Hydrogen peroxide photosynthesis from water and air using a scaled-up 1-m2 flow reactor
Not Available
Zheng, Xiaoshan↗
Engineering topics
Liu, Tian
Publications and source records attributed to Liu, Tian.
Role of phosphorus impurities in decomposition of La 2 NiO 4 –La 0.5 Ce 0.5 O 2-δ oxygen electrode in a solid oxide electrolysis cell
This study explored the decomposition mechanism of a La 2 NiO 4 (LNO) phase in the La 2 NiO 4 –La 0.5 Ce 0.5 O 2-δ (LNO-LDC) oxygen electrode in a solid oxide electrolysis cell (SOEC) after testing at 800 °C. Scanning electron microscopy and scanning transmission electron microscopy examinations of the LNO-LDC oxygen electrode before and after testing were undertaken. Other than phosphorus contamination in the form of P-rich grains and P-rich deposits along all grain boundaries (GBs), LNO and LDC phases were intact without degradation in the as-fabricated electrode. However, mild to aggressive LNO phase decomposition triggered by the phosphorus poisoned GBs was observed after testing at 800 °C for 900 h. The evolution of the LNO phase decomposition was noted beginning with the exsolution of Ni into the surrounding LNO matrix and GBs, forming La-rich and Ni-rich phases correspondingly, in the LNO. Importantly, this study illustrates a detailed decomposition progress of the LNO phase at the atomic level under an SOEC operation condition, and sheds light on how to ameliorate the fabrication process of SOECs to enhance their performance and durability.
25 ENERGY STORAGE↗
Grain boundary transport through thermally grown alumina scales on NiAl
The oxidation resistance of Ni-based alloys is typically improved by additions of elements segregating to grain boundaries, contributing to reducing scale growth, and improving scale adherence. To develop a mechanistic understanding of doping, outward Al and inward O fluxes through the scale formed on β-NiAl with Ti, Y, and Ti+Y additions were characterized for oxidation at 1200°C and times up to 100h. Doped alloys exhibited varying reductions in oxidation rates and Al and O fluxes affecting scale grain morphologies. In conclusion, Ti+Y co-doping further reduced the outward Al and inward O transport compared to doping with Ti or Y alone.
36 MATERIALS SCIENCE↗
A Multi-Scale Computational Platform for Predictive Modeling of Corrosion in Al-Steel Joints (Final Report)
The research team proposed to develop innovative multi-scale models to predict corrosion and the resulting mechanical performances in aluminum-steel joints. The methods of joining considered are resistance spot welding, self-piercing riveting, and rivet-welding, all suitable for mass production applications. The multi-scale models integrate high throughput first-principle calculations based on density functional theory (DFT), high throughput calculation of phase diagrams (CALPHAD) modeling, and finite element method (FEM) simulations. These models are to be validated through laboratory experiments. Furthermore, the models are available as open source so as to enable scientists and engineers in the community to adapt and contribute to the development and application. The approaches rely on the research team’s extensive experience on the prediction of properties of individual phases at finite temperatures and variable compositions through DFT calculations, and our broad expertise on dissimilar material joining and their corrosion. The proposed computational framework enables high throughput computations for improved predictions of corrosion and the associated mechanical performance in dissimilar material joints, resulting in significant reduction in computational time needed by the current state-of-the-art methods. With the participation of researchers from three universities, an auto manufacturer, two manufacturing technology/equipment suppliers, and a software developer/vendor, the interdisciplinary research team applies the technical development on both phase-based modeling and laboratory experiments into the automobile body joining processes for validation and technology demonstration. The global cost of corrosion was estimated at about 3.4% of the global GDP in 2013. By using available corrosion control practices, it is estimated a saving between 15-35% of the cost of corrosion. In the U.S., more than $276 billion is spent repairing corrosion damage. Prediction of the corrosion and its impact on performance of the dissimilar material joints is critical for reducing the massive number of the current corrosion-based recalls for automobiles. Thus, the project goal is to develop models to enable predictive maintenance and end-of-life planning of multi-metal joints with risk of corrosion under different conditions such as