QC 351 A7 no. 48 / New materials of low thermal expansion are finding wide application. The expansion coefficient (a) is a function of temperature, and this function must be known for each material before its applicability can be assessed. A novel method for determining a, which is at once precise and easily implemented, has been devised. It is based on the dependence of mode frequencies in a Fabry-Perot interferometer on the mirror separation. The expansion sample is formed into an interferometer spacer with ends polished flat and parallel. Spherical mirrors are optically contacted to the ends, forming a confocal interferometer. The assembly is maintained at controlled temperatures in an environmental chamber. The two lowest -order transverse modes are probed by variable -frequency sidebands derived from a 633 -nm He- Ne laser by amplitude modulation. A change in sample temperature AT causes a change in interferometer length AL, which shifts the resonance frequencies by Av. Then a = (1 /AT) (AL /L) _ - (1 /AT)(iv /v). Thus, a can be measured with precision limited ultimately by the stability of the source laser, in practice 1:109 with presently available commercial lasers. For a sample of Owens -Illinois Cer -Vit, a has been measured at 10 temperatures in the range 3.0 to 32.4 °C, with a mean error of 2 x10-9 and a maximum error of 3 x10 -9. For a sample of Corning ULE silica, a has been measured at six temperatures in the same range, with a mean error of <1 x10 -9 and a maximum error of <1.3 x10 -9.

No description available.

The work presented in this thesis detail the measurement of the thermal expansion coefficient of three magnetic spin materials. Thermal expansion coefficient values were measured by capacitive dilatometry in several key low (T < 250 K) temperature regions specific to each material. This thesis is separated into several key parts. The first part establishes the theory behind observing phase transitions through the thermal expansion coefficient. Beginning with the classical definitions of the specific heat, compressibility and thermal expansion coefficient, the three properties are related using a property known as the Grüneisen parameter. To first order, the parameter allows phase transitions to be observed by the thermal expansion coefficient. The second part introduces capacitive dilatometry; a technique used to measure the thermal expansion coefficient. Three capacitive dilatometer devices are presented in this section. The silver compact dilatometer, the fused quartz dilatometer and the copper dilatometer. Each device discusses merits and weaknesses to their designs. Particular focus is made on the fused quartz dilatometer which was built during the duration of this thesis. The third part presents research on three magnetic spin materials; LiHoF4, Tb2Ti2O7 and Ba3NbFe3Si2O14. These materials are studied individually focusing on specific aspects. LiHoF4, a candidate material for the transverse field Ising model, provides insight to quantum phase transitions. Thermal expansion coefficient and magnetostriction along the c-axis for T ≈ 1.3-1.8 K and transverse field Ht ≈ 0-4 T were measured extracting critical points for a Ht-T phase diagram. Existing thermal expansion coefficient measurements had evidence of possible re-entrant behaviour. With a high density of low transverse field critical points it was established that LiHoF4 showed no evidence of re-entrant behaviour. The highly debated material Tb2Ti2O7 has a rich, controversial low temperature behaviour. Originally believed to be a spin liquid, specific heat results propose a scenario involving a sample composition dependent ordered state. Still under considerably attention, thermal expansion coefficient measurements were performed for T < 1 K. The results are interpreted to either fit into the proposed scenario or provide evidence for an alternate scenario. The material Ba3NbFe3Si2O14 exhibits a magnetoelectric multiferroic phase below TN ≈ 27 K; a phase where magnetic and electric order simultaneously exist. The formation of this phase is believed to have a similar structural shift observed in hexagonal perovskite multiferroic materials. The ferroelectric ordering in those materials are brought about through a centrosymmetric to non-centrosymmetric structural shift. The thermal expansion and thermal expansion coefficient coefficient along the a and c axis are measured for T > TN searching for a displacive structural phase transition.

In this work , impurity free vacancy diffusion (IFVD) quantum well intermixing(QWI) technology by high thermal-expansion-induced stress is used to perform bandgap engineering. In this paper, 1530nm InGaAsP multiple QWs sandwiched by p-InP (2£gm thickeneess, top) and n-InP (bottom) material is used as testing material structure also laser fabrication material, where contact materials (InGaAs and InP) on p-InP are used for comparison. By the difference between thermal expansion coefficients of SiO2 on the different material (InGaAs, InP), large different behaviors of QWI are observed, while low different dependence on defects created by ion-implantation is found. Above 70nm photo luminance (PL) wavelength shift of InGaAsP MQW below 2£gm thick InP is realized in this method. Further more, CW in-plane laser structures are also successfully fabricated and demonstrated by such QWI, giving the same shift as PL. It shows that good qualify of material can be obtained in such QWI method. Using local deposition of SiO2 causes different bandgap materials, re-growth free processing for monolithic integration can be expected, offering a powerful scheme of QWI for bandgap engineering.

