The Journal of Physical Chemistry B最新文献

Rubbers prepared from technical poly(butadiene) and natural poly(isoprene) are studied by field-cycling (FC) ¹H NMR relaxometry to elucidate the changes of the relaxation spectrum. Starting with the non-cross-linked polymer successively cross-links are introduced via sulfur or peroxide vulcanization. Applying an advanced home-built relaxometer allows one to probe entanglement dynamics in addition to Rouse dynamics. We show that entanglement dynamics evidenced in terms of a characteristic power-law in the NMR susceptibility is still observed with an exponent identical to that in non-cross-linked linear polymers. Yet, the entanglement regime disappears more and more from the accessible frequency window upon increasing the cross-link density and a spectrally enlarged Rouse regime is revealed. Adding a swelling agent, the manifestation of the Rouse and entanglement regimes virtually does not change, yet, the apparent power-law exponents increase. Concomitant multiple-quantum (MQ) ¹H NMR experiments provide information on the structure of the rubber network in terms of the residual dipolar coupling and the fraction of the network defects, i.e., persisting entangled or nonentangled chains, introduced upon cross-linking and swelling.

The increased levels of carbon dioxide (CO₂) emissions due to the combustion of fossil fuels and the consequential impact on global climate change have made CO₂ capture, storage, and utilization a significant area of focus for current research. In most electrochemical CO₂ applications, water is used as a proton donor due to its high availability and mobility and use as a polar solvent. Additionally, supercritical CO₂ is a promising avenue for electrochemical applications due to its unique chemical and physical properties. Consequently, understanding the interactions between water and supercritical CO₂ is of great importance for future electrochemical applications. Molecular dynamics (MD) simulation is a powerful tool that enables atomistic-resolution dynamics of molecular systems, which can complement and guide future experimental investigations. This study employed atomistic MD to study the cosolubilities, codiffusivities, and structure of supercritical CO₂ and water systems, with a polarizable water model (SWM4-NDP) and a nonpolarizable CO₂ model (TraPPE). Additionally, ab initio MD simulations were used to better understand how atomistic polarizable/nonpolarizable models compare to explicit modeling of electron densities. The polarizable water model exhibited substantial improvement in water-associated properties. We anticipate the development of a compatible polarizable CO₂ model to yield similar improvement, providing a pathway for realizing novel high-pressure electrochemical systems.

As a liquid is supercooled toward the glass transition point, its dynamics slow significantly, provided that crystallization is avoided. With increased supercooling, the particle dynamics become more spatially heterogeneous, a phenomenon known as dynamic heterogeneity. Since its discovery, this characteristic of metastable supercooled liquids has garnered considerable attention in glass science. However, the precise physical origins of dynamic heterogeneity remain elusive and widely debated. In this perspective, we examine the relationship between dynamic heterogeneity and structural order, based on numerical simulations of fragile liquids with isotropic potentials and strong liquids with directional interactions. We demonstrate that angular ordering, arising from many-body steric interactions, plays a crucial role in the slow dynamics and dynamic cooperativity of fragile liquids. Additionally, we explore how the growth of static order correlates with slower dynamics. In fragile liquids exhibiting super-Arrhenius behavior, the spatial extent of regions with high angular order grows upon cooling, and the sequential propagation of particle rearrangements within these ordered regions increases the activation energy for particle motion. In contrast, strong liquids with spatially constrained local ordering display a distinct "two-state" dynamic characteristic, marked by a transition between two Arrhenius-type behaviors. We argue that dynamic heterogeneity, irrespective of a liquid's fragility, arises from underlying structural order, with its spatial extent determined by static ordering. This perspective aims to deepen our understanding of the interplay between structural and dynamic properties in metastable supercooled liquids.

Biological peptides have emerged as promising candidates for data storage applications due to their versatility and programmability. Recent advances in peptide synthesis and sequencing technologies have enabled the development of peptide-based data storage systems for realizing novel information storage technologies with enhanced capacity, durability, and data access speeds. In this study, we performed coarse-grained peptide sequencing of 12 distinct sequences through single-layer MoS₂ solid-state nanopores (SSNs) using molecular dynamics (MD). Peptide sequences were composed of 1 positively charged, 1 negatively charged, and 4 neutral amino acids, with the position of amino acids in the sequence being shuffled to generate all possible configurations. From MD, the goal was to evaluate the efficiency of these peptide sequences to encode binary information based on ionic current traces monitored during their passage through the SSNs. Classification approaches using LightGBM were trained and tested to analyze different sequence factors such as the position of amino acids or the spacing between charged amino acids in the sequences. Our findings reveal the presence of two distinct groups of sequences determined by the relative position of the positively charged amino acid compared to the negatively charged amino acid. Furthermore, we observe a strong correlation between discrimination accuracy and the separation in the sequence between charged amino acids, depending on the number of adjacent neutral amino acids between them. Finally, MD allowed us to establish the nonlinear relationship between amino acid positions inside the pore (called sequence motifs) and fluctuations in ionic current traces to discriminate false positives and to enable effective training of machine learning classification algorithms. These very promising results emphasized the best approaches to design peptide sequences as building blocks for molecular data storage. Finally, this study highlights the potential of the proposed approach for designing peptide sequence combinations that could help the development of efficient, scalable, and reliable molecular data storage solutions, with future research focused on encoding longer binary chains to enhance storage capacity and support the goal of stable, energy-free biological systems.

