Storage of mine tailings and waste concrete imposes economical and environmental impacts. Researchers have attempted to reuse wastes as construction material by utilizing ordinary Portland cement (OPC) to stabilize them. This method, however, has a number of limitations related to OPC. In this research, a recent technology called geopolymerization is used to stabilize mine tailings and concrete waste so that they can be completely recycled and reused. The research includes three main parts. The first part studies the effect of different factors on the mechanical properties, micro/nano structure, and elemental and phase composition of mine tailings-based geopolymer binder. The second part investigates the feasibility of producing geopolymer bricks using mine tailings. The physical and mechanical properties, micro/nano structure, durability, and environmental performance of the produced bricks are studied in a systematic way. Moreover, the enhancement of the mine tailings-based geopolymer bricks by adding cement kiln dust (CKD) is studied. The third part of the research investigates the recycling of the fines fraction of crushed waste concrete to produce binder through geopolymerization in order to completely recycle concrete waste. The results indicate the viability of geopolymerization of mine tailings by optimizing the synthesis conditions. By properly selecting these factors, mine tailings-based geopolymer bricks can be produced to meet the ASTM standard requirements and to be environmentally safe by effectively immobilizing the heavy metals in the mine tailings. The physical and mechanical properties and durability of the mine tailings-based geopolymer bricks can be further enhanced by adding a small amount of CKD. The results also show that the fines fraction of crushed waste concrete can be used together with fly ash to produce high performance geopolymer binder. Incorporation of calcium in the geopolymer structure and coexistence of the calcium products such as CSH gel and the geopolymer gel explains the enhancement of the mine tailings-based geopolymer bricks with CKD and the high performance of geopolymer binder from the waste concrete fines and fly ash. The research contributes to sustainable development by promoting complete recycling and utilization of mine tailings and concrete waste as construction material.

The marked increase in demand for miniaturized consumer products in a broad range of potential applications including medical, telecommunication, avionics, biotechnology and electronics is a result of advancements in miniaturization technologies. Consequently, engineering components are being drastically reduced in size. This coupled with the quest for higher quality components, has imposed more stringent requirements on manufacturing processes and materials used to produce micro components. Hence, the development of ultra precision manufacturing processes to fabricate micro-scale features in engineering products has become a focal point of recent academic and industrial research. However, much attention in the area of micro-manufacturing, especially micro-mechanical machining, has been devoted to building miniature machine tools with nanometer positioning resolution and sub-micron accuracy. There is lack of fundamental understanding of mechanical machining at the micro and nano scale. Specifically, basic understanding of chip formation mechanism, cutting forces, size-effect in specific cutting energy, and machined surface integrity in micro and nano scale machining and knowledge of how these process responses differ from those in macro-scale cutting are lacking. In addition, there is a lack of investigations of micro and nano scale cutting of common engineering materials such as aluminum alloys and ferrous materials. This thesis proposes to advance the understanding of machining at the micro and nano scale for common engineering alloys. This will be achieved through a series of systematic micro and nano cutting experiments. The effects of cutting conditions on the machining forces, chip formation and machined surface morphology in simple orthogonal micro-cutting of a ferrous, P20 mold steel (30 HRC), and a non-ferrous structural alloy, aluminum AL7075 (87 HRB), used in the mold making and rapid prototyping industry will be studied. The data will also be compared with data obtained from conventional macro-scale cutting. In addition, the applicability of conventional metal cutting theory to micro and nano cutting test data will be examined. The analysis will provide a better understanding of machining forces, chip formation, and surface generation in micro and nano scale cutting process and how it differs from macro-scale cutting.

