Nonvolatile redox transistors (NVRTs) based upon Li-ion battery materials are demonstrated as memory elements for neuromorphic computer architectures with multi-level analog states, "write" linearity, low-voltage switching, and low power dissipation. Simulations of backpropagation using the device properties reach ideal classification accuracy. Physics-based simulations predict energy costs per "write" operation of <10 aJ when scaled to 200 nm × 200 nm.

Neuromorphic computers could overcome efficiency bottlenecks inherent to conventional computing through parallel programming and readout of artificial neural network weights in a crossbar memory array. However, selective and linear weight updates and <10-nanoampere read currents are required for learning that surpasses conventional computing efficiency. We introduce an ionic floating-gate memory array based on a polymer redox transistor connected to a conductive-bridge memory (CBM). Selective and linear programming of a redox transistor array is executed in parallel by overcoming the bridging threshold voltage of the CBMs. Synaptic weight readout with currents <10 nanoamperes is achieved by diluting the conductive polymer with an insulator to decrease the conductance. The redox transistors endure >1 billion write-read operations and support >1-megahertz write-read frequencies.

Microcontact printing (µCP) is a new method of molecularly patterning surfaces on a micrometer scale. In this paper, we present the extension of microcontact printing to producing patterned layers of proteins on solid substrates. µCP avoids the use of strong acids and bases necessary in photolithographic patterning, allowing its use for patterning of proteins and other biological layers. We also describe the methods of thin stamp microcontact printing that allow printing of isolated features previously unattainable by microcontact printing. A solution of polylysine in borate-buffered saline was printed onto a glass coverslip, yielding micrometer scale features over an area of 4 cm 2 .

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We describe a method for producing high-resolution chemical patterns on surfaces to control the attachment and growth of cultured neurons. Microcontact printing has been extended to allow the printing of micron-scale protein lines aligned to an underlying pattern of planar microelectrodes. Poly-L-lysine (PL) lines have been printed on the electrode array for electrical studies on cultured neural networks. Rat hippocampal neurons showed a high degree of attachment selectivity to the PL and produced neurites that faithfully grew onto the electrode recording sites.

Neuronal cell networks have been reconstructed on planar microelectrode arrays (MEAs) from dissociated hippocampal pyramidal neurons. Microcontact printing (microCP) and a photoresist-liftoff method were used to selectively localize poly-L-lysine (PLL) on the surface of MEAs. Haptotaxis led to the organization of the neurons into networks localized adjacent to microelectrodes. Various grids of PLL with 2-25-microm-wide lines spaced by 50-200 microm with 15-25-microm nodes at intersection points were used to guide cell body attachment and neurite outgrowth. Bursting activity with spike amplitude attenuation was observed, and multichannel recordings detected instances of coincident firing activity. Finally, we present here an extracellular recording from a approximately 2 microm bundle of guided neurites.

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