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Organic field-effect transistors (OFETs) are of interest in unconventional form of electronics. However, high-performance OFETs are currently contact-limited, which represent a major challenge toward operation in the gigahertz regime. Here, we realize ultralow total contact resistance (Rc) down to 14.0 Ω ∙ cm in C10-DNTT OFETs by using transferred platinum (Pt) as contact. We observe evidence of Pt-catalyzed dehydrogenation of side alkyl chains which effectively reduces the metal-semiconductor van der Waals gap and promotes orbital hybridization. We report the ultrahigh performance OFETs, including hole mobility of 18 cm2 V−1 s−1, saturation current of 28.8 μA/μm, subthreshold swing of 60 mV/dec, and intrinsic cutoff frequency of 0.36 GHz. We further develop resist-free transfer and patterning strategies to fabricate large-area OFET arrays, showing 100% yield and excellent variability in the transistor metrics. As alkyl chains widely exist in conjugated molecules and polymers, our strategy can potentially enhance the performance of a broad range of organic optoelectronic devices.

SUMMARYIn this article we describe an approach for predicting average hourly concentrations of ambient PM 10 in Vancouver. We know our solution also applies to hourly ozone fields and believe it may be quite generally applicable. We use a hierarchical Bayesian approach. At the primary level we model the logarithmic field as a trend model plus Gaussian stochastic residual. That trend model depends on hourly meteorological predictors and is common to all sites. The stochastic component consists of a 24-hour vector response that we model as a multivariate AR(3) temporal process with common spatial parameters. Removing the trend and AR structure leaves 'whitened' time series of vector series. With this approach (as opposed to using 24 separate univariate time series models), there is little loss of spatial correlation in these residuals compared with that in just the detrended residuals (prior to removing the AR component). Moreover our multivariate approach enables predictions for any given hour to 'borrow strength' through its correlation with adjoining hours. On this basis we develop a spatial predictive distribution for these residuals at unmonitored sites. By transforming the predicted residuals back to the original data scales we can impute Vancouver's hourly PM 10 field.

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