We compare the structures of polymer globules, composed of flexible polymer chains, with liquid droplets made of nonbonded monomers of the same polymer in poor solvents. This comparison is performed in three different poor solvents, with and without the addition of cosolvents. Molecular dynamics simulations are used to analyze the properties of the polymer globules, while semigrand canonical Monte Carlo simulations are used to form metastable liquid droplets of nonbonded monomers through homogeneous nucleation in the same solvents. Our findings show that both globules and droplets are nearly spherical, although droplets display slightly more anisotropy. In the absence of cosolvents, the surrounding solvent structures are similar for both globules and droplets. However, in the presence of cosolvents, significant differences arise in the liquid structure, with the disparities increasing as the solvent quality worsens. Cosolvents tend to accumulate near the surface of globules due to the restricted movement of bonded monomers, which partially immobilizes the cosolvents. This effect becomes more pronounced as the solvent quality declines. Interfacial free energy calculations reveal that cosolvents act like surfactants, promoting larger interfacial areas for both globules and droplets. This effect is more significant for globules due to the greater accumulation of cosolvents at their surface. Therefore, modeling polymer globules as liquid droplets may underestimate the impact of cosolvents on the stability of the globule state. Additionally, the transition states involved in polymer collapse in the presence of cosolvents differ from those involved in the nucleation of liquid droplets in the same solution.

The light-harvesting pigment-protein complex II (LHCII) from plants can be used as a component for biohybrid photovoltaic devices, acting as a photosensitizer to increase the photocurrent generated when devices are illuminated with sunlight. LHCII is effective at photon absorption in the red and blue regions of the visible spectrum, however, it has low absorption in the green region (550-650 nm). Previous studies have shown that synthetic chromophores can be used to fill this spectral gap and transfer additional energy to LHCII, but it was uncertain whether this would translate into an improved performance for photovoltaics. In this study, we demonstrate amplified photocurrent generation from LHCII under green light illumination by coupling this protein to Texas Red (TR) chromophores that are coassembled into a lipid bilayer deposited onto electrodes. Absorption spectroscopy shows that LHCII and lipid-linked TR are successfully incorporated into lipid membranes and maintained on electrode surfaces. Photocurrent action spectra show that the increased absorption due to TR directly translates into a significant increase of photocurrent output from LHCII. However, the absolute magnitude of the photocurrent appears to be limited by the lipid bilayer acting as an insulator and the TR enhancement effect reaches a maximum due to protein, lipid or substrate-related quenching effects. Future work should be performed to optimize the use of extrinsic chromophores within novel biophotovoltaic devices.

Molecular dynamics simulations are a powerful tool for probing and understanding the theoretical aspects of chemical systems and solutions. Our research introduces a novel method for determining the excess chemical potential of non-ideal solutions by leveraging the equivalence between the chemical potential of the vapor phase and liquid phase. Traditional approaches have relied on bulk simulations and the integration of pair distribution functions (g(r)), which are computationally intensive to obtain accurate results. In contrast, our method utilizes a liquid-gas system, where determining the vapor pressure allows for a quick and accurate calculation of the excess chemical potential relative to a reference system, e.g., pure solvent. This approach significantly reduces computational effort while maintaining high accuracy and precision. We demonstrate the effectiveness of this method using a simplified Lennard-Jones model, although the method is broadly applicable to a wide range of systems, including those with complex interactions, varying concentrations, and different temperatures. The reduced computational demands and versatility of our approach make it a valuable tool for studying non-ideal solutions, including ionic solutions in molecular simulations.

Nonideality in a binary solvent mixture is manifested through anomalies in various physical properties like viscosity, dielectric constant, polarity, freezing point, boiling point, and so forth. Sometimes, such anomalies become much more prominent, leading to a synergistic behavior, where the physical property of the mixture is way different from its bulk counterparts. Various alcohols/chlorinated methane binary solvent mixtures show such a synergistic behavior. The reason is attributed to the unique but diverse interactions present in the system. We speculated that these diverse interactions must manifest heterogeneity in such a binary solvent mixture. Using the improved methodology developed by our group, we investigate the presence of dynamic and spatial heterogeneity in the chloroform/methanol synergistic binary solvent mixture. To our delight, we found that our projection is accurate, and indeed, the chloroform/methanol binary solvent mixtures are heterogeneous. Two maxima for the synergistic behavior have been observed for the chloroform/methanol binary solvent mixture (at ∼0.45 and 0.75 mole fractions of methanol in chloroform) in the literature, where the extent of heterogeneity was also found to be the highest. The present study portrays the intriguing complexity of simple binary solvent mixtures, and the findings may provide valuable insights into solvent engineering for diverse applications like extraction/purification media, reaction media, polymer processing, nanomaterial synthesis, pollutant extraction, active ingredient delivery, biofuel production, and battery technology.

Molecular dynamics simulations were employed to investigate the reorientation dynamics of water molecules under supercritical conditions. Our findings indicate that supercritical water consists of a fluctuating assembly of water clusters of varying sizes. The reorientational motions are characterized by large angular displacements and occur on fast time scales. We found that the decreasing density of supercritical water correlates with a decrease in the number of angular jumps as more water molecules were found in isolated or small clustered states at lower densities. Notably, the amplitude of rotational jumps in relative coordinates does not depend much on the density of supercritical water at a given temperature.