Browsing by Subject "computation"

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    Insights into Proton-Coupled Electron Transfer from Computation
    (2014-06) Provorse, Makenzie
    Proton-coupled electron transfer (PCET) is utilized throughout Nature to facilitate essential biological processes, such as photosynthesis, cellular respiration, and DNA replication and repair. The general approach to studying PCET processes is based on a two-dimensional More O'Ferrall-Jencks diagram in which electron transfer (ET) and proton transfer (PT) occur in a sequential or concerted fashion. Experimentally, it is difficult to discern the contributing factors of concerted PCET mechanisms. Several theoretical approaches have arisen to qualitatively and quantitatively investigate these reactions. Here, we present a multistate density functional theory (MSDFT) method to efficiently and accurately model PCET mechanisms. The MSDFT method is validated against experimental and computational data previously reported on an isoelectronic series of small molecule self-exchange hydrogen atom transfer reactions and a model complex specifically designed to study long-range ET through a hydrogen-bonded salt-bridge interface. Further application of this method to the hydrogen atom abstraction of ascorbate by a nitroxyl radical demonstrates the sensitivity of the thermodynamic and kinetic properties to solvent effects. In particular, the origin of the unusual kinetic isotope effect is investigated. Lastly, the MSDFT is employed in a combined quantum mechanical/molecular mechanical (QM/MM) approach to explicitly model PCET in condensed phases.
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    Journalism in an Era of Big Data: Cases, Concepts, and Critiques
    (Digital Journalism, 2015) Lewis, Seth C.
    “Journalism in an era of big data” is thus a way of seeing journalism as interpolated through the conceptual and methodological approaches of computation and quantification. It is about both the ideation and implementation of computational and mathematical mindsets and skill sets in newswork—as well as the necessary deconstruction and critique of such approaches. Taking such a wide-angle view of this phenomenon, including both practice and philosophy within this conversation, means attending to the social/cultural dynamics of computation and quantification—such as the grassroots groups that are seeking to bring pro-social “hacking” into journalism (Lewis and Usher 2013, 2014)—as well as the material/technological characteristics of these developments. It means recognizing that algorithms and related computational tools and techniques “are neither entirely material, nor are they entirely human—they are hybrid, composed of both human intentionality and material obduracy” (Anderson 2013, 1016). As such, we need a set of perspectives that highlight the distinct and interrelated roles of social actors and technological actants at this emerging intersection of journalism (Lewis and Westlund 2014a). To trace the broad outline of journalism in an era of big data, we need (1) empirical cases that describe and explain such developments, whether at the micro (local) or macro (institutional) levels of analysis; (2) conceptual frameworks for organizing, interpreting, and ultimately theorizing about such developments; and (3) critical perspectives that call into question taken-for-granted norms and assumptions. This special issue takes up this three-part emphasis on cases, concepts, and critiques.