Polymer, organic, and graphene based chemical sensors have shown excellent performance as chemical sensors. They can be chemically modified with receptor groups to provide additional sensitivity and selectivity. We propose and will demonstrate a three-synapse neuromorphic circuit for chemical sensing and olfactory pattern recognition. The circuit is implemented with 180 nm silicon technology and the sensing synapses can be incorporated in a back-end-of-the-line process on the silicon chip or be fabricated separately and electrically connected to the rest of the circuit. Our neuromorphic circuit is designed to be suited for analyzing mixtures of two analytes. We will present both simulation results and experimental data. The active sensing material for the sensing synapses can include conducting polymers such as PEDOT, monolayer graphene, reduced graphene oxide, copper phthalocyanine, as well as other materials.
Scaling down channel dimensions of organic and polymer semiconductor based thin-film transistors to submicron and nanoscale dimensions presents several challenges. Successful scaling will enable vastly improved device performance and hence the prospects are certainly very enticing. One of the biggest challenges is in making suitably good doped source and drain regions to facilitate relatively low-resistance contacts. A more thorough understanding of velocity saturation mechanisms and charge transport at high electric fields is also necessary. We describe charge transport in oxide and polymer TFTs with an emphasis on scaling. We show that for some TFTs, scaling of the channel width facilitates scaling down of channel length and a nanostripe or nanogroove array channel geometry has advantages. Finally, we describe hybrid TFTs – with multiple materials that are better suited to scaling down. The future prospects of scaled down TFTs are discussed.
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