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