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At least 19 records

Correlations between Molecular Structure, Solvation Topology, and Transport Properties of Aqueous Organic Flow Battery Electrolyte Solutions

Aqueous organic redox flow batteries (AORFBs) are considered promising technologies for storing energy generated from renewable resources. However, designing organic electrolyte molecules is limited by gaps between fundamental understanding of coupling between solvation structure and dynamics, and macroscopic transport properties like viscosity. Herein, we used molecular dynamics simulations to understand correlations between ionic molecular structures, ion clustering, and transport properties in 2,3-dihydrophenazine (2,3-DHP), a promising AORFB anolyte. We show that experimentally measured viscosity can be reproduced from simulations at relevant concentrations and that the asymmetric structure of 2,3-DHP leads to unique inhomogeneity in the solvation topology. However, order parameters and metrics need to be developed for better correlations over spatiotemporal scales, with careful consideration of the inhomogeneity of organic anolyte molecules. In conclusion, we show that the increased size and asymmetry of the anolyte leads to breakdown of assumptions within methods for determining ion transport mechanisms previously developed for Li-ion batteries.

25 ENERGY STORAGE↗

Solvation Structure of Methanol-in-Salt Electrolyte Revealed by Small-Angle X-ray Scattering and Simulations

The solvation structure of water-in-salt electrolytes was thoroughly studied, and two competing structures—anion solvated structure and anion network—were well-defined in recent publications. To further reveal the solvation structure in those highly concentrated electrolytes, particularly the influence of solvent, methanol was chosen as the solvent for this proposed study. In this work, small-angle X-ray scattering, small-angle neutron scattering, Fourier-transform infrared spectroscopy, and Raman spectroscopy were utilized to obtain the global and local structural information. With the concentration increment, the anion network formed by TFSI - became the dominant structure. Meanwhile, the hydrogen bonds among methanol were interrupted by the TFSI - anion and formed a new connection with them. Further, molecular dynamic simulations with two different force fields (GAFF and OPLS-AA) are tested, and GAFF agreed with synchrotron small-angle X-ray scattering/wide-angle X-ray scattering (SAXS/WAXS) results well and provided insightful information about molecular/ion scale solvation structure. This article not only deepens the understanding of the solvation structure in highly concentrated solutions, but more importantly, it provides additional strong evidence for utilizing SAXS/WAXS to validate molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unveiling the Liquid Electrolyte Solvation Structure by Small Angle X-ray Scattering

The fundamental understanding of the liquid electrolyte (LE) solvation structure and electrode–electrolyte interface behavior will bring more in-depth thinking and revolutionary changes to the entire electrochemical energy storage field. Regardless of the variety of techniques available, the methods employed to investigate electrolyte solvation structures over a long-range are severely limited. Small-angle X-ray scattering (SAXS) is an ideal complement to Raman spectroscopy, Fourier transform infrared spectroscopy, or nuclear magnetic resonance, which offers a unique perspective from a larger scale on clusters or networks in electrolytes. Understanding the solvation structures from a few angstroms to hundreds of nanometers will undoubtedly lay a good foundation for studying the macroscopic transport properties, such as viscosity and ionic conductivity, of the LEs. Here, in this Perspective, we discuss the use of SAXS to investigate the solvation structures in different electrolyte systems, a prospect for the SAXS broader application in the electrolyte study, and some challenges that need to be solved in the SAXS application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction and Experimental Verification of Electrolyte Solvation Structure from an OMol25-Trained Interatomic Potential