Turbine components operate under severe loading conditions and at high and varying temperatures that result in thermal stresses in the presence of temperature gradients created by hot gases and cooling air. Moreover, static and cyclic loads as well as the motion of rotating components create mechanical stresses. The combined effect of complex thermo-mechanical stresses promote nucleation and propagation of cracks that give rise to fatigue and creep failure of the turbine components. Therefore, the relationship between thermo-mechanical stresses, chemical composition, heat treatment, resulting microstructure, operating temperature, material damage, and potential failure modes, i.e. fatigue and/or creep, needs to be well understood and studied. Artificial neural networks are promising candidate tools for such studies. They are fast, flexible, efficient, and accurate tools to model highly non-linear multi-dimensional relationships and reduce the need for experimental work and time-consuming regression analysis. Therefore, separate neural network models for γ’ precipitate strengthened Ni based superalloys have been developed for predicting the γ’ precipitate size, thermal expansion coefficient, fatigue life, and hysteresis energy. The accumulated fatigue damage is then estimated as the product of hysteresis energy and fatigue life. The models for γ’ precipitate size, thermal expansion coefficient, and hysteresis energy converge very well and match experimental data accurately. The fatigue life proved to be the most challenging aspect to predict, and fracture mechanics proved to potentially be a necessary supplement to neural networks. The model for fatigue life converges well, but relatively large errors are observed partly due to the generally large statistical variations inherent to fatigue life. The deformation mechanism map for 1.23Cr-1.2Mo-0.26V rotor steel has been constructed using dislocation glide, grain boundary sliding, and power law creep rate equations. The constructed map is verified with experimental data points and neural network results. Although the existing set of experimental data points for neural network modeling is limited, there is an excellent match with boundaries constructed using rate equations which validates the deformation mechanism map.

The work presented in this thesis detail the measurement of the thermal expansion coefficient of three magnetic spin materials. Thermal expansion coefficient values were measured by capacitive dilatometry in several key low (T < 250 K) temperature regions specific to each material. This thesis is separated into several key parts. The first part establishes the theory behind observing phase transitions through the thermal expansion coefficient. Beginning with the classical definitions of the specific heat, compressibility and thermal expansion coefficient, the three properties are related using a property known as the Grüneisen parameter. To first order, the parameter allows phase transitions to be observed by the thermal expansion coefficient. The second part introduces capacitive dilatometry; a technique used to measure the thermal expansion coefficient. Three capacitive dilatometer devices are presented in this section. The silver compact dilatometer, the fused quartz dilatometer and the copper dilatometer. Each device discusses merits and weaknesses to their designs. Particular focus is made on the fused quartz dilatometer which was built during the duration of this thesis. The third part presents research on three magnetic spin materials; LiHoF4, Tb2Ti2O7 and Ba3NbFe3Si2O14. These materials are studied individually focusing on specific aspects. LiHoF4, a candidate material for the transverse field Ising model, provides insight to quantum phase transitions. Thermal expansion coefficient and magnetostriction along the c-axis for T ≈ 1.3-1.8 K and transverse field Ht ≈ 0-4 T were measured extracting critical points for a Ht-T phase diagram. Existing thermal expansion coefficient measurements had evidence of possible re-entrant behaviour. With a high density of low transverse field critical points it was established that LiHoF4 showed no evidence of re-entrant behaviour. The highly debated material Tb2Ti2O7 has a rich, controversial low temperature behaviour. Originally believed to be a spin liquid, specific heat results propose a scenario involving a sample composition dependent ordered state. Still under considerably attention, thermal expansion coefficient measurements were performed for T < 1 K. The results are interpreted to either fit into the proposed scenario or provide evidence for an alternate scenario. The material Ba3NbFe3Si2O14 exhibits a magnetoelectric multiferroic phase below TN ≈ 27 K; a phase where magnetic and electric order simultaneously exist. The formation of this phase is believed to have a similar structural shift observed in hexagonal perovskite multiferroic materials. The ferroelectric ordering in those materials are brought about through a centrosymmetric to non-centrosymmetric structural shift. The thermal expansion and thermal expansion coefficient coefficient along the a and c axis are measured for T > TN searching for a displacive structural phase transition.

