How Solvation Alters the Thermodynamics of Asymmetric Bond-Breaking: Quantum Simulation of NaK + in Liquid Tetrahydrofuran
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
SEARCH · Engineering Papers
Results for “solvates”
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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The Influence of Charge Correlation and Ion Solvation on the Phase Behavior of Single-Ion Conducting Polymer Blend Electrolytes Using SAXS/SANS
Single-ion conducting polymer blends (SICPBs) have demonstrated exceptional electrochemical performance as solid-state battery electrolytes; however, their nanoscale morphology and thermodynamic behavior remain unexplored. In this work, we investigate blends composed of deuterated poly(ethylene oxide) and poly[lithium sulfonyl(trifluoromethane sulfonyl)imide methacrylate], dPEO/P(LiMTFSI), and report the first experimental study of the nanostructures of charge-neutral polymer blends using small-angle neutron scattering (SANS) and small-angle X-ray scattering (SAXS). Despite the macroscopic miscibility indicated by a single glass-transition temperature, SANS and SAXS results reveal disordered, charge-correlated nanostructures that are strongly influenced by blend composition and temperature. At low concentrations of charge polymer, the scattering is dominated by concentration fluctuations, and the random phase approximation is applied to extract values of the Flory–Huggins interaction parameter, χ SC . At higher charged polymer content, concentration fluctuations are suppressed, and a correlation model is used to characterize the nanostructures of the charge correlations. We find that the structures of the charge correlations are highly dependent on blend composition─consistent with predictions from Sing’s self-consistent field theory-liquid state models. Understanding these features is essential for uncovering the ion transport mechanism that leads to improved electrochemical performance previously reported in SICPB systems.
25 ENERGY STORAGE↗
Solvation Environment and Interface Dynamics of Li 2 B 12 H 12 and Li 2 B 12 F 12 Electrolytes Uncovered by Theory and Operando Optical and FTIR Spectroelectrochemistry
In this work, we evaluated two closo-borate salts (Li 2 B 12 H 12 and Li 2 B 12 F 12 ) in propylene carbonate from theoretical and experimental perspectives to understand how the coordination environment influences their spectroscopic and electrochemical properties. The coordination environments of the closo-borate salts were modeled via density functional theory (DFT) and molecular dynamics (MD). Vibrational spectra calculated from the predicted coordination environments are in agreement with experimentally measured steady-state FTIR data. This theoretical investigation also suggested that Li 2 B 12 F 12 would possess a higher ionic conductivity than Li 2 B 12 H 12 , which was corroborated experimentally. Additionally, an electrochemical cell was designed and fabricated that enabled operando optical and FTIR spectroelectrochemical (OP-IR-SEC) measurements. This allowed for the simultaneous measurement of the relative changes of species at a lithium electrode-liquid electrolyte interface and the visualization of lithium plating at the electrode surface. This technique could provide new chemical insights and potentially link optical changes at the electrode–electrolyte interface to specific chemical species in similar electrochemical systems. The Li 2 B 12 F 12 electrolyte was found to have a higher thermal stability, which may find utility in applications for batteries that are subject to high-temperature conditions.
36 MATERIALS SCIENCE↗
High-entropy solvation chemistry towards affordable and practical Ah-level zinc metal battery
Not provided.
Science & Technology - Other Topics↗
Solvation and oxidation effects on the crystal structure and morphology of tetraoxolene-based materials
Owing to their rich redox behavior and strong metal chelating ability, tetraoxolene ligands have been established as one of the foundational building blocks for multifunctional metal–organic materials. Here, we show how simple and often overlooked synthetic parameters can be used to control the structures of transition metal and lanthanide-based metal–tetraoxolene materials across multiple length scales. Through the synthesis of twelve new compounds, we provide a comprehensive survey detailing how the choice of solvent, initial ligand redox state, and in situ oxidant impact the local coordination geometry and chain architecture, as well as the crystal size and shape (e.g., rods vs. platelets). This work represents an important step towards the synthesis of new metal–tetraoxolene materials with predictable architectures and, therefore, targeted functionality.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
2D nanoconfinement distorts the solvation structure of hydroxide but not of hydronium
Understanding ion-specific behavior in nanoconfined water is essential for controlling charge transport and selectivity in two-dimensional membranes. Motivated by recent experiments revealing anomalous dielectric and transport behavior of water confined between hBN sheets, we use machine-learning-accelerated first-principles molecular dynamics to investigate the interfacial propensities of hydronium and hydroxide ions under similar confinement. We find that hydronium remains interfacial across all confinement regimes, whereas hydroxide shifts toward the interior as the environment becomes more bulk-like. This contrasting behavior reflects the combined influence of hydrogen bonding, interfacial water layering, and the polarization of hBN, which collectively stabilize hydronium at the surface while making hydroxide slightly more favorable within the structured interior. These findings expose an asymmetry in ion-surface coupling and establish a microscopic origin for hydronium’s enhanced interfacial affinity. The results provide mechanistic insight into ion partitioning in two-dimensional channels and highlight the collective structuring of confined water as a key determinant of interfacial ion thermodynamics.
