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Viswanathan, Venkatasubramanian (ORCID:0000000310605495)

Publications and source records attributed to Viswanathan, Venkatasubramanian (ORCID:0000000310605495).

6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Differentiable physics-enabled closure modeling for Burgers’ turbulence

Abstract Data-driven turbulence modeling is experiencing a surge in interest following algorithmic and hardware developments in the data sciences. We discuss an approach using the differentiable physics paradigm that combines known physics with machine learning to develop closure models for Burgers’ turbulence. We consider the one-dimensional Burgers system as a prototypical test problem for modeling the unresolved terms in advection-dominated turbulence problems. We train a series of models that incorporate varying degrees of physical assumptions on an a posteriori loss function to test the efficacy of models across a range of system parameters, including viscosity, time, and grid resolution. We find that constraining models with inductive biases in the form of partial differential equations that contain known physics or existing closure approaches produces highly data-efficient, accurate, and generalizable models, outperforming state-of-the-art baselines. Addition of structure in the form of physics information also brings a level of interpretability to the models, potentially offering a stepping stone to the future of closure modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Magnetic Compton Scattering Study of Li-Rich Battery Materials

The redox process in a lithium-ion battery occurs when a conduction electron from the lithium anode is transferred to the redox orbital of the cathode. Understanding the nature of orbitals involved in anionic as well as cationic redox reactions is important for improving the capacity and energy density of Li-ion batteries. In this connection, we have obtained magnetic Compton profiles (MCPs) from the Li-rich cation-disordered rock-salt compound LixTi0.4Mn0.4O2 (LTMO). The MCPs, which involved the scattering of circularly polarized hard X-rays, are given by the momentum density of all the unpaired spins in the material. The net magnetic moment in the ground state can be extracted from the area under the MCP, along with a SQUID measurement. Our analysis gives insight into the role of Mn 3d magnetic electrons and O 2p holes in the magnetic redox properties of LTMO.

Suzuki, Kosuke (ORCID:0000000317110604)↗
DOE OSTI2020

Marcus–Hush–Chidsey kinetics at electrode–electrolyte interfaces

Electrochemical kinetics at electrode–electrolyte interfaces limit the performance of devices including fuel cells and batteries. While the importance of moving beyond Butler–Volmer kinetics and incorporating the effect of electronic density of states of the electrode has been recognized, a unified framework that incorporates these aspects directly into electrochemical performance models is still lacking. In this work, we explicitly account for the density functional theory-calculated density of states numerically in calculating electrochemical reaction rates for a variety of electrode–electrolyte interfaces. We first show the utility of this for two cases related to Li metal electrodeposition and stripping on a Li surface and a Cu surface (anode-free configuration). The deviation in reaction rates is minor for cases with flat densities of states such as Li, but is significant for Cu due to nondispersive d-bands creating large variation. Finally, we consider a semiconducting case of a solid-electrolyte interphase consisting of LiF and Li2CO3 and note the importance of the Fermi level at the interface pinned by the redox reaction occurring there. We identify the asymmetry in reaction rates as a function of discharge/charge naturally within this approach.

Kurchin, Rachel (ORCID:0000000221474809)↗
DOE OSTI2020

Machine learning enabled discovery of application dependent design principles for two-dimensional materials

Abstract The unique electronic and mechanical properties of two-dimensional (2D) materials make them promising next-generation candidates for a variety of applications. Large-scale searches for high-performing 2D materials are limited to calculating descriptors with computationally demanding first-principles density functional theory. In this work, we alleviate this issue by extending and generalizing crystal graph convolutional neural networks to systems with planar periodicity and train an ensemble of models to predict thermodynamic, mechanical and electronic properties. We carry out a screening of nearly 45,000 structures for two separate applications: mechanical strength and photovoltaics. By collecting statistics of the screened candidates, we investigate structural and compositional design principles that impact the properties of the structures surveyed. Our approach recovers some well-accepted design rules: hybrid organic-inorganic perovskites with lead and tin tend to be good candidates for solar cell applications and titanium based MXenes usually have high stiffness coefficients. Interestingly, other members of the group 4 elements also contribute to increasing the mechanical strength of MXenes. For all-inorganic perovskites, we discover some compositions that have not been deeply studied in the field of photovoltaics and thus open up paths for further investigation. We open-source the code-base to spur further development in this space.

Venturi, Victor (ORCID:0000000156727549)↗
DOE OSTI2020

Engineering Solid Electrolyte Interphase Composition by Assessing Decomposition Pathways of Fluorinated Organic Solvents in Lithium Metal Batteries

Studies have shown fluorinated electrolyte solvents can form desirable solid electrolyte interphase (SEI) in lithium metal batteries. In this study, we develop a detailed mechanistic understanding of two high performing electrolytes, Fluoroethylene Carbonate (FEC) and Difluoroethylene Carbonate (DFEC) to demonstrate minimal structural variations can lead to different decomposition products, and thereby the nature of the SEI. Using density functional theory (DFT) calculations, we find different initial bond-breaking mechanisms between FEC and DFEC. We develop free energy diagrams for the decomposition pathways including both electrochemical and chemical steps. Using the computational Li electrode, we identify the largest limiting potential of 1.77 V for FEC decomposition, associated with the formation of lithium fluoride, lithium oxide and FEC oligomers, and 1.53 V for DFEC, which correspond to the formation of polymerized vinylene carbonate and lithium fluoride. We suggest the formation of oligomers in the case of FEC instead of long polymers may lead to better SEI compactness. We also demonstrate the SEI components of FEC and DFEC are not stable on typical cathode voltage (3.87 V). This study presents a unified electrocatalytic perspective on SEI formation and decomposition.

25 ENERGY STORAGE↗