From skeptic to believer: The power of models

Complex systems that contain a chemical component benefit from clever application of computational and cheminformatics tools. As classically trained synthetic experimentalists, we initially viewed in silico methods with skepticism, in large part due to our own ignorance. Over time, we were each exposed to enlightening projects that completely altered our opinions on computation; we now firmly believe that better science occurs when experiments and models exist in harmony. The goal of our perspective is three-fold. We first provide historical context for the explosive growth of modern simulation-based techniques, with interesting parallels to the development of modern scientific thought. We next discuss the three short vignettes from our own research that illuminated us into appreciating computation. Finally, we propose several calls to action for the scientific community to better advocate for computation. Science education must better prepare learners of chemistry for an increasingly digital world that not only includes experimental data but also synthetic data from generative models. As scientists, we must make raw data (experimental and synthetic) accessible to the broader community.