Lithium–oxygen (Li–O2) batteries offer considerably higher gravimetric energy density than commercial Li-ion batteries (up to three times) but suffer from poor power, cycle life, and round-trip efficiency. Tuning the thermodynamics and pathway of the oxygen reduction reaction (ORR) in aprotic electrolytes can be used to enhance the Li–O2 battery rate and discharge capacity. In this work, we present a systematic study on the role of the solvent and anion on the thermodynamics and kinetics of Li+-ORR, from which we propose a unified descriptor for its pathway and kinetics. First, by thoroughly characterizing the solvation environment of Li+ ions using Raman spectroscopy, 7Li NMR, ionic conductivity, and viscosity measurements, we observe increasing Li+–anion interactions with increasing anion DN in low DN solvents such as 1,2-dimethoxyethane and acetonitrile but minimal Li+–anion interactions in the higher DN dimethyl sulfoxide. Next, by determining the electrolyte-dependent Li+/Li, TBA+,O2/TBA+–O2 –, and Li+,O2/Li+–O2 – redox potentials versus the solvent-invariant Me10Fc reference potential, we show that stronger combined solvation of Li+ and O2 – ions leads to weaker Li+–O2 ‑ coupling. Finally, using rotating ring disk electrode measurements, we show that weaker Li+–O2 – coupling in electrolytes with strong combined solvation leads to an increased generation of soluble Li+–O2 –-type species and faster overall kinetics during Li+-ORR.

Using dissipative particle dynamics (DPD) simulations, we model the interaction between nanoscopic lipid vesicles and Janus nanoparticles in the presence of an imposed flow. Both the vesicle and Janus nanoparticles are localized on a hydrophilic substrate and immersed in a hydrophilic solution. The fluid-driven vesicle successfully picks up Janus particles on the substrate and transports these particles as cargo along the surface. The vesicle can carry up to four particles as its payload. Hence, the vesicles can act as nanoscopic "vacuum cleaners", collecting nanoscopic debris localized on the floors of the fluidic devices. Importantly, these studies reveal how an imposed flow can facilitate the incorporation of nanoparticles into nanoscale vesicles. With the introduction of a "sticky" domain on the substrate, the vesicles can also robustly drop off and deposit the particles on the surface. The controlled pickup and delivery of nanoparticles via lipid vesicles can play an important step in the bottom-up assembly of these nanoparticles within small-scale fluidic devices.

We examine the effect of equilibration methodology and sampling on ab initio molecular dynamics (AIMD) simulations of systems of common solvents and salts found in lithium-oxygen batteries. We compare two equilibration methods: (1) using an AIMD temperature ramp and (2) using a classical MD simulation followed by a short AIMD simulation both at the target simulation temperature of 300 K. We also compare two different classical all-atom force fields: PCFF+ and OPLS. By comparing the simulated association/dissociation behavior of lithium salts in different solvents with the experimental behavior, we find that equilibration with the classical force field that produces more physically accurate behavior in the classical MD simulations, namely, OPLS, also results in more physically accurate behavior in the AIMD runs compared to equilibration with PCFF+ or with the AIMD temperature ramp. Equilibration with OPLS outperforms even the pure AIMD equilibration because the classical MD equilibration is much longer than the AIMD equilibration (nanosecond vs picosecond timescales). These longer classical simulations allow the systems to find a more physically accurate initial configuration, and in the short simulation times available for the AIMD production runs, the initial configuration has a large impact on the system behavior. We also demonstrate the importance of averaging coordination number over multiple starting configurations and Li+ ions, as the majority of Li+ ions do not undergo a single association or dissociation event even in an ∼40 ps long simulation and thus do not sample a statistically significant portion of the phase space. These results show the importance of both equilibration method and sufficient independent sampling for extracting experimentally relevant quantities from AIMD simulations.

Zirconia (zirconium dioxide) and hafnia (hafnium dioxide) are binary oxides used in a range of applications. Because zirconium and hafnium are chemically equivalent, they have three similar polymorphs, and it is important to understand the properties and energetics of these polymorphs. However, while density functional theory calculations can get the correct energetic ordering, the energy differences between polymorphs depend very much on the specific density functional theory approach, as do other quantities such as lattice constants and bulk modulus. We have used highly accurate quantum Monte Carlo simulations to model the three zirconia and hafnia polymorphs. We compare our results for structural parameters, bulk modulus, and cohesive energy with results obtained from density functional theory calculations. We also discuss comparisons of our results with existing experimental data, in particular for structural parameters where extrapolation to zero temperature can be attempted. We hope our results of structural parameters as well as for cohesive energy and bulk modulus can serve as benchmarks for density-functional theory based calculations and as a guidance for future experiments.

Using dissipative particle dynamics (DPD) simulations, we model the interaction between nanoscopic lipid vesicles and Janus nanoparticles localized on an adhesive substrate in the presence of an imposed flow. The system is immersed in a hydrophilic solution, and the hydrophilic substrate contains nanoscopic trenches, which are either step- or wedge-shaped. The fluid-driven vesicle successfully picks up Janus particles on the substrate, transports these particles as cargo along the surface, and then drops off the particles into the trenches. For Janus particles with a relatively large hydrophobic region, lipids from the bilayer membrane become detached from the vesicle and bound to the hydrophobic domain of the deposited particle. While the detachment of these lipids rips the vesicle, it provides a coating that effectively shields the hydrophobic portion of the nanoparticle from the outer solution. After the particle has been dropped off, the torn vesicle undergoes structural rearrangement, reforming into a closed structure that resembles its original shape. In effect, the vesicle displays pronounced adaptive behavior, shedding lipids to form a protective coating around the particle and undergoing a self-healing process after the particle has been deposited. This responsive, adaptive behavior is observed in cases involving both the step- and wedge-shaped trenches, but the step trench is more effective at inducing particle drop off. The results reveal that the introduction of grooves or trenches into a hydrophilic surface can facilitate the targeted delivery of amphiphilic particles by self-healing vesicles, which could be used for successive delivery events.

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