Abstract
<jats:p>We present L-SVECV-f12, a local-correlation, explicitly correlated composite protocol for the 10 accurate prediction of reaction barrier heights and as demonstrated on a 17-reaction atmospheric-11 chemistry subset at 298 K promising for thermal rate constants in gas-phase atmospheric chemistry 12 calculation. The method retains the three-step architecture of the parent SVECV-f12 protocol but replaces 13 the canonical CCSD(T)-F12/CBS valence step with DLPNO-CCSD(T)-F12, achieving wall-clock 14 speedups of 2.7-3.0 relative to the canonical reference while retaining sub-kcal mol-1 accuracy. To select 15 the DFT geometry and frequency step, fourteen density functionals spanning hybrid GGA, hybrid meta-16 GGA, range-separated hybrid, and double-hybrid families, paired with three correlation-consistent triple-17 zeta basis sets (chemical models), were benchmarked against the HTBH38/08, NHTBH38/08, and 18 DBH24/08 barrier-height databases and CCBGM17 experimental reaction rate subset, (17 experimental 19 rate constants spanning 19 orders of magnitude in k). Among the chemical models candidates, ranking by 20 a composite score identifies CAM-B3LYP-D3/def2-TZVPP as the best-performing chemical model 21 within L-SVECV-f12, achieving a MUD in the combined HTBH38/NHTBH38 dataset of 0.608 kcal mol-22 1, closely followed by revPBE0-D3/jun-cc-pV(T+d)Z (0.614 kcal mol-1) and CAM-B3LYP-D3/jun-cc-23 pV(T+d)Z (0.624 kcal mol-1). Monte Carlo sensitivity analysis over 1,000,000 random metric-weight 24 combinations confirms that CAM-B3LYP-D3/def2-TZVPP occupies first place in 96.9% of all weighting 25 scenarios, establishing it as a robust, weighting-independent choice. Within the parent SVECV-f12 26 framework, MN15-L/jun-cc-pV(T+d)Z and ωB97X-D4/def2-TZVPP emerge as co-leading candidates as 27 their score difference is not statistically decisive and reflects complementary strengths; ωB97X-D4/def2-28 TZVPP excels on barrier heights (MUD = 0.413 kcal mol-1), while MN15-L/jun-cc-pV(T+d)Z dominates 29 the kinetic benchmark (MUDlog10(k) = 0.802). Across all protocols, functional choice is found to exert a 30 stronger influence on predictive accuracy than basis-set selection, and balanced triple-zeta basis sets (def2-31 TZVPP, jun-cc-pV(T+d)Z) consistently outperform diffuse aug-cc-pVTZ.</jats:p>