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1. Interfacial structural crossover and hydration thermodynamics of charged C ₆₀ in water

   https://doi.org/10.1039/c8cp05422c  

   Sarhangi, Setare Mostajabi; Waskasi, Morteza M.; Hashemianzadeh, Seyed Majid; Matyushov, Dmitry V. (October 2018, Physical Chemistry Chemical Physics)

   Classical molecular dynamics simulations of the hydration thermodynamics, structure, and dynamics of water in hydration shells of charged buckminsterfullerenes are presented in this study. Charging of fullerenes leads to a structural transition in the hydration shell, accompanied by creation of a significant population of dangling O–H bonds pointing toward the solute. In contrast to the well accepted structure–function paradigm, this interfacial structural transition causes nearly no effect on either the dynamics of hydration water or on the solvation thermodynamics. Linear response to the solute charge is maintained despite significant structural changes in the hydration shell, and solvation thermodynamic potentials are nearly insensitive to the altering structure. Only solvation heat capacities, which are higher thermodynamic derivatives of the solvation free energy, indicate some sensitivity to the local hydration structure. We have separated the solvation thermodynamic potentials into direct solute–solvent interactions and restructuring of the hydration shell and analyzed the relative contributions of electrostatic and nonpolar interactions to the solvation thermodynamics. 

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2. Ultrafast Vibrational Dynamics of a Solute Correlates with Dynamics of the Solvent

   Crum, Vivian F.; Kiefer, Laura M.; Kubarych, K. J. (July 2021, Journal of chemical physics)

   null (Ed.)

   Two-dimensional infrared (2D-IR) spectroscopy is used to measure the spectral dynamics of the metal carbonyl complex, cyclopentadienyl manganese tricarbonyl (CMT) in a series of linear alkyl nitriles. 2D-IR spectroscopy provides direct readout of solvation dynamics through spectral diffusion, probing the decay of frequency correlation induced by fluctuations of the solvent environment. 2D-IR simultaneously monitors intramolecular vibrational energy redistribution (IVR) among excited vibrations, which can also be influenced by the solvent through the spectral density rather than the dynamical friction underlying solvation. Here, we report that the CMT vibrational probe reveals solvent dependences in both the spectral diffusion and the IVR time scales, where each slows with increased alkyl chain length. In order to assess the degree to which solute-solvent interactions can be correlated with bulk solvent properties, we compared our results with low-frequency dynamics obtained from optical Kerr effect (OKE) spectroscopy—performed by others—on the same nitrile solvent series. We find excellent correlation between our spectral diffusion results and the orientational dynamics time scales from OKE. We also find a correlation between our IVR time scales and the amplitudes of the low-frequency spectral densities evaluated at the 90-cm-1 energy difference, corresponding to the gap between the two strong vibrational modes of the carbonyl probe. 2D-IR and OKE provide complementary perspectives on condensed phase dynamics, and these findings provide experimental evidence that, at least at the level of dynamical correlations, some aspects of a solute vibrational dynamics can be inferred from properties of the solvent. 

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3. Molecular engineering of fluoroether electrolytes for lithium metal batteries

   https://doi.org/10.1039/D2ME00135G  

   Chen, Yuxi; Lee, Elizabeth M.; Gil, Phwey S.; Ma, Peiyuan; Amanchukwu, Chibueze V.; de Pablo, Juan J. (January 2023, Molecular Systems Design & Engineering)

   Fluoroether solvents are promising electrolyte candidates for high-energy-density lithium metal batteries, where high ionic conductivity and oxidative stability are important metrics for design of new systems. Recent experiments have shown that these performance metrics, particularly stability, can be tuned by changing the fraction of ether and fluorine content. However, little is known about how different molecular architectures influence the underlying ion transport mechanisms and conductivity. Here, we use all-atom molecular dynamics simulations to elucidate the ion transport and solvation characteristics of fluoroether chains of varying length, and having different ether segment and fluorine terminal group contents. The design rules that emerge from this effort are that solvent size determines lithium-ion transport kinetics, solvation structure, and solvation energy. In particular, the mechanism for lithium-ion transport is found to shift from ion hopping between solvation sites located in different fluoroether chains in short-chain solvents, to ion–solvent co-diffusion in long-chain solvents, indicating that an optimum exists for molecules of intermediate length, where hopping is possible but solvent diffusion is fast. Consistent with these findings, our experimental measurements reveal a non-monotonic behavior of the effects of solvent size on lithium-ion conductivity, with a maximum occurring for medium-length solvent chains. A key design principle for achieving high ionic conductivity is that a trade-off is required between relying on shorter fluoroether chains having high self-diffusivity, and relying on longer chains that increase the stability of local solvation shells. 

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4. MLIMC: Machine learning-based implicit-solvent Monte Carlo

   https://doi.org/10.1063/1674-0068/cjcp2109150  

   Chen, Jiahui; Geng, Weihua; Wei, Guo-Wei (December 2021, Chinese Journal of Chemical Physics)

   Monte Carlo (MC) methods are important computational tools for molecular structure optimizations and predictions. When solvent effects are explicitly considered, MC methods become very expensive due to the large degree of freedom associated with the water molecules and mobile ions. Alternatively implicit-solvent MC can largely reduce the computational cost by applying a mean field approximation to solvent effects and meanwhile maintains the atomic detail of the target molecule. The two most popular implicit-solvent models are the Poisson-Boltzmann (PB) model and the Generalized Born (GB) model in a way such that the GB model is an approximation to the PB model but is much faster in simulation time. In this work, we develop a machine learning-based implicit-solvent Monte Carlo (MLIMC) method by combining the advantages of both implicit solvent models in accuracy and efficiency. Specifically, the MLIMC method uses a fast and accurate PB-based machine learning (PBML) scheme to compute the electrostatic solvation free energy at each step. We validate our MLIMC method by using a benzene-water system and a protein-water system. We show that the proposed MLIMC method has great advantages in speed and accuracy for molecular structure optimization and prediction. 

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5. Entropy connects water structure and dynamics in protein hydration layer

   https://doi.org/10.1039/c8cp01674g  

   Dahanayake, Jayangika N.; Mitchell-Koch, Katie R. (January 2018, Physical Chemistry Chemical Physics)

   The enzyme Candida Antarctica lipase B (CALB) serves here as a model for understanding connections among hydration layer dynamics, solvation shell structure, and protein surface structure. The structure and dynamics of water molecules in the hydration layer were characterized for regions of the CALB surface, divided around each α-helix, β-sheet, and loop structure. Heterogeneous hydration dynamics were observed around the surface of the enzyme, in line with spectroscopic observations of other proteins. Regional differences in the structure of the biomolecular hydration layer were found to be concomitant with variations in dynamics. In particular, it was seen that regions of higher density exhibit faster water dynamics. This is analogous to the behavior of bulk water, where dynamics (diffusion coefficients) are connected to water structure (density and tetrahedrality) by excess (or pair) entropy, detailed in the Rosenfeld scaling relationship. Additionally, effects of protein surface topology and hydrophobicity on water structure and dynamics were evaluated using multiregression analysis, showing that topology has a somewhat larger effect on hydration layer structure–dynamics. Concave and hydrophobic protein surfaces favor a less dense and more tetrahedral solvation layer, akin to a more ice-like structure, with slower dynamics. Results show that pairwise entropies of local hydration layers, calculated from regional radial distribution functions, scale logarithmically with local hydration dynamics. Thus, the Rosenfeld relationship describes the heterogeneous structure–dynamics of the hydration layer around the enzyme CALB. These findings raise the question of whether this may be a general principle for understanding the structure–dynamics of biomolecular solvation. 

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