Organic photodiodes (OPDs) have in recent years reached a level of performance
comparable to their inorganic counterparts. Using additives like PMMA, we were able
to tune the transparency and viscosity of a P3HT:PCBM photoactive blend while at
the same time achieving a two-fold enhancement of the detection speed.
Furthermore, we have developed approaches towards the digital realization of image sensors using aerosol jet printing and a direct-printed patterning technique utilizing the self organization of functional inks. These techniques allow for a reproducible deposition of multilayer devices with high registration
accuracies and feature sizes down to a few microns. We present a comprehensive electrical
and optical characterization of these printed image sensors. The devices exhibit specific detectivities of
>1E12 Jones over a broad wavelength range (400-750 nm) and maximum responsivities of 0.25
A/W. An entirely printed matrix image sensor composing of 256 individual pixels with
an individual active area of ≈250 μm × 300 μm was fabricated.
In transformation optics, coordinate transformations are usually mapped onto equivalent (meta-)material parameter distributions. In 2015, we introduced an approach mapping coordinate transformations onto dielectric free-form surfaces. We presented model experiments on cloaking of reflective contact fingers on solar cells. We now report on the fabrication of masters by 3D laser lithography used for soft imprinting. For prototype silicon heterojunction solar cells investigated under 1-sun illumination, we demonstrate the predicted 9% relative efficiency increase. We additionally show that our approach is adaptable to Lambertian sources, thereby cloaking light-emitting diode contacts to achieve spatially homogeneous emission.
We report on a fluorescent optoelectronic nose for the trace detection of nitroaromatic explosive vapors. The sensor arrays, fabricated by aerosol-jet printing, consist of six different polymers as transducers. We demonstrate the nose’s ability to discriminate between several nitroaromatics including nitrobenzene, 1,3-dinitrobenzene and 2,4-dinitrotoluene at three different concentrations using linear discriminant analysis (LDA). We assess the within-batch reproducibility of the printing process and we report that the sensor polymers show efficient fluorescence quenching capabilities with detection limits of a few parts-per-billion in air.
Our approach enables the realization of highly integrated optical sensor arrays in optoelectronic noses for the sensitive and selective detection of nitroaromatic explosive trace vapors using a potentially low-cost digital printing technique suitable for high-volume fabrication. An important challenge is temperature-dependence which is often neglected even though organic emitters are strongly affected by temperature. For some materials, even small changes of a few Kelvin can lead to large changes in the emission intensity making a temperature-control for sensing applications inevitable. Therefore, the temperature-dependence of these sensors is investigated via a heated transparent thin film on the back of such sensors allowing the active layer to be temperature controlled. All of these led to the development of a portable system.
KEYWORDS: Sensors, Explosives detection, Chemical analysis, Luminescence, Biological and chemical sensing, Printing, Polymers, Explosives, Data modeling, Cameras, Visualization
In this work, we report on fluorescent sensor arrays fabricated by aerosol jet printing on glass substrates to detect explosives-related nitroaromatic species. The printed sensor arrays consist of six different fluorescent polymers responding to nitroaromatic vapors through a photo-induced electron transfer. This results in a quenched fluorescence proportional to the vapor concentration. Distinct fluorescence quenching patterns are detected for nitroaromatic species including nitrobenzene, 1,3-dinitrobenzene and 2,4-dinitrotoluene. The detected fingerprints are evaluated at low concentrations of only 1, 3 and 10 parts-per-billion in air. Linear discriminant analysis is used to train each sensor array enabling the discrimination of the target analyte vapors. To investigate the reproducibility of multiple sensor arrays on a single substrate, the measured fluorescence quenching patterns are used to benchmark the linear discriminant models. For this purpose, the target analytes and vapor concentrations are predicted for each sensor array. On average, we report low and reproducible misclassification rates of about 4 % indicating excellent discriminatory abilities at low concentrations close to the detection limits. We conclude that digital printing of fluorescent polymers offers the potential to realize low-cost sensor arrays for a reliable detection of trace explosives.
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