Publication

Fabrication of single crystal CuGaS2 nanorods by X-ray irradiation

Giorgio Margaritondo
2011
Journal Articles

Abstract

CuGaS2 nanorods were synthesized by irradiating the precursor solution with intense X-rays. The products are single crystal nanorods with preferential [220] growth and a uniform size distribution. We also report on the photoresponse of drop-cast films of these nanorods.

Official source

https://infoscience.epfl.ch/entities/publication/d31e598c-d1dc-43e9-adb6-d16a313c447d

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Giorgio Margaritondo
2011
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/d31e598c-d1dc-43e9-adb6-d16a313c447d

About this result

Related concepts (13)

Continuous uniform distribution

In probability theory and statistics, the continuous uniform distributions or rectangular distributions are a family of symmetric probability distributions. Such a distribution describes an experiment where there is an arbitrary outcome that lies between certain bounds. The bounds are defined by the parameters, and which are the minimum and maximum values. The interval can either be closed (i.e. ) or open (i.e. ). Therefore, the distribution is often abbreviated where stands for uniform distribution.

Discrete uniform distribution

In probability theory and statistics, the discrete uniform distribution is a symmetric probability distribution wherein a finite number of values are equally likely to be observed; every one of n values has equal probability 1/n. Another way of saying "discrete uniform distribution" would be "a known, finite number of outcomes equally likely to happen". A simple example of the discrete uniform distribution is throwing a fair die. The possible values are 1, 2, 3, 4, 5, 6, and each time the die is thrown the probability of a given score is 1/6.

Beta distribution

In probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval [0, 1] or (0, 1) in terms of two positive parameters, denoted by alpha (α) and beta (β), that appear as exponents of the variable and its complement to 1, respectively, and control the shape of the distribution. The beta distribution has been applied to model the behavior of random variables limited to intervals of finite length in a wide variety of disciplines.

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