Reaction Acceleration: Reviving the Second Derivative in Chemical Kinetics

How do we know when a chemical reaction is speeding up, slowing down, or switching between kinetic regimes? The answer lies in the time derivative of the rate: reaction acceleration , . Although the thermodynamic foundation laid by Raw and Yourgrau has existed for seven decades, and although second‐derivative landmarks are implicit throughout modern kinetics, no unified acceleration framework has been developed for the non‐monotonic dynamics typical of systems chemistry. Here, we develop such a framework. We (i) connect the Raw–Yourgrau single‐reaction limit to network kinetics through matrix flux–force relations and the autonomous identity ; (ii) derive closed‐form acceleration landmarks for canonical mechanisms, including the Finke–Watzky two‐step model; (iii) establish a sign‐change taxonomy that makes explicit why the pattern is a constraint rather than a unique identifier; and (iv) benchmark a smoothing‐plus‐bootstrap workflow by quantifying bias, root‐mean‐square error, empirical coverage, and detection for noisy progress curves in an open‐source Python implementation.