Turbine components operate under severe loading conditions and at high and varying temperatures that result in thermal stresses in the presence of temperature gradients created by hot gases and cooling air. Moreover, static and cyclic loads as well as the motion of rotating components create mechanical stresses. The combined effect of complex thermo-mechanical stresses promote nucleation and propagation of cracks that give rise to fatigue and creep failure of the turbine components. Therefore, the relationship between thermo-mechanical stresses, chemical composition, heat treatment, resulting microstructure, operating temperature, material damage, and potential failure modes, i.e. fatigue and/or creep, needs to be well understood and studied. Artificial neural networks are promising candidate tools for such studies. They are fast, flexible, efficient, and accurate tools to model highly non-linear multi-dimensional relationships and reduce the need for experimental work and time-consuming regression analysis. Therefore, separate neural network models for γ’ precipitate strengthened Ni based superalloys have been developed for predicting the γ’ precipitate size, thermal expansion coefficient, fatigue life, and hysteresis energy. The accumulated fatigue damage is then estimated as the product of hysteresis energy and fatigue life. The models for γ’ precipitate size, thermal expansion coefficient, and hysteresis energy converge very well and match experimental data accurately. The fatigue life proved to be the most challenging aspect to predict, and fracture mechanics proved to potentially be a necessary supplement to neural networks. The model for fatigue life converges well, but relatively large errors are observed partly due to the generally large statistical variations inherent to fatigue life. The deformation mechanism map for 1.23Cr-1.2Mo-0.26V rotor steel has been constructed using dislocation glide, grain boundary sliding, and power law creep rate equations. The constructed map is verified with experimental data points and neural network results. Although the existing set of experimental data points for neural network modeling is limited, there is an excellent match with boundaries constructed using rate equations which validates the deformation mechanism map.

京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第22673号 / エネ博第405号 / 新制||エネ||77(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応用科学専攻 / (主査)教授 平藤 哲司, 教授 馬渕 守, 教授 土井 俊哉 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM

The properties of composite materials in which spherical inclusions are embedded in a matrix of some kind, have been studied for many decades and many analytical models have been developed which measure these properties. There has been a steady progression in the complexity of models over the years, providing greater insight into the nature of these materials and improving the accuracy in the measurement of their properties. Some of the properties with which this thesis is concerned are, the elastic, thermal and electrical properties of such composites. The size of the spherical inclusion which acts as the reinforcing phase, has a major effect on the overall properties of composite materials. Once an inclusion is embedded into a matrix, a third region of different properties between the inclusion and matrix is known to develop which is called the interphase. It is well known in the composite community that the smaller the inclusion is, the larger the interphase region which develops around it. Therefore, with the introduction of nanoparticles as the preferred reinforcing phase for some composites, the interphase has a major effect on its properties. It is the aim of this thesis to consider the role of the interphase on the properties of composites by modeling it as an inhomogeneous region. There is much scientific evidence to support the fact that the interphase has an inhomogeneous nature and many papers throughout the thesis are cited which highlight this. By modeling the inhomogeneous properties by arbitrary mathematical functions, results are obtained for the various properties in terms of these general functions. Some specific profiles for the inhomogeneous region are considered for each property in order to demonstrate and test the models against some established results.

<p>  </p> <p>Metallic uranium-zirconium (U-Zr) nuclear fuel is a primary candidate for future fast reactors. The U-Zr system has been studied for decades with thousands of fuel pins being irradiated, yet the phase boundaries and lattice evolution with respect to temperature and composition remain poorly quantified. Historic engineering scale testing has resulted in empirical models for fuel evolution and subsequent fuel performance. However, these historic tests are on a convoluted system, consisting of dynamic temperatures, evolving thermal gradients, varying irradiation damage and damage rates, evolving compositions via fission and redistribution of primary constituents, and morphological evolution. This system proves exceedingly difficult to describe mechanistically due to the coexistence of various intertwined thermodynamic driving forces (e.g., temperature, composition, fluence, and fission rate which all vary concurrently). The driving forces influence the manifestation of the primary life-limiting phenomena present within the U-Zr system, specifically fuel-cladding mechanical interaction, fuel-cladding chemical interaction, fuel swelling, and fuel constituent redistribution. Although the phenomena present in the U-Zr system are known and qualitatively described, they are lacking in fundamental descriptions due to the historic inability to deconvolve the effects of temperature, composition, and fission rate. This study evaluates the current understanding of U-Zr fuel swelling and constituent redistribution in a uniquely quantified manner using Phenomena Identification and Ranking Tables. </p> <p><br></p> <p>In response to these findings, a novel separate effects irradiation test vehicle, housing uniquely fabricated U-Zr alloys, was proposed, developed, and successfully fabricated to provide the community with a means to decouple temperature, composition, initial microstructure, and fission rate from one-another. Initial out-of-pile characterization was conducted with scanning electron microscopy, transmission electron microscopy, and neutron diffraction with in-situ heating on various U-Zr alloys (U- 6, 10, 20, and 30 wt.% Zr). This work quantifies the initial microstructure throughout the fabrication process and the thermal response of the material. Results include the phase morphology, phase boundaries, absolute lattice parameters, and lattice specific coefficients of thermal expansion. The phase boundaries identified in this study were then used to develop a new U-Zr phase diagram. The isolation of thermal and compositional dependencies furthers the understanding of the fuel system and can be used to increase fuel longevity.</p>