shown the capability to describe combustion reactions requiring much fewer computational resources than ab initio methods. However, the time scale in those simulations still re- mains a problem when temperature is lowered, especially below 1000 K. To accelerate the simulation process and tackle the time scales required to study complex reaction systems, various methods have been developed that apply some sort of bias in thermal or potential energy or its gradient. Enhanced sampling methods, examples of which are metadynamics, Temperature-Accelerated Dynamics (TAD), and Adaptive Biasing Force (ABF), 21 concen- trate on improving the overall sampling of the conguration space and thus address the problem of ergodicity in the MD simulation. However, these methods either lack exibility, restricting the applicable scope to a small range of problems, which is a common weakness of accelerated MD methods, or, due to their biases, fail to accurately describe some reaction pathways and system properties. The requirements for the generality of a comprehensive PES searching process have led us to the Collective Variable-Driven Hyperdynamics (CVHD) method, which combines the strengths of accelerated MD methods and enhanced sampling methods and was recently developed by K. M. Bal.