Brandon Wood (15-ERD-022)
Solid electrolytes with high ionic conductivity are crucial for developing batteries, fuel cells, and membranes with dramatically improved mechanical, thermal, and electrochemical stability. However, unlike electronic conductivity, which can be predicted from electronic structure, the physiochemical factors that regulate ionic conductivity are poorly understood. This has inhibited rational design strategies that are routinely adopted within the electrode and catalyst communities. Our objective is to use an integrated theory and experimental approach to extract the structural and property relationships that govern ionic conductivity. This will inform descriptors for use in rapid screening of new solid electrolyte materials, thereby dramatically improving the stability of energy storage and conversion devices. We are pursuing three objectives to: (1) develop a horizontal approach that uses computational "experiments" to test diffusion in known electrolytes under various conditions, (2) perform an in-depth vertical analysis of diffusive materials with high sensitivity to system perturbations, and (3) integrate ab initio and mesoscale techniques to predict conductivity under device operation.
We expect to establish an integrated approach for understanding and predicting high ionic conductivity in materials at multiple scales. Currently, the physiochemical drivers for ionic conductivity are poorly understood. Successful completion of this project will elucidate these mechanisms by isolating common features among known classes of solid electrolytes (e.g., garnets, metal oxides, solid acids, perovskites, and halides) and correlating them with ionic conductivity. The resulting descriptors could eventually be used in rapid screening of candidate electrolytes and designing materials, shortening the lead time to deployment. We will also deliver a modeling framework to couple kinetic descriptions at different scales, thereby improving conductivity predictions in real devices under nonequilibrium conditions that can be directly compared with electrochemical measurements.
Computational simulations probing ion diffusion and correlations between structural quantities and transport behavior advances Livermore's core competency in high-performance computing, simulation, and data science specific to the modeling and design of alternative energy production and storage. Because of its potential for improving the safety, reliability, and performance of many energy storage and conversion devices, this research benefits the Laboratory's strategic focus area in energy and climate security. At the same time, increasing or limiting mass transport in solids is also an essential enabling technology for other applications of interest to DOE and the nation, including the development of high-sensitivity sensors and radiation detectors for nonproliferation monitoring.
FY16 Accomplishments and Results
In FY16 we (1) initiated a new collaboration with Sandia National Laboratory and the National Institute of Standards and Technology on an emerging class of polyborate electrolytes; (2) completed the high-throughput dynamics framework for computational experiments and applied it to the polyborates (see figure); (3) discovered the fundamental mechanism for super-ionic activity in polyborates; (4) developed an analytical toolkit and began implementing new routines in the toolkit; (5) developed a model for amorphous diffusion based on combining first principles with a kinetic Monte Carlo method and compared it to experimental measurements; and (6) completed a study of the lithium indium bromide (Li3InBr6) conductivity mechanism.
Publications and Presentations
- Adelstein, N., and B. C. Wood, Electronic frustration-driven ionic conductivity in a superionic solid electrolyte. (2016). LLNL-PRES-690937.
- Heo, T. W., et al., “Defects, entropy, and the stabilization of alternative phase boundary orientations in battery electrode particles.” Adv. Energ. Mater. 6(6), 1501759 (2016). LLNL-JRNL-673242. http://doi.org/10.1002/aenm.201501759
- Kweon, K. E., et al., Unlocking hidden factors controlling conductivity in superionic solid state electrolytes. (2016). LLNL-POST-698944.
- Shea, P. T., et al., Diffusion of lithium in titanium oxide. (2016). LLNL-PRES-685844.
- Varley, J. B., et al., Assessing the ionic conductivity of Li and Na-containing borohydrides. Materials Research Society Mtg., Phoenix, AZ, Mar. 28–Apr. 1, 2016. LLNL-PRES-686881.
- Varley, J. B., et al., Assessing the ionic conductivity of Li and Na-containing borohydrides. Materials Research Society Mtg. Phoenix, AZ, Mar. 28–Apr. 1, 2016. LLNL-ABS-678289.
- Varley, J. B., et al., First-principles investigations of ionic conduction in Li and Na borohydrides. (2016). LLNL-PRES-685851.
- Varley, J. B., et al., Mechanistic insights into the alkali conduction mechanisms of closoborane solid electrolytes. Materials Research Society Mtg., Boston, MA. Nov. 27–Dec. 2, 2016. LLNL-ABS-695419.
- Wood, B. C., Ab Initio simulations of charged interface effects in graphene-based supercapacitors. American Chemical Society Mtg., San Diego, CA, 2016. LLNL-PRES-685853.
- Wood, B. C., Charge-induced phenomena in graphene-based supercapacitors from ab initio simulations. (2016). LLNL-PRES-679992.