Producing carbon nanotubes from thermochemical conversion of waste plastics using Ni/ceramic based catalyst

As the amount of waste plastic increases, thermo-chemical conversion of plastics provides an economic flexible and environmental friendly method to manage recycled plastics, and generate valuable materials, such as carbon nanotubes (CNTs). The choice of catalysts and reaction parameters are critical to improving the quantity and quality of CNTs production. In this study, a ceramic membrane catalyst (Ni/Al2O3) was studied to control the CNTs growth, with reaction parameters, including catalytic temperature and Ni content investigated. A fixed two-stage reactor was used for thermal pyrolysis of plastic waste, with the resulting CNTs characterized by various techniques including scanning electronic microscopy (SEM), transmitted electronic microscopy (TEM), temperature programmed oxidation (TPO), and X-ray diffraction (XRD). It is observed that different loadings of Ni resulted in the formation of metal particles with various sizes, which in turn governs CNTs production with varying degrees of quantity and quality, with an optimal catalytic temperature at 700 °C

Ultra-high mobility transparent organic thin film transistors grown by an off-centre spin-coating method

Organic semiconductors with higher carrier mobility and better transparency have been actively pursued for numerous applications, such as flat-panel display backplane and sensor arrays. The carrier mobility is an important figure of merit and is sensitively influenced by the crystallinity and the molecular arrangement in a crystal lattice. Here we describe the growth of a highly aligned meta-stable structure of 2,7-dioctyl[1]benzothieno[3,2-b][1]benzothiophene (C8-BTBT) from a blended solution of C8-BTBT and polystyrene by using a novel offcentre spin-coating method. Combined with a vertical phase separation of the blend, the highly aligned, meta-stable C8-BTBT films provide a significantly increased thin film transistor hole mobility up to 43 cm2 Vs�1 (25 cm2 Vs�1 on average), which is the highest value reported to date for all organic molecules. The resulting transistors show high transparency of 490% over the visible spectrum, indicating their potential for transparent, high-performance organic electronics

Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV

Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated $\mathrm{t}\overline{\mathrm{t}}$ events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The heavy-flavour jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV)

Evidence for the Higgs boson decay to a bottom quark–antiquark pair

info:eu-repo/semantics/publishe

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

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

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe

Measurement of prompt open-charm production cross sections in proton-proton collisions at root s=13 TeV

The production cross sections for prompt open-charm mesons in proton-proton collisions at a center-of-mass energy of 13TeV are reported. The measurement is performed using a data sample collected by the CMS experiment corresponding to an integrated luminosity of 29 nb(-1). The differential production cross sections of the D*(+/-), D-+/-, and D-0 ((D) over bar (0)) mesons are presented in ranges of transverse momentum and pseudorapidity 4 < p(T) < 100 GeV and vertical bar eta vertical bar < 2.1, respectively. The results are compared to several theoretical calculations and to previous measurements.Peer reviewe