400 research outputs found

    Incorporation of atomic Fe-oxide triggers a quantum leap in the CO2 methanation performance of Ni-hydroxide

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    The heterogeneous catalytic conversion of carbon dioxide (CO2) to methane (CH4) via CO2 methanation offers a promising avenue for establishing the closed carbon loop. Nevertheless, the lack of effective catalysts limits its industrial applications. Considering this, we developed a novel heterogeneous catalyst comprising oxygen vacancies enriched atomic Fe-oxide clusters confined in the TiO2-supported Ni-hydroxide (denoted as NiFe-TiO2) via wet chemical reduction method. This material delivers an unprecedently high CH4 productivity of ∼24,358 mmol g-1h−1 in CO2 methanation at 300 °C, surpassing the Ni-TiO2 (12,481 mmol g-1h−1) by ∼ 95 %. On top of that, the high structural reliability of the Fe-oxide atomic clusters endows the NiFe-TiO2 catalyst with outstanding durability, where it achieves an optimum CH4 productivity of ∼ 36,399 mmol g-1h−1 after 116 cycles (155 h) with CH4 selectivity of 90.5 % and retains the pristine performance up to 220 cycles (330 h) in the stability test. With evidence from in-situ X-ray absorption and ambient pressure X-ray photoelectron spectroscopy studies, the performance descriptors and reaction pathways were unveiled, where the oxygen vacancies in the atomic Fe-oxide clusters and the adjacent Ni-hydroxide domains synergistically boost the CO2 activation and the H2 dissociation, respectively. Such a potential synergy enables the simultaneous operation of all intermediate steps for enhanced CO2 methanation kinetics on the NiFe-TiO2 surface. Most importantly, these findings not only unravel the merits of oxygen vacancies in transition metals for CO2 methanation but mark a step ahead for the rational design of heterogeneous catalysts in various catalytic applications

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

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    A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

    Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

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    Measurement of the top quark mass using charged particles in pp collisions at root s=8 TeV

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    Peer reviewe

    Search for anomalous couplings in boosted WW/WZ -> l nu q(q)over-bar production in proton-proton collisions at root s=8TeV

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    Hierarchical deployment of factors regulating temporal fate in a diverse neuronal lineage of the Drosophila central brain

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    The anterodorsal projection neuron lineage of Drosophila melanogaster produces 40 neuronal types in a stereotypic order. Here we take advantage of this complete lineage sequence to examine the role of known temporal fating factors, including Chinmo and the Hb/Kr/Pdm/Cas transcriptional cascade, within this diverse central brain lineage. Kr mutation affects the temporal fate of the neuroblast (NB) itself, causing a single fate to be skipped, whereas Chinmo null only elicits fate transformation of NB progeny without altering cell counts. Notably, Chinmo operates in two separate windows to prevent fate transformation (into the subsequent Chinmo-indenpendent fate) within each window. By contrast, Hb/Pdm/Cas play no detectable role, indicating that Kr either acts outside of the cascade identified in the ventral nerve cord or that redundancy exists at the level of fating factors. Therefore, hierarchical fating mechanisms operate within the lineage to generate neuronal diversity in an unprecedented fashion
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