A molecular-level understanding of electrolyte solvation structure and ion–ion correlations is critical to developing next-generation battery chemistries. Atomistic simulation capabilities with sufficient accuracy, speed, and transferability to deliver reliable structural insights while avoiding arduous system-specific reparameterization are thus highly desirable. Machine learning interatomic potentials (MLIPs) trained on large, chemically diverse data sets are revolutionizing computational chemistry, enabling molecular dynamics simulations of battery electrolytes with near-DFT accuracy over 10,000× faster than DFT. While previous MLIP training data sets with suitable elemental coverage for electrolytes have been based on inorganic materials, the Open Molecules 2025 (OMol25) data set provides large-scale molecular DFT MLIP training data with broad elemental coverage and specifically samples tens of millions of electrolyte configurations. Here, we integrate computational modeling with experimental validation to systematically assess the ability of large-scale MLIPs pretrained on materials data or on OMol25 to accurately resolve nanoscale structural organization and ion-solvation characteristics in Na-ion battery electrolytes across diverse physicochemical conditions and compositional regimes. We find that the OMol25-trained Universal Model of Atoms (UMA-OMol) predicts experimentally measured densities and X-ray structure factors in substantially better agreement compared to state-of-the-art models trained only on inorganic materials data. Using UMA-OMol, we further analyze systematic trends in solvation structure as a function of cation identity, anion chemistry, salt concentration, and solvent topology. We observe that increasing system temperature amplifies the heterogeneity within the solvation environment, perturbing cation–solvent interactions and promoting the formation of contact ion pairs (CIPs). Moreover, subtle variations in the solvent topology of glyme-based electrolytes cause pronounced changes in ion correlations and solvation structure. The experimental agreement and microscopic insights shown here position OMol25-trained MLIPs as a practical route to predictive, high-throughput electrolyte simulations beyond the limits of classical force fields and direct DFT molecular dynamics, serving as a powerful tool for accelerating the design of next-generation Na-ion battery electrolytes and beyond.

MLIPs↗

Generalizable, tunable control of divalent cation solvation structure via mixed anion contact ion pair formation

Multivalent batteries are a promising new technology for energy storage, but they face challenges to developing suitable electrolytes that can support reversible deposition/dissolution at the metal anode and enable compatibility with high voltage oxide cathode materials. Here, in this work, we investigate the solvation behavior of Zn 2+ , Mg 2+ , Ca 2+ and Cu 2+ in mixed anion electrolytes containing TFSI - and Cl - . Raman and nuclear magnetic resonance spectroscopies are utilized to probe the bulk solvation structure of these electrolytes and demonstrate that mixed anion contact ion pairs (CIPs) are formed in all four systems, indicating this behavior is likely general to divalent cations. Furthermore, the relative population of mixed anion CIPs can be tuned by controlling the relative ratio of TFSI : Cl, with significant CIP populations observed even at low relative fractions of Cl - . These findings imply that modifying the anion chemistry can easily adjust the solvation structure of bulk cations, which has important implications for the development of next-generation electrolytes. By understanding the factors that influence the formation of mixed anion CIPs, we can design systems that promote the formation of electrochemically-active solvation structures that can enable multivalent batteries with improved performance and lifetimes.

25 ENERGY STORAGE↗

Elucidating the Solvation Structures and Dynamics in Iron-Based TFSI – Aqueous Systems

This study investigates the solvation structures and dynamics of bis(trifluoromethanesulfonyl)imide (TFSI – )-based aqueous electrolytes, focusing on Fe(TFSI) 2 and Fe(TFSI) 3 . Using advanced characterization techniques, including small-angle X-ray scattering, molecular dynamics simulations, Raman spectroscopy, Fourier-transform infrared spectroscopy, and nuclear magnetic resonance, we elucidate how the electrolyte concentration influences ion association, solvation structures, and transport properties. Furthermore, our findings show that higher electrolyte concentrations promote the formation of contact ion pairs and anion networks, leading to reduced ion mobility and altered hydrogen-bonding dynamics. These insights provide a deeper understanding of solvation phenomena in TFSI-based electrolytes and contribute to the development of efficient and environmentally friendly iron electrodeposition processes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Fine‐Tuning Li‐Ion Solvation Structure by Enhanced Solvent‐Diluent Interactions for Long‐Cycling Lithium Metal Batteries

