  Autonomous reaction network exploration algorithms offer a systematic
approach to explore mechanisms of complex chemical processes. However, the
resulting reaction networks are so vast that an exploration of all potentially
accessible intermediates is computationally too demanding. This renders
brute-force explorations unfeasible, while explorations with completely
pre-defined intermediates or hard-wired chemical constraints, such as
element-specific coordination numbers, are not flexible enough for complex
chemical systems. Here, we introduce a Steering Wheel to guide an otherwise
unbiased automated exploration. The Steering Wheel algorithm is intuitive,
generally applicable, and enables one to focus on specific regions of an
emerging network. It also allows for guiding automated data generation in the
context of mechanism exploration, catalyst design, and other chemical
optimization challenges. The algorithm is demonstrated for reaction mechanism
elucidation of transition metal catalysts. We highlight how to explore
catalytic cycles in a systematic and reproducible way. The exploration
objectives are fully adjustable, allowing one to harness the Steering Wheel for
both structure-specific (accurate) calculations as well as for broad
high-throughput screening of possible reaction intermediates.
