Spectroscopic properties and thermal stability of Er3+-doped tungsten-tellurite glass for waveguide amplifier application

Tungsten-tellurite glass with molar composition of 60TeO(2)-30WO(3)-10Na(2)O has been investigated for developing planar broadband waveguide amplifier application. Spectroscopic properties and thermal stability of Er3+-doped tungsten-tellurite glass have been discussed. The results show that the introduction Of WO3 increases significantly the glass transition temperature and the maximum phonon energy. Er3+-doped tungsten-tellurite glass exhibits high glass transition temperature (377 degrees C), large emission cross-section (0.91 x 10(-20) cm(2)) at 1532 nm and broad full width at half maximum (FWHM), which make it preferable for broadband Er3+-doped waveguide amplifier application. (c) 2005 Elsevier B.V. All rights reserved.

Sorting nanoparticles by centrifugal fields in clean media

The on-demand availability of nanomaterials with selected size and well-defined chemical/physical properties is of fundamental importance for their widespread application. We report two clean, rapid, and non-destructive approaches for nanoparticle (NP) size selection in centrifugal fields. The first exploits rate zonal separation in a high viscosity gradient. The second exploits selective sedimentation of NPs with different sizes. These methods are here applied to metallic nanoparticles (MNPs) with different compositions and surface chemistry, dispersed either in water or organic solvents. The approach is general and can also be exploited for the separation of NPs of any material. We selectively sort both Au and AgNPs with sizes in the 10-30 nm range, achieving chemical-free MNPs with low polydispersivity. We do not use solutes, thus avoiding contamination, and only require low centrifugal fields, easily achievable in benchtop systems. © 2013 American Chemical Society.

First principles interatomic potential for tungsten based on Gaussian process regression

An accurate description of atomic interactions, such as that provided by first principles quantum mechanics, is fundamental to realistic prediction of the properties that govern plasticity, fracture or crack propagation in metals. However, the computational complexity associated with modern schemes explicitly based on quantum mechanics limits their applications to systems of a few hundreds of atoms at most. This thesis investigates the application of the Gaussian Approximation Potential (GAP) scheme to atomistic modelling of tungsten - a bcc transition metal which exhibits a brittle-to-ductile transition and whose plasticity behaviour is controlled by the properties of $\frac{1}{2} \langle 111 \rangle$ screw dislocations. We apply Gaussian process regression to interpolate the quantum-mechanical (QM) potential energy surface from a set of points in atomic configuration space. Our training data is based on QM information that is computed directly using density functional theory (DFT). To perform the fitting, we represent atomic environments using a set of rotationally, permutationally and reflection invariant parameters which act as the independent variables in our equations of non-parametric, non-linear regression. We develop a protocol for generating GAP models capable of describing lattice defects in metals by building a series of interatomic potentials for tungsten. We then demonstrate that a GAP potential based on a Smooth Overlap of Atomic Positions (SOAP) covariance function provides a description of the $\frac{1}{2} \langle 111 \rangle$ screw dislocation that is in agreement with the DFT model. We use this potential to simulate the mobility of $\frac{1}{2} \langle 111 \rangle$ screw dislocations by computing the Peierls barrier and model dislocation-vacancy interactions to QM accuracy in a system containing more than 100,000 atoms.

Accuracy and transferability of GAP models for tungsten

We introduce interatomic potentials for tungsten in the bcc crystal phase and its defects within the Gaussian Approximation Potential (GAP) framework, fitted to a database of first principles density functional theory (DFT) calculations. We investigate the performance of a sequence of models based on databases of increasing coverage in configuration space and showcase our strategy of choosing representative small unit cells to train models that predict properties only observable using thousands of atoms. The most comprehensive model is then used to calculate properties of the screw dislocation, including its structure, the Peierls barrier and the energetics of the vacancy-dislocation interaction. All software and raw data are available at www.libatoms.org.