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Advanced Thermodynamics and Molecular Simulations

Advanced Thermodynamics and Molecular Simulations

IIT Roorkee July 2018 via YouTube Direct link

Advanced Thermodynamics and Molecular Simulations

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Advanced Thermodynamics and Molecular Simulations

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Advanced Thermodynamics and Molecular Simulations

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  1. 1 Advanced Thermodynamics and Molecular Simulations
  2. 2 Lecture 01-Introduction to the course
  3. 3 Lecture 02: Molecular basis of energy and entropy
  4. 4 Lecture 03: Probability and probability distributions
  5. 5 Lecture 04: Probability distributions and thermodynamic equilibrium
  6. 6 Lecture 05: Energy distribution in molecular systems
  7. 7 Lecture 06: First and second law of thermodynamics
  8. 8 Lecture 07- Reversible and irreversible processes; third law; legendre transformation...
  9. 9 Lecture 08- Thermodynamic functions for multi-component systems; chemical potential...
  10. 10 Lecture 09-Extensive and intensive variables; gibbs duhem relation; euler theorem; maxwell relations
  11. 11 Lecture 10- Discrete and continuous probabilities; stirling approximation
  12. 12 Lecture 11- Binomial distribution approaches gaussian distribution for large n...
  13. 13 Lecture 12- Solution of drunkard walk; lagrange multipliers
  14. 14 Lecture 13: Energy distribution in molecular system revisited
  15. 15 Lecture 14: Canonical ensemble: most probable distribution, partition function
  16. 16 Lecture 15: Definition of temperature; third law of thermodynamics
  17. 17 Lecture 16: Canonical ensemble: Helmholtz free energy, averages and fluctuations, specific heat
  18. 18 Lecture 17: Partition function of a dense gas; grand canonical ensemble: partition function
  19. 19 Lecture 18: Computing properties in grand canonical ensemble
  20. 20 Lecture 19: Isothermal isobaric ensemble
  21. 21 Lecture 20: Summary of thermodynamic ensembles; partition function of an ideal gas
  22. 22 Lecture 21: Mixing and phase separation, phase equilibrium of a multiphase multicomponent system
  23. 23 Lecture 22: Pure component phase diagram; Solution thermodynamics: Helmholtz free energy density
  24. 24 Lecture 23: Characterizing mixing and phase separation using Helmholtz free energy density
  25. 25 Lecture 24: Common tangent construction, definition of binodal, spinodal, and critical point
  26. 26 Lecture 25: Osmotic pressure and chemical potential
  27. 27 Lecture 26: Lattice model of liquid solutions I
  28. 28 Lecture 27: Lattice model of liquid solutions II
  29. 29 Lecture 28: Lattice model of liquid solutions III
  30. 30 Lecture 29: Critical review of Lattice model, theoretical basis of molecular dynamics simulation
  31. 31 Lecture 30: Theoretical basis of molecular dynamics simulation
  32. 32 Lecture 31: Interaction energy and force field
  33. 33 Lecture 32: Liouiville theorem; theoretical basis of Monte Carlo simulation
  34. 34 Lecture 33: Introduction to Monte Carlo simulation method
  35. 35 Lecture 34: Markov chain algorithm, condition for equilibrium and detailed balance
  36. 36 Lecture 35: Metropolis algorithm, periodic boundary condition
  37. 37 Lecture 36: Numerical implementation of Monte Carlo simulation: python examples I
  38. 38 Lecture 37: Numerical implementation of Monte Carlo simulation: python examples II
  39. 39 Lecture 38: Numerical implementation of Monte Carlo simulation: python examples III
  40. 40 Lecture 39: Numerical implementation of Monte Carlo simulation: python examples IV
  41. 41 Lecture 40: Numerical implementation of Monte Carlo simulation: python examples V
  42. 42 Lecture 41: Particle simulations: comparison with quantum chemical and continuum simulations
  43. 43 Lecture 42: Pair potentials
  44. 44 Lecture 43: Saving CPU time: short range and long range interactions
  45. 45 Lecture 44: Bonded and nonbonded interactions, force fields
  46. 46 Lecture 45: Practical aspects of molecular simulations
  47. 47 lecture 46: Numerical implementation of MD; thermostat and barostat
  48. 48 Lecture 47: MD simulations - efficiency and parallelization, sampling and averaging
  49. 49 Lecture 48: MD simulations - analysis of simulation trajectories (continued), case studies I
  50. 50 Lecture 49: MD simulations - case studies II
  51. 51 Lecture 50: MD simulations - case studies III
  52. 52 Lecture 51: Free energies and phase behavior; extension of canonical ensemble monte carlo...
  53. 53 Lecture 52: Extension of canonical ensemble monte carlo to other ensembles (continued)
  54. 54 Lecture 53: Monte carlo in gibbs ensemble and semi-grand canonical ensemble...
  55. 55 Lecture 54: Thermodynamic integration (continued); widom's particle insertion...
  56. 56 Lecture 55: Multiple histogram method; umbrella sampling; thermodynamic cycle...
  57. 57 Lecture 56:Tackling time scale issues (continued); nonequilibrium molecular dynamics...
  58. 58 Lecture 57: Multiparticle collision dynamics; lattice boltzmann method; coarse-graining
  59. 59 Lecture 58: Case studies
  60. 60 Lecture 59: Simulations of chemical reactions using kinetic monte carlo simulations
  61. 61 Lecture 60: Reactive force fields; ab initio molecular dynamics and other advanced methods ...

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