| Case Study | Materials System | Modeling Chain | Key Insight | |------------|------------------|----------------|-------------| | | CoCrFeMnNi | DFT → Cluster expansion → Monte‑Carlo → Thermodynamic phase diagram | Identified a composition window with low ordering temperature. | | 8.2. Battery cathode degradation | LiNi₀.₈Co₀.₁₅Al₀.₀₅O₂ | DFT (defect formation) → Kinetic Monte‑Carlo (diffusion) → FEM (stress) | Linked Li‑vacancy clustering to crack nucleation. | | **8.3. 2‑D material heter
| Aspect | Recommended Practice | |--------|----------------------| | | Compare against analytical solutions (e.g., harmonic oscillator) or standard benchmark suites (e.g., NIST MD benchmarks). | | Model validation | Cross‑check with experimental data: lattice constants, elastic constants, phonon frequencies, diffusion coefficients, etc. | | Uncertainty quantification | Perform sensitivity analysis on key parameters (e.g., cutoff energy, time step). Use bootstrapping or Bayesian inference to estimate confidence intervals. | | Error propagation | Document how uncertainties in lower‑scale models affect higher‑scale predictions (e.g., DFT‑derived force‑field errors → MD diffusion errors). | | Reproducibility tests | Run the same workflow on different hardware or with different compilers; verify identical outputs within tolerance. | handbook of materials modeling pdf