Events

High-Throughput Simulations to Design Optimal Electrolytes for Energy Storage Devices

Free Food,
Seminar / Lecture
 
For NYU Community

Nav Nidhi Rajput

Speaker:

Nav Nidhi Rajput
Department of Chemical and Biological Engineering, Tufts University

Abstract:

Today, the pursuit of transformative gains in the performance of electrical energy storage (EES) systems and industrial technologies is intrinsically a materials problem, which requires the development of novel electrode materials, electrolytes, and architecture. Such innovations of novel electrodes as well as electrolytes for future EES systems lie inherently in the computationally driven design of materials by obtaining a fundamental understanding of the interplay between events scaling over wide spatial and temporal ranges. The composition of electrolytes has critical implications for the performance of current and future energy storage systems; from the formation and stability of the electrode-electrolyte interface to the transport properties, speciation, and viscosity of the bulk electrolyte. In this talk, I will present a high-throughput modeling approach for screening salts and solvents important to multivalent (e.g., Mg2+, Ca2+ and Zn2+), chemical transformation (e.g., Li-S), and redox flow batteries. Using the high-throughput infrastructure developed in the Electrolyte Genome project, we have screened over 25,000 molecules for their application in batteries. Here, we uncover a novel effect between concentration dependent ion pair formation and anion stability at reducing potential, e.g., at the metal anode. This work led to our knowledge, the first rational design of electrolytes for contemporary multivalent batteries through computational insight. We also employ a multi-modal approach to analyze the spectroscopic signatures of different complexes and aggregates in lithium polysulfide solution by coupling classical molecular dynamics, ab initio metadynamics calculations, and density functional theory (DFT) with experimental NMR, PFG-NMR, and XAS data. This approach allows us to gain atomic insights about clustering and lithium exchange dynamics, which is critical for the predictive understanding of polysulfide shuttling and nucleation processes that dictate the Li-S battery performance. This works shows that the combination of modeling with experimental techniques provides unprecedented insight into the origin of the electrochemical, structural, and transport properties of electrolytes, which is crucial in designing optimal electrolytes for beyond Li-ion batteries.

  • 10:30 Refreshments
  • 10:45–12:00 Talk