7,877 research outputs found
Data mining and accelerated electronic structure theory as a tool in the search for new functional materials
Data mining is a recognized predictive tool in a variety of areas ranging
from bioinformatics and drug design to crystal structure prediction. In the
present study, an electronic structure implementation has been combined with
structural data from the Inorganic Crystal Structure Database to generate
results for highly accelerated electronic structure calculations of about
22,000 inorganic compounds. It is shown how data mining algorithms employed on
the database can identify new functional materials with desired materials
properties, resulting in a prediction of 136 novel materials with potential for
use as detector materials for ionizing radiation. The methodology behind the
automatized ab-initio approach is presented, results are tabulated and a
version of the complete database is made available at the internet web site
http://gurka.fysik.uu.se/ESP/ (Ref.1).Comment: Project homepage: http://gurka.fysik.uu.se/ESP
Analytic continuation by averaging Pad\'e approximants
The ill-posed analytic continuation problem for Green's functions and
self-energies is investigated by revisiting the Pad\'{e} approximants
technique. We propose to remedy the well-known problems of the Pad\'{e}
approximants by performing an average of several continuations, obtained by
varying the number of fitted input points and Pad\'{e} coefficients
independently. The suggested approach is then applied to several test cases,
including Sm and Pr atomic self-energies, the Green's functions of the Hubbard
model for a Bethe lattice and of the Haldane model for a nano-ribbon, as well
as two special test functions. The sensitivity to numerical noise and the
dependence on the precision of the numerical libraries are analysed in detail.
The present approach is compared to a number of other techniques, i.e. the
non-negative least-square method, the non-negative Tikhonov method and the
maximum entropy method, and is shown to perform well for the chosen test cases.
This conclusion holds even when the noise on the input data is increased to
reach values typical for quantum Monte Carlo simulations. The ability of the
algorithm to resolve fine structures is finally illustrated for two relevant
test functions.Comment: 10 figure
Simulation of hydrogenated graphene Field-Effect Transistors through a multiscale approach
In this work, we present a performance analysis of Field Effect Transistors
based on recently fabricated 100% hydrogenated graphene (the so-called
graphane) and theoretically predicted semi-hydrogenated graphene (i.e.
graphone). The approach is based on accurate calculations of the energy bands
by means of GW approximation, subsequently fitted with a three-nearest neighbor
(3NN) sp3 tight-binding Hamiltonian, and finally used to compute ballistic
transport in transistors based on functionalized graphene. Due to the large
energy gap, the proposed devices have many of the advantages provided by
one-dimensional graphene nanoribbon FETs, such as large Ion and Ion/Ioff
ratios, reduced band-to-band tunneling, without the corresponding disadvantages
in terms of prohibitive lithography and patterning requirements for circuit
integration
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