1. Ab initio studies of the optoelectronic structure of undoped and doped silicon nanocrystals and nanowires: the role of size, passivation, symmetry and phase
- Author
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Riccardo Rurali, Enric Canadell, Maurizia Palummo, Michele Amato, Stefano Ossicini, Ivan Marri, Università degli studi di Modena e Reggio Emilia, CINECA, European Commission, Institut du Développement et des Ressources en Informatique Scientifique (France), Agence Nationale de la Recherche (France), Istituto Nazionale di Fisica Nucleare, Ministerio de Economía, Industria y Competitividad (España), Ministerio de Ciencia, Innovación y Universidades (España), and Generalitat de Catalunya
- Subjects
Materials science ,Passivation ,Nanowire ,Ab initio ,doping ,02 engineering and technology ,010402 general chemistry ,01 natural sciences ,7. Clean energy ,Ab initio quantum chemistry methods ,Phase (matter) ,Thermoelectric effect ,Silicon nanocrystals, SIlicon nanowires, doping, symmetry ,Physical and Theoretical Chemistry ,symmetry ,Settore FIS/03 ,business.industry ,Doping ,021001 nanoscience & nanotechnology ,0104 chemical sciences ,3. Good health ,Nanocrystal ,Silicon nanocrystals ,SIlicon nanowires ,Optoelectronics ,0210 nano-technology ,business - Abstract
Silicon nanocrystals and nanowires have been extensively studied because of their novel properties and their applications in electronic, optoelectronic, photovoltaic, thermoelectric and biological devices. Here we discuss results from ab initio calculations for undoped and doped Si nanocrystals and nanowires, showing how theory can aid and improve comprehension of the structural, electronic and optical properties of these systems., S. O. acknowledges support/funding from University of Modena and Reggio Emilia under project “FAR2017INTERDISC”. S. O. and I. M. thank the Super-Computing Interuniversity Consortium CINECA for support and high-performance computing resources under the Italian Super-Computing Resource Allocation (ISCRA) initiative, PRACE for awarding us access to the resource MARCONI HPC cluster based in Italy at CINECA. I. M. acknowledges support/funding from European Union H2020-EINFRA-2015-1 and H2020-INFRAEDI-2018-1 programs under grant agreement No. 676598 and No. 824143, project MaX-MAterials at the eXascale. M. A. greatly acknowledges the Transnational Access Programme of the HPC-EUROPA3 (project HPC17PB9IZ). Some of the high-performance computing (HPC) resources for this project were granted by the Institut du development et des ressources en informatique scientifique (IDRIS) under the allocation A0040910089 via GENCI (Grand Equipment National de Calcul Intensif). This work was supported by the ANR HEXSIGE project (ANR-17-CE030-0014-01) of the French Agence Nationale de la Recherche. M. P. acknowledges INFN for financial support through the National project Nemesys. We also acknowledge financial support by the Ministerio de Economía, Industria y Competitividad (MINECO) and MICIU (Ministerio de Ciencia y Universidades) under Grants FEDER-MAT2017-90024-P, FIS2015-64886-C5-4-P and PGC2018-096955-B-C44-P, the Severo Ochoa Centres of Excellence Program under Grant SEV-2015-0496 and the Generalitat de Catalunya under Grant 2017 SGR 1506.
- Published
- 2020
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