Statistical modelling of organic thin film transistor behaviour
Organic Electronics, ISSN: 1566-1199, Vol: 92, Page: 105846
2021
- 2Citations
- 11Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Three analyses of the expressions describing the electrical characteristics of organic thin film transistors (OTFT's) are presented. The first is the field-independent approach to mobility originally used for inorganic semiconductor materials, often referred to as the Square Law (SQL). The second is appropriate for both the Multiple Trapping and Release (MTR) and the Variable Range Hopping (VRH) descriptions of mobility, where dependence on a transverse field is consistent with the Universal Mobility Law (UML). The third is appropriate for the Extended Gaussian Disorder (EGD) description where an exponential dependence of mobility on the transverse field occurs. In each case master equations have been derived, including Schottky contact effects, where the polarity of the voltage drop across the source and drain contacts is correctly taken into account for the first time. The effect of the bulk semiconductor material beyond the accumulation layer is also accounted for, and defines the sub-threshold performance in a low-voltage regime. A new statistical modelling procedure has been developed to extract the key parameters of these expressions simultaneously from experimental data. For the analysis of TRANSFER data, no more than five parameters are used in the SQL, UML and EGD treatments. All three models are considered so that the effect the choice of model has on the extracted parameters can be revealed; analysis of data from different metallophthalocyanines is used to illustrate the different effects. When the contact resistances correctly take into account possible Schottky-like behaviour, all three descriptions provide equally excellent fits to the data from TRANSFER experiments. In a following report, a family of copper phthalocyanine-related semiconductors will be examined in detail using these new analysis procedures to explore the effect of non-peripheral substituent bulk, and aza-nitrogen replacement by CH, on mobility.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S1566119920302329; http://dx.doi.org/10.1016/j.orgel.2020.105846; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85103079794&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S1566119920302329; https://api.elsevier.com/content/article/PII:S1566119920302329?httpAccept=text/xml; https://api.elsevier.com/content/article/PII:S1566119920302329?httpAccept=text/plain; https://dul.usage.elsevier.com/doi/; https://dx.doi.org/10.1016/j.orgel.2020.105846
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know