Achieving durable lithium (Li) metal anodes in liquid electrolytes remains challenging, primarily due to the instability of the formed solid-electrolyte interphases (SEIs). Modulating the Li-ion solvation structures is pivotal in forming a stable SEI for stabilizing Li metal anodes. Here a strategy is developed to fine-tune the Li-ion solvation structures through enhanced dipole–dipole interactions between the Li-ion-coordinated solvent and the non-Li-ion-coordinating diluent, for creating a stable SEI in the developed binary salt electrolyte. The enhanced dipole–dipole interactions weaken the coordination between Li-ions and the solvents while strengthening the interaction between Li-ions and dual anions, thereby facilitating the Li-ion transport and a robust anion-derived SEI with a distinct bilayer structure. Consequently, the developed electrolyte exhibited exceptional electrochemical performance in high energy-density Li||LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cells, with long calendar life, stable cyclability at 1 C, and reliable operation between 25 and −20 °C, and it also demonstrat remarkable cycling stability for a Li||NMC811 pouch cell with projected energy density of 402 Wh kg −1 , maintaining 80% capacity retention over 606 cycles under practical conditions.

25 ENERGY STORAGE↗

Interfacial solvation-structure regulation for stable Li metal anode by a desolvation coating technique

Rechargeable lithium (Li) metal batteries face challenges in achieving stable cycling due to the instability of the solid electrolyte interphase (SEI). The Li-ion solvation structure and its desolvation process are crucial for the formation of a stable SEI on Li metal anodes and improving Li plating/stripping kinetics. This research introduces an interfacial desolvation coating technique to actively modulate the Li-ion solvation structure at the Li metal interface and regulate the participation of the electrolyte solvent in SEI formation. Through experimental investigations conducted using a carbonate electrolyte with limited compatibility to Li metal, the optimized desolvation coating layer, composed of 12-crown-4 ether-modified silica materials, selectively displaces strongly coordinating solvents while simultaneously enriching weakly coordinating fluorinated solvents at the Li metal/electrolyte interface. This selective desolvation and enrichment effect reduce solvent participation to SEI and thus facilitate the formation of a LiF-dominant SEI with greatly reduced organic species on the Li metal surface, as conclusively verified through various characterization techniques including XPS, quantitative NMR, operando NMR, cryo-TEM, EELS, and EDS. The interfacial desolvation coating technique enables excellent rate cycling stability (i.e., 1C) of the Li metal anode and prolonged cycling life of the Li||LiCoO 2 pouch cell in the conventional carbonate electrolyte (E/C 2.6 g/Ah), with 80% capacity retention after 333 cycles.

42 ENGINEERING↗

Calcium Cosalt Addition to Alter the Cation Solvation Structure and Enhance the Ca Metal Anode Performance

Accessing the energy density and sustainability of calcium metal batteries requires mastering reversible calcium electrodeposition through electrolyte design. Several electrolytes support reversible, ambient temperature deposition but at utilization and rate too low for practical applications. These challenges stem from solvation structures characterized by either high barriers for cation desolvation or thermodynamic instability, leading to parasitic decomposition of the salt and solvent. The optimal solvation structure for the effective delivery of calcium to the electrode interface is not known. In this work, we show that adding a relatively small amount of a weakly associating calcium salt (calcium carba-closo-dodecaborate) to an otherwise strongly associated solution (calcium borohydride in tetrahydrofuran) produces a surprising population of fully solvent-coordinated Ca2+ cations in the form of solvent-separated ion pairs (SSIPs). We further demonstrate that the formation of these SSIPs beneficially impacts the kinetics and thermodynamics of calcium electrodeposition, revealing the unexpected finding that direct coordination of Ca2+ by the BH4– anion limits the electrodeposition process. These findings reveal how the competition between solvent and anion coordination to Ca2+ affects calcium deposition kinetics and cycling stability, setting the stage for a new calcium electrolyte design based on mixed anion electrolytes.

