The Journal of Physical Chemistry B最新文献

Live-cell imaging using fluorescence microscopy enables researchers to study cellular processes in unprecedented detail. These techniques are becoming increasingly popular among microbiologists. The emergence of microfluidics and deep learning has significantly increased the amount of quantitative data that can be extracted from such experiments. However, these techniques require highly specialized expertise and equipment, making them inaccessible to many biologists. Here we present a guide for microbiologists, with a basic understanding of microfluidics, to construct a custom-made live-cell interrogation system that is capable of recording and analyzing thousands of bacterial cell-cycles per experiment. The requirements for different microbiological applications are varied, and experiments often demand a high level of versatility and custom-designed capabilities. This work is intended as a guide for the design and engineering of microfluidic master molds and how to build polydimethylsiloxane chips. Furthermore, we show how state-of-the-art deep-learning techniques can be used to design image processing algorithms that allow for the rapid extraction of highly quantitative information from large populations of individual bacterial cells.

A new model is developed to quantify the surface tension of ionic surfactants from surface affinity and ionization equilibrium. The model successfully predicts two important molecular structure-surface activity factors: the length of single-branch homologues and the nature of counterions. The modeling results also clarify the underlying mechanisms of the two processes. Changing the counterion only affects the ionization, not the affinity. On the other hand, increasing carbon length dramatically increases the affinity while having a small effect on ionization. The modeling framework consistently resolves structure-activity observations, some of which have been reported since the 19th century. The model can be extended for surfactants with more than one ionic state and surfactant/electrolyte mixtures.

Nile Red is a fluorescent dye used extensively in bioimaging due to its strong solvatochromism. The photophysics underpinning Nile Red's fluorescence has been disputed for decades, with some studies claiming that the dye fluoresces from two excited states and/or that the main emissive state is twisted and intramolecular charge-transfer (ICT) in character as opposed to planar ICT (PICT). To resolve these long-standing questions, a combined experimental and theoretical study was used to unravel the mechanism of Nile Red's fluorescence. Time-resolved fluorescence measurements indicated that Nile Red emission occurs from a single excited state. Theoretical calculations revealed no evidence for a low-lying TICT state, with the S₁ minimum corresponding to a PICT state. Ultrafast pump-probe spectroscopic data contained no signatures associated with an additional excited state involved in the fluorescence decay of Nile Red. Collectively, these data in polar and nonpolar solvents refute dual fluorescence in Nile Red and definitively demonstrate that emission occurs from a PICT state.

Protic ionic liquids (PILs) are promising candidates as electrolytes for proton exchange polymer membrane fuel cells. In order to optimize their properties, a detailed understanding of the molecular interactions within the bulk and at the electrode-electrolyte interface is needed, which can be obtained by infrared spectra. A prerequisite for extracting information on the molecular structure and inter- or intramolecular interactions from an experimental spectrum is a reasonable interpretation of the observed spectral features. Here, we employed density functional theory to understand the vibration modes of PILs composed of ammonium cations and different counteranions. Different from the previous calculation methods performed on small cluster model systems consisting of isolated species, a periodically repeated system of four ion pairs was used in order to approximate the bulk liquid environment. The computed frequencies and IR intensity match well with the corresponding experimental spectra, allowing for its proper interpretation, especially the characteristic features of the interionic interaction. The presented approach enables accurate computation of a variety of ionic liquid systems in a highly efficient way.

Traditionally the broadness of the spectrum of the relaxation times observed in glass-forming materials has been rationalized by local heterogeneity, where a variety of atomistic environments leads to spectrum of single-exponential relaxation responses. However, the assumption of heterogeneity can break down when tested against the shape of the relaxation spectrum. An alternative homogeneous scenario assumes that the relaxation is inherently multiexponential. A recently developed switchback model [Medvedev, G. A. Phys. Rev. E 2023, 107 (3), 034122] naturally results in a multiexponential wedge-like spectrum that is consistent with the dielectric relaxation, light scattering, and the NMR data. As a particular case the switchback model allows for the spectrum to become single-exponential; under the heterogeneous scenario this would require the heterogeneities to completely vanish, which is hard to justify. Using data from photobleaching experiments and molecular dynamic simulations, it is shown that the relaxation spectrum may become single-exponential under large anisotropic deformation. This is interpreted as an argument in favor of the homogeneous scenario and specifically the switchback model for the relaxation of the glass formers.