exposure to high temperatures in summer and salt solutions in winter, quantified through its pH. An academia-industry consortium led by the University of Michigan and including Pennsylvania State University, University of Illinois Urbana-Champaign, University of Georgia, General Motors Company, Livermore Software Technology Corporation, and Optimal Process Technologies, LLC. created multi-scale models for prediction of corrosion in aluminum-steel joint structures such of them used in vehicle subassemblies – chassis and transmission systems. Starting from the first principle calculations, the team developed mathematical and data-driven models to predict the metallic components, which are formed during joining of two metals, for example aluminum and steel - a lightweight multilateral system which is currently used in more than 60% car bodies. These models were used for simulating chemical reactions that are happening when the joining metallic components are exposed to high temperatures and different pH values. The team was able to predict how the corrosion installs on the metallic components and how they lead to a sudden failure of components in cars. Newly developed machine learning algorithms combining Science, Technology, Engineering and Math disciplines, advanced finite element simulation and experimental validations have been integrated in a platform for prediction of the corrosion evolution and prediction the failure of joints under mechanical loadings and fatigue. Moreover, based on machine learning and inverse analysis, the team proposed solutions for designing new metallic alloys less susceptible to corrosion when joining multi-material assembles. An average of 4% error compared with experiments was achieved for the most common joints that are used in vehicle subassemblies.
36 MATERIALS SCIENCE↗
Atom probe tomography characterization of ion and neutron irradiated Alloy 800H
Alloy 800H is a high temperature and creep resistant alloy, and is considered as a candidate alloy for use in Generation IV nuclear reactor systems. To clarify the alloy's behavior under irradiation, samples were subjected to single ion irradiations up to 20 dpa at 440°C, a dual ion/He irradiation to 17 dpa at 460°C, and a neutron irradiation to 17 dpa at 385°C. The irradiated microstructures were characterized using atom probe tomography to complement previously published transmission electron microscopy studies. Additionally, after single ion irradiation, sparse fine Al and Ti clusters were observed after 1dpa, while high number densities of nanoscale Ni-Al-Ti clusters, Cr-Ti rich carbides, and Si-decorated dislocation loops developed after 10 and 20 dpa. The microstructure formed during single ion irradiation exhibited a strong depth dependence. No significant differences were observed between the single and dual ion irradiations. While Ni-Al-Ti clusters, Cr-Ti rich carbides, and Si-decorated dislocation loops were also observed after neutron irradiation, the neutron-irradiated microstructure differed from those found in the ion-irradiated samples.
36 MATERIALS SCIENCE↗
Quantifying dislocation density in Al-Cu coatings produced by cold spray deposition
This work quantifies the plastic deformation in terms of dislocation density for a series of cold sprayed Al-Cu coatings with copper contents from 2 mass% to 5 mass%. The success of the deposition and consolidation of the feedstock powders during the cold spray process rely on the occurrence of significant plastic deformation. Inert gas atomized Al-Cu alloy powders were sprayed onto substrates made of an Al-Cu-Mg-Mn alloy (AA2024) to produce dense coatings using a low pressure cold spray system with helium as the carrier gas. X-ray diffraction patterns were obtained from the Al-Cu feedstock powder material and the cold sprayed coatings using a monochromatic X-ray source, and the dislocation density was determined via an X-ray whole profile analysis. Increasing the Cu alloy content (from 2 mass% to 5 mass%) systematically increased the dislocation density in the Al-Cu coatings from (4.3 ± 0.5) × 10 14 m -2 to (7.5 ± 0.8) × 10 14 m -2 . The dislocation densities in the feedstock powders ranging from (0.4 ± 0.1) × 10 14 m -2 to (1.8 ± 0.2) × 10 14 m -2 were all lower than the dislocation densities in the corresponding coatings. The increasing deformation level in the Al-Cu coatings with Cu additions were confirmed by the classic and modified Williamson-Hall analyses of X-ray diffraction data, and peak breadth measurements from neutron diffraction data. Finally, a high density of dislocations was also observed in these coatings via electron backscatter diffraction and transmission electron microscopy.
36 MATERIALS SCIENCE↗