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Maginn, Edward J.

Publications and source records attributed to Maginn, Edward J..

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Assessing Melting and Solid–Solid Transition Properties of Choline Chloride via Molecular Dynamics Simulations

Choline chloride (ChCl) is used extensively as a hydrogen bond donor in deep eutectic solvents (DESs). However, determining its melting properties experimentally is challenging due to decomposition upon melting, leading to widely varying literature values. Accurate melting properties are crucial for understanding the solid–liquid phase behavior of ChCl-containing DESs. Here, we employ molecular dynamics simulations to compute the phase transitions of ChCl, testing a variety of atomistic force fields. We find that the results are sensitive to the choice of force field, but a melting temperature of 627 K and a melting enthalpy of 7.8 kJ/mol seem most reasonable, in good agreement with some literature values. Furthermore, we suggest these as the likely melting properties of ChCl, though the results are tentative due to limited experimental data for the liquid ChCl phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Molecular dynamics simulations of uranyl and plutonyl cations in a task-specific ionic liquid

Ionic liquids (ILs) are a unique class of solvents with potential applications in advanced separation technologies relevant to the nuclear industry. ILs are salts with low melting points and a wide range of tunable physical properties, such as viscosity, hydrophobiciy, conductivity, and liquidus range. ILs have negligible vapor pressure, are often non-flammable, and can have high thermal stability and a wide electrochemical window, making them attractive for use in separations processes relevant to the nuclear industry. Metal salts generally have a low solubility in ILs; however, by incorporating new functional groups into the IL cation or anion that promote complexation with the metal, the solubility can be greatly increased. One such task-specific ionic liquid (TSIL) is 1-carboxy-N, N, N-trimethylglycine bis(trifluoromethylsulfonyl)imide ([Hbet][Tf 2 N]). Water, which is detrimental for electrochemical separations, is a common impurity in ILs and can coordinate with actinyl cations, particularly in ILs containing only weakly coordinating components. Understanding the behavior of actinides in TSIL/water mixtures on a molecular level is vital for designing improved separations processes. Classical molecular dynamics simulations of uranyl(VI) and plutonyl(VI) in 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][Tf 2 N]) with deprotonated Hbet (betaine) and water have been performed to understand the coordination and dynamics of the actinyl cations. We find that betaine is a much stronger ligand than water and prefers to coordinate the metal in a bidentate manner. Potential of mean force simulations yield a relative free energy for betaine coordination of approximately -120 to -90 kJ/mol in mixtures with water. As the amount of betaine coordinated to the actinide increases, the diffusion coefficient of the actinyl cation decreases. Moreover, the betaine ligand is able to bridge between two metal centers, resulting in dimeric complexes with actinide–actinide distances of ~5 Å. Potential of mean force simulations show that these structures are stable, with relative free energies of up to -40 kJ/mol. The crystal structure for [(UO 2 ) 2 (bet) 6 (H 2 O) 2 ][Tf 2 N] 4 shows that the betaine bridges between two uranium atoms to form dimeric complexes similar to those found in our simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Combining High-Throughput Experiments and Active Learning to Characterize Deep Eutectic Solvents

The high tunability of deep eutectic solvents (DESs) stems from the ease of changing their precursors and relative compositions. However, measuring the physicochemical properties across large composition and temperature ranges, necessary to properly design target-specific DESs, is tedious and error-prone and represents a bottleneck in the advancement and scalability of DES-based applications. As such, active learning (AL) methodologies based on Gaussian processes (GPs) were developed in this work to minimize the experimental effort necessary to characterize DESs. Owing to its importance for large-scale applications, the reduction of DES viscosity through the addition of a low-molecular-weight solvent was explored as a case study. A high-throughput experimental screening was initially performed on nine different ternary DESs. Then, GPs were successfully trained to predict DES viscosity from its composition and temperature, showcasing the ability of these stochastic, nonparametric models to accurately describe the physicochemical properties of complex mixtures. Finally, the ability of GPs to provide estimates of their own uncertainty was leveraged through an AL framework to minimize the number of data points necessary to obtain accurate viscosity modes. This led to a significant reduction in data requirements, with many systems requiring only five independent viscosity data points to be properly described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Computing the solubility of argon and xenon in molten sodium chloride and potassium chloride salts

