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The PC₃ Model

PC₃ uses a modular, pan-Canadian model to deliver graduate-level training in computational chemistry. Each course is co-taught by faculty from multiple institutions, combining diverse expertise with shared teaching responsibilities. Synchronous online delivery and hands-on assignments ensure students gain both theoretical understanding and practical skills. The program fosters consistent learning outcomes, research readiness, and national collaboration among students and instructors.

PC3 Model.JPG
In the Library

PC₃ Curriculum at a Glance

The Introductory Module
(Intro)

Delivery Mode:

  • Synchronous Zoom (2 × 1.5 hrs/week over a full semester)

Key Topics:

  • Molecular mechanics and force fields

  • Statistical mechanics and thermodynamics

  • Molecular dynamics and Monte Carlo methods

  • Hartree-Fock and post-HF methods

  • Basis sets, correlation methods, and multi-reference approaches

  • DFT and DFTB frameworks

Learning Outcomes:

  • Understand and apply core theoretical models in molecular simulation

  • Use modern software tools (GROMACS, ORCA, Gaussian, DFTB+)

  • Perform geometry optimization, conformational analysis, and property prediction

  • Evaluate electronic structure using both wavefunction and density-based approaches

Advanced Module I
(AM I)

Delivery Mode:

  • Synchronous Zoom (2 × 1.5 hrs/week for 6 weeks)

Key Topics:

  • Exchange-correlation functionals in DFT

  • Solid-state modeling and periodic boundary conditions

  • Plane waves, k-point sampling, band structure

  • Relativistic effects and effective core potentials

Learning Outcomes:

  • Perform DFT calculations for molecules and solids using tools like Quantum ESPRESSO

  • Model surfaces, adsorption, and periodic systems

  • Understand and apply relativistic corrections in electronic structure calculations

  • Choose and justify appropriate functionals and modeling techniques for complex systems

Advanced Module II
(AM II)

Delivery Mode:

  • Synchronous Zoom (2 × 1.5 hrs/week for 6 weeks)

Key Topics:

  • Reaction energies, bond dissociation enthalpies, free energy corrections

  • Transition state theory and kinetic modeling

  • Solvent effects, conformational sampling, Boltzmann averaging

  • Orbital analysis and mechanism prediction

Learning Outcomes:

  • Calculate reaction barriers, rates, and thermodynamic properties using DFT and wavefunction methods

  • Perform conformational and solvation analysis using Gaussian and ORCA

  • Apply TST and interpret kinetic data in the context of reaction mechanisms

  • Evaluate the influence of electronic structure, solvation, and theory level on chemical reactivity

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