Coordination-Dependent Chemical Reactivity of TFSI Anions at a Mg Metal Interface.

Charge transfer across the electrode-electrolyte interface is a highly complex and convoluted process involving diverse solvated species with varying structures and compositions. Despite recent advances in in situ and operando interfacial analysis, molecular specific reactivity of solvated species is inaccessible due to a lack of precise control over the interfacial constituents and/or an unclear understanding of their spectroscopic fingerprints. However, such molecular-specific understanding is critical to the rational design of energy-efficient solid-electrolyte interphase layers. We have employed ion soft landing, a versatile and highly controlled method, to prepare well-defined interfaces assembled with selected ions, either as solvated species or as bare ions, with distinguishing molecular precision. Equipped with precise control over interfacial composition, we employed in situ multimodal spectroscopic characterization to unravel the molecular specific reactivity of Mg solvated species comprising (i.e., bis(trifluoromethanesulfonyl)imide, TFSI-) anions and solvent molecules (i.e., dimethoxyethane, DME/G1) on a Mg metal surface relevant to multivalent Mg batteries. In situ multimodal spectroscopic characterization revealed higher reactivity of the undercoordinated solvated species [Mg-TFSI-G1]+ compared to the fully coordinated [Mg-TFSI-(G1)2]+ species or even the bare TFSI-. These results were corroborated by the computed reaction pathways and energy barriers for decomposition of the TFSI- within Mg solvated species relative to bare TFSI-. Finally, we evaluated the TFSI reactivity under electrochemical conditions using Mg(TFSI)2-DME-based phase-separated electrolytes representing different solvated constituents. Based on our multimodal study, we report a detailed understanding of TFSI- decomposition processes as part of coordinated solvated species at a Mg-metal anode that will aid the rational design of improved sustainable electrochemical energy technologies.

High-Dimensional Neural Network Potential for Liquid Electrolyte Simulations.

Liquid electrolytes are one of the most important components of Li-ion batteries, which are a critical technology of the modern world. However, we still lack the computational tools required to accurately calculate key properties of these materials (viscosity and ionic diffusivity) from first principles necessary to support improved designs. In this work, we report a machine learning-based force field for liquid electrolyte simulations, which bridges the gap between the accuracy of range-separated hybrid density functional theory and the efficiency of classical force fields. Predictions of material properties made with this force field are quantitatively accurate compared to experimental data. Our model uses the QRNN deep neural network architecture, which includes both long-range interactions and global charge equilibration. The training data set is composed solely of non-periodic density functional theory (DFT), allowing the practical use of an accurate theory (here, ωB97X-D3BJ/def2-TZVPD), which would be prohibitively expensive for generating large data sets with periodic DFT. In this report, we focus on seven common carbonates and LiPF6, but this methodology has very few assumptions and can be readily applied to any liquid electrolyte system. This provides a promising path forward for large-scale atomistic modeling of many important battery chemistries.

Interactions of CO2 Anion Radicals with Electrolyte Environments from First-Principles Simulations.

Successful transformation of carbon dioxide (CO2) into value-added products is of great interest, as it contributes in part to the circular carbon economy. Understanding chemical interactions that stabilize crucial reaction intermediates of CO2 is important, and in this contribution, we employ atom centered density matrix propagation (ADMP) molecular dynamics simulations to investigate interactions between CO2 - anion radicals with surrounding solvent molecules and electrolyte cations in both aqueous and nonaqueous environments. We show how different cations and solvents affect the stability of the CO2 - anion radical by examining its angle and distance to a coordinating cation in molecular dynamics simulations. We identify that the strength of CO2 - interactions can be tailored through choosing an appropriate cation and solvent combination. We anticipate that this fundamental understanding of cation/solvent interactions can facilitate the optimization of a chemical pathway that results from selective stabilization of a crucial reaction intermediate.

Fluorination Enables Simultaneous Improvements of a Dialkoxybenzene-Based Redoxmer for Nonaqueous Redox Flow Batteries.

Redoxmers or redox-active organic materials, are one critical component for nonaqueous redox flow batteries (RFBs), which hold high promise in enabling the time domain of the grid. While tuning redox potentials of redoxmers is a very effective way to enhance energy densities of NRFBs, those improvements often accompany accelerated kinetics of the charged species, undermining stability and cycling performance. Herein, a strategy for designing redoxmers with simultaneous improvements in redox potential and stability is proposed. Specifically, the redoxmer 1,4-di-tert-butyl-2,5-bis(2,2,2-trifluoroethoxy)benzene (ANL-C46) is developed by incorporating fluorinated substitutions into the dialkoxybenzene-based platform. Compared to the non-fluorinated analogue, ANL-C46 demonstrates not only an increased (∼0.41 V) redox potential but also much enhanced stability (1.6 times) and cyclability (4 times) evidenced by electron paramagnetic resonance kinetic study, H-cell and flow cell cycling. In fact, the cycling performance of ANL-C46 is among the best of high potential (>1.0 V vs Ag/Ag+) redoxmers ever reported. Density functional theory calculations suggest that while the introduced fluorine substitutions elevate the redox potentials, they also help to depress the decomposition reactions of the charged redoxmers, affording excellent stability. The findings represent an interesting strategy for simultaneously improving energy density and stability, which could further prompt the development of high-performance redoxmers.

Insights into Spontaneous Solid Electrolyte Interphase Formation at Magnesium Metal Anode Surface from Ab Initio Molecular Dynamics Simulations.

