Fast Diagnosis of Failure Mechanisms and Lifetime Prediction of Li Metal Batteries.

Lithium (Li) metal serving as an anode has the potential to double or triple stored energies in rechargeable Li batteries. However, they typically have short cycling lifetimes due to parasitic reactions between the Li metal and electrolyte. It is critically required to develop early fault-detection methods for different failure mechanisms and quick lifetime-prediction methods to ensure rapid development. Prior efforts to determine the dominant failure mechanisms have typically required destructive cell disassembly. In this study, non-destructive diagnostic method based on rest voltages and coulombic efficiency are used to easily distinguish the different failure mechanisms-from loss of Li inventory, electrolyte depletion, and increased cell impedance-which are deeply understood and well validated by experiments and modeling. Using this new diagnostic method, the maximum lifetime of a Li metal cell can be quickly predicted from tests of corresponding anode-free cells, which is important for the screenings of electrolytes, anode stabilization, optimization of operating conditions, and rational battery design.

Response surface data for sensitivity study of industrial spray injected fluidized bed reactor.

An industrial fluidized bed reactor was designed to convert an aqueous solid laden stream into a consistent granular product. CFD simulations were run using the MFiX two-fluid model for a fluidizing bed operating at 650 °C. A set of simulations were run over a Latin-hypercube sample of five model parameters - bed particle size, bed particle density, coal particle size, spray feed flow rate, and fluidizing gas flow rate. Data from the simulations were collected on three quantities of interest - bed differential temperature, low solids velocity, and bed void fraction. The data presented here is the full set of response surfaces generated using the process Gaussian response surface model in the Dakota toolkit, as well as the table of data for coefficients of the fitted model. The fits to the five-dimensional Gaussian Process models were 0.7797, 0.8664, and 0.9440 for the temperature, velocity, and solids packing, respectively.