Engineering topics

Boyle, David T.

Publications and source records attributed to Boyle, David T..

5 records

DOE OSTI2024

Failure Process During Fast Charging of Lithium Metal Batteries with Weakly Solvating Fluoroether Electrolytes

While improving the lithium metal (Li) Coulombic efficiency has been a focus for electrolyte design, the performance under high current densities is less studied yet highly relevant for practical applications. Here, we evaluate the charge-rate-dependent cycling stability using three types of weakly solvating fluoroether electrolytes. Although good cycle life was achieved in all three electrolytes under low current densities, they all exhibited a soft shorting behavior above various threshold current densities (between 2 and 5.2 mA cm –2 ). In this study, we attributed the current-dependent electrode morphology to both Li growth and residual solid electrolyte interface (rSEI) growth processes. In early cycles, Li morphology guided the formation of rSEI structures. In later cycles, the rSEI structure partially impacted Li growth. Under low current densities, the rSEI was inhomogeneous with large voids for subsequent bulky lithium growth. Under high current densities, the rSEI became more dense, which aggravated the high-surface/volume-ratio Li growth through and on the top of the rSEI. Among the three weakly solvating fluoroether electrolytes, the ones with lower ionic conductivity were observed to short within fewer cycles and at lower charge current densities. Our work suggests that fast ion transport in electrolytes may be a desirable feature for the stable operation at >1C charging in high-energy-density lithium metal batteries.

25 ENERGY STORAGE↗

DOE OSTI2023

High-entropy electrolytes for practical lithium metal batteries

Electrolyte engineering is crucial for improving battery performance, particularly for lithium metal batteries. Recent advances in electrolytes have greatly improved cyclability by enhancing electrochemical stability at the electrode interfaces, but concurrently achieving high ionic conductivity has remained challenging. Here we report an electrolyte design strategy for enhanced lithium metal batteries by increasing the molecular diversity in electrolytes, which essentially leads to high entropy electrolytes (HEEs). We find that in weakly solvating electrolytes, the entropy effect reduces ion clustering while preserving the characteristic anion-rich solvation structures, which is characterized by synchrotron-based X-ray scattering and molecular dynamics simulations. Electrolytes with smaller- sized clusters exhibit a 2-fold improvement in ionic conductivity compared to conventional weakly- solvating electrolytes, enabling stable cycling at high current densities up to 2C (6.2 mA cm -2 ) in anode- free LiNi 0.6 Mn 0.2 Co 0.2 (NMC622)||Cu pouch cells. In conclusion, the efficacy of the design strategy is verified by performance improvements in three disparate weakly solvating electrolyte systems.

25 ENERGY STORAGE↗

DOE OSTI2023

Dissolution of the Solid Electrolyte Interphase and Its Effects on Lithium Metal Anode Cyclability

At >95% Coulombic efficiencies, most of the capacity loss for Li metal anodes (LMAs) is through the formation and growth of the solid electrolyte interphase (SEI). However, the mechanism through which this happens remains unclear. One property of the SEI that directly affects its formation and growth is the SEI’s solubility in the electrolyte. Here, in this work, we systematically quantify and compare the solubility of SEIs derived from ether-based electrolytes optimized for LMAs using in-operando electrochemical quartz crystal microbalance (EQCM). A correlation among solubility, passivity, and cyclability established in this work reveals that SEI dissolution is a major contributor to the differences in passivity and electrochemical performance among battery electrolytes. Together with our EQCM, X-ray photoelectron spectroscopy (XPS), and nuclear magnetic resonance (NMR) spectroscopy results, we show that solubility depends on not only the SEI’s composition but also the properties of the electrolyte. This provides a crucial piece of information that could help minimize capacity loss due to SEI formation and growth during battery cycling and aging.

25 ENERGY STORAGE↗

DOE OSTI2023

LiH formation and its impact on Li batteries revealed by cryogenic electron microscopy

Little is known about how evolved hydrogen affects the cycling of Li batteries. Hypotheses include the formation of LiH in the solid-electrolyte interphase (SEI) and dendritic growth of LiH. Here, we discover that LiH formation in Li batteries likely follows a different pathway: Hydrogen evolved during cycling reacts to nucleate and grow LiH within already deposited Li metal, consuming active Li. We provide the evidence that LiH formed in Li batteries electrically isolates active Li from the current collector that degrades battery capacity. We detect the coexistence of Li metal and LiH also on graphite and silicon anodes, showing that LiH forms in most Li battery anode chemistries. Last, we find that LiH has its own SEI layer that is chemically and structurally distinct from the SEI on Li metal. Our results highlight the formation mechanism and chemical origins of LiH, providing critical insight into how to prevent its formation.

25 ENERGY STORAGE↗

DOE OSTI2023

Data-driven electrolyte design for lithium metal anodes

Improving Coulombic efficiency (CE) is key to the adoption of high energy density lithium metal batteries. Liquid electrolyte engineering has emerged as a promising strategy for improving the CE of lithium metal batteries, but its complexity renders the performance prediction and design of electrolytes challenging. Here, we develop machine learning (ML) models that assist and accelerate the design of high-performance electrolytes. Using the elemental composition of electrolytes as the features of our models, we apply linear regression, random forest, and bagging models to identify the critical features for predicting CE. Our models reveal that a reduction in the solvent oxygen content is critical for superior CE. We use the ML models to design electrolyte formulations with fluorine-free solvents that achieve a high CE of 99.70%. This work highlights the promise of data-driven approaches that can accelerate the design of high-performance electrolytes for lithium metal batteries.

25 ENERGY STORAGE↗