Simon Tricard *a, Efraim Feinstein b, Robert F. Shepherd a, Meital Reches a, Phillip W. Snyder a, Dileni C. Bandarage a, Mara Prentiss b and George M. Whitesides *ac
Current computational simulations can not accurately quantify the very large number of interactions and conformations required to describe molecular phenomena (for example, polymer dynamics, solvation, crystal nucleation and growth, molecular recognition, etc.). Descriptions of the kinetics of dynamic phenomena are mostly unapproachable without drastic simplifications. Assumptions and approximations – some major – are required to make aspects of static and equilibrium problems tractable for theoretical modeling or simulation. Although we applaud the value of digital, computational models, we also believe that analog, physical methods1–4 have a role to play in understanding molecular (and supramolecular) phenomena, and we are exploring such models as a complement to theory and in silico simulation.
Current computational simulations can not accurately quantify the very large number of interactions and conformations required to describe molecular phenomena (for example, polymer dynamics, solvation, crystal nucleation and growth, molecular recognition, etc.). Descriptions of the kinetics of dynamic phenomena are mostly unapproachable without drastic simplifications. Assumptions and approximations – some major – are required to make aspects of static and equilibrium problems tractable for theoretical modeling or simulation. Although we applaud the value of digital, computational models, we also believe that analog, physical methods1–4 have a role to play in understanding molecular (and supramolecular) phenomena, and we are exploring such models as a complement to theory and in silico simulation.
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