We are working to understand and substantially improve lithium ion battery performance, lifetime, and safety.

To accomplish that, we are developing a new methodology for performing first-principles quantum molecular dynamics (QMD) simulations at an unprecedented scale, harnessing the nation’s largest supercomputers, to understand key aspects of the chemistry and dynamics in lithium-ion (Li-ion) batteries, particularly at interfaces. By virtue of its power and generality, the new methodology and code so developed will enable corresponding breakthroughs in understanding the gamut of materials systems from liquids to solids, from metals to insulators, from molecules to nanostructures to bulk.

Li-ion batteries have revolutionized personal electronics and have the potential to do the same for transportation and electrical distribution.  In transportation in particular, a significant advance in battery performance and lifetime will allow the transition from current gasoline- and diesel-based vehicles to plug-in hybrids and all-electrics with comparable or better power, range, and cost. This, in turn, would greatly reduce the nation’s dependence on fossil fuels and carbon emissions associated with them.  An advance in safety will have significant implications for aviation as well, as the recent grounding of Boeing 787s worldwide due to Li-ion battery fires has made all too clear.

However, progress in improving the performance, lifetime, and safety of Li-ion batteries has been hindered by an incomplete understanding of the basic chemistry and dynamics.

Using supercomputers at Lawrence Livermore National Laboratory (LLNL) and Lawrence Berkeley National Laboratory (LBNL), the team will combine current state-of-the-art quantum mechanical methods and new methodology being developed to reach the length and time scales required to capture the essential dynamics of these complex, multiphase Li-ion systems. In so doing, we aim to achieve a breakthrough in the understanding of these ubiquitous electrochemical systems, and thereby pave the way for fundamental advances in these technologies.

Key limitations of current Li-ion technologies center on the formation and evolution of the solid-electrolyte interphase (SEI) layer between anode and electrolyte, a product of electrolyte decomposition. Particularly, long-term reliability is affected as the flow of Li+ into and out of the anode is impeded during the charging cycle, and also the electrical characteristics of the battery degrade as the SEI layer forms.

However, the SEI layer is critical for performance, since it helps prevent further decomposition of the electrolyte at the anode interface. In practice, a thin, stable SEI layer with high Li+ ion conductivity and low electrical conductivity is required. Any dynamic build-up or modification of the SEI film during operation must be avoided. A sudden change/malfunction of the SEI layer could pose a significant safety concern.

To date, there has not been a comprehensive theoretical understanding of the details of SEI layer formation and evolution, which has hindered progress in the design of optimal electrolyte/anode systems.

To understand these processes, we are undertaking QMD simulations of an extensive series of systems, beginning with bulk pure-electrolyte systems, proceeding to mixed electrolytes with various salts, and finally to complete liquid-on-anode simulations. The initial simulations, requiring configurations of up to 1,000 atoms, are being carried out using the massively parallel Qbox planewave code developed at LLNL. Larger simulations, requiring 10,000 atoms or more, will be carried out using the new Discontinuous Galerkin (DG) methodology being developed as a cornerstone of the present work. It is only with the advent of computational resources on the scale now available and breakthrough new quantum mechanical and numerical methods which can effectively harness them, that this research is now possible.


The primary goals of this project are:
  1. To develop and implement a new discontinuous approach to quantum mechanical materials calculations to make possible complex, realistic simulations of unprecedented size.
  2. To apply the new methodology to reach for the first time the length and time scales necessary to accurately model solid-electrolyte interfaces in lithium-ion batteries, thus paving the way for breakthroughs in understanding, device performance, and safety.
  3. To make the resulting codes available to the larger research community for application to the gamut of physical systems amenable to such large-scale quantum mechanical calculations.
To accomplish the above goals, we are applying and further developing the massively parallel Qbox planewave quantum molecular dynamics (QMD) code for liquid and small solid-liquid interface calculations within its reach (< ~2000 atoms), while developing new Discontinuous Galerkin (DG) and Pole Expansion and Selected Inversion (PEXSI) methods to reach systems of 10,000 atoms or more to model full liquid-on-anode configurations. Of particular interest in this regard is the solid-electrolyte interphase (SEI) layer, a key factor in battery performance, lifetime, and safety.

The new DG methodology achieves planewave accuracy in both total energy and forces with a basis size on the order of minimal Gaussians. The basis is strictly local, orthonormal, and systematically improvable, thus enabling high accuracy and efficient large-scale parallel implementation. These remarkable properties are made possible by releasing the constraint of continuity through the DG formulation of the Kohn-Sham equations. This permits construction of a highly efficient representation of Kohn-Sham wavefunctions in the computational domain as a straightforward union of Kohn-Sham solutions in any chosen set of subdomains. In practice, a large computational unit cell is partitioned into subdomains ("elements") containing just a few atoms each. The Kohn-Sham equations can then be solved in each of the small subdomains in parallel to form the desired highly efficient basis for the full domain. 

The new PEXSI methodology is a Fermi operator based approach which removes the O(N^3) scaling bottleneck inherent in conventional wavefunction based Kohn-Sham approaches, where N is the number of atoms, by eliminating the need to compute wavefunctions altogether; computing instead needed densities, energies, and forces directly from the Kohn-Sham Hamiltonian without diagonalization, while retaining strict systematic improvability and applicability to metals and insulators alike. In combination with atomic-orbital bases, our initial implementation has accomplished Kohn-Sham calculations on systems of over 45,000 atoms.

By combining the new DG and PEXSI approaches, we seek to reach for the first time the length and time scales necessary to accurately model complex solid-electrolyte Li-ion systems.

Having reached a sufficient level of robustness and efficiency, we have now released a parallel implementation of PEXSI (see Software page). Current work centers on the development and application of the combined DG-PEXSI methodology and code which, when complete, will be released also.