journal article·2018

Efficient, non-stochastic, Monte-Carlo-like-accurate method for the calculation of the temperature-dependent mobility in nanocrystal films

Francisco M. Gómez-Campos, Salvador Rodríguez-Bolívar, Erik S. Skibinsky-Gitlin, Marco Califano

Nanoscale· Volume 10· Issue 20
Publisher page

Abstract

We present a new non-stochastic framework for the calculation of the temperature dependence of the mobility in nanocrystal films, that enables speed-ups of several orders of magnitude compared to conventional Monte Carlo approaches, while maintaining a similar accuracy. Our model identifies a new contribution to the reduction of the mobility with increasing temperature in these systems (conventionally attributed to interactions with phonons), that alone is sufficient to explain the observed experimental trend up to room temperature. Comparison of our results with the theoretical predictions of the hopping model and the observed temperature dependence of recent field-effect mobility measurements in nanocrystal films, provides the means to discriminate between band-like and hopping transport and a definitive answer to whether the former has been achieved in quantum dot films.
Source: openalex_inverted_index · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Quantum Dots Synthesis And Properties · Theoretical and Computational Physics · Advanced Thermoelectric Materials and Devices

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Departamento de Electrónica y Tecnología de Computadores

Facultad de Ciencias

Universidad de Granada

18071 Granada

Spain

Pollard Institute

School of Electronic and Electrical Engineering

University of Leeds

Leeds LS2 9JT

UK

Funding

University of Leeds · Ministerio de Economía, Industria y Competitividad, Gobierno de España

References (24)

Show source-provided references
1. Weidman · ACS Nano · 2014 · 8 · 636310.1021/nn5018654 ↗
2. Maulu · RSC Adv. · 2016 · 6 · 8020110.1039/C6RA14782H ↗
3. Baumgardner · Nano Lett. · 2013 · 13 · 322510.1021/nl401298s ↗
4. Choi · Nano Lett. · 2012 · 12 · 263110.1021/nl301104z ↗
5. Lee · Nat. Nanotechnol. · 2011 · t6 · 34810.1038/nnano.2011.46 ↗
6. Guyot-Sionnest · J. Phys. Chem. Lett. · 2012 · 3 · 116910.1021/jz300048y ↗
7. Chu · J. Phys. Chem. C · 2011 · 115 · 2140910.1021/jp206526s ↗
8. Shabaev · Nano Lett. · 2013 · 13 · 545410.1021/nl403033f ↗
9. Wang · Phys. Rev. B: Condens. Matter Mater. Phys. · 1996 · 53 · 957910.1103/PhysRevB.53.9579 ↗
10. Gómez-Campos · ACS Photonics · 2016 · 3 · 205910.1021/acsphotonics.6b00377 ↗
11. Yang · Appl. Phys. Lett. · 2016 · 109 · 24210310.1063/1.4971985 ↗
12. Salvador · J. Chem. Phys. · 2006 · 125 · 18470910.1063/1.2363190 ↗
13. Nomura · Phys. Rev. B: Condens. Matter Mater. Phys. · 1992 · 45 · 130510.1103/PhysRevB.45.1305 ↗
14. Rodriguez-Suarez · Phys. Rev. B: Condens. Matter Mater. Phys. · 2000 · 62 · 1100610.1103/PhysRevB.62.11006 ↗
15. Chandler · Phys. Rev. B: Condens. Matter Mater. Phys. · 2007 · 75 · 08532510.1103/PhysRevB.75.085325 ↗
16. Gagorik · J. Phys. Chem. Lett. · 2013 · 4 · 3610.1021/jz3016292 ↗
17. Ando · J. Appl. Phys. · 1993 · 74 · 398310.1063/1.354441 ↗
18. Basharin · Linear Algebra Appli. · 2004 · 386 · 310.1016/j.laa.2003.12.041 ↗
19. Jacoboni · Rev. Mod. Phys. · 1983 · 55 · 64510.1103/RevModPhys.55.645 ↗
20. Yang · J. Phys. Chem. C · 2015 · 119 · 333810.1021/jp5098469 ↗
21. Liu · Nano Lett. · 2010 · 10 · 196010.1021/nl101284k ↗
22. Gao · ACS Nano · 2012 · 6 · 960610.1021/nn3029716 ↗
23. Rodríguez-Bolívar · J. Appl. Phys. · 2011 · 109 · 07430310.1063/1.3562160 ↗
24. García · J. Appl. Phys. · 2013 · 114 · 06431110.1063/1.4817893 ↗