Modeling hydrogen-bonded systems like water clusters and atmospheric hydrates presents challenges on many fronts. First, the configurational space increases exponentially with system size and efficient sampling methods are needed to explore this vast space. A few of these configurational sampling approaches include molecular dynamics (MD), basin hopping (BH) and genetic algorithms (GA). Second, once a set of low energy structures have been identified, they are studied using rigorous ab initio methods like MP2 and CCSD(T). To get benchmark quality structures and binding energies, a proper account of basis set superposition error (BSSE) and incompleteness error (BSIE) as well as post-MP2 electron correlation effects is necessary. Third, factoring in zero-point and finite thermal corrections requires that we include anharmonic effects in a reasonable way. Each one of these choices dictates the quality of predictions that can be expected from computational models of hydrogen-bonded systems. The evolution of our methodology for modeling water clusters, (H2O)n=1-15 and atmospheric hydrates containing sulfuric acid, ammonia, and methylamine will be discussed. Future plans to expand these studies to larger clusters using efficient local correlation methods will also be outlined.

Evolution of methods for modeling hydrogen-bonded systems accurately and efficiently

249th National Meeting (2015)

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