Property evaluation and microstructure characterization of the A3-3 matrix graphite for the Chinese HTR-PM pebble-style fuel elements
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Development of high-strength materials often involves introduction of additional strengthening microstructures that also serve as tritium trapping sites. Such additions in fusion material development could degrade the fuel efficiency in fusion reactors and raise radiological concerns. The contribution of individual microstructure features in hydrogen trapping must be evaluated to ensure fuel efficiency and radiological safety. This study explores the mechanistic origins of deuterium trapping in reduced-activation ferritic–martensitic steels and its correlation to mechanical strengthening. A series of model alloys and engineering steels were fabricated and subjected to different heat treatments to control deuterium trapping site density. Deuterium retention was evaluated using D 2 gas charging and thermal desorption spectroscopy, focusing on the role of grain boundary, dislocation, M 23 C 6 precipitates, and TiC precipitates. Multiscale microstructure characterization and synchrotron X-ray diffraction were performed to characterize microstructure, which was correlated to the deuterium retention property. Results show that TiC precipitates exhibit the highest deuterium trapping capacity, followed by M 23 C 6 precipitates. Dislocation and grain boundary demonstrate the lowest and similar efficiencies. Furthermore, the relationship of trapping quantity and mechanical strengthening of these microstructure features was quantified, demonstrating that TiC precipitates offer highest deuterium trapping per unit of mechanical strengthening.
The science of organic photovoltaic (OPV) cells has made dramatic advances over the past three years with power conversion efficiencies (PCEs) now reaching ~12%. The upper PCE limit of light-to-electrical power conversion for single-junction OPVs as predicted by theory is ~23%. With further basic research, the vision of such devices, composed of non-toxic, earth-abundant, readily easily processed materials replacing/supplementing current-generation inorganic solar cells may become a reality. Organic cells offer potentially low-cost, roll-to-roll manufacturable, and durable solar power for diverse in-door and out-door applications. Importantly, further gains in efficiency and durability, to that competitive with inorganic PVs, will require fundamental, understanding-based advances in transparent electrode and interfacial materials science and engineering. This team-science research effort brought together an experienced and highly collaborative interdisciplinary group with expertise in hard and soft matter materials chemistry, materials electronic structure theory, solar cell fabrication and characterization, microstructure characterization, and low temperature materials processing. We addressed in unconventional ways critical electrode-interfacial issues underlying OPV performance -- controlling band offsets between transparent electrodes and organic active-materials, addressing current loss/leakage phenomena at interfaces, and new techniques in cost-effective low temperature and large area cell fabrication. The research foci were: 1) Theory-guided design and synthesis of advanced crystalline and amorphous transparent conducting oxide (TCO) layers which test our basic understanding of TCO structure-transport property relationships, and have high conductivity, transparency, and tunable work functions but without (or minimizing) the dependence on indium. 2) Development of theory-based understanding of optimum configurations for the interfaces between oxide electrodes/interfacial layers and OPV active layer organic molecules/polymers. 3) Exploration and perfection of new processing strategies and cell architectures for the next-generation, large-area flexible OPVs. The goal has been to develop for the solar energy community the fundamental scientific understanding needed to design, fabricate, prototype, and ultimately test high-efficiency cells incorporating these new concepts. We achieved success in all of these directions.
A salient grand challenge for a number of Department of Energy programs such as Fuels Cycle Research and Development ( includes Accident Tolerant Fuel research and the Transient Reactor Test Facility Restart experiments), Light Water Sustainability, and Advanced Reactor Technologies is to enhance our fundamental understanding of fuel and materials behavior under irradiation. Robust and accurate in-pile measurements will be instrumental to develop and validate a computationally predictive multi-scale understanding of nuclear fuel and materials. This sensing technology will enable the linking of fundamental micro-structural evolution mechanisms to the macroscopic degradation of fuels and materials. The in situ sensors and measurement systems will monitor local environmental parameters as well as characterize microstructure evolution during irradiation. One of the major road blocks in developing practical robust, and cost effective in-pile sensor systems, are instrument leads. If a wireless telemetry infrastructure can be developed for in-pile use, in-core measurements would become more attractive and effective. Thus to be successful in accomplishing effective in-pile sensing and microstructure characterization an interdisciplinary measurement infrastructure needs to be developed in parallel with key sensing technology. For the discussion in this research, infrastructure is defined as systems, technology, techniques, and algorithms that may be necessary in the delivery of beneficial and robust data from in-pile devices. The architecture of a system’s infrastructure determines how well it operates and how flexible it is to meet future requirements. The limiting path for the effective deployment of the salient sensing technology will not be the sensors themselves but the infrastructure that is necessary to communicate data from in-pile to the outside world in a non-intrusive and reliable manner. This article gives a high level overview of a promising telemetry infrastructure based on acoustic wireless transmission of data that is being developed and tested by the INL, Penn State and Westinghouse.
Highlights: • Microstructures were characterized based on orientation-invariant image-texture features. • A new parameter called “amplitude”, was formulated and is based on image rotation and the Haralick parameters: texture contrast, correlation, homogeneity and energy. • The proposed method is insensitive to changing image resolution and image contrast/brightness settings. - Abstract: Microstructures were analyzed by an improved texture-based method using gray level co-occurrence matrices (GLCM). This method is based on a new parameter calculated from the stepwise rotation of images and thereby, calculating the values independent of the original texture orientation. The proposed method was applied on a database of etched and scanning electron microscopy (SEM)-imaged low-carbon steel microstructures that are currently extensively used for automated microstructure classification. The results on the microstructures consisting of pearlitic, lath martensitic and lower bainitic constituents revealed that the method allows a significant separation of various types of microstructures in the ideal case of square-shaped cutouts. For complete grains of the corresponding second phases, the results imply that the application of a classifier is advantageous to distinguish them with a sufficient accuracy. The robustness and workability of the method was further demonstrated by discussing the effect of varying the image resolution and contrast/brightness settings during image acquisition. It was shown that such user-dependent setting parameters do not impair the separability of the steel constituents by using the proposed method.
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In this paper, we employ gigahertz frequency ultrasonic waves to non-invasively image grain microstructure in polycrystalline ceria, an important electrolyte material for solid oxide fuel cells. This technique, termed time domain Brillouin scattering (TDBS), is a pump-probe technique that launches and monitors ultrasonics waves as they propagate from the surface into the depth of a sample. We demonstrate the capability of TDBS to image surface and subsurface grain structure by measuring mode and depth dependent velocity of the ultrasonic wave. A neural network tool is adopted to determine grain orientation from measured velocities. The TDBS results compare closely with electron backscatter diffraction (EBSD) measurements. This work expands the application of picosecond ultrasonics to three-dimensional imaging and offers a new route for the nondestructive microstructure characterization and in situ examination of polycrystalline materials.