Nested sampling is a Bayesian sampling technique developed to explore probability distributions localised in an exponentially small area of the parameter space. The algorithm provides both posterior samples and an estimate of the evidence (marginal likelihood) of the model. The nested sampling algorithm also provides an efficient way to calculate free energies and the expectation value of thermodynamic observables at any temperature, through a simple post-processing of the output. Previous applications of the algorithm have yielded large efficiency gains over other sampling techniques, including parallel tempering. In this paper we describe a parallel implementation of the nested sampling algorithm and its application to the problem of protein folding in a Gō-like force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations. We demonstrate the method by conducting folding simulations on a number of small proteins which are commonly used for testing protein folding procedures. A topological analysis of the posterior samples is performed to produce energy landscape charts, which give a high level description of the potential energy surface for the protein folding simulations. These charts provide qualitative insights into both the folding process and the nature of the model and force field used.
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Hydrogen technologies and fuel cells evoke, for many people, vision of a future in which electrical energy and heat can be generated not only cleanly but also noiselessly and efficiently—with only water as by‐product at the point of use. These technologies—particularly for transport applications—are viewed as a bridge to a sustainable and secure energy future. But despite its clear promise, hydrogen is today still largely only a potential energy carrier of the future; this chemical element is usually a key component of long‐term energy policies. But, as recently noted by Eames and McDowall: “…it is expectations about, and visions of, the future of hydrogen that are currently driving investment and research.” This article explores some of these expectations; in particular, we examine important scientific and technological issues concerning the production, storage, and utilization of hydrogen, as well as outlining the interrelated—and equally challenging—socioeconomic issues for a future hydrogen energy economy. We hope that this approach allows the reader to assess the complexities, challenges—and, of course, the considerable potential—of hydrogen and fuel cells in long‐term transport strategies. We illustrate the very considerable central role of chemistry in building innovative solutions to key areas of a future hydrogen energy economy.
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