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Jiang, Fangming

Publications and source records attributed to Jiang, Fangming.

Simulated annealing reconstruction and characterization of the three-dimensional microstructure of a LiCoO{sub 2} Lithium-ion battery cathode

We adapt the simulated annealing approach for reconstruction of the 3D microstructure of a LiCoO{sub 2} cathode from a commercial Li-ion battery. The real size distribution curve of LiCoO{sub 2} particles is applied to regulate the reconstruction process. By discretizing a 40 × 40 × 40 μm cathode volume with 8,000,000 numerical cubes, the cathode involving three individual phases: 1) LiCoO{sub 2} as active material, 2) pores or electrolyte, and 3) additives (polyvinylidene fluoride + carbon black) is reconstructed. The microstructural statistical properties required in the reconstruction process are extracted from 2D focused ion beam/scanning electron microscopy images or obtained by analyzing the powder mixture used to make the cathode. Characterization of the reconstructed cathode gives important structural and transport properties including the two-point correlation functions, volume-specific surface area between phases, tortuosity and geometrical connectivity of individual phase. - Highlights: • Simulated annealing approach is adapted for 3D reconstruction of LiCoO{sub 2} cathode. • Real size distribution of LiCoO{sub 2} particles is applied in reconstruction process. • Reconstructed cathode accords with real one at important statistical properties. • Effective electrode-characterization approaches have been established. • Extensive characterization gives important structural properties, say, tortuosity.

36 MATERIALS SCIENCE↗

Systematic parameter estimation and sensitivity analysis using a multidimensional PEMFC model coupled with DAKOTA.

Current computational models for proton exchange membrane fuel cells (PEMFCs) include a large number of parameters such as boundary conditions, material properties, and numerous parameters used in sub-models for membrane transport, two-phase flow and electrochemistry. In order to successfully use a computational PEMFC model in design and optimization, it is important to identify critical parameters under a wide variety of operating conditions, such as relative humidity, current load, temperature, etc. Moreover, when experimental data is available in the form of polarization curves or local distribution of current and reactant/product species (e.g., O2, H2O concentrations), critical parameters can be estimated in order to enable the model to better fit the data. Sensitivity analysis and parameter estimation are typically performed using manual adjustment of parameters, which is also common in parameter studies. We present work to demonstrate a systematic approach based on using a widely available toolkit developed at Sandia called DAKOTA that supports many kinds of design studies, such as sensitivity analysis as well as optimization and uncertainty quantification. In the present work, we couple a multidimensional PEMFC model (which is being developed, tested and later validated in a joint effort by a team from Penn State Univ. and Sandia National Laboratories) with DAKOTA through the mapping of model parameters to system responses. Using this interface, we demonstrate the efficiency of performing simple parameter studies as well as identifying critical parameters using sensitivity analysis. Finally, we show examples of optimization and parameter estimation using the automated capability in DAKOTA.

30 DIRECT ENERGY CONVERSION↗

Toward developing a computational capability for PEM fuel cell design and optimization.

In this paper, we report the progress made in our project recently funded by the US Department of Energy (DOE) toward developing a computational capability, which includes a two-phase, three-dimensional PEM (polymer electrolyte membrane) fuel cell model and its coupling with DAKOTA (a design and optimization toolkit developed and being enhanced by Sandia National Laboratories). We first present a brief literature survey in which the prominent/notable PEM fuel cell models developed by various researchers or groups are reviewed. Next, we describe the two-phase, three-dimensional PEM fuel cell model being developed, tested, and later validated by experimental data. Results from case studies are presented to illustrate the utility of our comprehensive, integrated cell model. The coupling between the PEM fuel cell model and DAKOTA is briefly discussed. Our efforts in this DOE-funded project are focused on developing a validated computational capability that can be employed for PEM fuel cell design and optimization.

30 DIRECT ENERGY CONVERSION↗