Solid oxide membrane (SOM) process for ytterbium and silicon production from their oxides

The Solid oxide membrane (SOM) electrolysis is an innovative green technology that produces technologically important metals directly from their respective oxides. A yttria-stabilized zirconia (YSZ) tube, closed at one end is employed to separate the molten salt containing dissolved metal oxides from the anode inside the YSZ tube. When the applied electric potential between the cathode in the molten salt and the anode exceeds the dissociation potential of the desired metal oxides, oxygen ions in the molten salt migrate through the YSZ membrane and are oxidized at the anode while the dissolved metal cations in the flux are reduced to the desired metal at the cathode. Compared with existing metal production processes, the SOM process has many advantages such as one unit operation, less energy consumption, lower capital costs and zero carbon emission. Successful implementation of the SOM electrolysis process would provide a way to mitigate the negative environmental impact of the metal industry. Successful demonstration of producing ytterbium (Yb) and silicon (Si) directly from their respective oxides utilizing the SOM electrolysis process is presented in this dissertation. During the SOM electrolysis process, Yb2O3 was reduced to Yb metal on an inert cathode. The melting point of the supporting electrolyte (LiF-YbF3-Yb2O3) was determined by differential thermal analysis (DTA). Static stability testing confirmed that the YSZ tube was stable with the flux at operating temperature. Yb metal deposit on the cathode was confirmed by scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy (EDS). During the SOM electrolysis process for silicon production, a fluoride based flux based on BaF2, MgF2, and YF3 was engineered to serve as the liquid electrolyte for dissolving silicon dioxide. YSZ tube was used to separate the molten salt from an anode current collector in the liquid silver. Liquid tin was chosen as cathode to dissolve the reduced silicon during SOM electrolysis. After electrolysis, upon cooling, silicon crystals precipitated out from the Si-Sn liquid alloy. The presence of high-purity silicon crystals in the liquid tin cathode was confirmed by SEM/EDS. The fluoride based flux was also optimized to improve YSZ membrane stability for long-term use

Direct and inverse scattering problems for domains with multiple corners

Direct and inverse scattering problems have wide applications in geographical exploration, radar, sonar, medical imaging and non-destructive testing. In many applications, the obstacles are not smooth. Corner singularity challenges the design of a forward solver. Also, the nonlinearity and ill-posedness of the inverse problem challenge the design of an efficient, robust and accurate imaging method. This dissertation presents numerical methods for solving the direct and inverse scattering problems for domains with multiple corners. The acoustic wave is sent from the transducers, scattered by obstacles and received by the transducers. This forms the response matrix data. The goal for the direct scattering problem is to compute the response matrix data using the knowledge of the shape of the obstacles. The goal for the inverse scattering problem is to image the location and geometry of the obstacles based on the response matrix data. Both the near field and far field cases are considered. For the direct problem, the challenges of logarithmic singularity from Green\u27s functions and corner singularity are both taken care of. For the inverse problem, an efficient and robust direct imaging method similar to the Multiple Signal Classification algorithm is proposed. Multiple frequency data are combined to capture details while not losing robustness. The near field and far field response matrices are compared and their singular value patterns are compared as well. The singular value perturbation is carefully studied. Extensive numerical results demonstrate that our forward solver is capable of handling domains with multiple corners by solving a linear system with low condition numbers generated from a boundary integral equation, that our inverse problem solver is efficient, accurate and robust. It could handle response matrix data with noise

WILL THEY STILL PAY? A STUDY OF CONSUMER BEHAVIOR IN AN UNMANNED RETAIL ENVIRONMENT

An unmanned retail shelf is a new retail format made possible by the advance in mobile internet and digital payment technologies. With drastically reduced personnel costs and upfront equipment investment, unmanned retail shelves promise the potential of deeper penetration into more convenient locations for consumers. However, a lack of onsite staff can also mean that unmanned retail shelves are more vulnerable to incidences of theft as compared to traditional stores. We investigate the impact of formal and informal surveillance technology in the context of an unmanned retail environment. By investigating the impact of surveillance technology on consumer behavior outcomes such as theft rate, approach rate, and conversion rate, we hope to better understand if surveillance technologies live up to the promises of improving net economic outcomes by delivering better security

Globalisation and China's Military Modernisation: Fear not China

China has one of the most powerful military forces in the world. However, a little over 100 years ago, the Chinese military was repeatedly defeated by Western colonial powers and Japan. These defeats motivated the Chinese to make dramatic changes to their military forces

PACE: Improving Prompt with Actor-Critic Editing for Large Language Model

Large language models (LLMs) have showcased remarkable potential across various tasks by conditioning on prompts. However, the quality of different human-written prompts leads to substantial discrepancies in LLMs' performance, and improving prompts usually necessitates considerable human effort and expertise. To this end, this paper proposes Prompt with Actor-Critic Editing (PACE) for LLMs to enable automatic prompt editing. Drawing inspiration from the actor-critic algorithm in reinforcement learning, PACE leverages LLMs as the dual roles of actors and critics, conceptualizing prompt as a type of policy. PACE refines prompt, taking into account the feedback from both actors performing prompt and critics criticizing response. This process helps LLMs better align prompt to a specific task, thanks to real responses and thinking from LLMs. We conduct extensive experiments on 24 instruction induction tasks and 21 big-bench tasks. Experimental results indicate that PACE elevates the relative performance of medium/low-quality human-written prompts by up to 98\%, which has comparable performance to high-quality human-written prompts. Moreover, PACE also exhibits notable efficacy for prompt generation