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.

Material model of lung parenchyma based on living precision-cut lung slice testing.

We describe a novel constitutive model of lung parenchyma, which can be used for continuum mechanics based predictive simulations. To develop this model, we experimentally determined the nonlinear material behavior of rat lung parenchyma. This was achieved via uni-axial tension tests on living precision-cut rat lung slices. The resulting force-displacement curves were then used as inputs for an inverse analysis. The Levenberg-Marquardt algorithm was utilized to optimize the material parameters of combinations and recombinations of established strain-energy density functions (SEFs). Comparing the best-fits of the tested SEFs we found Wpar = 4.1 kPa(I1-3)2 + 20.7 kPa(I1 - 3)3 + 4.1 kPa(-2 ln J + J2 - 1) to be the optimal constitutive model. This SEF consists of three summands: the first can be interpreted as the contribution of the elastin fibers and the ground substance, the second as the contribution of the collagen fibers while the third controls the volumetric change. The presented approach will help to model the behavior of the pulmonary parenchyma and to quantify the strains and stresses during ventilation.