organic↗
Solvation-derived amorphous motifs in lithium-metal SEI
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25 ENERGY STORAGE↗
Catalytic Activation of Pyran Ethers in Self-Solvating Saccharides with Alkaline Earth Metals (Final Report)
Catalytic activation of cellulose ethers occurs via hydroxyl-stabilized cleavage of inter-monomer glycosidic bonds. Cooperativity between two hydroxyl groups lowers the ether cleavage transition state necessary to break apart long carbohydrate chains to initiate small molecule formation as fuel precursors. Metals existing with lignocellulosic materials including alkaline earth metals (Ca 2+ , Mg 2+ ) or alkali (Na + , K + ) also can catalyze ether scission cooperatively. By bonding with carbohydrate hydroxyl groups, a metal cation disrupt the hydrogen bonding network and free carbohydrate functional groups to react; a second metal cation stabilizes the carbohydrate ether transition state and enhances the rate of polymer scission. In this work, we expanded our initial understanding of metal-catalyzed glycoside ether scission. Within polysaccharides such as cellulose, two ether groups exist: one between monomers (glycosidic linkages) and one within a pyran ring. The hydroxyl-group hydrogen bonding network and bound metal ions form low energy binding states that interact with both ether oxygens simultaneously. Based on this interaction, our primary hypothesis was that the competition between stabilizing the two ether scission transition states determines the extent of the major pathways. Metals that disrupt the hydrogen bonding network of the C6 of sugars and stabilize the glycosidic ether promote transglycosylation to levoglucosan; in contrast, metals that stabilize the pyran ether oxygen promote sugar ring fragmentation to furans such as furfural. Varying characteristics of metal cation catalysts and configurations of bound polysaccharide chains dictate the relative rates of ether scission.
09 BIOMASS FUELS↗
Solvation agent for disulfide precipitates from inhibited glycol-water solutions
Small additions /0.01 percent or less/ of triethanoloamine sodium sulfite adduct to mercapto benzothiazole inhibited glycol water heat transfer solutions containing disulfide precipitate produce marked reduction in amount of precipitate. Adduct is useful as additive in glycol base antifreezes and coolants.
Taylor, M. F.↗
Combustion, solvation, and ion-paring. A selectivity approach
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Harris, J. M.↗
Association-solvation characteristic of fuels and lubricating and hydraulic oils
For abstract see A78-26758
Szachnowski, W.↗
Protein Solvation in Membranes and at Water-Membrane Interfaces
Different salvation properties of water and membranes mediate a host of biologically important processes, such as folding, insertion into a lipid bilayer, associations and functions of membrane proteins. These processes will be discussed in several examples involving synthetic and natural peptides. In particular, a mechanism by which a helical peptide becomes inserted into a model membrane will be described. Further, the molecular mechanism of recognition and association of protein helical segments in membranes will be discussed. These processes are crucial for proper functioning of a cell. A membrane-spanning domain of glycophorin A, which exists as a helical dimer, serves as the model system. For this system, the free energy of dissociation of the helices is being determined for both the wild type and a mutant, in which dimerization is disrupted.
Pohorille, Andrew↗
Structural and energetic consequences of mutations in a solvated hydrophobic cavity
The structural and energetic consequences of modifications to the hydrophobic cavity of interleukin 1-beta (IL-1beta) are described. Previous reports demonstrated that the entirely hydrophobic cavity of IL-1beta contains positionally disordered water. To gain a better understanding of the nature of this cavity and the water therein, a number of mutant proteins were constructed by site-directed mutagenesis, designed to result in altered hydrophobicity of the cavity. These mutations involve the replacement of specific phenylalanine residues, which circumscribe the cavity, with tyrosine, tryptophan, leucine and isoleucine. Using differential scanning calorimetry to determine the relative stabilities of the wild-type and mutant proteins, we found all of the mutants to be destabilizing. X-ray crystallography was used to identify the structural consequences of the mutations. No clear correlation between the hydrophobicities of the specific side-chains introduced and the resulting stabilities was found.
Solvents/chemistry↗
Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning
Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. Furthermore, these findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.
