Electron transport through Al-ZnO-Al: an {\it ab initio} calculation

The electron transport properties of ZnO nano-wires coupled by two aluminium electrodes were studied by {\it ab initio} method based on non-equilibrium Green's function approach and density functional theory. A clearly rectifying current-voltage characteristics was observed. It was found that the contact interfaces between Al-O and Al-Zn play important roles in the charge transport at low bias voltage and give very asymmetric I-V characteristics. When the bias voltage increases, the negative differential resistance occurs at negative bias voltage. The charge accumulation was calculated and its behavior was found to be well correlated with the I-V characteristics. We have also calculated the electrochemical capacitance which exhibits three plateaus at different bias voltages which may have potential device application.Comment: 10 pages, 6 figure

Quantum information processing architecture with endohedral fullerenes in a carbon nanotube

A potential quantum information processor is proposed using a fullerene peapod, i.e., an array of the endohedral fullerenes 15N@C60 or 31P@C60 contained in a single walled carbon nanotube (SWCNT). The qubits are encoded in the nuclear spins of the doped atoms, while the electronic spins are used for initialization and readout, as well as for two-qubit operations.Comment: 8 pages, 8 figure

Statistical calibration and exact one-sided simultaneous tolerance intervals for polynomial regression

Statistical calibration using linear regression is a useful statistical tool having many applications. Calibration for infinitely many future y-values requires the construction of simultaneous tolerance intervals (STI’s). As calibration often involves only two variables x and y and polynomial regression is probably the most frequently used model for relating y with x, construction of STI’s for polynomial regression plays a key role in statistical calibration for infinitely many future y-values. The only exact STI’s published in the statistical literature are provided by Mee et al. (1991) and Odeh and Mee (1990). But they are for a multiple linear regression model, in which the covariates are assumed to have no functional relationships. When applied to polynomial regression, the resultant STI’s are conservative. In this paper, one-sided exact STI’s have been constructed for a polynomial regression model over any given interval. The available computer program allows the exact methods developed in this paper to be implemented easily. Real examples are given for illustration

Counting by weighing:know your numbers with confidence

Counting by weighing is often more efficient than counting manually, which is time consuming and prone to human errors, especially when the number of items (e.g. plant seeds, printed labels or coins) is large. Papers in the statistical literature have focused on how to count, by weighing, a random number of items that is close to a prespecified number in some sense. The paper considers the new problem, arising from a consultation with a company, of making inference about the number of 1p coins in a bag with known weight for infinitely many bags, by using the estimated distribution of coin weight from one calibration data set only. Specifically, a lower confidence bound has been constructed on the number of 1p coins for each of infinitely many future bags of 1p coins, as required by the company. As the same calibration data set is used repeatedly in the construction of all these lower confidence bounds, the interpretation of coverage frequency of the lower confidence bounds that is proposed is different from that of a usual confidence set

Confidence sets for optimal factor levels of a response surface

Construction of confidence sets for the optimal factor levels is an important topic in response surfaces methodology. In Wan et al. (2015), an exact inline image confidence set has been provided for a maximum or minimum point (i.e., an optimal factor level) of a univariate polynomial function in a given interval. In this article, the method has been extended to construct an exact inline image confidence set for the optimal factor levels of response surfaces. The construction method is readily applied to many parametric and semiparametric regression models involving a quadratic function. A conservative confidence set has been provided as an intermediate step in the construction of the exact confidence set. Two examples are given to illustrate the application of the confidence sets. The comparison between confidence sets indicates that our exact confidence set is better than the only other confidence set available in the statistical literature that guarantees the inline image confidence level