In this exercise, you will perform ab initio molecular dynamics using Second Generation Car-Parrinello (SGCP) molecular dynamics. Please cite [[ https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.98.066401 | Phys. Rev. Lett. 98, 066401 ]], if you use this method. Published work using SGCP method: [[https://pubs.acs.org/doi/10.1021/acs.jpcc.8b05933 | J. Phys. Chem. C 2018, 122, 42, 24068–24076]] [[ https://doi.org/10.1021/acs.jpclett.0c01025 |J. Phys. Chem. Lett. 2020, 11, 9, 3724–3730]] ====1. Introduction==== Second Generation CPMD (2ndG CPMD) is a molecular dynamics method that combines the efficiency of Car-Parrinello MD (CPMD) with the accuracy of Born-Oppenheimer MD (BOMD). It avoids fully self-consistent field (SCF) optimizations at each time step while enabling larger integration steps and maintaining accuracy close to BOMD. **Goal:** Retain the efficiency of CPMD while achieving BOMD-level accuracy. - **Efficiency**: Large time steps ; No full SCF loops - **Accuracy**: Forces nearly indistinguishable from BOMD - **Stability**: Effective for systems with vanishing band gaps - **Error Control**: Controlled deviation from BO surface using adaptive correction ====2. Comparison with CPMD and BOMD==== | Feature | CPMD | BOMD | SGCP | | SCF at each step | No | Yes | Partially (predictor-corrector) | | Time step | Small (~0.1 fs) | Large (~1 fs) | Large (~1–2 fs) | | Conserved quantity preservation | Excellent | Reasonable | Excellent | | On Born-Oppenheimer surface | Slightly above| Yes | Very close | | Works for small-gap systems | Poor | Good | Good | ====3. ASPC Method==== ASPC Method: Always Stable Predictor Corrector ASPC is a **Gear-type integrator** for electronic wavefunctions: Predictor: \[ C_p(t_n) = \sum_{m=1}^{K} (-1)^{m+1} \cdot m \cdot B_m \cdot P_S(t_{n-m}) \] where: - \( B_m \): Kolafa predictor coefficients - \( P_S \): projection onto the overlap matrix \( S \) Corrector: \[ C(t_n) = \omega \cdot \min[C_p(t_n)] + (1 - \omega) \cdot C_p(t_n), \quad \omega = \frac{K}{2K - 1} \] Langevin Dynamics & Dissipation Compensation Because ASPC introduces small dissipation, **Langevin-type equations** are used to stabilize the dynamics: \[ M_I \ddot{R}_I = F_\text{BO} - (\gamma_D + \gamma_L)\dot{R}_I + \Xi_I \] - \( \gamma_D \): implicit friction from ASPC - \( \gamma_L \): Langevin thermostat - \( \Xi_I \): Langevin random noise ====4. How to Set Up in CP2K==== | Parameter | Purpose | Notes | | EXTRAPOLATION_ORDER | Higher gives better predictor | 1–4 typical, 0 for metallic is more stable | | MAX_SCF_HIST | Controls SCF correction | ≥2 helps smoother convergence | | STEPSIZE | Time step in fs | ~0.5–2 fs depending on system | | PRECONDITIONER | Affects SCF convergence | `FULL_SINGLE_INVERSE` slightly better | | NOISY_GAMMA (γ_D) | ASPC dissipation compensation | Adjust to control drift in T and energy | | GAMMA (γ_L) | Langevin thermostat strength | Set to 0 for dissipation-only integration | 1. ASPC Extrapolation &FORCE_EVAL &DFT &QS EXTRAPOLATION ASPC EXTRAPOLATION_ORDER 0 # Higher gives better corrector &END QS &SCF MAX_SCF_HIST 2 &END SCF &END DFT &END FORCE_EVAL 2. Langevin Thermostat &MOTION &MD ENSEMBLE LANGEVIN &LANGEVIN GAMMA 0.005 ! γ_L NOISY_GAMMA 4.0E-4 ! γ_D &END LANGEVIN &END MD &END MOTION 3. Atom-Specific γ_D (Optional) &THERMAL_REGION DO_LANGEVIN_DEFAULT TRUE &DEFINE_REGION TEMPERATURE 500 NOISY_GAMMA_REGION 4.E-4 LIST 577..745 &END DEFINE_REGION &END THERMAL_REGION