Spontaneous chemical reactivity at multivalent (Mg, Ca, Zn, Al) electrode surfaces is critical to solid electrolyte interphase (SEI) formation, and hence, directly affects the longevity of batteries. Here, we report an investigation of the reactivity of 0.5 M Mg(TFSI)2 in 1,2-dimethoxyethane (DME) solvent at a Mg(0001) surface using ab initio molecular dynamics (AIMD) simulations and detailed Bader charge analysis. Based on the simulations, the initial degradation reactions of the electrolyte strongly depend on the structure of the Mg(TFSI)2 species near the anode surface. At the surface, the dissociation of Mg(TFSI)2 species occurs via cleavage of the N-S bond for the solvent separated ion pair (SSIP) and via cleavage of the C-S bond for the contact ion pair (CIP) configuration. In the case of the CIP, both TFSI anions undergo spontaneous bond dissociation reactions to form atomic O, C, S, F, and N species adsorbed on the surface of the Mg anode. These products indicate that the initial SEI layer formed on the surface of the pristine Mg anode consists of a complex mixture of multiple components such as oxides, carbides, sulfides, fluorides, and nitrides. We believe that the atomic-level insights gained from these simulations will lay the groundwork for the rational design of tailored and functional interphases that are critical for the success of multivalent battery technology.

Anion Association Strength as a Unifying Descriptor for the Reversibility of Divalent Metal Deposition in Nonaqueous Electrolytes.

Developing next-generation battery chemistries that move beyond traditional Li-ion systems is critical to enabling transformative advances in electrified transportation and grid-level energy storage. In this work, we provide the first evidence for common descriptors for improved reversibility of metal plating/stripping in nonaqueous electrolytes for multivalent ion batteries. Focusing first on the specific role of chloride (Cl-) in promoting electrochemical reversibility in multivalent systems, rotating disk (RDE) and ring-disk electrode (RRDE) investigations were performed utilizing a variety of divalent cations (Mg2+, Zn2+, and Cu2+) and the bis-(trifluoromethane sulfonyl) imide (TFSI-) anion. By introducing varying concentrations of Cl-, a cooperative effect is observed between TFSI- and Cl- that yields the more reversible behavior of mixed electrolytes relative to electrolytes containing only TFSI-. This effect is shown to be general for Mg, Zn, and Cu electrodeposition, and mechanistic understanding of the role of Cl- in improving reversibility of TFSI-based electrolytes is obtained through the combination of R(R)DE experimental results and density functional theory (DFT) evaluation of the redox activity and thermodynamic stability of various TFSI- and Cl-based solution complexes of metal ions. The cooperative anion effect is further generalized to other mixed-anion systems, where systematic variations in anion association strength predicted from DFT (i.e., Cl- > OTf- ≈ TFSI- > BF4- > PF6-) yield corresponding trends in redox potentials and improvements of ≥200 mV in the reversibility of metal deposition/dissolution. These results identify anion association strength as a common descriptor for the reversibility of divalent metal anodes and suggest a set of general design principles for developing new electrolytes with improved activity and stability.

Deformation Twinning in Polycrystalline Mg Microstructures at High Strain Rates at the Atomic Scales.

Large scale molecular dynamics (MD) simulations are carried out to investigate the twinning behavior as well as the atomic scale micromechanisms of growth of tension and compression twins in polycrystalline Mg microstructures at high strain rates. A new defect characterization algorithm (extended-common neighbor analysis (E-CNA)) is developed that allows for an efficient identification of various types of twins in HCP microstructures. Unlike other local orientation analysis methods, the E-CNA method allows for atomic scale characterization of the structure of different types of twin boundaries in HCP microstructures. The MD simulations suggest that the local orientation of individual grains with the loading axis plays a critical role in determining the ability of grains to nucleate either compression twins or tension twins. The twinning behavior is observed through nucleation of a pair of planar faults and lateral growth of the twins occurs through nucleation of steps along the planar faults. The kinetics of migration of steps that determine the rate of growth of twins are investigated at the atomic scales. The twin tip velocity computed at high strain rates compares well with the experimentally reported values in the literature.

The Quasi-Coarse-Grained Dynamics Method to Unravel the Mesoscale Evolution of Defects/Damage during Shock Loading and Spall Failure of Polycrystalline Al Microstructures.

A long-standing problem in modeling of shock response of metals is the ability to model defect nucleation and evolution mechanisms during plastic deformation and failure at the mesoscales. This paper demonstrates the capability of the "quasi-coarse-grained dynamics" (QCGD) simulation method to unravel microstructural evolution of polycrystalline Al microstructures at the mesoscales. The various QCGD simulations discussed here investigate the shock response of Al microstructures comprising of grain sizes ranging from 50 nm to 3.20 µm and correspond to system sizes ranging from 150 nm to 9.6 µm, respectively. The QCGD simulations are validated by demonstrating the capability to retain atomistic characteristics of the wave propagation behavior, plastic deformation mechanisms (dislocation nucleation, dissociation/recombination behavior, dislocation interactions/reactions), evolution of damage (voids), and evolution of temperature during shock loading. The capability to unravel the mesoscale evolution of microstructure is demonstrated by investigating the effect of grain size, shock pulse and system size on the shock response and spall failure of the metal. The computed values of spall strengths predicted using the QCGD simulations agree very well with the trend predicted by MD simulations and a strain rate dependence of the spall strength is proposed that fits the experimentally available values in the literature.