56016 research outputs found
Sort by
Analysis of circularly polarized emission from perovskite thin-film devices
No full textDepartment of Materials Science and Engineeringclos
Anti-oxidant self-adhesive flexible devices based on Ag@Au core-sheath nanowires and 3D micro-architectures
No full textDepartment of Mechanical Engineeringclos
Applications of machine learning techniques for estimating VS30 and within-rock PSAs in Japan
No full textDepartment of Urban and Environmental Engineering (Disaster Management Engineering)clos
Circularly polarized emission from compact light-emitting devices: design & analysis
No full textDepartment of Materials Science and Engineeringclos
Conversion of Red Phosphorus to Two-Dimensional Crystalline Violet and Black Phosphorus
No full textSchool of Energy and Chemical Engineering (Energy Engineering)clos
????????? ????????? ??? ?????? ????????? ?????? ????????? ???????????? ?????? ???????????? ??????
Get PDFSchool of Energy and Chemical Engineering (Energy Engineering)Solar water splitting is regarded as alternative technology to produce green hydrogen with sustainable solar energy, which enable to reduce massive carbon emissions released from a grey hydrogen production. Water splitting process consist of two half-reactions???hydrogen (HER) and oxygen evolution reaction (OER)???and is conducted by semiconductor photoabsorbers modified with various types of catalysts. For efficient solar water splitting, structural and compositional modification of catalysts have been studied to improve their charge separation and transfer efficiency, and it has focused on the development of inorganic based catalysts so far. However, it has revealed that a main role of inorganic catalysts is increase of charge separation rather than water oxidation kinetics, thereby showing limited PEC performance in solar water splitting. In this regard, we introduced functional molecular multilayers including various types of polyelectrolyte and molecular polyoxometalate (POM) catalyst to enhance charge separation and transfer efficiency together. Polyelectrolytes and POM were deposited by solution-processable method through electrostatic force of each component, and molecular multilayers showed improved solar water splitting efficiency compared to conventional inorganic catalysts. Furthermore, we also confirmed that PEC property of photoelectrodes could be modulated by surface treatment with polyelectrolyte multilayers, providing highly efficient solar water splitting, even without molecular catalysts. Our photoelectrochemical investigation conducted by electrochemical impedance spectroscopy and rate law analysis suggested that functional multilayers enable to achieve efficient charge separation and transfer by surface state passivation and facile charge injection from polyelectrolyte and POM, respectively. To the best of our knowledge, functional molecular multilayers is a first approach to accomplish overall enhancement of water splitting catalysts, and we believe that our study provides new insight for modification of catalysts to elevate the efficiency of solar water splitting as distinct from conventional catalysts.ope
????????? ?????? ????????? ?????? ????????? ?????? ?????? ?????? ??????
Get PDFDepartment of Materials Science and EngineeringSunlight is an essential energy source that profoundly affects our lives (e.g., photosynthesis), and as light is regarded as one of the next-generation energy sources owing to its economic and environmental benefits, there have been attempted to utilize light as an energy source. To handle the sunlight in organic chemistry, in the beginning, sunlight was employed just as a heat source for distillation. Today, beyond thermal energy source, photochemistry has attracted much academic interest for generation of new reactive species (i.e., photoexcited species) in organic synthesis and polymerization. Consequently, in more future-oriented perspectives, those synthetic advances have been expanding into the utilization of the visible-light or near-infrared regions over the ultraviolet light region.
In the present dissertation, the design strategies for highly efficient photoredox catalysis under visible-light irradiation was studied. In addition, designed purely organic photoredox catalysts (PCs) based on cyanoarenes, one of the classes of thermally activated delayed fluorescence (TADF) compounds, were prepared to perform highly efficient organic (i.e., reductive dehalogenation) and polymeric (i.e., pressure-sensitive adhesive, PSA) syntheses. Chapter 1 presents an introduction to photoredox catalysis and a synopsis of the dissertation. In Chapter 2, the design strategies for highly efficient formation of radical anion of cyanoarene-based PCs (PC??????) were studiedunder visible-light irradiation, photoexcited PCs which have long-lived triplet excited state (T1) become one-electron-reduced species in the presence of sacrificial reducing agents. Furthermore, the photodegradation behavior of PCs, which would reduce their catalytic efficiencies, was studied using the density functional theory (DFT) calculations and detailed structural analysis of photodegraded products. Subsequently, based on the understanding of formation and degradation of PC??????, the highly efficient photoredox-mediated reductive dehalogenation combined with both ultra-low PC loading (ca. 0.005 mol%) and oxygen tolerance was realized. In Chapter 3, UV-blocking acrylic PSAs were successfully prepared with cyanoarene-based PCs under visible-light irradiation. In particular, PC design strategies were studied to efficiently generate the PC?????? with various donor moieties to control their electrochemical properties. Bulk polymerization of the prepolymer was mechanistically studied combined with DFT calculations. Oxygen tolerance behavior in bulk polymerization was also observed, and an oxygen tolerance mechanism was proposed. The overall conclusion of this dissertation and additional supplementary contents are presented in Chapter 4 and the Appendix, respectively.ope
Development of deep learning integrated futuristic biomedical platforms for digital healthcare
No full textDepartment of Biomedical EngineeringThe success of artificial intelligence to harness the complexity of data is becoming more vivid for biomedical use. For the digital transformation of healthcare, its role is essential: evidence-based decisions could become a new norm and understanding of our health could be augmented with the help of the technology integration. Moreover, enhanced efficiency, safety, and access in the delivery of healthcare services could be achieved. Working in symbiosis with human, AI devices should be developed to aid in hard tasks, help interpreting complex patterns behind abnormality processes, which are less likely to be solved with conventional computational methods or intuition.
We believe the new generation of digital healthcare tools are required to integrate emerging technologies: artificial intelligence into portable platforms (mobile, wearables, etc.). One approach towards this goal could be the development of narrow use, but targeted and capable instrumentation. Therefore, in this thesis, we demonstrated the utilization of engineering techniques to build integrated, localized solutions. We initially applied deep learning technique to accelerate tissue imaging with OCT. With the help of generative adversarial networks, we suggest inpainting missing volumes. This tool could have practical implications for in vivo applications, including skin studies in the cosmetics industry. Later, we focused on the development of customized imaging setup with automated segmentation and quantitative analysis functionality targeting drug screening purposes. We believe the high-throughput element of the system brings unique value compared to previous methods. Finally, we suggest mobile, AI-powered otoscope device for non-specialist ear examination. This tool represents an engineering approach to cultivate smart and accessible aspects of digital healthcare devices, which could be vital to address the situation in low-resource communities and empower point-of-care diagnosis.clos
??????????????? ????????? ???????????? ????????? ????????? ????????? ???????????? ???????????? ??????
No full textDepartment of Mechanical Engineeringclos
Domain Knowledge-Informed Functional Outlier Detection for Line Quality Control Systems
No full textDepartment of Industrial Engineeringclos