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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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16 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Binary Cation Matrix Electrolyte and Its Effect on Solid Electrolyte Interphase Suppression and Evolution of Si Anode

An unstable solid electrolyte interphase (SEI) has been recognized as one of the biggest challenges to commercializing silicon (Si) anodes for high-energy-density batteries. This work thoroughly investigates a binary cation matrix of Mg 2+ +Li + electrolyte and its role in SEI development, suppression, and evolution of a Si anode. Findings demonstrate that introducing Mg ions dramatically reduces the SEI growth before lithiation occurs, primarily due to the suppression of solvent reduction, particularly ethylene carbonate (EC) reduction. The Mg 2+ alters the Li + cation solvation environment as EC preferably participates in the oxophyllic Mg 2+ solvation sheath, thereby altering the solvent reduction process, resulting in a distinct SEI formation mechanism. The initial SEI formation before lithiation is reduced by 70% in the electrolyte with the presence of Mg 2+ cations. While the SEI continues to develop in the postlithiation, the inclusion of Mg ions results in an approximately 80% reduction in the postlithiation SEI growth. Continuous electrochemical cycling reveals that Mg 2+ plays a crucial role in stabilizing the deep-lithiated Si phases, which effectively mitigates side reactions, resulting in controlled SEI growth and stable interphase while eliminating complex Li x Si y formation. Mg ions promote the development of a notably more rigid and homogeneous SEI, characterized by a reduced dissipation (ΔD) in the Mg 2+ +Li + ion matrix compared to the solely Li + system. In conclusion, this report reveals how the Mg 2+ +Li + ion matrix affects the SEI evolution, viscoelastic properties, and electrochemical behavior at the Si interface in real time, laying the groundwork for devising strategies to enhance the performance and longevity of Si-based next-generation battery systems.

25 ENERGY STORAGE↗
DOE OSTI2025

Toward Establishing Uniqueness of Experimentally Determined Transference Numbers

The passage of current through a battery results in the development of concentration gradients in the electrolytic phase. For a fully characterized binary electrolyte, where the conductivity, salt diffusion coefficient, cation transference number, and the thermodynamic factor are known, concentration and potential gradients in the electrolytic phase can be modeled using Newman’s concentrated solution theory. We report two methods for measuring the transference number: the standard method based on electrochemical measurements ( t + , echem 0 ) and electrophoretic NMR ( t + , eNMR 0 ). The electrochemical approach requires combining measurements from multiple experiments; the equations used to determine the cation transference number and the thermodynamic factor are coupled, nonlinear algebraic equations. In the electrophoretic-NMR-based approach, however, the equations used to determine the cation transference number and the thermodynamic factor are decoupled. We find for a liquid electrolyte comprised of a lithium salt dissolved in tetraglyme, the values of the transference numbers obtained by these two methods are distinct. For example, at 30 °C, t + , echem 0 = −1.02 ± 1.11 and t + , eNMR 0 = 0.25 ± 0.04. The corresponding thermodynamic factors are also different. While the magnitude of the predicted concentration gradients based on the two sets of parameters are different, the predicted current-voltage relationships are similar.

Hickson, Darby T. (ORCID:0000000251339755)↗
DOE OSTI2025

Identifying High Ionic Conductivity Compositions of Ionic Liquid Electrolytes Using Features of the Solvation Environment

Binary mixtures of ionic liquids with molecular solvents are gaining interest in electrochemical applications due to the improvement in their performance over neat ionic liquids. Dilution with suitable molecular solvents can reduce the viscosity and facilitate faster diffusion of ions, thereby yielding substantially higher ionic conductivity than that for a pure ionic liquid. Although viscosity and diffusion coefficients typically behave as monotonic functions of concentration, ionic conductivity often passes through a peak value at an optimum molar ratio of the molecular solvent to the ionic liquid. The ionic conductivity maximum is generally explained in terms of a balance between the ease of charge transport and the concentration of the charge carriers. In this work, fluctuation in the local environment surrounding an ion is invoked as a plausible explanation for the ionic conductivity mechanism with a binary mixture of 1-ethyl-3-methylimidazolium tetrafluoroborate and ethylene glycol as an example. The magnitude of the dynamism in the local environment is captured by measuring the spatial and temporal features of the solvation environment. Standard deviation in the number of ions in the solvation environment serves as a spatial feature, while the cage correlation lifetimes for oppositely charged ions within the first solvation shell serve as a temporal feature. Large standard deviations in the cluster ion population and short cage correlation lifetimes are indicators of highly dynamic ionic environment at the molecular level and consequently yield high ionic conductivity. Such compositions were found to be in good agreement with the optimum ionic liquid mole fractions obtained through experimental measurement. Short cage correlation lifetimes enable the identification of optimum mixture compositions using simulation trajectories significantly shorter than those required to implement the Nernst–Einstein or Einstein formalisms for calculating ionic conductivity. We validated the applicability of this approach across force fields and in six ionic liquid-molecular solvent electrolytes formed with combination of cations, anions, and solvents. We offer a computationally efficient approach of screening ionic liquid-molecular solvent binary mixture electrolytes to identify molar ratios that yield high ionic conductivity.

