I. Toward Non-blinking Robust Vis and NIR Active Fluorophores: Controlled Fabrication and Applications of Thick-Shell CdSe/nCdS and Ge/nCdS (n\u3e10) Nanocrystals II. Shape-Programmed Nanofabrication: Understanding the Reactivity of Dichalcogenide Precursors

Core/shell colloidal semiconductor nanocrystals are one of the most active areas of nanotechnology research. CdSe/nCdS core/shell heterostructures show remarkable suppressed fluroscence intermittency at the single-particle level. Although syntheses of thin- shelled core/shells have been reported in the past, reproducible syntheses for thick-shelled core/shells are less understood. Moreover, most of the core/shell reports are on CdSe/nCdS heterostructures, while other core materials -such as Ge- are absent from the literature. In the first part of this thesis, we present a thorough investigation of thick-shelled nanocrystal synthesis. We successfully grow metal sulfide shells on two different cores: CdSe and Ge. We explored the effect that the concentration of amine, amine type, core size, cadmium precursor concentration, annealing time, injection-rate and surface priming have on the synthesis of core/shell heterostructures. Adopting a similar method that uses surface priming, we are also able to grow epitaxial cadmium sulfide and zinc sulfide shells on Ge cores. The obtained Ge/nMS heterostructures show a large emission enhancement in the near-infrared range. We discuss the optical behavior of thick-shelled CdSe/nCdS nanocrystals at the ensemble and single-particle levels. Through collaboration with analytical research groups, we study the applications of these core/shell nanocrystals in bio-imaging and tracking using total internal reflection microscopy and stimulated emission depletion microscopy. Beyond spherical or spheroidal nanocrystals, anisotropic nanostructures such as nanorods and tetrapods are of particular interest in photocatalysis and energy harvesting. Controlling the size and morphology of more ophisticated structures such as these remains difficult. Dichalcogenide precursors enable the isolation of metastable nanocrystalline phases with unusual composition and morphology. It remains unclear what factors play a determinant role in controlling the outcome of preparations that utilize these interesting family of precursors. In the second part of this thesis, by studying a variety of commercially available dichalcogenides and the outcome of their reaction, and with the help of computational calculations, we demonstrate that the formation and degree of anisotropy of different nanocrystaline products can be traced back to the precise molecular structure and reactivity of the precursor used. We expect our results will not only lead to a larger throughput of these materials, but also lead to reliable syntheses of colloidal nanomaterials for customized applications

マイクロ波探傷法による配管減肉の検出性・位置特定・形状評価手法に関する研究

Tohoku University博士（工学）要約のみthesi

KINEMATIC ANALYSIS OF SPIKING IN ELITE VOLLEYBALL PLAYERS DURING COMPETITION

INTRODUCTION: Spiking is the most complex skill in volleyball game. The height and velocity are major factors influencing the performance of spiking. The purpose of this study was to investigate the characteristics of spike technique of elite male volleyball players during competition for reference in the teaching and coaching volleyball

The infuence ofoilspilland enteromorphaon syntheticaperture radar backscatter coefficient

In this Paper presentation, compare the normal Radar backscatter coefficient between oil spill area, clean sea area, Ship, platform area and Enteromorpha area. The result display the backscatter coefficient of oil spill area is lower than clean sea and the Enteromorpha area, ship, platform area is higher than clean sea.</p

Data-driven Preference Learning Methods for Multiple Criteria Sorting with Temporal Criteria

The advent of predictive methodologies has catalyzed the emergence of data-driven decision support across various domains. However, developing models capable of effectively handling input time series data presents an enduring challenge. This study presents novel preference learning approaches to multiple criteria sorting problems in the presence of temporal criteria. We first formulate a convex quadratic programming model characterized by fixed time discount factors, operating within a regularization framework. Additionally, we propose an ensemble learning algorithm designed to consolidate the outputs of multiple, potentially weaker, optimizers, a process executed efficiently through parallel computation. To enhance scalability and accommodate learnable time discount factors, we introduce a novel monotonic Recurrent Neural Network (mRNN). It is designed to capture the evolving dynamics of preferences over time while upholding critical properties inherent to MCS problems, including criteria monotonicity, preference independence, and the natural ordering of classes. The proposed mRNN can describe the preference dynamics by depicting marginal value functions and personalized time discount factors along with time, effectively amalgamating the interpretability of traditional MCS methods with the predictive potential offered by deep preference learning models. Comprehensive assessments of the proposed models are conducted, encompassing synthetic data scenarios and a real-case study centered on classifying valuable users within a mobile gaming app based on their historical in-app behavioral sequences. Empirical findings underscore the notable performance improvements achieved by the proposed models when compared to a spectrum of baseline methods, spanning machine learning, deep learning, and conventional multiple criteria sorting approaches

A new model to estimate significant wave heights with ERS-1/2 scatterometer data

A new model is proposed to estimate the significant wave heights with ERS-1/2 scatterometer data. The results show that the relationship between wave parameters and radar backscattering cross section is similar to that between wind and the radar backscattering cross section. Therefore, the relationship between significant wave height and the radar backscattering cross section is established with a neural network algorithm, which is, if the average wave period is &lt;= 7s, the root mean square of significant wave height retrieved from ERS-1/2 data is 0.51 m, or 0.72 m if it is &gt;7s otherwise.</p

Shape-Programmed Nanofabrication: Understanding the Reactivity of Dichalcogenide Precursors

Dialkyl and diaryl dichalcogenides are highly versatile and modular precursors for the synthesis of colloidal chalcogenide nanocrystals. We have used a series of commercially available dichalcogenide precursors to unveil the molecular basis for the outcome of nanocrystal preparations, more specifically, how precursor molecular structure and reactivity affect the final shape and size of II-VI semiconductor nanocrystals. Dichalcogenide precursors used were diallyl, dibenzyl, di-tert-butyl, diisopropyl, diethyl, dimethyl, and diphenyl disulfides and diethyl, dimethyl, and diphenyl diselenides. We find that the presence of two distinctively reactive C-E and E-E bonds makes the chemistry of these precursors much richer and interesting than that of other conventional precursors such as the more common phosphine chalcogenides. Computational studies (DFT) reveal that the dissociation energy of carbon-chalcogen (C-E) bonds in dichalcogenide precursors (R-E-E-R, E = S or Se) increases in the order (R): diallyl \u3c dibenzyl \u3c di-tert-butyl \u3c diisopropyl \u3c diethyl \u3c dimethyl \u3c diphenyl. The dissociation energy of chalcogen-chalcogen (E-E) bonds remains relatively constant across the series. The only exceptions are diphenyl dichalcogenides, which have a much lower E-E bond dissociation energy. An increase in C-E bond dissociation energy results in a decrease in R-E-E-R precursor reactivity, leading to progressively slower nucleation and higher selectivity for anisotropic growth, all the way from dots to pods to tetrapods. Under identical experimental conditions, we obtain CdS and CdSe nanocrystals with spherical, elongated, or tetrapodal morphology by simply varying the identity and reactivity of the dichalcogenide precursor. Interestingly, we find that precursors with strong C-E and weak E-E bond dissociation energies such as Ph-S-S-Ph serve as a ready source of thiol radicals that appear to stabilize small CdE nuclei, facilitating anisotropic growth. These CdS and CdSe nanocrystals have been characterized using structural and spectroscopic methods. An intimate understanding of how molecular structure affects the chemical reactivity of molecular precursors enables highly predictable and reproducible synthesis of colloidal nanocrystals with specific sizes, shapes, and optoelectronic properties for customized applications