Molten salt reactors (MSRs) offer significant advancements in nuclear reactor safety and efficiency by operating at higher temperatures and lower pressures compared to traditional reactors. A critical aspect of MSR operation involves understanding the solubility of fission byproducts, particularly noble gases, in the molten salts used. This study employs molecular dynamics (MD) simulations to compute Henry’s law constants and enthalpies of solvation for argon and xenon in molten sodium chloride (NaCl) and potassium chloride (KCl). We developed a new pairwise potential for the noble gas and salt interactions based on first principles calculations. We then used this potential to calculate Henry’s law constants of the two gases in the molten salts, which were modeled using both a rigid ion model (RIM) and a polarizable ion model (PIM). The solubility calculations, performed using the Widom insertion method, show qualitative agreement with limited experimental data, highlighting the temperature dependence and greater solubility of both gases in KCl compared to NaCl. Additionally, free volume analysis elucidated the role of available space within the molten salts in governing solubility trends. Our findings suggest that PIM trajectories provide more reliable predictions for noble gas solubility than RIM due to their accurate density representation. Furthermore, these results enhance understanding of gas solubility in MSR environments, and the methods can be readily extended to other systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Stochastic machine learning via sigma profiles to build a digital chemical space

This work establishes a different paradigm on digital molecular spaces and their efficient navigation by exploiting sigma profiles. To do so, the remarkable capability of Gaussian processes (GPs), a type of stochastic machine learning model, to correlate and predict physicochemical properties from sigma profiles is demonstrated, outperforming state-of-the-art neural networks previously published. The amount of chemical information encoded in sigma profiles eases the learning burden of machine learning models, permitting the training of GPs on small datasets which, due to their negligible computational cost and ease of implementation, are ideal models to be combined with optimization tools such as gradient search or Bayesian optimization (BO). Gradient search is used to efficiently navigate the sigma profile digital space, quickly converging to local extrema of target physicochemical properties. While this requires the availability of pretrained GP models on existing datasets, such limitations are eliminated with the implementation of BO, which can find global extrema with a limited number of iterations. A remarkable example of this is that of BO toward boiling temperature optimization. Holding no knowledge of chemistry except for the sigma profile and boiling temperature of carbon monoxide (the worst possible initial guess), BO finds the global maximum of the available boiling temperature dataset (over 1,000 molecules encompassing more than 40 families of organic and inorganic compounds) in just 15 iterations (i.e., 15 property measurements), cementing sigma profiles as a powerful digital chemical space for molecular optimization and discovery, particularly when little to no experimental data is initially available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Impact of fluorination on Li + solvation and dynamics in ionic liquid-hydrofluoroether locally concentrated electrolytes

The thermal, physical, structural, and transport properties of ionic liquid (IL) electrolytes based on n-methyl-n-butylpyrrolidinium bis(trifluoromethanesulfonyl)imide [PYR14][TFSI] and Li-salts of lithium (nonafluorobutane)(trifluoromethanesulfonyl)imide [Li][IM14] and [Li][TFSI] (0 ≤ x Li ≤ 0.3), with addition of 1,1,2,2-tetrafluoroethyl 2,2,3,3-tetrafluoropropyl ether (TTE) (0 ≤ x TTE ≤ 0.45) were studied. While [IM14] increases glass transition, TTE improves conductivity over a wider liquidus range. Li + is solvated primarily by [TFSI] with some contribution by [IM14]. However, both 7 Li- 19 F HOESY NMR and spatial distribution functions (SDFs) derived from molecular dynamics (MD) indicate short contacts between the fluorines of TTE and Li + . This is a result of tighter anion-solvated Li + without aggregation of the Li + solvates, consistent with Raman measurements, thus confirming the existence of fluorous domains in the bulk which leads to improved fluidity and a Li + diffusivity of 1.26 x 10 –12 m 2 /s at 0 °C (x Li = 0.20) with a Li + transference of 0.16. Improved transport properties translated to a higher capacity of the TTE/IL electrolyte in a Li||LiFePO 4 half-cell with 95mAh/g at 0.1C, compared to the IL electrolyte without TTE (60 mAh/g). Furthermore, this study demonstrates the tunability of solvation and transport properties in IL electrolytes by asymmetric fluorinated anions and hydrofluoroether co-solvents for low temperature Li-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Understanding the Surprising Ionic Conductivity Maximum in Zn(TFSI) 2 Water/Acetonitrile Mixture Electrolytes

