Anomalous Angle-Dependent Magnetotransport Properties of Single InAs Nanowires.

We study the magnetotransport properties of single InAs nanowires grown by selective-area metal-organic vapor-phase epitaxy. The semiconducting InAs nanowires exhibit a large positive ordinary magnetoresistance effect. However, a deviation from the corresponding quadratic behavior is observed for an orientation of the applied magnetic field perpendicular to the nanowire axis. This additional contribution to the magnetoresistance can be explained by diffuse boundary scattering of free carriers in the InAs nanowire and results in a reduction of the charge carrier mobility. As a consequence, angle-dependent magnetotransport measurements reveal a highly anomalous behavior. Numerical simulations have been conducted to further investigate the effect of classical boundary scattering in the nanowires. On the basis of the numerical simulations, an empirical description is derived, which yields excellent agreement with the experimental data and allows one to quantify the contribution of boundary scattering to the magnetoresistance effect.

Framework for automatic information extraction from research papers on nanocrystal devices.

To support nanocrystal device development, we have been working on a computational framework to utilize information in research papers on nanocrystal devices. We developed an annotated corpus called " NaDev" (Nanocrystal Device Development) for this purpose. We also proposed an automatic information extraction system called "NaDevEx" (Nanocrystal Device Automatic Information Extraction Framework). NaDevEx aims at extracting information from research papers on nanocrystal devices using the NaDev corpus and machine-learning techniques. However, the characteristics of NaDevEx were not examined in detail. In this paper, we conduct system evaluation experiments for NaDevEx using the NaDev corpus. We discuss three main issues: system performance, compared with human annotators; the effect of paper type (synthesis or characterization) on system performance; and the effects of domain knowledge features (e.g., a chemical named entity recognition system and list of names of physical quantities) on system performance. We found that overall system performance was 89% in precision and 69% in recall. If we consider identification of terms that intersect with correct terms for the same information category as the correct identification, i.e., loose agreement (in many cases, we can find that appropriate head nouns such as temperature or pressure loosely match between two terms), the overall performance is 95% in precision and 74% in recall. The system performance is almost comparable with results of human annotators for information categories with rich domain knowledge information (source material). However, for other information categories, given the relatively large number of terms that exist only in one paper, recall of individual information categories is not high (39-73%); however, precision is better (75-97%). The average performance for synthesis papers is better than that for characterization papers because of the lack of training examples for characterization papers. Based on these results, we discuss future research plans for improving the performance of the system.

Transport properties of hybrids with ferromagnetic MnAs nanoclusters and their potential for new magnetoelectronic devices.

Granular hybrid structures containing ferromagnetic nanoclusters embedded in a semiconducting matrix are an interesting class of materials as their properties can be tuned in a wide range. Hybrids are a promising alternative to dilute magnetic semiconductors in the field of spintronics and magnetoelectronics, because the nanoclusters can show ferromagnetic behavior even at room temperature. In this review, it is focused on the rather well investigated dilute magnetic semiconductor (Ga,Mn)As with MnAs inclusions. Different preparation methods are presented which were developed over the last two decades in order to obtain MnAs nanoclusters in the semiconducting matrix and to tune the structural and magnetic properties of these clusters. Recent results on the influence of the nanoclusters on the hybrids' transport properties as well as first approaches to use hybrids with a random nanocluster distribution in new spintronic devices are discussed. In addition, the perspective of using single MnAs nanoclusters as well as ordered arrangements of a few nanoclusters in new planar magnetoelectronic devices is illustrated.

Structural transition in indium phosphide nanowires.

We study the catalyst-free growth of InP nanowires using selective-area metalorganic vapor phase epitaxy (SA-MOVPE) and show that they undergo transition of crystal structures depending on the growth conditions. InP nanowires were grown on InP substrates where the mask for the template of the growth was defined. The nanowires were grown only in the opening region of the mask. It was found that uniform array of InP nanowires with hexagonal cross section and with negligible tapering were grown under two distinctive growth conditions. The nanowires grown in two different growth conditions were found to exhibit different crystal structures. It was also found that the orientation and size of hexagon were different, suggesting that the difference of the growth behavior. A model for the transition of crystal structure is presented based on the atomic arrangements and termination of InP surfaces. Photoluminescence measurement revealed that the transition took place for nanowires with diameters up to 1 microm.