In this study, the thermal properties of low dimensional materials such as graphene and boron nitride nanotube were investigated. As one of important heat transfer characteristics, interfacial thermal resistance (ITR) between graphene and Cu film was estimated by both experiment and simulation. In order to characterize ITR, the micropipette sensing technique was utilized to measure the temperature profile of suspended and supported graphene on Cu substrate that is subjected to continuous wave laser as a point source heating. By measuring the temperature of suspended graphene, the intrinsic thermal conductivity of suspended graphene was measured and it was used for estimating interfacial thermal resistance between graphene and Cu film. For simulation, a finite element method and a multiparameter fitting technique were employed to find the best fitting parameters. A temperature profile on a supported graphene on Cu was extracted by a finite element method using COMSOL Multiphysics. Then, a multiparameter fitting method using MATLAB software was used to find the best fitting parameters and ITR by comparing experimentally measured temperature profile with simulation one. In order to understand thermal transport between graphene and Cu substrate with different interface distances, the phonon density of states at the interface between graphene and Cu substrate was calculated by MD simulation.As another low dimensional material for thermal management applications, the thermal conductivity of BNNT was measured by nanoscale thermometry. For this work, a noble technique combining a focused ion beam (FIB) and nanomanipulator was employed to pick and to place a single BNNT on the desired location. The FIB technology was used to make nanoheater patterns (so called nanothermometer) on a prefabricated microelectrode device by conventional photolithography processes. With this noble technique and the nanoheater thermometry, the thermal conductivity of BNNT was successfully characterized by temperature gradient and heat flow measurements through BNNT.

Le nitrure de bore hexagonal (hBN) est un semi-conducteur à grand gap (>6 eV) appartenant à la nouvelle famille des cristaux 2D. Ses propriétés isolantes et sa structure cristalline font de lui un matériau stratégique dans la réalisation d’hétérostructures 2D à base de graphène. L’objectif de cette thèse a été d’étudier les propriétés optiques et structurales des feuillets de hBN.Après une description des méthodes expérimentales, les propriétés du matériau massif - loin des interfaces - sont étudiées sur le cristal de référence synthétisé par croissance haute-pression haute-température au Japon. L’étude en microscopie électronique à transmission a permis d’identifier l’empilement AA’, caractéristique du hBN. Les 3 principales régions d’émission de luminescence du hBN sont identifiées et analysées dans le détail : excitons libres, excitons piégés et défauts profonds. L’efficacité radiative excitonique a été analysée sur des cristaux issus de différentes voies de synthèse mettant en évidence des qualités dispersées. L’origine des processus de luminescence est discutée en regard des différentes interprétations actuelles, théoriques et expérimentales.Le cœur de la thèse porte sur les propriétés des cristaux 2D de faibles épaisseurs obtenus par clivage mécanique, ceci jusqu’à la monocouche atomique. Les expériences réalisées en spectroscopie Raman basse fréquence, en spectroscopie de pertes d’énergie et en cathodoluminescence ont mis en évidence une série d’effets de basse dimensionnalité sur les propriétés vibrationnelles, diélectriques et excitoniques du hBN. L’étude des défauts introduits lors de l’étape d’exfoliation et leur impact sur les émissions de luminescence ont permis d’isoler les propriétés intrinsèques des cristaux 2D de hBN. Les premiers résultats obtenus sur des feuillets suspendus dans le vide sont présentés et les effets de déformation élastique et plastique sur la luminescence de hBN discutés.La dernière partie de cette thèse porte sur des cristaux de nitrure de bore rhomboédrique (rBN) où les feuillets atomiques forment un empilement ABC. Ces cristaux ont permis d’aborder l’effet de l’empilement des plans atomiques sur la luminescence du BN en hybridation sp². / Hexagonal boron nitride (hBN) is a wide bandgap semi-conductor (>6 eV) which belongs to the 2D crystals family. Its structure and insulating properties make him as a strategic component towards the conception of graphene-based 2D heterostructures. This thesis focuses on the structural and optical properties of hBN layers.After a brief description of experimental methods, bulk material properties have been investigated on the reference HPHT-grown crystal fabricated in Japan. The characteristic stacking AA’ sequence of the hexagonal BN phase has been identified by transmission electron microscopy. Characteristics features of the 3 main luminescence regions have been identified and analyzed into details: free excitons, bound excitons and deep defects. The radiative efficiency of excitons recombinations in hBN has been studied on crystals obtained through various synthesis routes. The origin of hBN luminescence processes is discussed on the basis of current theoretical and experimental interpretations.The main part of the thesis is dedicated to the study of nanometer-thick hBN crystals obtained by mechanical cleavage, down to the monolayer. Experiments carried out by low-frequency Raman spectroscopy, energy loss spectroscopy and cathodoluminescence demonstrated a series of low-dimensionality effects on the vibrational, dielectric and excitonic properties of hBN. Defects introduced during the exfoliation step have been studied, their impact on luminescence emissions allowed us to isolate the intrinsic properties of 2D hBN flakes. Preliminary results obtained on hBN layers suspended in vacuum are presented and the effects of elastic and plastic deformation on BN luminescence are discussed.The last part of the work focuses on rhombohedral boron nitride (rBN) crystals where the BN stacking sequence follows the ABC type. Studying these crystals made possible the investigation of the influence of the stacking sequence on sp² BN luminescence.