Aqueous electrolytes composed of 0.1 M zinc bis-(trifluoromethyl-sulfonyl)-imide (Zn-(TFSI) 2 ) and acetonitrile (ACN) were studied using combined experimental and simulation techniques. The electrolyte was found to be electrochemically stable when the ACN V% is higher than 74.4. In addition, it was found that the ionic conductivity of the mixed solvent electrolytes changes as a function of ACN composition, and a maximum was observed at 91.7 V% of ACN although the salt concentration is the same. This behavior was qualitatively reproduced by molecular dynamics (MD) simulations. Detailed analyses based on experiments and MD simulations show that at high ACN composition the water network existing in the high water composition solutions breaks. As a result, the screening effect of the solvent weakens and the correlation among ions increases, which causes a decrease in ionic conductivity at high ACN V%. Furthermore, this study provides a fundamental understanding of this complex mixed solvent electrolyte system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Revisiting the pseudo-supercritical path method: An improved formulation for the alchemical calculation of solid–liquid coexistence

Alchemical free energy calculations via molecular dynamics have been applied to obtain thermodynamic properties related to solid–liquid equilibrium conditions, such as melting points. In recent years, the pseudo-supercritical path (PSCP) method has proved to be an important approach to melting point prediction due to its flexibility and applicability. In the present work, we propose improvements to the PSCP alchemical cycle to make it more compact and efficient through a concerted evaluation of different potential energies. The multistate Bennett acceptance ratio (MBAR) estimator was applied at all stages of the new cycle to provide greater accuracy and uniformity, which is essential concerning uncertainty calculations. In particular, for the multistate expansion stage from solid to liquid, we employed the MBAR estimator with a reduced energy function that allows affine transformations of coordinates. Free energy and mean derivative profiles were calculated at different cycle stages for argon, triazole, propenal, and the ionic liquid 1-ethyl-3-methyl-imidazolium hexafluorophosphate. Comparisons showed a better performance of the proposed method than the original PSCP cycle for systems with higher complexity, especially the ionic liquid. Furthermore, a detailed study of the expansion stage revealed that remapping the centers of mass of the molecules or ions is preferable to remapping the coordinates of each atom, yielding better overlap between adjacent states and improving the accuracy of the methodology.

25 ENERGY STORAGE↗
DOE OSTI2023

Activity coefficient acquisition with thermodynamics–informed active learning for phase diagram construction

This work explores the use of thermodynamics-informed Gaussian processes (GPs) and active learning (AL) to model activity coefficients and construct phase diagrams. Relying on synthetic data generated from an excess Gibbs energy model, GPs were found to accurately describe the activity coefficients of several binary mixtures across large composition and temperature ranges. Moreover, GPs could estimate their own uncertainty and identify composition/temperature regions where activity coefficient data provide the most information to the models. This was leveraged to build AL algorithms targeted at modeling phase equilibria. In many cases, a single active-learning-acquired data point was sufficient to describe the phase diagrams studied. Lastly, the ability of AL to greatly reduce the amount of data needed to obtain accurate models was further verified on experimental case studies, namely individual ion activity coefficients, the solid–liquid and vapor–liquid equilibrium of deep eutectic solvents, and phase equilibria in ternary mixtures.

