Novel process for recycling magnesium alloy employing refining and solid oxide membrane electrolysis

Thesis (Ph.D.)--Boston UniversityMagnesium is the least dense engineering metal, with an excellent stiffness-to-weight ratio. Magnesium recycling is important for both economic and environmental reasons. This project demonstrates feasibility of a new environmentally friendly process for recycling partially oxidized magnesium scrap to produce very pure magnesium at low cost. It combines refining and solid oxide membrane (SOM) based oxide electrolysis in the same reactor. Magnesium and its oxide are dissolved in a molten flux. This is followed by argon-assisted evaporation of dissolved magnesium, which is subsequently condensed in a separate condenser. The molten flux acts as a selective medium for magnesium dissolution, but not aluminum or iron, and therefore the magnesium collected has high purity. Potentiodynamic scans are performed to monitor the magnesium content change in the scrap as well as in solution in the flux. The SOM electrolysis is employed in the refining system to enable electrolysis of the magnesium oxide dissolved in the flux from the partially oxidized scrap. During the SOM electrolysis, oxygen anions are transported out of the flux through a yttria stabilized zirconia membrane to a liquid silver anode where they are oxidized. Simultaneously, magnesium cations are transported through the flux to a steel cathode where they are reduced. The combination of refining and SOM electrolysis yields close to 100% removal of magnesium metal from partially oxidized magnesium scrap. The magnesium recovered has a purity of 99.6w%. To produce pure oxygen it is critical to develop an inert anode current collector for use with the non-consumable liquid silver anode. In this work, an innovative inert anode current collector is successfully developed and used in SOM electrolysis experiments. The current collector employs a sintered strontium-doped lanthanum manganite (La0.8Sr0.2Mn03-δ or LSM) bar, an Inconel alloy 601 rod, and a liquid silver contact in between. SOM electrolysis experiments with the new LSM-Inconel current collector are carried out and performance comparable to the state-of-the-art SOM electrolysis for Mg production employing the non-inert anode has been demonstrated. In both refining and SOM electrolysis, magnesium solubility in the flux plays an important role. High magnesium solubility in the flux facilitates refining. On the other hand, lower magnesium solubility benefits the SOM electrolysis. The dissolution of magnesium imparts electronic conductivity to the flux. The effects of the electronic conductivity of the flux on the SOM electrolysis performance are examined in detail through experiments and modeling. Methods for mitigating the negative attributes of the electronic conductivity during SOM electrolysis are presented

Design of optimum solid oxide membrane electrolysis cells for metals production

AbstractOxide to metal conversion is one of the most energy-intensive steps in the value chain for metals production. Solid oxide membrane (SOM) electrolysis process provides a general route for directly reducing various metal oxides to their respective metals, alloys, or intermetallics. Because of its lower energy use and ability to use inert anode resulting in zero carbon emission, SOM electrolysis process emerges as a promising technology that can replace the state-of-the-art metals production processes. In this paper, a careful study of the SOM electrolysis process using equivalent DC circuit modeling is performed and correlated to the experimental results. A discussion on relative importance of each resistive element in the circuit and on possible ways of lowering the rate-limiting resistive elements provides a generic guideline for designing optimum SOM electrolysis cells

Efficient Bayesian inference using physics-informed invertible neural networks for inverse problems

In the paper, we propose a novel approach for solving Bayesian inverse problems with physics-informed invertible neural networks (PI-INN). The architecture of PI-INN consists of two sub-networks: an invertible neural network (INN) and a neural basis network (NB-Net). The invertible map between the parametric input and the INN output with the aid of NB-Net is constructed to provide a tractable estimation of the posterior distribution, which enables efficient sampling and accurate density evaluation. Furthermore, the loss function of PI-INN includes two components: a residual-based physics-informed loss term and a new independence loss term. The presented independence loss term can Gaussianize the random latent variables and ensure statistical independence between two parts of INN output by effectively utilizing the estimated density function. Several numerical experiments are presented to demonstrate the efficiency and accuracy of the proposed PI-INN, including inverse kinematics, inverse problems of the 1-d and 2-d diffusion equations, and seismic traveltime tomography