25 ENERGY STORAGE↗
DOE OSTI2020

Onsager Transport Coefficients and Transference Numbers in Polyelectrolyte Solutions and Polymerized Ionic Liquids

Electrolytes featuring negatively charged polymers, such as nonaqueous polyelectrolyte solutions and polymerized ionic liquids, are currently under investigation as potential high cation transference number (t+) electrolytes for lithium-ion batteries. Herein, we use coarse-grained molecular dynamics simulations to characterize the Onsager transport coefficients of polyelectrolyte solutions as a function of chain length and concentration. For all the systems studied, we find that the rigorously computed transference number is substantially lower than that approximated by the ideal solution (Nernst-Einstein) equations typically used to characterize these systems due to the presence of strong anion-anion and cation-anion correlations. None of the polyelectrolyte solutions achieve t+ greater than that of the conventional binary salt electrolyte, with some solutions having negative t+. Overall, this work demonstrates that the Nernst-Einstein assumption does not provide a physically meaningful estimate of the transference number in these solutions and calls into question the expectation of polyelectrolytes to exhibit a high cation transference number.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Influence of solvents on electrochemical stability window of ionic liquid solutions

The electrochemical stability window (ESW) defines the voltage range within which an electrolyte remains stable against oxidation and reduction, serving as a key descriptor for ionic liquid (IL)-based systems. The ESWs of 15 ILs with diverse cation-anion combinations were systematically investigated, both in their neat forms and as binary mixtures with three representative solvents, i.e., propylene carbonate (PC), ethylene glycol (EG), and tetrahydrofuran (THF). Cyclic voltammetry on a glassy carbon electrode determined anodic and cathodic stability limits, revealing that ESW protection in IL-solvent mixtures strongly depends on solvent polarity, proticity, and IL compatibility. PC, with a high dielectric constant and aprotic character, broadened anodic limits and moderately stabilized cathodic limits. THF maintained compact interfacial structure, offering additional cathodic protection, whereas EG, being protic, reduced ESWs via proton-coupled electron transfer and hydrogen evolution. The solvent protection trend followed by PC > THF > EG, with bulky, hydrophobic cations ([HMIM] + , [BMPYRR] + ) and weakly coordinating anions ([NTF 2 ] - , [DCA] - , [DEP] - ) showing the highest ESW protection for 50 mol% IL in these solvents. Among the neat ILs, [EMIM][DEP], [HMIM][PF 6 ], and [BMPYRR][DCA] showed wide ESWs of ∼5.5 V. These results provide valuable insight into solvent-modulated electrochemical stability, enabling rational design of IL-based electrolytes for energy storage and electrosynthesis.

25 ENERGY STORAGE↗
DOE OSTI2024

From Bulk to Interface: Solvent Exchange Dynamics and Their Role in Ion Transport and the Interfacial Model of Rechargeable Magnesium Batteries

Multivalent battery chemistries have been explored in response to the increasing demand for high-energy rechargeable batteries utilizing sustainable resources. Solvation structures of working cations have been recognized as a key component in the design of electrolytes; however, most structure–property correlations of metal ions in organic electrolytes usually build upon favorable static solvation structures, often overlooking solvent exchange dynamics. We here report the ion solvation structures and solvent exchange rates of magnesium electrolytes in various solvents by using multimodal nuclear magnetic resonance (NMR) analysis and molecular dynamics/density functional theory (MD/DFT) calculations. These magnesium solvation structures and solvent exchange dynamics are correlated to the combined effects of several physicochemical properties of the solvents. Moreover, Mg 2+ transport and interfacial charge transfer efficiency are found to be closely correlated to the solvent exchange rate in the binary electrolytes where the solvent exchange is tunable by the fraction of diluent solvents. Our primary findings are (1) most battery-related solvents undergo ultraslow solvent exchange coordinating to Mg 2+ (with time scales ranging from 0.5 μs to 5 ms), (2) the cation transport mechanism is a mixture of vehicular and structural diffusion even at the ultraslow exchange limit (with faster solvent exchange leading to faster cation transport), and (3) an interfacial model wherein organic-rich regions facilitate desolvation and inorganic regions promote Mg 2+ transport is consistent with our NMR, electrochemistry, and cryogenic X-ray photoelectron spectroscopy (cryo-XPS) results. In conclusion, this observed ultraslow solvent exchange and its importance for ion transport and interfacial properties necessitate the judicious selection of solvents and informed design of electrolyte blends for multivalent electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2022

