by Theresa Pepin
In the brave new world of scientific computation and simulation, it can often seem as though the experiment never ends. Experiments feed data to computation, which, in turn, offers back structure and analysis based upon required parameters. The resulting models can be compared with laboratory findings to validate and fine-tune continuing experimentation—all toward the goal of rapidly optimizing performance and accelerating progress.
David Keffer has become well versed in this multiscale modeling process and now his JDRD team applies their high-performance computing parallelized tool kit to understand the fundamental relationship between nanostructure and lithium-ion conductivity in lignin-based carbon fiber (LCF) anodes.
The challenge for modelers in exploring structure-property relationships from materials is to effectively employ multiscale modeling techniques incorporating four scales of “description”—the quantum scale in which electron distributions are important; the molecular scale in which the distribution of atoms and molecules is important; the mesoscale in which the larger clusters of molecules are important; and macro-scale in which the material is treated as a continuum.
By extension from previous work on proton transport in fuel cell membranes, Keffer’s JDRD study employs an integrated suite of multiscale modeling tools. The demonstrated ability to integrate all four levels of modeling into a coherent, dynamic rendering of the structure-property relationship is a unique hallmark of Keffer’s Computational Materials Research Group.
So why does this research matter? If a new lignin-based carbon anode can be developed for lithium-ion battery packs, many advantages accrue: the new material will enable a complete redesign of the anode with superior capabilities that can be “tuned”—that is, tailored—to greatly improve electrochemical performance; cost, weight, and volume of the fabricated battery are substantially reduced; and lignin constitutes a renewable resource available for extraction in abundance from biomass in paper mills and future bio-refineries.
In the joint collaboration, Keffer’s JDRD team, including post-doc Qifei Wang and graduate student Nick McNutt, provides high-performance, multiscale computational modeling in support of the experimental synthesis and characterization work on novel battery electrode materials from the corresponding LDRD, led by Orlando Rios of the Materials Processing Group at ORNL. Based upon data and parameter specifications from the experimental team, the JDRD simulations provide the experimental LDRD group with molecular-level guidance in their task of synthesis of tailored nanostructures in the LCF anodes; and the subject/materials expertise of the LDRD team gives the JDRD team the opportunity to expand its range of applications into the strategically critical area of batteries.
Combining theory and experiment in this highly effective and synergistic package will allow both teams to more aggressively compete in applying for larger grants in energy storage initiatives.
See example animations and interactive structures created from molecular dynamics simulation and quantum calculations.
Lignin-based high performance Li-Ion anode materials synthesized from low-cost renewable resources
David Keffer, UT Department of Chemical and Biomolecular Engineering
Lignin-based High-Performance Li-Ion Anode Materials Synthesized from Low-Cost Renewable Resources
Orlando Rios, ORNL Materials Science and Technology Division