Higher-order multi-scale method for high-accuracy nonlinear thermo-mechanical simulation of heterogeneous shells

In the present work, we consider multi-scale computation and convergence for nonlinear time-dependent thermo-mechanical equations of inhomogeneous shells possessing temperature-dependent material properties and orthogonal periodic configurations. The first contribution is that a novel higher-order macro-micro coupled computational model is rigorously devised via multi-scale asymptotic technique and Taylor series approach for high-accuracy simulation of heterogeneous shells. Benefitting from the higher-order corrected terms, the higher-order multi-scale computational model keeps the conservation of local energy and momentum for nonlinear thermo-mechanical simulation. Moreover, a global error estimation with explicit rate of higher-order multi-scale solutions is first derived in the energy norm sense. Furthermore, an efficient space-time numerical algorithm with off-line and on-line stages is presented in detail. Adequate numerical experiments are conducted to confirm the competitive advantages of the presented multi-scale approach, exhibiting not only the exceptional numerical accuracy, but also the less computational expense for heterogeneous shells

Superconvergence Analysis of Finite Element Method for a Second-Type Variational Inequality

This paper studies the finite element (FE) approximation to a second-type variational inequality. The supe rclose and superconvergence results are obtained for conforming bilinear FE and nonconforming EQrot FE schemes under a reasonable regularity of the exact solution u∈H5/2(Ω), which seem to be never discovered in the previous literature. The optimal L2-norm error estimate is also derived for EQrot FE. At last, some numerical results are provided to verify the theoretical analysis

Mushroom polysaccharides with potential in anti-diabetes: Biological mechanisms, extraction, and future perspectives: A review

Diabetes mellitus (DM) is a global health threat. Searching for anti-diabetic components from natural resources is of intense interest to scientists. Mushroom polysaccharides have received growing attention in anti-diabetes fields due to their advantages in broad resources, structure diversity, and multiple bioactivities, which are considered an unlimited source of healthy active components potentially applied in functional foods and nutraceuticals. In this review, the current knowledge about the roles of oxidative stress in the pathogenesis of DM, the extraction method of mushroom polysaccharides, and their potential biological mechanisms associated with anti-diabetes, including antioxidant, hypolipidemic, anti-inflammatory, and gut microbiota modulatory actions, were summarized based on a variety of in vitro and in vivo studies, with aiming at better understanding the roles of mushroom polysaccharides in the prevention and management of DM and its complications. Finally, future perspectives including bridging the gap between the intervention of mushroom polysaccharides and the modulation of insulin signaling pathway, revealing structure-bioactivity of mushroom polysaccharides, developing synergistic foods, conducting well-controlled clinical trials that may be very helpful in discovering valuable mushroom polysaccharides and better applications of mushroom polysaccharides in diabetic control were proposed

Mitigating Electronic Current in Molten Flux for the Magnesium SOM Process

The solid oxide membrane (SOM) process has been used at 1423 K to 1473 K (1150 °C to 1200 °C) to produce magnesium metal by the direct electrolysis of magnesium oxide. MgO is dissolved in a molten MgF[subscript 2]-CaF[subscript 2] ionic flux. An oxygen-ion-conducting membrane, made from yttria-stabilized zirconia (YSZ), separates the cathode and the flux from the anode. During electrolysis, magnesium ions are reduced at the cathode, and Mg[subscript (g)] is bubbled out of the flux into a separate condenser. The flux has a small solubility for magnesium metal which imparts electronic conductivity to the flux. The electronic conductivity decreases the process current efficiency and also degrades the YSZ membrane. Operating the electrolysis cell at low total pressures is shown to be an effective method of reducing the electronic conductivity of the flux. A two steel electrode method for measuring the electronic transference number in the flux was used to quantify the fraction of electronic current in the flux before and after SOM process operation. Potentiodynamic scans, potentiostatic electrolyses, and AC impedance spectroscopy were also used to characterize the SOM process under different operating conditions.National Science Foundation (U.S.) (Grant No. 102663)United States. Dept. of Energy (Grant No. DE-EE0005547