Under the guidance of a supervisor, conducts research on development of mathematical models to understand the synthesis of materials used in lithium ion batteries. Synthesis of battery cathode particles occur through two steps, namely, coprecipitation and calcination. The project involves understanding and mathematically describing the physicochemical phenomena associated with the coprecipitation inside a chemical reactor and calcination at elevated temperatures. Successful candidate will develop phase field, Monte Carlo, and continuum level models at the mesoscale and macroscale level to describe the evolution of chemical composition and particle morphology during the synthesis processes. The candidate will be reporting to their supervisor in the Applied Materials Division (AMD) within the Advanced Energy Technologies Directorate (AET) inside the Argonne National Lab. The successful candidate will collaborate extensively with experimental (cathode synthesis, synchrotron analysis) and theoretical groups (atomistic simulations, DFT, AIMD) within Argonne National Lab, and other Labs and Universities in the US and across the world.

The successful candidate will be expected to understand the physicochemical processes occurring during the synthesis, develop mathematical models, implement them, run simulations, analyze data, and compare with experimental observations. The candidate will also be responsible for prepare manuscripts for submission to peer-reviewed publications, present papers at scientific meetings, and prepare reports, presentations, and papers for group meetings or meetings with sponsors.

Position Requirements

• Recently completed Ph. D Degree in Chemistry, Chemical Engineering, Mechanical Engineering, Materials Science, or Electrochemistry with 0 to 3 years of experience or equivalent.

• Skills of developing continuum level computational models form the principles of mass, momentum, and energy balance.

• General understanding of synthesis processes and the physicochemical phenomena occurring during the synthesis.

• Experience in understanding, proposing, planning, and designing experiments.

• Knowledge of processing and analyzing results.

• Skill in formulating scientific problems.

• Considerable skill in written and oral communication.

• Ability to work in a team-based environment.

• A successful candidate must have the ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork. 

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