We review the history of the parallel tempering simulation method. From its origins in data analysis, the parallel tempering method has become a standard workhorse of physicochemical simulations. We discuss the theory behind the method and its various generalizations. We mention a selected set of the many applications that have become possible with the introduction of parallel tempering, and we suggest several promising avenues for future research.

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Analogous to the way the Human Genome Project advanced an array of biological sciences by mapping the human genome, the Materials Genome Initiative aims to enhance our understanding of the fundamentals of materials science by providing the information we need to accelerate the development of new materials.This approach is particularly applicable to recently developed classes of nanoporous materials, such as metal-organic frameworks (MOFs), which are synthesized from a limited set of molecular building blocks that can be combined to generate a very large number of different structures. In this Perspective, we illustrate how a materials genome approach can be used to search for high-performance adsorbent materials to store natural gas in a vehicular fuel tank. Drawing upon recent reports of large databases of existing and predicted nanoporous materials generated in silico, we have collected and compared on a consistent basis the methane uptake in over 650 000 materials based on the results of molecular simulation. The data that we have collected provide candidate structures for synthesis, reveal relationships between structural characteristics and performance, and suggest that it may be difficult to reach the current Advanced Research Project Agency-Energy (ARPA-E) target for natural gas storage. Broader contextNatural gas, mostly methane, is an attractive replacement for petroleum fuels for automotive vehicles because of its economic and environmental advantages. However, it suffers from a low volumetric energy density, necessitating densication to yield reasonable driving ranges from a full fuel tank. Densication strategies in the market today, liquefaction and compression, require expensive and cumbersome vehicular fuel tanks and rell station infrastructure. If we are able to develop a nanoporous adsorbent material to store natural gas at ambient temperature and moderate pressure, one could envision a simple fuel tank that can be relled at home. Modern, advanced nanoporous materials are highly tunable, inundating researchers with practically innite possibilities of materials to synthesize and test for methane storage. The current research is focused on nding among these millions of possible materials one that can be used to store natural gas without using liquefaction or compression processes. In this Perspective, we adopt a computational approach to screen databases of over 650 000 nanoporous material structures. Using this nanoporous materials genome approach, we reveal relationships between structural characteristics and performance, and suggest that it may be difficult, if not impossible, to reach the current Advanced Research Project Agency-Energy (ARPA-E) target for natural gas storage using nanoporous materials.

We here describe a database of computationally predicted zeolite-like materials. These crystals were discovered by a Monte Carlo search for zeolite-like materials. Positions of Si atoms as well as unit cell, space group, density, and number of crystallographically unique atoms were explored in the construction of this database. The database contains over 2.6 M unique structures. Roughly 15% of these are within +30 kJ mol(-1) Si of α-quartz, the band in which most of the known zeolites lie. These structures have topological, geometrical, and diffraction characteristics that are similar to those of known zeolites. The database is the result of refinement by two interatomic potentials that both satisfy the Pauli exclusion principle. The database has been deposited in the publicly available PCOD database and in www.hypotheticalzeolites.net/database/deem/.