Identifying small molecules that bind strongly to target proteins in rational molecular design is crucial. Machine learning techniques, such as generative adversarial networks (GAN), are now essential tools for generating such molecules. In this study, we present an enhanced method for molecule generation using objective-reinforced GANs. Specifically, we introduce BEGAN (Boltzmann-enhanced GAN), a novel approach that adjusts molecule occurrence frequencies during training based on the Boltzmann distribution exp(-ΔU/τ), where ΔU represents the estimated binding free energy derived from docking algorithms and τ is a temperature-related scaling hyperparameter. This Boltzmann reweighting process shifts the generation process toward molecules with higher binding affinities, allowing the GAN to explore molecular spaces with superior binding properties. The reweighting process can also be refined through multiple iterations without altering the overall distribution shape. To validate our approach, we apply it to the design of sex pheromone analogs targeting Spodoptera frugiperda pheromone receptor SfruOR16, illustrating that the Boltzmann reweighting significantly increases the likelihood of generating promising sex pheromone analogs with improved binding affinities to SfruOR16, further supported by atomistic molecular dynamics simulations. Furthermore, we conduct a comprehensive investigation into parameter dependencies and propose a reasonable range for the hyperparameter τ. Our method offers a promising approach for optimizing molecular generation for enhanced protein binding, potentially increasing the efficiency of molecular discovery pipelines.

Ionic liquids (ILs) exhibit a unique nanoscale structure (i.e., nanodomains) characterized by their organization into distinct domains. We present evidence of nanodomains in trihexyl(tetradecyl)phosphonium chloride, [P₆₆₆₁₄][Cl], using single-molecule tracking (SMT) and the maximum entropy method (MEM) to analyze single-molecule trajectories. The diffusion properties of ATTO 647N were assessed as the temperature of [P₆₆₆₁₄][Cl] increased from 20 °C (4020 cP), 35 °C (1239 cP), 45 °C (599 cP) to 50 °C (439 cP). The MEM analysis revealed a distinct two-population distribution of diffusion coefficients representing nanodomains in [P₆₆₆₁₄][Cl] at 20 °C (4020 cP). The slow population accounts for 16%, with a diffusion coefficient of 0.104 μm²/s, while the fast population constitutes 84% with a diffusion coefficient of 0.634 μm²/s. Two diffusing populations were also measured for the chemically different probes ATTO 647N, DiD, and Nile Blue chloride in [P₆₆₆₁₄][Cl] at 20 °C. In contrast, only a single fast population was measured in [P₆₆₆₁₄][Cl] at 50 °C. At a similar viscosity (640 cP) but a lower temperature of 20 °C, trihexyl(tetradecyl)phosphonium bis[(trifluoromethyl)-sulfonyl]imide, [P₆₆₆₁₄][NTf₂], also showed only a single diffusing population. The elimination of the slow population and the presence of a single diffusing population in [P₆₆₆₁₄][Cl] as the temperature increases and the viscosity decreases is consistent with liquid-liquid phase separation (LLPS) as a mechanism of nanodomain formation. In addition, the measurement of two diffusing populations for three fluorophores with different chemical structures is also consistent with a physical mechanism, and not a chemical mechanism, for nanodomain formation.

Synthetic polymers have a distribution of chain lengths which can be characterized by dispersity, Đ. Their macroscopic properties are influenced by chain mobility in the melt, and controlling Đ can significantly impact these properties. In this work, we present a detailed study of the static and dynamic behavior of fully flexible polymer chains that follow the Schulz-Zimm molecular weight distribution up to Đ = 2.0 using coarse-grained molecular dynamics simulations. We analyze the behavior of test chains with molecular weights that are equal to, above, or below the molecular weight (M_w) of the melt. Static analysis shows that the conformation of these test chains remains unaffected by the heterogeneity of the surrounding chains. To study the dynamics, we computed the mean-squared displacement of test chains in melts of the same M_w and different dispersities. The mobility of test chains with N > M_w steadily increases with dispersity, due to the shorter chains contributing to early onset of disentanglement of the long chains. However, the dynamics of test chains of length N < M_w is nonmonotonic with respect to dispersity; this behavior arises from a trade-off between the increased mobility of shorter chains and the corresponding slowdown caused by the presence of longer chains. We examine the dynamic structure factor and find a weakening of tube confinement, with the effects becoming less pronounced with increasing dispersity and M_w. These findings provide insights into the rich dynamic heterogeneity of disperse polymer melts.