Due to the multi-tasking and miniaturization of electronic devices, faster heat transfer is required from the device to avoid the thermal failure. Die-attached polymer adhesives are used to bond the chips in electronic packaging. These adhesives have to hold strong mechanical, thermal, dielectric, and moisture resistant properties. As polymers are insulators, heat conductive particles are inserted in it to enhance the thermal flow with an attention that there would be no electrical conductivity as well as no reduction in dielectric strength. This thesis focuses on the characterization of polymer nanocomposites for thermal and electrical properties with experimental and computational tools. Platelet geometry of hexagonal boron nitride offers highly anisotropic properties. Therefore, their alignment and degree of orientation offers tunable properties in polymer nanocomposites for thermal, electrical, and mechanical properties. This thesis intends to model the anisotropic behavior of thermal and dielectric properties using finite element and molecular dynamics simulations as well as experimental validation.

京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第20476号 / エネ博第345号 / 新制||エネ||69(附属図書館) / 京都大学大学院エネルギー科学研究科エネルギー社会・環境科学専攻 / (主査)教授 石原 慶一, 教授 野平 俊之, 准教授 奥村 英之 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM

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Yes / Alumina-cubic boron nitride (cBN) composites were prepared using the spark plasma sintering (SPS) technique. Alpha-alumina powders with particle sizes of ∼15 µm and ∼150 nm were used as the matrix while cBN particles with and without nickel coating were used as reinforcement agents. The amount of both coated and uncoated cBN reinforcements for each type of matrix was varied between 10 to 30 wt%. The powder materials were sintered at a temperature of 1400 °C under a constant uniaxial pressure of 50 MPa. We studied the effect of the size of the starting alumina powder particles, as well as the effect of the nickel coating, on the phase transformation from cBN to hBN (hexagonal boron nitride) and on the thermo-mechanical properties of the composites. In contrast to micro-sized alumina, utilization of nano-sized alumina as the starting powder was observed to have played a pivotal role in preventing the cBN-to-hBN transformation. The composites prepared using nano-sized alumina reinforced with nickel-coated 30 wt% cBN showed the highest relative density of 99% along with the highest Vickers hardness (Hv2) value of 29 GPa. Because the compositions made with micro-sized alumina underwent the phase transformation from cBN to hBN, their relative densification as well as hardness values were relatively low (20.9–22.8 GPa). However, the nickel coating on the cBN reinforcement particles hindered the cBN-to-hBN transformation in the micro-sized alumina matrix, resulting in improved hardness values of up to 24.64 GPa.

Contemporary diagnostics rely on expensive, time-consuming, and optically-limited mechanisms that prevent at-home point-of-care molecular diagnostics with the accuracy of laboratory tools and the convenience of affordability. In this Thesis, biosensing was explored with commercial two-dimensional (2D) materials which have been investigated extensively over the last two decades yielding a variety of sensor metrics for detecting biomolecules. 2D materials have intrinsic properties that depend on the quality of material and substrate surface being employed. Here, graphene/SiO2 and monolayer hexagonal boron nitride (hBN) capping layer on graphene/SiO2 field-effect transistors (FETs) were used. Until recently, monolayer hBN has not been commercially available at the wafer-scale and has been observed in the literature to augment the properties of graphene-based devices and better control of processing repeatability. The work in this Thesis combines biochemistry with the wafer-scale production and surface-dependent properties of graphene and monolayer hBN/graphene via a FET fabrication process circumventing the use of photoresist. This was done to avoid photoresist resin that may contaminate the transducer surface and contribute to repeatability issues when studying biochemistry with 2D materials. Briefly, surface engineering of graphene/SiO2 and hBN/graphene/SiO2 was done, and the transfer characteristics were measured as a function of either the concentration of protons, genes, or proteins. Compared to bare 2D materials, the pH sensitivity of the shift in Dirac voltage was enhanced to -99 mV/pH when using 8.6 nm of Al2O3 on hBN/graphene/SiO2 FET. Graphene devices were then engineered for sensing SARS-CoV-2 genome with a signal-to-noise ratio of 3 at 100 aM and a linearized sensitivity of +22 mV/molar decade of SARS-CoV-2 ribonucleic acid and a dynamic range of four orders of magnitude. This was done by conjugating single-stranded deoxyribonucleic acid to sub-percolation threshold gold nanofilms deposited directly on the graphene sensing mesa. Finally, the 2D devices were studied for detecting SARS-CoV-2 spike protein after being functionalized with rabbit immunoglobulin G (IgG) monoclonal antibody (mAb). Additionally, preliminary work was done regarding the partial reduction and fragmentation of anti-SARS-CoV-2 spike protein human mAb IgG in an approach to leverage gold-thiol chemistry for covalently bonding the IgG to the 2D sensing mesa. In summary, the utilization of wide- and zero-bandgap nanomaterials may have profound implications in augmenting molecular diagnosis and treatment of disease through economically decentralizing biosensing. / 2024-01-20T00:00:00Z

This work presents a step forward in the use of 2D layered materials (2DLM), specifically hexagonal boron nitride (h-BN), for the fabrication of memristors. In this study, we fabricate, characterize, and use h-BN based memristors with Ag/few-layer h-BN/Ag structure to implement a fully functioning artificial leaky integrate-and-fire neuron on hardware. The devices showed volatile resistive switching behavior with no electro-forming process required, with relatively low VSET and long endurance of beyond 1.5 million cycles. In addition, we present some of the failure mechanisms in these devices with some statistical analyses to understand the causes, as well as a statistical study of both cycle-to-cycle and device-to-device variabilities in 20 devices. Moreover, we study the use of these devices in implementing a functioning artificial leaky integrate-and-fire neuron similar to a biological neuron in the brain. We provide SPICE simulation as well as hardware implementation of the artificial neuron that are in full agreement, showing that our device could be used for such application. Additionally, we study the use of these devices as an activation function for spiking neural networks (SNNs) by providing a SPICE simulation of a fully trained network, where the artificial spiking neuron is connected to the output terminal of a crossbar array. The SPICE simulations provide a proof of concept for using h-BN based memristor for activation function for SNNs.