I am a Distinguished Staff Scientist in the INL Energy Storage & Technology department. I have been involved in battery testing and R&D for over 20 of my 35 years at INL. I am a leading figure in developmental and applied diagnostic testing and modeling of electrochemical systems, having considerable experience in designing experimental protocols for battery testing, as well as diagnostic analysis and modeling of numerous forms of battery test data. I oversee projects with emphasis on electrolytes, battery cell designs, non-equilibrium conditions, and surface-driven and interfacial phenomena.  Also, I am an established expert in the field of state-of-the-art molecular-based electrolyte models for electrochemical systems (Advanced Electrolyte Model, AEM), and have developed novel performance and lifecycle (aging) models for lithium-ion battery systems covering mechanistic aspects of kinetic limitations and performance loss over battery life (CellSage).  AEM generates more than 100 property metrics with each simulation, giving genomic-level information for electrolyte characterization. CellSage simulations perform mechanism-wise analyses of battery aging while accounting for multiple concurrent stress factors that can change over the timeline. I am well qualified to speak on issues of electrolyte transport, characterization, screening, and optimization for lithium-ion systems, wherein particular areas of expertise are highly concentrated electrolytes and  low-temperature battery performance.  During AEM development I achieved milestones in formulating mathematics and new modeling techniques that capture properties that were previously very difficult to measure and model over wide ranges of temperature and salt concentration, such as solution permittivity, conductivity, diffusivity, viscosity, surface tension, ion desolvation energy and kinetics, double-layer composition and properties, osmotic pressure, preferential ion solvation, and many others. I provided key contributions for electrolyte design to the DOE program eXtreme Fast Charge Cell Evaluation of Lithium-ion Batteries (XCEL), and am involved in integrating CellSage battery life-prediction methods with a machine learning (ML) protocol under the DOE-VTO program HD-Volts.  Recently, I accepted a leadership role in the DOE Rapid Operational Validation Initiative (ROVI) program, where my focus is accelerated battery life testing and computational life predictions. Also, under an OCED program for long-duration energy storage I am the PI for a demonstration project involving a new type of flow battery. I have a diverse background in modeling complex systems, where other previous work covered developing a methane hydrates marine basin model, a dynamic passive aeration compost model, blast wave calculations, transport model for pulsed catalytic reactors, and others. I actively collaborate within DOE labs, universities, and the private sector, and I am an advocate of domestic intellectual property, having several patents issued and pending, and under license.  AEM and CellSage tools have seen increased licensing, speaking to the growing impact of INL to meet industrial needs.

• Battery Systems: performance, achievable power, aging, state of health (capacity, conductance, power), polarization, battery second-use, advanced battery management
• Battery Materials: design and characterization of electrolytes, electrodes, and their interfaces: “molecules to materials”
• Thermodynamics: species equilibria, transport in porous media (advective, diffusive, etc.), mass continuity, reaction limits, phase equilibria
• Chemical Kinetics; Transport in Catalysts
• Applied Mathematics (numerous topics)