In our opinion a central challenge with simulations is that incorrect results often do not look unrealistic or incorrect, and therefore care must be taken to validate that the results of a polymer simulation are meaningful. With this optimistic view of the growing power of polymer modeling and simulations, we feel it is more important now than ever to educate the researchers-new students at undergraduate and graduate levels or experts in other fields who choose to use simulations for the first time to complement their work-of the right/ correct ways to design and perform polymer simulations. Nonetheless, from our perspective, for every one of those incorrect simulation studies, there are many more carefully and correctly done, creative, powerful, and insightful simulations (or in silico experiments) whose predictions have been proven correct by in vitro experiments and/or whose insights have inspired novel experiments. We believe that part of this skepticism stems from a non-negligible number of peer-reviewed articles in reputable journals that present incorrectly/hastily done computational studies and/or predict phenomena that prove to be wrong by follow-up simulations/theory/experiments. Yet, we sometimes hear skeptics label simulations as an “easy” and/or “unreal” tool in contrast to (more difficult) theory and (real) experiments.
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With these software and hardware advances, a growing number of simulation studies of polymers provide valuable insight into new as well as existing macromolecular materials and through predictions inspire polymer chemists to find synthetic routes to design new materials that show tremendous promise. It is not surprising that with these advances we have reached a point where molecular simulations of polymers can be done significantly faster than some of the earliest simulations of polymers (1) and on a device as small as a smartphone! Perhaps it is not an exaggeration to say that the power to do polymer simulations is at our fingertips. Many, but not all, of these computational challenges have been addressed over the years with numerous developments in software and algorithms as well as through significant improvements in computer hardware. Polymers are a class of complex fluids that present unique challenges to a computational scientist, as they exhibit interesting and important phenomena over a broad range of length scales starting from monomer (angstroms) to the polymer radius of gyration (nanometers) and time scales ranging from femtoseconds to seconds/minutes or even years (in the case of glasses). We highlight best practices, key challenges, and important advances in model development/selection, computational method choices, advanced sampling methods, and data analysis, with the goal of educating potential polymer simulators about ways to improve the validity, usefulness, and impact of their polymer computational research. With these considerations in mind, in this Perspective we discuss our philosophy for carefully developing or selecting appropriate models, performing, and analyzing polymer simulations. To ensure that this growing power of simulations is harnessed correctly, and meaningful results are achieved, care must be taken to ensure the validity and reproducibility of these simulations.
With recent advances in computing power, polymer simulations can synergistically inform, guide, and complement in vitro macromolecular materials design and discovery efforts. These computational approaches enable predictions and provide explanations of experimentally observed macromolecular structure, dynamics, thermodynamics, and microscopic and macroscopic material properties. Molecular modeling and simulations are invaluable tools for the polymer science and engineering community.