Paper-like electronic displays: Large-area rubber-stamped plastic sheets of electronics and microencapsulated electrophoretic inks

Electronic systems that use rugged lightweight plastics potentially offer attractive characteristics (low-cost processing, mechanical flexibility, large area coverage, etc.) that are not easily achieved with established silicon technologies. This paper summarizes work that demonstrates many of these characteristics in a realistic system: organic active matrix backplane circuits (256 transistors) for large (≈5 × 5-inch) mechanically flexible sheets of electronic paper, an emerging type of display. The success of this effort relies on new or improved processing techniques and materials for plastic electronics, including methods for (i) rubber stamping (microcontact printing) high-resolution (≈1 μm) circuits with low levels of defects and good registration over large areas, (ii) achieving low leakage with thin dielectrics deposited onto surfaces with relief, (iii) constructing high-performance organic transistors with bottom contact geometries, (iv) encapsulating these transistors, (v) depositing, in a repeatable way, organic semiconductors with uniform electrical characteristics over large areas, and (vi) low-temperature (≈100°C) annealing to increase the on/off ratios of the transistors and to improve the uniformity of their characteristics. The sophistication and flexibility of the patterning procedures, high level of integration on plastic substrates, large area coverage, and good performance of the transistors are all important features of this work. We successfully integrate these circuits with microencapsulated electrophoretic “inks” to form sheets of electronic paper.

Localization of the central rhythm generator involved in spontaneous consummatory licking in rats: functional ablation and electrical brain stimulation studies.

Localization of the central rhythm generator (CRG) of spontaneous consummatory licking was studied in freely moving rats by microinjection of tetrodotoxin (TTX) into the pontine reticular formation. Maximum suppression of spontaneous water consumption was elicited by TTX (1 ng) blockade of the oral part of the nucleus reticularis gigantocellularis (NRG), whereas TTX injections into more caudal or rostral locations caused significantly weaker disruption of drinking. To verify the assumption that TTX blocked the proper CRG of licking rather than some relay in its output, spontaneously drinking thirsty rats were intracranially stimulated via electrodes chronically implanted into the oral part of the NRG. Lick-synchronized stimulation (a 100-ms train of 0.1-ms-wide rectangular pulses at 100 Hz and 25-150 microA) applied during continuous licking (after eight regular consecutive licks) caused a phase shift of licks emitted after stimulus delivery. The results suggest that the stimulation has reset the CRG of licking without changing its frequency. The reset-inducing threshold current was lowest during the tongue retraction and highest during the tongue protrusion period of the lick cycle. It is concluded that the CRG of licking is located in the oral part of NRG.

Approximation algorithms

Increasing global competition, rapidly changing markets, and greater consumer awareness have altered the way in which corporations do business. To become more efficient, many industries have sought to model some operational aspects by gigantic optimization problems. It is not atypical to encounter models that capture 106 separate “yes” or “no” decisions to be made. Although one could, in principle, try all 2106 possible solutions to find the optimal one, such a method would be impractically slow. Unfortunately, for most of these models, no algorithms are known that find optimal solutions with reasonable computation times. Typically, industry must rely on solutions of unguaranteed quality that are constructed in an ad hoc manner. Fortunately, for some of these models there are good approximation algorithms: algorithms that produce solutions quickly that are provably close to optimal. Over the past 6 years, there has been a sequence of major breakthroughs in our understanding of the design of approximation algorithms and of limits to obtaining such performance guarantees; this area has been one of the most flourishing areas of discrete mathematics and theoretical computer science.