Accurate and reproducible mobility estimation enables high-throughput analysis of organic field-effect transistors

The charge carrier mobility is one of the most important properties of organic semiconductors. It determines the speed of operation of the device and can be measured by using OFET configuration. Common approaches to estimating the mobility can yield biased estimates and are based on subjective decisions about OFET transfer characteristic curves. These approaches typically estimate the slopes of the curves for a group of OFETs using a fixed range selected by the researcher and then average the slope estimates. We developed a new approach to slope estimation that uses nonlinear regression so that the researcher does not have to choose a range for slope estimation. Simulations were conducted to compare the proposed approach to three alternatives. In the first set of simulations, the goal was to estimate the mean slope of a group. In the second set, the goal was to detect a difference in mean slope between two groups. We show that our new approach is superior to the alternatives. It produces more accurate mean slope estimates and in difference detection has a well-calibrated false positive rate and good statistical power.We created a Shiny application named OFETAnalysisApp that implements the proposed approach. It is located at https://ofetanalysisapp.shinyapps.io/OFETAnalysisApp. We present a case study in which the app is used to find the optimal temperature to heat the OFET substrate to when depositing a layer of tetratetracontane (TTC). The case study shows that OFETAnalysisApp greatly reduces the amount of work that needs to be done by the researcher when analyzing OFET data. The app produces visualizations of the data, fits models, and computes estimates that would otherwise require a substantial amount of manual effort. Furthermore, an analysis carried out with OFETAnalysisApp is more reproducible as the results file that can be downloaded from it shows the choices the researcher made during the analysis.