Spontaneous Lithiation of Binary Oxides during Epitaxial Growth on LiCoO 2

Epitaxial growth is a powerful tool for synthesizing heterostructures and integrating multiple functionalities. Interfacial mixing can readily occur at temperatures required for complete film crystallization and can significantly modify the properties of layered structures, particularly for those containing energy storage materials with smaller cations. Here we show a two-step sequence involving the growth of an epitaxial LiCoO 2 cathode layer followed by the deposition of a binary transition metal oxide (WO 3 , TiO 2 , and others) in which controlled lithiation of the binary oxide occurs. Orientation-controlled epitaxial synthesis of the model solid-state-electrolyte Li 2 WO 4 and model anode material Li 4 Ti 5 O 12 occurs as WO 3 and TiO 2 nucleate their respective host lattices and attract Li ions from the underlying cathode. The cathode layer readily provides a tunable amount of Li ions for the controlled lithiation of the subsequent layer. We demonstrate that this approach can be used for energy materials discovery and exploring different combinations of epitaxial interfaces that can serve as well-defined model systems for mechanistic studies of energy storage and conversion processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Effect of Solvent Motion on Ion Transport in Electrolytes

We use concentrated solution theory to derive an equation governing solvent velocity in a binary electrolyte when a current passes through it. This equation, in combination with the material balance equation, enables the prediction of electrolyte concentration profiles and species velocities as a function of space and time. This framework is used to predict ion velocities in Li-Li symmetric cells containing a mixture of lithium bis(trifluoromethanesulfonyl)imide and poly(ethylene oxide) (LiTFSI/PEO), for which the cation transference number relative to the solvent velocity, ${t}_{+}^{0},$ can be either positive or negative, depending on salt concentration. Accounting for the solvent motion is increasingly important at higher concentrations. Especially for negative ${t}_{+}^{0},$ if solvent velocity is set to zero, the cation velocity, based on the electrode-electrolyte interface reference frame, is pointed opposite to the current flow. However, when solvent motion is taken into account, the cation velocity, based on the same reference frame, is in the same direction as the current. This analysis demonstrates the importance of accounting for solvent velocity rigorously in seemingly simple systems such as symmetric cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Fluctuation-enhanced electric conductivity in electrolyte solutions

Significance Using fluctuating hydrodynamics, we demonstrate that thermal fluctuations contribute to charge transport in binary electrolyte solutions. We show the existence of an enhancement, or renormalization, of the electric conductivity due to the coupling between fluctuations of charge and fluid velocity. This coupling results in nontrivial corrections to the classical Poisson–Nernst–Planck equations, which are of the order of the square root of the salt concentration and therefore significant even for dilute solutions. Our calculations predict a cation–anion cross-diffusion coefficient that is in quantitative agreement with experimental measurements. Our findings have important implications for the fields of both mesoscale hydrodynamics and electrolyte transport.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Field-Driven Simulations to Probe the Impact of Ionic Correlations on Solution Transport Coefficients in Binary, Ternary, and Reciprocal Quaternary Aqueous Electrolytes

Ionic correlations play a critical role in governing transport properties of mixed-salt aqueous electrolyte solutions, yet their quantitative characterization remains challenging, particularly for multicomponent aqueous systems. Here, we develop a general nonequilibrium molecular dynamics framework to efficiently compute Onsager transport coefficients and ionic correlations in mixed-salt aqueous solutions. Using field-driven simulations, we obtain accurate Onsager matrices for LiCl/ KCl, KCl/KBr, and LiBr/KCl electrolyte solutions with significantly reduced computational cost relative to equilibrium Green−Kubo methods. The framework enables direct assessment of how attractive cation−anion and repulsive like-ion interactions contribute to conductivity and salt diffusivity across compositions. While static ion pairing exhibits strong composition dependence, dynamic ion correlations remain nearly invariant, leading to constant deviations from Nernst−Einstein predictions. These results highlight the disconnect between static ion association and dynamic transport correlations, and they establish a transferable approach for analyzing ion transport in complex electrolyte environments relevant to separation processes and electrochemical systems.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Difference between approximate and rigorously measured transference numbers in fluorinated electrolytes