Adsorption↗
Liquid Phase Modeling in Porous Media: Adsorption of Methanol and Ethanol in H-MFI in Condensed Water
Zeolites are used in the chemical and separation industries for their exceptional selectivity, adsorption capacity, regenerability, and stability in gas and liquid phase processing. Here, we developed an explicit solvation method for predicting solvent/condensed phase effects on adsorption free energies in microporous media such as zeolites based on the hybrid quantum mechanical/molecular mechanical free energy perturbation (QM/MM-FEP) technique. Our explicit solvation method for zeolite systems, called eSZS, aims to capture site-specific interactions during the adsorption process at the Brønsted acid sites of H-MFI zeolite while still considering the diverse configuration space of the solvent molecules. This strategy is ideal for chemical reactions or adsorbates that interact with the microporous medium in few distinct adsorbate/transition state configurations, i.e., the harmonic or similar approximations are acceptable for the adsorbate/transition state while such approximations break down for the solvent molecules that require extensive configuration space sampling. In this way, our approach effectively overcomes the limitations of implicit solvation models and classical force field methods for describing solvation effects on chemical reactions within porous materials such as zeolites. Specifically, in this study, we investigated various aspects of our hybrid QM/MM approach, including QM cluster size dependencies in a periodic electrostatically embedded cluster model (PEECM), rules for link atoms at the QM/MM boundary, and functional and basis set considerations for converged and reasonably accurate gas and aqueous phase methanol and ethanol adsorption free energy predictions in H-MFI. For gas phase adsorption of methanol and ethanol in H-MFI at a Brønsted acid site in T12 position, we compute adsorption free energies at 298 K of −0.61 and −0.75 eV, respectively, using a PEECM containing 50 Si and 1 Al atom with ωB97x-D/def2-TZVP level of theory. For solvent effect calculations, we sample the aqueous phase using grand canonical Monte Carlo (GCMC) simulations to (1) obtain a mean field of electrostatic interactions in the reaction system and (2) perform a rigorous free energy perturbation calculation. Similar to the experimentally and computationally observed endergonic solvation effects observed for hydrocarbon adsorption on metal surfaces, we also observe that a condensed aqueous environment destabilizes methanol and ethanol at these acid sites in H-MFI at 298 K. Specifically, the computed solvation free energies of adsorption (ΔΔG solv ) for methanol and ethanol are +0.44 and +0.54 eV, respectively. From this study, it is evident that adsorbates (methanol and ethanol) are competing with water for adsorption space inside the H-MFI zeolite, leading to an endergonic solvation effect. Here, we expect that the endergonic, aqueous solvent effect during adsorption in microporous zeolites is highly tunable by changing the pore size and hydrophobicity of the microporous material as this will affect the water density inside the pore structure.
Adsorption↗
Phenolic Polymer Interactions with Water and Ethylene Glycol Solvents
Interactions between pre-cured phenolic polymer chains and a solvent have a significant impact on the structure and properties of the final post-cured phenolic resin. Developing an understanding of the nature of these interactions is important and will aid in the selection of the proper solvent that will lead to the desired final product. Here, we investigate the role of the phenolic chain structure and the solvent type on the overall solvation performance of the system through ab initio techniques and molecular dynamics simulations. Two types of solvents are considered: ethylene glycol (EGL) and H2O. Three phenolic chain structures are considered, including two novolac-type chains with either an ortho-ortho (OON) or an ortho-para (OPN) backbone network and a resole-type (RES) chain with an ortho-ortho network. Each system is characterized through a structural analysis of the solvation shell and the hydrogen-bonding environment as well as through a quantification of the solvation free energy along with partitioned interaction energies between specific molecular species. The combination of simulations and the analyses indicate that EGL provides a higher solvation free energy than H2O due to more energetically favorable hydrophilic interactions as well as favorable hydrophobic interactions between CH element groups. In addition, the phenolic chain structure significantly affects the solvation performance, with OON having limited intermolecular hydrogen-bond formations, while OPN and RES interact more favorably with the solvent molecules. The results suggest that a resole-type phenolic chain with an ortho-para network should have the best solvation performance in EGL, H2O, and other similar solvents.
Haskins, Justin B.↗
Integrated machine learning-molecular dynamics framework for electrolyte property prediction
Electrochemical stability windows determine the operating range of battery electrolytes, yet accurate prediction remains challenging because stability emerges from statistical ensembles of local solvation environments rather than single ground-state molecular structures. Traditional density functional theory calculations on energy-minimized clusters cannot capture the thermal variations in local coordination environments and geometries that govern decomposition, while SMILES-based machine learning methods lack explicit representation of three-dimensional solvation structure and ion pairing. Here, we introduce a structure-aware machine learning framework that predicts frontier orbital energies (HOMO and LUMO) directly from molecular dynamics-sampled solvation configurations, achieving sub-0.6 eV accuracy at computational costs 3–4 orders of magnitude lower than first-principles methods. Across twelve representative battery electrolytes, we demonstrate that solvent-separated and contact ion pairs exhibit strong size- and local chemistry dependent electronic stability, with variations in coordination shifts of HOMO or LUMO level by 2–3 eV, and that extended solvation structure and partially desolvated environment further modulate stability by up to 3 eV. By encoding the statistical nature of electrochemical failure through ensemble sampling of explicit solvation geometries, our approach enables high-throughput screening and rational design of next-generation battery electrolytes with mechanistic understanding of structure–property relationships.
Energy - Storage↗