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Research papers are a repository of information on the various elements that make up science and technology R&D activities. Generating knowledge maps based on research papers enables identification of specific areas of scientific and technical research as well as understanding of the flow of knowledge between those areas. Recently, as the number of electronic publishing and informatics archives along with the amount of accumulated knowledge related to science and technology has proliferated, the need to utilize the meta-knowledge obtainable from research papers has increased. Therefore, this study devised a model based on meta-knowledge (i.e., text information including citations, abstracts, area codes) for prediction of future growth potential using deep learning algorithms and investigated the applicability of the various forms of meta-knowledge to the prediction of future growth potential. It also proposes how to select the promising technology clusters based on the proposed model. [ABSTRACT FROM AUTHOR]

We synthesized 4,5-bis(octadecylthio)-4′,5′-bis(ethylcarbamoyl)tetrathiafulvalene and measured the electrical conductivity of its perchlorate (ClO4−)-doped nanofibers, which have double and triple helix structures. The nanostructure of the bis(octadecylthio)-TTF–diamide and its ClO4−-doped fibers in a 3 : 1 ratio was deduced in relation to the X-ray crystal structure of bis(methylthio)-TTF–diamide. The doubly coiled nanofibers form when initially formed spiral ribbons of lamellarly arranged TTF–diamide perchlorate split in the middle, and a further split of the double helix produces the triplex structure. Temperature-dependent conductance and current–voltage (I–V) characteristics of the coiled fibers were measured in the temperature (T) range of 70–300 K. The conductance decreased with a decrease in T, and the I–Vcharacteristics were nonlinear over the entire Trange. The results were analyzed by using a modified fluctuation-induced tunneling conduction model, where the barrier height and width were linearly dependent on the electric field. [ABSTRACT FROM AUTHOR]

Abstract: We have investigated the temperature dependence of electrical conductivity and thermoelectric power (TEP) at 1.7K< T <300K in an organo metallic complex, the iodine doped poly(vinyl alcohol)–Cu2+ chelate. We observed intrinsic metallic temperature dependence of resistivity from room temperature to 68K with a broad minimum [ρ(68K)/ρ(300K) ∼0.75], which has not been observed previously in similar organo metallic complexes. There occurs an unusual metal-insulator transition at T ∼68K and the resisitivity increases upon cooling below 68K. However, the low temperature resistivity becomes finite (instead of going to infinity), [ρ(1.7K)/ρ(300K) ∼0.98] indicating that a quantum mechanical tunneling conduction is dominant at this low temperature. It is remarkable that the resistivity at 1.7K is as small as that of room temperature. Such unusual temperature dependence of conductivity could be understood as thermally assisted hopping conduction between metallic islands. However, the observed intrinsic metallic temperature dependence of resistivity implies that such hopping conduction barrier is not important at high temperature (T >68K). The intrinsic metallic characteristics are confirmed by the quasi-linear temperature dependence of TEP for the whole measured temperature range (1.7K< T <300K) with a small slope change at low temperature, T <68K, which is understood as an effect of variable range hopping (VRH) conduction at low temperature. The results of magneto resistance (MR) and magneto thermoelectric power (MTEP) are consistent with the above interpretation. [Copyright &y& Elsevier]