Using RMG Out-of-the-Box for Formic Acid Pyrolysis and Oxidation

As both a prototype oxygenated biofuel and a central intermediate in combustion chemistry, the predictive modeling of formic acid (HOCHO) reactivity is of fundamental importance. Prior literature work [Energy Fuels 2022, 36, 23, 14382–14392] argued that an automatically-generated chemical kinetic model cannot reproduce jet-stirred reactor (JSR) speciation adequately, concluding that hand-tuned mechanisms are required. Here, we overturn that conclusion by demonstrating the fidelity of an automated model. An out-of-the-box, fully automated predictive model, built deliberately without quantum-chemical refinement or ad hoc fitting, reliably captures formic acid JSR oxidation speciation across 550–1150 K and an equivalence ratio range of 0.5–2.0, as well as laminar burning velocity observations at different mixture compositions. The model’s remaining discrepancies, which appear under pyrolysis conditions, stem from the same core issue masked in prior work [Combust. Flame 2021, 223, 77–87]: the absence of a physically consistent description of the CH2O2 pressure-dependent network. We demonstrate that the apparent agreement in prior pyrolysis modeling relied on fitted, pressure-independent rate coefficients that obscured the unresolved branching ratio between decarboxylation (HOCHO <=> CO2 + H2) and dehydration (HOCHO <=> CO + H2O). By clarifying these issues, we establish that predictive, automated kinetic models are already within reach for small oxygenated fuels and identify this pressure-dependent network as the key remaining challenge for fully reliable formic acid modeling.