Low-voltage polymer field-effect transistors for nonvolatile memories

We demonstrate organic nonvolatile memories based on transistors, made from spin-coated polymers, that have programming voltages of 15 V and good data retention capabilities. The low-voltage programmable ferroelectric field-effect transistors were obtained by an optimized ferroelectric polymer deposition method using cyclohexanone as a solvent from which films can be obtained that are thin, smooth and defect free. The data retention characteristics were measured for 3 h under constant read conditions. Extrapolation predicts that the data retention capability exceeds 10 years. (C) 2005 American Institute of Physics

Gate-bias assisted charge injection in organic field-effect transistors

The charge injection barriers in organic field-effect transistors (OFETs) seem to be far less critical as compared to organic light-emitting diodes (OLEDs). Counter intuitively; we show that the origin is image-force lowering of the barrier due to the gate bias at the source contact; although the corresponding gate field is perpendicular to the channel current. In coplanar OFETs; injection barriers up to 1 eV can be surmounted by increasing the gate bias; enabling extraction of bulk transport parameters in this regime. For staggered transistors; however; the injection is gate-assisted only until the gate bias is screened by the accumulation channel opposite to the source contact. The gate-assisted injection is supported by two-dimensional numerical charge transport simulations that reproduce the gate-bias dependence of the contact resistance and the typical S-shaped output curves as observed for OFETs with high injection barriers.

Dipolar Interactions and Origin of Spin Ice in Ising Pyrochlore Magnets

Recent experiments suggest that the Ising pyrochlore magnets ${\rm Ho_{2}Ti_{2}O_{7}}$ and ${\rm Dy_{2}Ti_{2}O_{7}}$ display qualitative properties of the spin ice model proposed by Harris {\it et al.} \prl {\bf 79}, 2554 (1997). We discuss the dipolar energy scale present in both these materials and consider how they can display spin ice behavior {\it despite} the presence of long range interactions. Specifically, we present numerical simulations and a mean field analysis of pyrochlore Ising systems in the presence of nearest neighbor exchange and long range dipolar interactions. We find that two possible phases can occur, a long range ordered antiferromagnetic one and the other dominated by spin ice features. Our quantitative theory is in very good agreement with experimental data on both ${\rm Ho_{2}Ti_{2}O_{7}}$ and ${\rm Dy_{2}Ti_{2}O_{7}}$. We suggest that the nearest neighbor exchange in ${\rm Dy_{2}Ti_{2}O_{7}}$ is {\it antiferromagnetic} and that spin ice behavior is induced by long range dipolar interactions.Comment: 4 postscript figures included. Submitted to Physical Review Letters Contact: [email protected]

The Quantum Affine Origin of the AdS/CFT Secret Symmetry

We find a new quantum affine symmetry of the S-matrix of the one-dimensional Hubbard chain. We show that this symmetry originates from the quantum affine superalgebra U_q(gl(2|2)), and in the rational limit exactly reproduces the secret symmetry of the AdS/CFT worldsheet S-matrix.Comment: 22 page

Tensor Regression with Applications in Neuroimaging Data Analysis

Classical regression methods treat covariates as a vector and estimate a corresponding vector of regression coefficients. Modern applications in medical imaging generate covariates of more complex form such as multidimensional arrays (tensors). Traditional statistical and computational methods are proving insufficient for analysis of these high-throughput data due to their ultrahigh dimensionality as well as complex structure. In this article, we propose a new family of tensor regression models that efficiently exploit the special structure of tensor covariates. Under this framework, ultrahigh dimensionality is reduced to a manageable level, resulting in efficient estimation and prediction. A fast and highly scalable estimation algorithm is proposed for maximum likelihood estimation and its associated asymptotic properties are studied. Effectiveness of the new methods is demonstrated on both synthetic and real MRI imaging data.Comment: 27 pages, 4 figure