Band gap opening and engineering is one of the high priority goals in the development of graphene electronics. Here, we report on the opening and scaling of band gap in BN doped graphene (BNG) films grown by low-pressure chemical vapor deposition method. High resolution transmission electron microscopy is employed to resolve the graphene and h-BN domain formation in great detail. X-ray photoelectron, micro-Raman, and UV-vis spectroscopy studies revealed a distinct structural and phase evolution in BNG films at low BN concentration. Synchrotron radiation based XAS-XES measurements concluded a gap opening in BNG films, which is also confirmed by field effect transistor measurements. For the first time, a significant band gap as high as 600 meV is observed for low BN concentrations and is attributed to the opening of the π-π* band gap of graphene due to isoelectronic BN doping. As-grown films exhibit structural evolution from homogeneously dispersed small BN clusters to large sized BN domains with embedded diminutive graphene domains. The evolution is described in terms of competitive growth among h-BN and graphene domains with increasing BN concentration. The present results pave way for the development of band gap engineered BN doped graphene-based devices.

We propose a new method of testing stochastic dominance that improves on existing tests based on the standard bootstrap or subsampling. The method admits prospects involving in…nite as well as …nite dimensional unknown parameters, so that the variables are allowed to be residuals from nonparametric and semiparametric models. The proposed bootstrap tests have asymptotic sizes that are less than or equal to the nominal level uniformly over probabilities in the null hypothesis under regularity conditions. This paper also characterizes the set of probabilities that the asymptotic size is exactly equal to the nominal level uniformly. As our simulation results show, these characteristics of our tests lead to an improved power property in general. The improvement stems from the design of the bootstrap test whose limiting behavior mimics the discontinuity of the original test's limiting distribution.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract. This paper develops tests for inequality constraints of nonparametric regression functions. The test statistics involve a one-sided version of L p -type functionals of kernel estimators. Drawing on the approach of Poissonization, this paper establishes that the tests are asymptotically distribution free, admitting asymptotic normal approximation. Furthermore, the tests have nontrivial local power against a certain class of local alternatives converging to the null at the rate of n −1/2 . Some results from Monte Carlo simulations are presented. Terms of use: Documents in EconStor may

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This paper proposes new tests of conditional independence of two random variables given a single-index involving an unknown finite-dimensional parameter. The tests employ Rosenblatt transforms and are shown to be distribution-free while retaining computational convenience. Some results from Monte Carlo simulations are presented and discussed.Comment: Published in at http://dx.doi.org/10.1214/09-AOS704 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org