Kirkendall effect has been studied experimentally as well as theoretically for decades already. There are theoretical indications, that the Kirkendall effect must operate from the beginning of the diffusion process but there are practically no measurements on this short time and length scale. For that reason, diffusion on the nanometer scale was investigated experimentally in different binary systems in thin film geometry. We followed the diffusion process as well as the Kirkendall effect by different methods (TEM, SNMS and synchrotron X-ray waveguide technique). Investigations were performed in systems with complete solubility (Bi-Sb, Cu-Ni, Bi-Sb) as well as in systems forming intermetallic phase (Fe-Sb, Fe- Pd). It was found that with these methods the Kirkendall shift can be well followed on the nano-scale. In Fe-Sb system even the bifurcation of the Kirkendall plane was observed.

京都大学 / 0048 / 新制・論文博士 / 博士(工学) / 乙第13008号 / 論工博第4133号 / 新制||工||1649(附属図書館) / 32936 / (主査)教授 北村 隆行, 教授 北條 正樹, 教授 琵琶 志朗 / 学位規則第4条第2項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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Spherical micro- and nano-particles have found widespread use in many various applications from paint to cosmetics to medicine. Due to the multiplicity of desired particle material(s), structure, size range, and functionality, many approaches exist for generating such particles. Bottom-up methods such as chemical synthesis have a high yield and work with a wide range of materials; however, these processes typically lead to large polydispersity and cannot produce structured particles. Top-down approaches such as microfluidics overcome the polydispersity issue and may produce a few different structures in particles, but at lower rates and only at the micro-scale. A method that can efficiently produce uniformly-sized, structured particles out of a variety of materials and at both the micro- and nano-scales does not yet exist. Over the past few years, I have developed an in-fiber particle fabrication method that relies on a surface tension-driven fluid instability, the Plateau-Rayleigh capillary instability (PRI). Thermal treatment of a multimaterial core/cladding fiber induces the PRI, causing the initially intact core to break up into a periodic array of uniformly-sized spherical particles. During this time, I have demonstrated that this method can produce particles from both polymers and glasses, in a multiplicity of structures, and from diameters of over 1 mm down to 20 nm. Furthermore, by using a stack-and-draw method, a high density of cores may be incorporated into a single fiber, making the in-fiber PRI approach a highly scalable process. Finally, I have shown that it is possible to add dopants to the particles to give them functionality. By structuring the particles, it is thus possible to fabricate multi-functional particles whose functionalities may be allocated arbitrarily throughout the volume of the particles.

Background: IDH-wild-type glioblastoma (GBM) is the most frequent brain-derived malignancy. Despite intense research efforts, it is still associated with a very poor prognosis. Several parameters were identified as prognostic, including general physical performance. In neuro-oncology (NO), special emphasis is put on focal deficits and cognitive (dys-)function. The Neurologic Assessment in Neuro-Oncology (NANO) scale was proposed in order to standardize the assessment of neurological performance in NO. This study evaluated whether NANO scale assessment provides prognostic information in a standardized collective of GBM patients. Methods: The records of all GBM patients treated between 2014 and 2019 at our facility were retrospectively screened. Inclusion criteria were age over 18 years, at least 3 months postoperative follow-up, and preoperative and postoperative cranial magnetic resonance imaging. The NANO scale was assessed pre- and postoperatively as well as at 3 months follow-up. Univariate and multivariate survival analyses were carried to investigate the prognostic value. Results: One hundred and thirty-one patients were included. In univariate analysis, poor postoperative neurological performance (HR 1.13, p = 0.004), poor neurological performance at 3 months postsurgery (HR 1.37, p < 0.001), and neurological deterioration during follow-up (HR 1.38, p < 0.001), all assessed via the NANO scale, were associated with shorter survival. In multivariate analysis including other prognostic factors such as the extent of resection, adjuvant treatment regimen, or age, NANO scale assessment at 3 months postoperative follow-up was independently associated with survival prediction (HR 1.36, p < 0.001). The optimal NANO scale cutoff for patient stratification was 3.5 points. Conclusion: Neurological performance assessment employing the NANO scale might provide prognostic information in patients suffering from GBM.