25 ENERGY STORAGE↗
DOE OSTI2022

Lithium Solvation and Mobility in Ionic Liquid Electrolytes with Asymmetric Sulfonyl-Cyano Anion

The solvation structure and transport properties of Li + in ionic liquid (IL) electrolytes based on n-methyl-n-butylpyrrolidinium cyano(trifluoromethanesulfonyl)imide [PYR 14 ][CTFSI] and [Li][CTFSI] (0 ≤ x Li ≤ 0.7) were studied by Raman and Nuclear Magnetic Resonance (NMR) diffusometry, and molecular dynamics (MD) simulations. At x Li < 0.3, Li + coordination is dominated by the cyano group. As x Li is increased, free cyano-sites become limited, resulting in increased coordination via the sulfonyl group. Here, the 1:1 mixture of the symmetric anions bis(trifluoromethanesulfonyl)imide ([TFSI]) and dicyanamide ([DCA]) results in similar physical properties as the IL with [CTFSI]. However, anion asymmetry is shown to increase Li-salt solubility and promote Li+ transference. The lifetimes of Li + -cyano coordination for [CTFSI] are calculated to be shorter than those for [DCA], indicating that the competition from the sulfonyl group weakens its solvation with Li + . This resulted in higher Li + transference for the electrolyte with [CTFSI]. In relation to the utility of these electrolytes in energy storage, the Li–LiFePO 4 half cells assembled with IL electrolyte (x Li = 0.3, 0.5, and 0.7) demonstrated a nominal capacity of 140 mAh/g at 0.1C rate and 90 °C where the cell with x Li = 0.7 IL electrolyte demonstrated 61% capacity retention after 100 cycles and superior rate capability owing to increased electrochemical stability.

25 ENERGY STORAGE↗
DOE OSTI2022

Exchange-Mediated Transport in Battery Electrolytes: Ultrafast or Ultraslow?

Understanding the mechanisms of charge transport in batteries is important for the rational design of new electrolyte formulations. Persistent questions about ion transport mechanisms in battery electrolytes are often framed in terms of vehicular diffusion by persistent ion–solvent complexes versus structural diffusion through the breaking and reformation of ion–solvent contacts, i.e., solvent exchange events. Ultrafast two-dimensional (2D) IR spectroscopy can probe exchange processes directly via the evolution of the cross-peaks on picosecond time scales. However, vibrational energy transfer in the absence of solvent exchange gives rise to the same spectral signatures, hiding the desired processes. Here we employ 2D IR on solvent resonances of a mixture of acetonitrile isotopologues to differentiate chemical exchange and energy-transfer dynamics in a comprehensive series of Li + , Mg 2+ , Zn 2+ , Ca 2+ , and Ba 2+ bis(trifluoromethylsulfonyl)imide electrolytes from the dilute to the superconcentrated regime. No exchange phenomena occur within at least 100 ps, regardless of the ion identity, salt concentration, and presence of water. All of the observed spectral dynamics originate from the intermolecular energy transfer. These results place the lower experimental boundary on the ion–solvent residence times to several hundred picoseconds, much slower than previously suggested. With the help of MD simulations and conductivity measurements on the Li + and Zn 2+ systems, we discuss these results as a continuum of vehicular and structural modalities that vary with concentration and emphasize the importance of collective electrolyte motions to ion transport. These results hold broadly applicable to many battery-relevant ions and solvents.

25 ENERGY STORAGE↗
DOE OSTI2022

Structure of water-in-salt and water-in-bisalt electrolytes

We report a systematic diffraction study of two “water-in-salt” electrolytes and a “water-in-bisalt” electrolyte combining high-energy X-ray diffraction (HEXRD) with polarized and unpolarized neutron diffraction (ND) on both H 2 O and D 2 O solutions. The measurements provide three independent combinations of correlations between the different pairs of atom types that reveal the short- and intermediate-range order in considerable detail. The ND interference functions show pronounced peaks around a scattering vector Q ~ 0.5 Å -1 that change dramatically with composition, indicating significant rearrangements of the water network on a length scale around 12 Å. The experimental results are compared with two sets of Molecular Dynamics (MD) simulations, one including polarization effects and the other based on a non-polarizable force field. The two simulations reproduce the general shapes of the experimental structure factors and their changes with concentration, but differ in many detailed respects, suggesting ways in which their force fields might be modified to better represent the actual systems.

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