Data Mining - Concepts and Techniques.

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Global energy consumption is projected to increase, even in the face of substantial declines in energy intensity, at least 2-fold by midcentury relative to the present because of population and economic growth. This demand could be met, in principle, from fossil energy resources, particularly coal. However, the cumulative nature of CO2 emissions in the atmosphere demands that holding atmospheric CO2 levels to even twice their preanthropogenic values by midcentury will require invention, development, and deployment of schemes for carbon-neutral energy production on a scale commensurate with, or larger than, the entire present-day energy supply from all sources combined. Among renewable energy resources, solar energy is by far the largest exploitable resource, providing more energy in 1 hour to the earth than all of the energy consumed by humans in an entire year. In view of the intermittency of insolation, if solar energy is to be a major primary energy source, it must be stored and dispatched on demand to the end user. An especially attractive approach is to store solar-converted energy in the form of chemical bonds, i.e., in a photosynthetic process at a year-round average efficiency significantly higher than current plants or algae, to reduce land-area requirements. Scientific challenges involved with this process include schemes to capture and convert solar energy and then store the energy in the form of chemical bonds, producing oxygen from water and a reduced fuel such as hydrogen, methane, methanol, or other hydrocarbon species.

/pdf/powering-the-planet-chemical-challenges-in-solar-energy-1kb0jbsg7k.pdf

Powering the planet: Chemical challenges in solar energy utilization

語用論(Pragmatics)を考える

The site-selective formation of carbon-carbon bonds through direct functionalizations of otherwise unreactive carbon-hydrogen bonds constitutes an economically attractive strategy for an overall streamlining of sustainable syntheses. In recent decades, intensive research efforts have led to the development of various reaction conditions for challenging C-H bond functionalizations, among which transition-metal-catalyzed transformations arguably constitute thus far the most valuable tool. For instance, the use of inter alia palladium, ruthenium, rhodium, copper, or iron complexes set the stage for chemo-, site-, diastereo-, and/or enantioselective C-H bond functionalizations. Key to success was generally a detailed mechanistic understanding of the elementary C-H bond metalation step, which depending on the nature of the metal fragment can proceed via several distinct reaction pathways. Traditionally, three different modes of action were primarily considered for CH bond metalations, namely, (i) oxidative addition with electronrich late transition metals, (ii) σ-bond metathesis with early transition metals, and (iii) electrophilic activation with electrondeficient late transition metals (Scheme 1). However, more recent mechanistic studies indicated the existence of a continuum of electrophilic, ambiphilic, and nucleophilic interactions. Within this continuum, detailed experimental and computational analysis provided strong evidence for novel C-H bond metalationmechanisms relying on the assistance of a bifunctional ligand bearing an additional Lewis-basic heteroatom, such as that found in (heteroatom-substituted) secondary phosphine oxides or most prominently carboxylates (Scheme 1, iv). This novel insight into the nature of stoichiometric metalations has served as stimulus for the development of novel transformations based on cocatalytic amounts of carboxylates, which significantly broadened the scope of C-H bond functionalizations in recent years, with most remarkable progress being made in palladiumor ruthenium-catalyzed direct arylations and direct alkylations. These carboxylate-assisted C-H bond transformations were mostly proposed to proceed via a mechanism in which metalation takes place via a concerted base-assisted deprotonation. To mechanistically differentiate these intramolecular metalations new acronyms have recently been introduced into the literature, such as CMD (concerted metalationdeprotonation), IES (internal electrophilic substitution), or AMLA (ambiphilic metal ligand activation), which describe related mechanisms and will be used below where appropriate. This review summarizes the development and scope of carboxylates as cocatalysts in transition-metal-catalyzed C-H functionalizations until autumn 2010. Moreover, experimental and computational studies on stoichiometric metalation reactions being of relevance to the mechanism of these catalytic processes are discussed as well. Mechanistically related C-H bond cleavage reactions with ruthenium or iridium complexes bearing monodentate ligands are, however, only covered with respect to their working mode, and transformations with stoichiometric amounts of simple acetate bases are solely included when their mechanism was suggested to proceed by acetate-assisted metalation.

Carboxylate-assisted transition-metal-catalyzed C-H bond functionalizations: mechanism and scope.

Arene-Bridged Diuranium Complexes: Inverted Sandwiches Supported by δ Backbonding

Cleavage of the Nitrous Oxide NN Bond by a Tris(amido)molybdenum(III) Complex

Accurate automatic optimization heuristics are necessary for dealing with thecomplexity and diversity of modern hardware and software. Machine learning is aproven technique for learning such heuristics, but its success is bound by thequality of the features used. These features must be hand crafted by developersthrough a combination of expert domain knowledge and trial and error. This makesthe quality of the final model directly dependent on the skill and availabletime of the system architect.Our work introduces a better way for building heuristics. We develop a deepneural network that learns heuristics over raw code, entirely without using codefeatures. The neural network simultaneously constructs appropriaterepresentations of the code and learns how best to optimize, removing the needfor manual feature creation. Further, we show that our neural nets can transferlearning from one optimization problem to another, improving the accuracy of newmodels, without the help of human experts.We compare the effectiveness of our automatically generated heuristics againstones with features hand-picked by experts. We examine two challenging tasks:predicting optimal mapping for heterogeneous parallelism and GPU threadcoarsening factors. In 89% of the cases, the quality of our fully automaticheuristics matches or surpasses that of state-of-the-art predictive models usinghand-crafted features, providing on average 14% and 12% more performance withno human effort expended on designing features.

/pdf/end-to-end-deep-learning-of-optimization-heuristics-2kyfxz87um.pdf

End-to-End Deep Learning of Optimization Heuristics

Tri-tert-butylsilyl)imido complexes of titanium: benzene carbon-hydrogen activation and structure of [(tert-Bu3SiNH)Ti]2(.mu.-NSi-tert-Bu3)2

We report a mild method for generating the diphosphorus molecule or its synthetic equivalent in homogeneous solution; the P 2 allotrope of the element phosphorus is normally obtained only under extreme conditions (for example, from P 4 at 1100 kelvin). Diphosphorus is extruded from a niobium complex designed for this purpose and can be trapped efficiently by two equivalents of an organic diene to produce an organodiphosphorus compound. Diphosphorus stabilized by coordination to tungsten pentacarbonyl can be generated similarly at 25°C, and in this stabilized form it still efficiently consumes two organic diene molecules for every diphosphorus unit.

https://science.sciencemag.org/content/sci/313/5791/1276.full.pdf

Christopher C. Cummins

Papers

Arene-Bridged Diuranium Complexes: Inverted Sandwiches Supported by δ Backbonding

Cleavage of the Nitrous Oxide NN Bond by a Tris(amido)molybdenum(III) Complex

End-to-End Deep Learning of Optimization Heuristics

Tri-tert-butylsilyl)imido complexes of titanium: benzene carbon-hydrogen activation and structure of [(tert-Bu3SiNH)Ti]2(.mu.-NSi-tert-Bu3)2

Triple-Bond Reactivity of Diphosphorus Molecules