Abstract
The past few decades have seen an uptick in the scope and range of device applications of organic semiconductors, such as organic field-effect transistors, organic photovoltaics and light-emitting diodes. Several researchers have studied electrical transport in these materials and proposed physical models to describe charge transport with different material parameters, with most disordered semiconductors exhibiting hopping transport. However, there exists a lack of a consensus among the different models to describe hopping transport accurately and uniformly. In this work, we first evaluate the efficacy of using a purely data-driven approach, i.e., symbolic regression, in unravelling the relationship between the measured field-effect mobility and the controllable inputs of temperature and gate voltage. While the regressor is able to capture the scaled mobility well with mean absolute error (MAE) ~ O(10–2), better than the traditionally used hopping transport model, it is unable to derive physically interpretable input–output relationships. We then examine a physics-inspired renormalization approach to describe the scaled mobility with respect to a scale-invariant reference temperature. We observe that the renormalization approach offers more generality and interpretability with a MAE of the ~ O(10–1), still better than the traditionally used hopping model, but less accurate as compared to the symbolic regression approach. Our work shows that physics-based approaches are powerful compared to purely data-driven modelling, providing an intuitive understanding of data with extrapolative ability.
Highlights
The past few decades have seen an uptick in the scope and range of device applications of organic semiconductors, such as organic field-effect transistors, organic photovoltaics and light-emitting diodes
We investigate the efficacy of a powerful mathematical approach, namely symbolic regression (SR), in recapturing underlying physics after fitting transport data of three different organic field-effect transistors (OFETs) based on organic molecules of p-type pentacene, and n-type buckminsterfullerene (C60) as well as conjugated polymer poly(3-hexylthiophene-2,5-diyl) (P3HT)
We demonstrate that this approach is powerful as it helps to differentiate between processing conditions for the same molecules by comparing the extent of activation energy that is accessed over the range of the applied gate voltages
Summary
The past few decades have seen an uptick in the scope and range of device applications of organic semiconductors, such as organic field-effect transistors, organic photovoltaics and light-emitting diodes. The resulting equation fits the entire dataset at once instead of providing a solution that is repeatable curve-by-curve by varying the value of the second variable/parameter (gate voltage in this case) To overcome this missing physical insight, we compare this with a renormalization approach to describe the transport by defining dimensionless quantities from the temperature dependent mobility data. Derivation of dimensionless quantities captures both the effects of temperature as well as gate voltage embedded in a single parameter, rather than in multiple parameters as seen in the existing m odels[18], and provides us with a one-shot approach in describing and characterising hopping transport in organic semiconductors We demonstrate that this approach is powerful as it helps to differentiate between processing conditions for the same molecules by comparing the extent of activation energy that is accessed over the range of the applied gate voltages.
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