Novel nonvolatile memory with multibit storage based on a ZnO nanowire transistor.

We demonstrate a room temperature processed ferroelectric (FE) nonvolatile memory based on a ZnO nanowire (NW) FET where the NW channel is coated with FE nanoparticles. A single device exhibits excellent memory characteristics with the large modulation in channel conductance between ON and OFF states exceeding 10(4), a long retention time of over 4 × 10(4) s, and multibit memory storage ability. Our findings provide a viable way to create new functional high-density nonvolatile memory devices compatible with simple processing techniques at low temperature for flexible devices made on plastic substrates.

Nonvolatile memory functionality of ZnO nanowire transistors controlled by mobile protons.

We demonstrated the nonvolatile memory functionality of ZnO nanowire field effect transistors (FETs) using mobile protons that are generated by high-pressure hydrogen annealing (HPHA) at relatively low temperature (400 °C). These ZnO nanowire devices exhibited reproducible hysteresis, reversible switching, and nonvolatile memory behaviors in comparison with those of the conventional FET devices. We show that the memory characteristics are attributed to the movement of protons between the Si/SiO(2) interface and the SiO(2)/ZnO nanowire interface by the applied gate electric field. The memory mechanism is explained in terms of the tuning of interface properties, such as effective electric field, surface charge density, and surface barrier potential due to the movement of protons in the SiO(2) layer, consistent with the UV photoresponse characteristics of nanowire memory devices. Our study will further provide a useful route of creating memory functionality and incorporating proton-based storage elements onto a modified CMOS platform for FET memory devices using nanomaterials.

Tree-Structured Stick Breaking Processes for Hierarchical Data

Many data are naturally modeled by an unobserved hierarchical structure. In this paper we propose a flexible nonparametric prior over unknown data hierarchies. The approach uses nested stick-breaking processes to allow for trees of unbounded width and depth, where data can live at any node and are infinitely exchangeable. One can view our model as providing infinite mixtures where the components have a dependency structure corresponding to an evolutionary diffusion down a tree. By using a stick-breaking approach, we can apply Markov chain Monte Carlo methods based on slice sampling to perform Bayesian inference and simulate from the posterior distribution on trees. We apply our method to hierarchical clustering of images and topic modeling of text data.

Holographic memory with correlator based readout

The investigation of an inverted hybrid digital/ optical VanderLugt type correlator based on a holographic memory is reported in this paper. A set of reference templates is stored in a photorefractive crystal (PRC) by angular hologram multiplexing. In the filter plane, a phase-modulating liquid crystal television (LCTV) serves as a phase-only input device. During the recognition process, which is based on the pure phase correlation, the reference templates are correlated sequentially with the input object. This correlator shows high sensitivity to object rotation, sharp correlation peaks, high light efficiency, and is fully shift-invariant in spite of the PRC thickness. The influences of the LCTV on the performance of the system are discussed and experimental results are shown.