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Major challenges in maintaining quality and reliability in today’s microelectronics devices come from the ever increasing level of integration in the device fabrication, as well as the high level of current densities that are carried through the microchip during operation. In order to have a framework for design and reliability assessment, it is imperative to develop a predictive capability for the thermal response of micro-electronic components. A computationally efficient and accurate multi-scale transient thermal methodology was developed using a combination of two different approaches: “Progressive Zoom-in” method and “Proper Orthogonal Decomposition (POD)” technique. The proposed technique has the capability of handling several decades of length scale from tens of millimeter at “package” level to several nanometers at “interconnects” level at a considerably lower computational cost, while maintaining satisfactory accuracy. This ability also applies for time scales from seconds to microseconds corresponding to various transient thermal events. The proposed method also provides the ability to rapidly predict thermal responses under different power input patterns, based on only a few representative detailed simulations, without compromising the desired spatial and temporal resolutions. It is demonstrated that utilizing the proposed model, the computational time is reduced by at least two orders of magnitude at every step of modeling. Additionally, a novel experimental platform was developed to evaluate rapid transient Joule heating in embedded nanoscale metallic films representing buried on-chip interconnects that are not directly accessible. Utilizing the state-of-the-art sub-micron embedded resistance thermometry the effect of rapid transient power input profiles with different amplitudes and frequencies were studied. It is also demonstrated that a spatial resolution of 6 µm and thermal time constant of below 1 µs can be achieved using this technique. Ultimately, the size effects on the thermal and material properties of embedded metallic films were studied. A state-of-the-art technique to extract thermal conductivity of embedded nanoscale interconnects was developed. The proposed structure is the first device that has enabled the conductivity measurement of embedded metallic films on a substrate. It accounts for the effect of the substrate and interface without compromising the sensitivity of the device to the thermal conductivity of the metallic film. Another advantage of the proposed technique is that it can be integrated within the structure and be used for measurements of embedded or buried structures such as nanoscale on chip interconnects, without requiring extensive micro-fabrication. The dependence of the thermal conductivity on temperature was also investigated. The experimentally measured values for thermal conductivity and its dependence on temperature agree well with previous studies on free-standing nanoscale metallic bridges.

Nano-scale machining, or Nanomachining is a hybrid process in which the total thermal energy necessary to remove atoms from a work-piece surface is applied from external sources. In the current study, the total thermal energy necessary to remove atoms from a work-piece surface is applied from two sources: (1) localized energy from a laser beam focused to a micron-scale spot to preheat the work-piece, and (2) a high-precision electron-beam emitted from the tips of carbon nano-tubes to remove material via evaporation/sublimation. Macro-to-nano scale heat transfer models are discussed for understanding their capability to capture and its application to predict the transient heat transfer mechanism required for nano-machining. In this case, thermal transport mechanism during nano-scale machining involves both phonons (lattice vibrations) and electrons; it is modeled using a parabolic two-step (PTS) model, which accounts for the time lag between these energy carriers. A numerical algorithm is developed for the solution of the PTS model based on explicit and implicit finite-difference methods. Since numerical solution for simulation of nanomachining involves high computational cost in terms of wall clock time consumed, performance comparison over a wide range of numerical techniques has been done to devise an efficient numerical solution procedure. Gauss-Seidel (GS), successive over relaxation (SOR), conjugate gradient (CG), d -form Douglas-Gunn time splitting, and other methods have been used to compare the computational cost involved in these methods. Use of the Douglas-Gunn time splitting in the solution of 3D time-dependent heat transport equations appears to be optimal especially as problem size (number of spatial grid points and/or required number of time steps) becomes large. Parallel computing is implemented to further reduce the wall clock time required for the complete simulation of nanomachining process. Domain decomposition with inter-processor communication using Message Passing Interface (MPI) libraries is adapted for parallel computing. Performance tuning has been implemented for efficient parallelization by overlapping communication with computation. Numerical solution for laser source and electron-beam source with different Gaussian distribution are presented. Performance of the parallel code is tested on four distinct computer cluster architecture. Results obtained for laser source agree well with available experimental data in the literature. The results for electron-beam source are self-consistent; nevertheless, they need to be validated experimentally.