The performance of binary electrolytes is governed by three transport properties: conductivity, salt diffusion coefficient, and transference number. Rigorous methods for measuring conductivity and the salt diffusion coefficient are well established and used routinely in the literature. The commonly used methods for measuring transference number are the steady-state current method, t +,id, and pulsed field gradient NMR, t +,NMR . These methods yield the transference number only if the electrolyte is ideal, i.e., the salt dissociates completely into non-interacting anions and cations. In this work, we present a complete set of ion transport properties for mixtures of a functionalized perfluoroether, dimethyl carbonate terminated perfluorinated tetraethylene ether, and lithium bis(fluorosulfonyl)imide (LiFSI). The equations used to determine these properties from experimental data are based on Newman's concentrated solution theory. The concentrated-solution-theory-based transference number, t 0 +, is negative across all salt concentrations, and it increases with increasing salt concentration. In contrast, the ideal transference number, t +,id , is positive across all salt concentrations and it decreases with salt concentration. The NMR-based transference number, t +,NMR , is approximately 0.5, independent of salt concentration. The disparity between the three transference numbers, which indicates the dominance of ion clustering, is resolved by the use of Newman's concentrated solution theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Mixed Ionic Liquid Improves Electrolyte Dynamics in Supercapacitors

Well-tailored mixtures of distinct ionic liquids can act as optimal electrolytes that extend the operating electrochemical window and improve charge storage density in supercapacitors. Here, we explore two room-temperature ionic liquids, 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (EmimTFSI) and 1-ethyl-3-methylimidazolium tetrafluoroborate (EmimBF 4 ). We study their electric double-layer behavior in the neat state and as binary mixtures on the external surfaces of onion-like carbon electrodes using quasielastic neutron scattering (QENS) and classical density functional theory techniques. Computational results reveal that a mixture with 4:1 EmimTFSI/EmimBF 4 volume ratio displaces the larger [TFSI – ] anions with smaller [BF 4 – ] ions, leading to an excess adsorption of [Emim + ] cations near the electrode surface. These findings are corroborated by the manifestation of nonuniform ion diffusivity change, complementing the description of structural modifications with changing composition, from QENS measurements. In conclusion, molecular-level understanding of ion packing near electrodes provides insight for design of ionic liquid formulations that enhance the performance of electrochemical energy storage devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Revealing EDL-driven reduction mechanisms in binary, ternary, and quaternary fluorinated electrolytes via an integrated MD–DFT–ML framework

Accurately predicting solid electrolyte interphase (SEI) formation requires explicitly resolving the electric double layer (EDL) structure, which deviates significantly from that of the bulk electrolyte. Although an established molecular dynamics (MD) and Density Functional Theory (DFT) framework can model SEI formation by evaluating reduction reactions of local clusters in the EDL, it suffers from a combinatorial computational bottleneck. To overcome this limitation, we introduce a machine-learning-accelerated simulation workflow (MD–DFT–ML), integrating a gradient-boosted regression model trained on EDL composition data to efficiently predict reduction potentials. We apply this framework to seven fluorinated electrolytes comprising fluorinated anions, a fluorinated ester solvent, two types of diluent (ion-solvating ester vs. non-solvating ether), and an FEC additive. The analysis shows that the EDL selectively accumulates cation-binding species; consequently, the non–cation-binding ether diluent rarely enters the EDL and makes minimal contributions to SEI formation. DFT calculations on statistically representative EDL clusters provide reduction potentials and fluorine-release pathways, while the ML model, which substantially reduces the DFT workload, predicts cluster reduction energies with a mean absolute error of 0.1 eV. The combined MD–DFT–ML approach also quantifies contributions from different sources to LiF formation in the SEI. This methodology establishes a generalizable route for multiscale modeling electrolyte and interphase design for next-generation electrochemical energy-storage systems.

