Charge injection, electroluminescence, and ageing of an epoxy resin in high divergent fields

[INTRODUCTION]Most experimental studies of electrical ageing have concentrated on semi-crystalline polymers such as those used in cable insulation and capacitors (see for example [1]). Theoretical models [2-4] for electrical ageing have been developed on the basis of these studies. The consensus is that ageing involves the formation of low-density regions, though the mechanisms responsible are disputed. For example, bond scission by high-energy electrons [2,5], and mechanical deformation have both been suggested. Both of these mechanisms are related to charge injection and the subsequent formation of high local fields. The semi-crystalline polymers studied so far have similar chemistries and almost identical morphologies. They tend, therefore, to show many similarities in, for example, the size of the energy barriers for the ageing reaction, critical ageing levels, and field dependence of ageing [4]. These similarities make it difficult to discriminate between mechanisms. Epoxy resins, however, are network polymers with a different molecular chemistry to that of the semi-crystalline polymers and are thus ideal to evaluate the proposed ageing mechanisms. We have therefore studied an epoxy resin (CY1301) under both uniform field and high divergent field conditions. Uniform field conditions were used to gain baseline characteristics for the properties of the unaged epoxy resin, and also for the effects of electrical ageing in low fields. Studies in high divergent fields were made using an electrode arrangement adapted from that of [6]. A number of wires set approximately 0.5mm apart were embedded, parallel to the flat faces, in thin (290 m ) flat samples. The radius of the wires ranged from 5 m (gold plated tungsten) to 25 m (tungsten). Relatively small voltages applied to the wires (5 kV DC) therefore produced local fields up to 170 kV/mm depending upon the wire radius chosen. These field levels are high enough to inject space-charge [6] without leading to instantaneous failure. This geometry, therefore, may both inject charge and simulate local stress enhancements arising from charge accumulation. The number of wires is large (30) so that the volume affected is big enough to allow changes on ageing to be detectable

Riding in silence: a little snowboarding, a lot of small RNAs

The recent symposium, RNA silencing: Mechanism, Biology and Applications, organized by Phillip D. Zamore (University of Massachusetts Medical School) and Beverly Davidson (University of Iowa), and held in Keystone, Colorado, brought together scientists working on diverse aspects of RNA silencing, a field that comprises a multitude of gene regulatory pathways guided by microRNAs, small interfering RNAs and PIWI-interacting RNAs

The decay of space charge in a glassy epoxy resin following voltage removal

The PEA technique is used to measure the distribution of space charge in an epoxy resin after polarisation for one week at an applied field of 7.14kV/mm over a range of temperatures. The decay of the space charge is followed for times up to 114 hours after removal of the voltage and analysed in terms of a number of alternative decay mechanisms. It is shown that the rate-determining stage of the decay mechanism is that of a thermally activated process that has been associated with charge de-trapping. At times greater than 102s the de-trapping process behaves as though the space charge field does not exist and the retention time of the space charge depends only upon the depth of the deepest occupied traps and the temperature

A novel Border Identification algorithm based on an “Anti-Bayesian” paradigm

Border Identification (BI) algorithms, a subset of Prototype Reduction Schemes (PRS) aim to reduce the number of training vectors so that the reduced set (the border set) contains only those patterns which lie near the border of the classes, and have sufficient information to perform a meaningful classification. However, one can see that the true border patterns (“near” border) are not able to perform the task independently as they are not able to always distinguish the testing samples. Thus, researchers have worked on this issue so as to find a way to strengthen the “border” set. A recent development in this field tries to add more border patterns, i.e., the “far” borders, to the border set, and this process continues until it reaches a stage at which the classification accuracy no longer increases. In this case, the cardinality of the border set is relatively high. In this paper, we aim to design a novel BI algorithm based on a new definition for the term “border”. We opt to select the patterns which lie at the border of the alternate class as the border patterns. Thus, those patterns which are neither on the true discriminant nor too close to the central position of the distributions, are added to the “border” set. The border patterns, which are very small in number (for example, five from both classes), selected in this manner, have the potential to perform a classification which is comparable to that obtained by well-known traditional classifiers like the SVM, and very close to the optimal Bayes’ bound

Improving music genre classification using automatically induced harmony rules

We present a new genre classification framework using both low-level signal-based features and high-level harmony features. A state-of-the-art statistical genre classifier based on timbral features is extended using a first-order random forest containing for each genre rules derived from harmony or chord sequences. This random forest has been automatically induced, using the first-order logic induction algorithm TILDE, from a dataset, in which for each chord the degree and chord category are identified, and covering classical, jazz and pop genre classes. The audio descriptor-based genre classifier contains 206 features, covering spectral, temporal, energy, and pitch characteristics of the audio signal. The fusion of the harmony-based classifier with the extracted feature vectors is tested on three-genre subsets of the GTZAN and ISMIR04 datasets, which contain 300 and 448 recordings, respectively. Machine learning classifiers were tested using 5 × 5-fold cross-validation and feature selection. Results indicate that the proposed harmony-based rules combined with the timbral descriptor-based genre classification system lead to improved genre classification rates

Clustering data by inhomogeneous chaotic map lattices

A new approach to clustering, based on the physical properties of inhomogeneous coupled chaotic maps, is presented. A chaotic map is assigned to each data-point and short range couplings are introduced. The stationary regime of the system corresponds to a macroscopic attractor independent of the initial conditions. The mutual information between couples of maps serves to partition the data set in clusters, without prior assumptions about the structure of the underlying distribution of the data. Experiments on simulated and real data sets show the effectiveness of the proposed algorithm.Comment: 8 pages, 6 figures. Revised version accepted for publication on Physical Review Letter

Non-Fermi liquid behavior and scaling of low frequency suppression in optical conductivity spectra of CaRuO3_3

Optical conductivity spectra $\sigma_1(\omega)$ of paramagnetic CaRuO$_3$ are investigated at various temperatures. At T=10 K, it shows a non-Fermi liquid behavior of $\sigma_1(\omega)\sim 1/{\omega}^{\frac 12}$, similar to the case of a ferromagnet SrRuO$_3$. As the temperature ($T$) is increased, on the other hand, $\sigma_1(\omega)$ in the low frequency region is progressively suppressed, deviating from the 1/{\omega}^{\frac 12%}-dependence. Interestingly, the suppression of $\sigma_1(\omega)$ is found to scale with $\omega /T$ at all temperatures. The origin of the $$ scaling behavior coupled with the non-Fermi liquid behavior is discussed.Comment: 4 pages, 3 figure

Large Deviations of the Maximum Eigenvalue in Wishart Random Matrices

We compute analytically the probability of large fluctuations to the left of the mean of the largest eigenvalue in the Wishart (Laguerre) ensemble of positive definite random matrices. We show that the probability that all the eigenvalues of a (N x N) Wishart matrix W=X^T X (where X is a rectangular M x N matrix with independent Gaussian entries) are smaller than the mean value =N/c decreases for large N as $\sim \exp[-\frac{\beta}{2}N^2 \Phi_{-}(\frac{2}{\sqrt{c}}+1;c)]$, where \beta=1,2 correspond respectively to real and complex Wishart matrices, c=N/M < 1 and \Phi_{-}(x;c) is a large deviation function that we compute explicitly. The result for the Anti-Wishart case (M < N) simply follows by exchanging M and N. We also analytically determine the average spectral density of an ensemble of constrained Wishart matrices whose eigenvalues are forced to be smaller than a fixed barrier. The numerical simulations are in excellent agreement with the analytical predictions.Comment: Published version. References and appendix adde