Landers, Alan T.↗

Exploring solvation structure and transport behavior for rational design of advanced electrolytes for next generation of lithium batteries

The efficacy of electrolytes significantly affects battery performance, leading to the development of several strategies to enhance them. Despite this, the understanding of solvation structure remains inadequate. It is imperative to understand the structure–property–performance relationship of electrolytes using diverse techniques. Here, this review explores the recent advancements in electrolyte design strategies for high capacity, high-voltage, wide-temperature, fast-charging, and safe applications. To begin, the current state-of-the-art electrolyte design directions are comprehensively reviewed. Subsequently, advanced techniques and computational methods used to understand the solvation structure are discussed. Additionally, the importance of high-throughput screening and advanced computation of electrolytes with the help of machine learning is emphasized. Finally, future horizons for studying electrolytes are proposed, aimed at improving battery performance and promoting their application in various fields by enhancing the microscopic understanding of electrolytes.

25 ENERGY STORAGE↗

Lithium–Sulfur Batteries Enabled by Fluorine-Free Electrolytes with a Compressed Solvation Structure

In this paper, a fluorine-free aromatic cosolvent strategy is presented to regulate electrolyte solvation chemistry in Li-S batteries with sulfurized polyacrylonitrile (SPAN) cathodes. Assisted by the Uni-ELF AI tool and experimental validation, toluene is identified as an optimal weakly solvating cosolvent. Its incorporation compresses the Li⁺ solvation sheath and induces an anion-dominated solvation structure, thereby enhancing interfacial ion transport and sulfur redox kinetics through controlled π-π interactions with polysulfides. Consequently, Li || Li symmetric cells exhibit stable cycling for over 1,000 cycles at a current density of 1 mA cm⁻². Meanwhile, Li-S cells employing high-loading SPAN cathodes retain more than 75% of their initial capacity after 250 cycles at -10 °C. Additionally, a practical pouch cell with high SPAN loading and a low electrolyte-to-SPAN ratio of 3 µL mg⁻¹ delivers an initial capacity of around 600 mAh gSPAN⁻¹, underscoring the potential of fluorine-free electrolytes for practical metal-sulfur batteries.

25 ENERGY STORAGE↗

Modulating Solvation Structure in Concentrated Aqueous Organic Redox Flow Battery Electrolyte for Solubility and Transport Enhancement via Polycomplex Ion

Aqueous organic redox flow batteries hold great promise as a technology for creating economical grid energy storage using sustainable materials. Nonetheless, the solubility limit presents a universal barrier for all redox-active organic molecules. In this paper, a new approach is proposed to surpass the solubility limit by manipulating the solvation structure with polycomplex ion additives (PIA). Using poly(3,4-ethylenedioxythiophene) polystyrenesulfonate colloids as one example, its role in dismantling the rigid supramolecular clusters within the highly concentrated 7,8-dihydroxyphenazine-2-sulfonic acid electrolyte is investigated. 1 H and 23 Na NMR spectra and molecular dynamics simulation studies demonstrate that the bipolar structure of the PIA effectively disrupts the aggregations of DHPS and Na + ion in the highly concentrated anolyte, thus rendering a more flexible solvation structure and less restrictive ion transport, leading to substantially improved battery performance of an AORFB cell. The anolyte with PIA achieved 1.6 M and 74.3 Ah L –1 anolyte energy capacity.

25 ENERGY STORAGE↗

Solvation Structure of 237 Np 4+ in a Noncomplexing Environment

Here, the solvation structure of an Np 4+ ion in an aqueous, noncomplexing and nonoxidizing environment of trifluoromethanesulfonic (triflic) acid was investigated with X-ray absorption spectroscopy (XAS) combined with ab initio molecular dynamics (AIMD) and time-dependent density functional theory (TDDFT) calculations. Np L III -edge X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) data were collected for Np 4+ in 1, 3, and 7 M triflic acid using a laboratory-scale spectrometer and separately at a synchrotron facility, producing data sets in excellent agreement. TDDFT calculations revealed a weak pre-edge feature not previously reported for Np L III -edge XANES. AIMD modeling results showed differences in the hydration shell of the Np 4+ ion at different concentrations of triflic acid; these results are supported by the experiment. EXAFS fit models to the experiment resulted in similar coordination of Np 4+ in noncomplexing aqueous media as reported in the literature for 1 M perchloric acid but, together with calculations, revealed more than one distance between Np and O atoms in 7 M triflic acid. These results imply monodentate coordination with sulfonate groups in 7 M triflic acid and suggest the possibility of proto-neptunyl species in relatively low-concentration Np 4+ acid solutions.

