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Molecular simulation methods

Molecular simulation methods. Ab-initio methods (Few approximations but slow) DFT CPMD Electron and nuclei treated explicitly. Classical atomistic methods (More approximations) Classical molecular dynamics Monte Carlo Brownian dynamics

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Molecular simulation methods

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  1. Molecular simulation methods • Ab-initio methods (Few approximations but slow) • DFT • CPMD • Electron and nuclei treated explicitly. • Classical atomistic methods (More approximations) • Classical molecular dynamics • Monte Carlo • Brownian dynamics • No electronic degrees of freedom. Electrons are approximated through fixed partial charges on atoms. • Continuum methods (No atomistic details)

  2. mm m nm Atomistic methods Ab-initio methods ns s ms ps Statistical and continuum methods

  3. Simplified interactions used in classical simulations V = Vbond + Vangle + Vdihedral + VLJ + VElecrostatics

  4. Implementation of classical interactions • Molecular topologies are fixed so the bonded interactions are implemented as static neighbor lists • One time expense in the beginning • Non-bonded interactions are implemented as dynamic neighbor lists • Usually not updated at every time step • Only two body interactions, so relatively easy to implement.

  5. Reactive systems • Chemical reactions are association and dissociation of chemical bonds • Classical simulations cannot simulate reactions • ab-initio methods calculate overlap of electron orbitals to investigate chemical reactions • ReaX force field postulates a classical bond order interaction to mimic the association and dissociation of chemical bonds1 1 van Duin et al , J. Phys. Chem. A, 105, 9396 (2001)

  6. Bond order for C-C bond Bond order interaction • Uncorrected bond order: • Where is for andbonds • The total uncorrected bond order is sum of three types of bonds • Bond order requires correction to account for the correct valency 1 van Duin et al , J. Phys. Chem. A, 105, 9396 (2001)

  7. Bond order interaction • After correction the bond order between a pair of atoms depends on the uncorrected bond orders of the neighbors of each atoms • The uncorrected bond orders are stored in a tree structure for efficient access. (I think Metin will be able to elaborate on this) • The bond orders rapidly decay to zero as a function of distance so it is reasonable to construct a neighbor list for efficient computation of bond orders

  8. Neighbor lists for bond order

  9. Bond order : Choline

  10. Bond order : Benzene

  11. Other local energy terms • The other interaction terms common to classical simulations, e.g. bond energy, valence angle and torsion, are appropriately modified and contribute for non-zero bond order pairs of atoms • These terms also become many body interactions as bond order itself depends on the neighbors and neighbor’s neighbors • Due to variable bond structure there are other interaction terms, such as over/under coordination energy, lone pair interaction, 3 and 4 body conjugation, and three body penalty energy

  12. Non bonded van der Waals interaction • The van der Waals interactions are modeled using distance corrected Morse potential • Where R(rij) is the shielded distance given by

  13. Electrostatics • Shielded electrostatic interaction is used to account for orbital overlap of electrons at closer distances • The long range electrostatics interactions are handled using the Fast Multipole Method (FMM).

  14. FMM method

  15. Charge equilibration (QEq) method • The fixed partial charge model used in classical simulations is inadequate for reacting systems. Ideally one would like to compute the partial charges on atoms at each time step using some ab-initio method. • We compute the partial charges on atoms at each time step using a simplified approach call Qeq method • We expand electrostatic energy as a Taylor series in charge around neutral charge

  16. Charge equilibration (QEq) method • Further we identify the term linear in charge as electronegativity of the atom and the qudratic term as electrostatic potential and self energy • Thus we optimize the • where • for {qi} under charge neutrality constraint

  17. Charge equilibration (QEq) method • This constraint optimization problem is rewritten as two vector unconstraint optimization problem using Lagrange’s multiplier method • The unconstraint system is solved using GMRES method (Please add details of the method)

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