

Towards Materials AgeingA Case Study in Navigating Energy Landscapes

Sidney Yip

Nuclear Science and Engineering/Materials Science and Engineering

MIT

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Connecting a few dots …

energy landscape view of time evolution of atomic system

An algorithm (metadynamics) to sample transition state pathway

Use TSP trajectories to explain the viscosity of glasses-- the nature of fragility in the glass transition

Other problems of slow dynamics (materials ageing) where atomistic simulations can elucidate the molecular mechanisms

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Energy Landscape Perspective

Transition State Pathway Sampling (ABC)

TSP trajectories → Q(T)

Calculate viscosity of supercooled liquids

Connection with other materials ageing phenomena

creepcorrosionCement setting viscosity

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Viscosities of vitrified liquids are in need of explanation by atomistic simulation

C. A. Angell, J. Phys. Chem. Solids 49 (1988)

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A metadynamics algorithm : Autonomous Basin Climbing

A. Kushima et al, J Chem Phys 130 (2009)

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Viscosity of a binary LJ model (Kob) calculatedusing a coarse-graining formulation based on TSP trajectory

A. Kushima et al, J Chem Phys 130 (2009)

]/)(exp[)( 0 TkTQT B

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A. Kushima et al, J. Chem. Phys.130 (2009)

TSP trajectory analysis to obtain an effective temp-dep activation barrier Q(T)

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Green-Kubo calculation using Network Model and TSP trajectories

A. Kushima et al, J. Chem. Phys.130 (2009), J. Li, Plos ONE 6, e17909 (2011)

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MD

Green-Kubo calculation using Network Model and TSP trajectories

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SiO2

Saika-Voivid et al, Nature (2001)

Potential: Feuston and Garofalini, JCP (1988)

Horbach and Kob, Phys.Rev. B (1999)

C. A. Angell, J Phys Chem Solids 88 (1988)

A. Kushima et al, J. Chem. Phys.131 (2009)

Experimental test of predicted viscosity of SiO2

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Disconnectivity Graphs of a fragile and strong glass former

A. Kushima, JCP 131 (2009) See Becker and Karplus, JCP 106 (1977), D. Wales (2006)

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Potential energy landscape profiles (derived from TSP trajectories)

F. H. Stillinger, JCP 88 (1988)

A. Kushima et al., JCP 131 (2009)

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Explanation of the signature behavior of glass transition-- revealing the underlying energy landscape that gives rise to the fragile temperature scaling of the shear viscosity η(T)

Mystery (mechanism) of the dynamical crossover(physical nature of fragility)

Transition from strong to fragile behavior with decreasing T signals the onset of deep local energy minimagiving rise to the sharp increase of Q(T)

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contributors

Akihiro Kushima (MIT/UPenn)Xi Lin (BU)

Ju Li (UPenn/MIT)

John Mauro (Corning Research Center) Jacob Eapen (NCSU)Xiaofeng Qian (MIT)

Phong Diep (Corning Research Center)

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That was Stop 1

Continuing onto Creep, Corrosion, and Cement,which is Stop 2 (end of navigation)

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R. L.Klueh, Int. Mat. Rev. 50, 287 (2005)

Creep deformation in steel P-91MD strain rates ~ 107 s-1 !

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Stress corrosion cracking

C. Ciccotti, J. Phys. D 42 (2009)

J. W. Martin, BP Research (2010)

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DOE Energy Innovation Hub in Nuclear Modeling and Simulation

CASL: Consortium for Advanced Simulationof Light Water Reactors

Core partnersOak Ridge National LaboratoryElectric Power Research InstituteIdaho National LaboratoryLos Alamos National LaboratoryMassachusetts Institute of TechnologyNorth Carolina State UniversitySandia National LaboratoriesTennessee Valley AuthorityUniversity of MichiganWestinghouse Electric Company

Vision: Create a predictive simulation capabilityfor a virtual LWR

Awarded May 28, 2010

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Chalk River Unidentified Deposits (CRUD)

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CRUD deposition/growth (early stage) and CRUD-inducedlocalized corrosion (late stage) leading to clad cracking

Fe++ Ni++

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Cement hydration (setting) is a ‘grand challenge’ to molecular simulation

ShearmodulusG* [Pa]

Ultrason measurement, w/c = 0.8 [Lootens 2004]C3S + H2O → C-S-H + Ca(OH)2

C3S = Ca3SiO3 C-S-H = CaO-SiO2-H2O

gelation

C-S-H precipitation

percolation/jamming

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(CaO)1.65(SiO2)(H20)1.75

• green = inter-layer Ca• grey = intra-layer Ca• blue = oxygen• white = hydrogen

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Binary Colloidal Model with sticky potentials [P. Monasterio, 2010]

Model is undergoing further development to incorporate

C-S-H nucleation/growth

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Energy Landscape Perspective

Transition State Pathway Sampling (ABC)

TSP trajectories → Q(T)

Calculate viscosity of supercooled liquids

Connection with other materials ageing phenomena

creepcorrosionCement setting viscosity

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Energy Landscape Perspective

viscosity

TSP trajectory

ABC

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Energy Landscape Perspective

creepcorrosionCement setting viscosity

TSP trajectory

ABC

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Energy Landscape Perspective

creepcorrosionCement setting viscosity

TSP trajectory

ABC

processes relevant to materials ageing