Boglaienko, Daria V. [Pacific Northwest National L↗

Resolving the Solvation Structure and Transport Properties of Aqueous Zinc Electrolytes from Salt-in-Water to Water-in-Salt Using Neural Network Potential

Zn Cl 2 solutions are promising electrolytes for aqueous zinc-ion batteries. Here, we report a joint computational and experimental study of the structural and dynamic properties of aqueous Zn Cl 2 electrolytes with concentrations ranging from salt-in-water to water-in-salt (WIS). By developing a neural network potential (NNP) model, we perform molecular dynamics (MD) simulations with accuracy but at much larger lengths and longer timescales. The NNP predicted structures are validated by the structure factors measured by X-ray total scattering experiments. The MD trajectories provide a comprehensive and quantitative picture of the Zn 2 + solvation shell structures. Additionally, we find that the O − H covalent bonds in water are strengthened with increasing salt concentration, thus expanding the electrochemical stability window of aqueous electrolytes. In terms of dynamic properties, the calculated and experimentally measured conductivities are in good agreement. Through the analysis of the calculated cation transference number, we propose a three-stage charge carrier transport mechanism with increasing concentration: independent ion transport, strongly correlated ion transport, and small positive charge carrier diffusion through negatively charged polymeric clusters. Our study provides fundamental atomic scale insights into the structure and transport properties of the Zn Cl 2 electrolyte that can aid the optimization and development of WIS electrolytes. Published by the American Physical Society 2025

25 ENERGY STORAGE↗

The effect of hydroxyl spacing in diols on the solvation structure, dynamics, and transport properties of choline chloride-based deep eutectic solvents

Deep eutectic solvents (DESs) are a class of liquids that offer great potential in alleviating some of the challenges present in today's long-term energy storage methods because they have physical properties that are favorable for storable electrolyte solutions. In this work, a series of glycols (ethylene glycol, 1,3-propanediol, 1,4-butanediol, and 1,5-pentanediol) were studied as potential hydrogen bond donors (HBD) with a common choline chloride (ChCl) as the hydrogen bond acceptor (HBA). The solvation dynamics of the prepared systems were studied by measuring the solvent reorganization response using femtosecond transient absorption spectroscopy (fs-TA). Conductivity, viscosity, density, ET(30) polarity, and dynamics of the prepared DESs were analyzed, with a particular interest in determining the effect of HBD chain length on these parameters. Here, classical molecular dynamics simulations were employed to investigate how the local liquid structure, solvent dynamics, and bulk solvent properties vary with changes in glycol chain length.

Conductivity↗

Deciphering the Solvation Structure of Aqueous ZnCl 2 Solutions from X-ray Absorption Spectra Using the Interpretable Graph Neural Network

Machine learning (ML) provides powerful pathways for predicting spectroscopic observables from atomic structures, but its broader impact depends on making model predictions interpretable in terms of physical and chemical principles. Here, we introduce a physics-guided graph neural network (GNN) model that predicts Zn K-edge X-ray spectroscopy (XAS) spectra of aqueous ZnCl 2 solutions. Training data are generated from ab initio XAS calculations on molecular dynamics snapshots obtained using a machine learning interatomic potential. The GNN reproduces experimental spectra across concentrations from dilute (<0.1 m) to highly concentrated (30 m, “water-in-salt”) regimes and scales efficiently to large, disordered liquid systems beyond the reach of conventional ab initio approaches. Gradient-based attribution analysis reveals that the model learns physically meaningful structure-spectrum relationships. Ligand-specific attributions reflect orbital hybridization patterns and the origin of the excitations derived from the density functional theory. Bond-length attributions recover spectral shifts consistent with multiple-scattering theory. Finally, this work bridges data-driven prediction with electronic-structure theory, establishing a general paradigm for interpretable ML that links atomic structure, electronic structure, and spectroscopic observables.

25 ENERGY STORAGE↗