High field degradation and electric breakdown of dielectrics are extremely complex phenomena as a result of the interplay among the electric field, temperature, material morphology, and extrinsic material properties. Fundamental understanding of carrier mobility related prebreakdown phenomena in dielectrics provides insights into high field transport phenomena as well as associated aging and onset of charge injection induced instability. Investigation of such extreme field conduction has been traditionally limited to the divergent field distribution generated using point-plane electrode configuration, as testing of parallel plate sample configuration under quasi steady-state conditions can only reach around two thirds of the breakdown field as a result of rapid high field aging. A circuit has been developed for transient characterization of conduction through a planar dielectric film during a linear ramp voltage to breakdown via the cancellation of displacement current to facilitate the measurement of small resistive currents down to 10ppm level. The dynamic cancellation of displacement current during an applied voltage waveform is realized through the use of a high frequency sinusoidal “bias” voltage to generate a capacitive current that can be cancelled using a feedback circuit based on a voltage-controlled amplifier with negligible phase shift and a dual-phase digital lock-in amplifier. Such capability of transient characterization of conduction in dielectrics will provide insights into dielectric aging and breakdown mechanism and form a quantitative basis for the extraction of critical transport parameters for conduction under extreme electric fields.

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The study of gene functions requires high-quality DNA libraries. However, a large number of tests and screenings are necessary for compiling such libraries. We describe an algorithm for extracting as much information as possible from pooling experiments for library screening. Collections of clones are called pools, and a pooling experiment is a group test for detecting all positive clones. The probability of positiveness for each clone is estimated according to the outcomes of the pooling experiments. Clones with high chance of positiveness are subjected to confirmatory testing. In this paper, we introduce a new positive clone detecting algorithm, called the Bayesian network pool result decoder (BNPD). The performance of BNPD is compared, by simulation, with that of the Markov chain pool result decoder (MCPD) proposed by Knill et al. in 1996. Moreover, the combinatorial properties of pooling designs suitable for the proposed algorithm are discussed in conjunction with combinatorial designs and d-disjunct matrices. We also show the advantage of utilizing packing designs or BIB designs for the BNPD algorithm.

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We study the group test for DNA library screening based on a probabilistic approach. The group test is a method of detecting a few positive items from among a large number of items, and has a wide range of applications. In DNA library screening, a positive item corresponds to the clone having a specified DNA segment, and it is necessary to identify and isolate the positive clones for compiling the libraries. In the group test, a group of items, called a pool, is assayed in a lump in order to save the cost of testing, and positive items are detected based on the observation from each pool. It is known that the design of grouping, that is, pooling design, is important to achieve accurate detection. In the probabilistic approach, positive clones are picked up based on the posterior probability. Naive methods of computing the posterior, however, involve exponentially many sums, and thus we need a device. The loopy belief propagation (loopy BP) algorithm is one of the popular methods to obtain approximate posterior probability efficiently. There are some works investigating the relation between the accuracy of the loopy BP and the pooling design. Based on these works, we develop a pooling design with a small estimation bias of posterior probability, and we show that the balanced incomplete block design (BIBD) has nice properties for our purpose. Some numerical experiments show that bias correction under the BIBD is useful to improve the estimation accuracy.