Gómez-Campos, FM, Rodríguez-Bolivar, S and Califano, M orcid.org/0000-0003-3199-3896 (2019) Effective Approach for an Order-of-Magnitude-Accurate Evaluation of the Electron Mobility in Colloidal Quantum Dot Films. Journal of Nanomaterials, 2019. 5106909. ISSN 1687-4110
Abstract
Being able to estimate the electron mobility of colloidal quantum dot films is of great importance for determining their suitability to specific applications and would lead to huge savings in terms of time and resources that may otherwise be wasted trying to build and optimize a device whose transport characteristics can be predicted to be poor from the outset. This task is however complicated by the complexity of the system and the large number of parameters that can potentially affect the final result. Here, we derive a simple, fitting-parameter-free, order-of-magnitude-accurate expression to estimate the dark mobility of such 2D structures and validate it by applying it to real systems and comparing its predictions with those of other recently proposed approaches and with available experimental data. The results quantify the superiority of our expression to estimate mobilities in colloidal quantum dot films.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Francisco M. Gómez-Campos et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Pollard Institute (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Jan 2019 13:31 |
Last Modified: | 27 Mar 2019 15:47 |
Status: | Published |
Publisher: | Hindawi Publishing Corporation |
Identification Number: | 10.1155/2019/5106909 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:140929 |