DFT-MD-ML workflow↗
DOE OSTI2023

Polymer electrolytes based on protic ionic liquids with perfluorinated anions for safe lithium-ion batteries

Here, the quest for safe and high-performance polymer electrolytes in lithium-ion batteries (LIBs) has led researchers to explore protic ionic liquids (PILs) as potential candidates to be entrapped in polymer matrices. In this context, we present an investigation into solid polymeric systems based on poly(methyl methacrylate) (PMMA) as a host for PILs, featuring 1,8-diazabicyclo-[5,4,0]-undec-7-ene (DBU) cation paired with three different anions: bis(trifluoromethanesulfonyl)imide (TFSI – ), trifluoromethanesulfonate (TFO – ), and (trifluoromethanesulfonyl-nonafluorobutylsulfonyl)imide (IM14 – ). Additionally, we explore the lithium-doped IM14-gel-like system to broaden our understanding of these intriguing materials. Through comprehensive thermal analysis, solid-state NMR, and diffusion NMR techniques, we delve into the interactions and structural features of these binary and ternary polymeric systems. Our investigation reveals unique dynamics and ion interactions within the PMMA matrix, shedding light on the potential of these materials for advanced energy storage technologies. Particularly, we highlight the distinctive features of DBUH-IM14 and its specific interaction with the polymeric matrix and the lithium ions, underscoring its significance in advancing safer and more efficient energy storage devices.

25 ENERGY STORAGE↗
DOE OSTI2026

Ternary Phosphides Ba M 2 P 2 : Tailoring Crystal and Electronic Structures Enables Highly Efficient HER Electrocatalysis

Binary transition metal phosphides and their solid solutions have emerged as promising hydrogen evolution reaction (HER) catalysts. Although many research endeavors have adopted strategies to vary compositions to optimize catalytic performance, they mainly focus on binary structures, which represent only a small fraction of the abundant phase space of structure types among transition metal phosphides. Here, the largely unexplored class of ternary and multinary ordered phosphides in catalysis comprises two or more metals with quite different chemical nature, concealing the structure–property relationships essential for advancing catalyst design. Here, we explored phosphides crystallizing in one of the most abundant ordered intermetallic structure types, —the ThCr 2 Si 2 type, —where square nets of 3d transition metal M and P atoms are separated by layers of electropositive Ba cations. Four ternary BaM 2 P 2 (M = Fe, Fe/Cu, Fe/Ni, Ni) catalysts were synthesized and characterized. BaNi 2 P 2 showed high HER activity in acidic electrolyte, which required an overpotential, η 10 , of only 62 mV to drive current density j = –10 mA/cm 2 and high stability with a potential drop rate of 0.25 mV/h. BaNi 2 P 2 outperformed other Ni-based catalysts, such as Ni 2 P and Ni 5 P 4 . Notably, at current densities above –170 mA/cm 2 , BaNi 2 P 2 outperformed the standard Pt electrode measured under identical conditions. Electronic structure analysis revealed a volcano-type activity trend among the four BaM 2 P 2 catalysts based on their d-band center positions, highlighting the role of electropositive Ba cations in shifting the Ni-3d orbitals into an optimal position.

BaNi2P2↗
DOE OSTI2021

Investigating Ternary Li–Mg–Si Zintl Phase Formation and Evolution for Si Anodes in Li-Ion Batteries with Mg(TFSI) 2 Electrolyte Additive

Improved electrochemical performance of Si was recently reported by adding multivalent cation salts (such as Mg 2+ , Al 3+ , Ca 2+, etc.) in the electrolyte. This is achieved via the formation in an in situ manner of relatively more stable Li-M-Si ternary phases with less chemical reactivity. These phases stabilize Si anions and thus reduce side reactions with electrolytes at the surface and eventually benefit the overall electrochemistry. To understand the mechanism of ternary Zintl phase formation and its dynamics upon lithiation/delithiation, high-resolution solid-state 7 Li and 29 Si nuclear magnetic resonance (NMR) are utilized to directly probe the local Li and Si environments on Si electrodes harvested from coin and pouch cells at various states of (de)lithiation. The NMR spectra along with the electrochemical characterization reveal that lithiation of Si starts from the surface Si-O layer further confirmed by 7 Li– 29 Si cross-polarization NMR. Lithiation progresses with heterogeneous silicon clustering with Si -4 anions at high states of lithiation. At a fully lithiated state, the formation of overlithiated Si species is detected. At a low-voltage region (below 100 mV), direct evidence for Mg-ion insertion is found, postulated by two possible mechanisms: ion exchange with fully or overlithiated binary domains (Li 3.75+x Si) and/or a coinsertion with slightly underlithiated domains (similar to Li 3.55 Si). Upon delithiation, Li extraction starts from overlithiated Si domains. No evidence is found for electrochemical Mg removal. Evidence for a lithium-deficient Li y Mg 0.1 Si phase is found as a result of Li removal during charging. This investigation sheds light on the possible mechanisms of a new Si anode chemistry, which could enable the development of stable Si-based anodes for lithium-ion batteries.

25 ENERGY STORAGE↗