Journal of Chemical Physics最新文献

Classical molecular dynamics simulations were carried out for liquid water using the TIP4P-2005 potential model along the 50 MPa isobar, covering a wide temperature range from ambient to near-critical conditions. Particular attention was given to the behavior of various local structural descriptors of liquid water, as well as to the corresponding dynamics and entropic quantities. The results obtained reveal the existence of two distinct structural transitions, located in the temperature range around 423.15 and 498.15 K, respectively. The observed transitions have been characterized by local extrema and crossovers in many of the above-mentioned quantities. Significant changes in the hydrogen bond network were also observed across these transitions. These structural rearrangements are reflected in the calculated intermolecular vibrational and librational dynamics, as evidenced by clear modifications in the spectral densities of atomic velocity correlation functions and in the translational and rotational densities of states.

The ion-activated patchy particle model is an important theoretical framework to investigate the phase behavior of globular proteins in the presence of multivalent ions. In this study, we examine and highlight the influence of patch heterogeneity on the extension, appearance, and disappearance of the liquid-liquid coexistence region of the phase diagram. We demonstrate that within this model the binding energy between salt ions and patches of different types is a key factor in determining the phase behavior. Specifically, we show under which conditions liquid-liquid phase separation (LLPS) in these systems can appear or disappear for varying binding energy and ion-mediated attraction energy between ion-occupied and unoccupied patches. In particular, we address the influence of the patch type dependence of these energies on the (dis)appearance of LLPS. These results rationalize our new results on ion-dependent liquid-liquid phase separation in solutions of bovine serum albumin with trivalent cations. In comparison with models with non-activated patches, where the gas-liquid transition disappears when the number of patches approaches two, we find the complementary mechanism that ions may shift the attractions from stronger to weaker patches (with an accompanying disappearance of the transition) if their binding energy to the patches changes. The results have implications for the understanding of charge-driven LLPS in biological systems and its suppression.

Singlet Fission (SF) into two triplets offers exciting avenues for high-efficiency photovoltaics and optically initializable qubits. While the chemical space of SF chromophores is ever-expanding, the underlying mechanistic details of electronic-nuclear motions accompanying SF are often glossed over. Rigid SF dimers with well-defined orientations are helpful to decipher such details. Here, using polarization-controlled white-light two-dimensional and pump-probe spectroscopies, we investigate a new class of contorted naphthalenediimide dimers, recently reported to have a favorable intramolecular SF (iSF) pathway. 2D cross-peaks directly identify the two Davydov components of the dimer. 2D maps reveal that excitation of either Davydov component leads to an intermediate state, which is generated within our instrument response. This intermediate proceeds to form a relaxed TT1 state whose formation kinetics is strongly dependent on which Davydov component is excited. We also find that the intermediate formation and relaxation are vibronically coherent with enhanced quantum beats only in the TT1 photoproduct, suggesting that intermolecular twisting and ruffling coordinates are strongly displaced upon TT1 formation. Polarization anisotropy directly tracks electronic motion during these steps and curiously reveals minimal electronic reorientation during TT1 formation. A likely hypothesis for this observation is that significantly mixed singlet-triplet electronic character is maintained throughout the nuclear evolution away from the Franck-Condon geometry toward relaxed TT1 without any reduction in the singlet electronic character. Such a mixing can introduce triplet annihilation channels and can therefore prevent the formation of long-lived high-spin triplets. The synthetic design of iSF dimers should aim to minimize this electronic mixing.

Correlated Orbital Theory (COT) provides an exact one-particle framework by imposing rigorous physical constraints on Kohn-Sham eigenvalues and, as a consequence, directly incorporates essential electron correlation into molecular orbitals. This approach paves the way toward a new class of approximations within Kohn-Sham Density Functional Theory (KS-DFT). However, since all existing quantum theory project functionals are derived from CAM-B3LYP, we pose the question: Can COT improve the hybrid versions of different exchange-correlation functionals as well? To that end, we explore two optimization strategies for adjusting the existing parameters within PBE0, TPSS0, and LC-PBE0: (i) the ionization potential condition and (ii) the HOMO-LUMO condition. In this sense, we critically assess how these functionals address the "Devil's Triangle" of KS-DFT: self-interaction error, integer discontinuity, and one-particle spectra. We further examine how the COT influences the description of two challenging properties, charge transfer and reaction barrier heights. Overall, enforcing both COT conditions systematically enhances the performance of functionals within the PBE family, although the description of reaction barriers still leaves room for improvement.

The experimental determination of eutectic points is a long-established and widely used technique, but it is generally only practical for systems with relatively low melting points. Many modern, promising materials, however, are ultra-refractory, with melting points exceeding 3000 K. For these systems, conventional melting experiments become prohibitively expensive and technically challenging. Advanced AI modeling can serve as a powerful precursor to guide successful experimentation in such cases. This work proposes a novel criterion for determining the eutectic point concentration in ultra-refractory alloys. The approach is verified using the Ti-B-C system-the most thoroughly studied three-component refractory system to date. The core of the algorithm is a machine-learning interatomic potential, based on a neural network, which achieves accuracy comparable to ab initio methods. Crucially, the algorithm operates effectively in the liquid phase, eliminating the need for information about the solid alloy's crystalline structure to estimate eutectic points.

We investigate a set of design principles that link specific features of interparticle interactions to predictable structural and dynamic outcomes in two-dimensional self-assembly, a framework relevant to soft matter and biological condensates. Using extensive molecular dynamics simulations of single- and two-component systems, we systematically dissect how modifications to competing short-range attraction and long-range repulsion (SALR) potentials (both isotropic and anisotropic) serve as independent control parameters. In particular, we have focused on tuning the repulsive barrier height, decorating the attractive well with oscillatory components, and changing particle geometry. We demonstrate that these modifications dictate cluster size distributions, the degree of intra-cluster ordering, the geometry of the clusters, and the propensity for inter-cluster crystallization. A key finding is the decoupling of internal and global dynamics: oscillatory wells promote solid-like order within clusters while maintaining liquid-like cluster mobility. Furthermore, we show how asymmetric interactions in a binary SALR mixture can be designed to induce internal phase segregation within condensates. Complementing this, we observe that in anisotropic models in which the short-range component of the interaction stems from the presence of attractive patchy sites, stoichiometry and the geometric distribution of the patches are essential to control self-assembly and cluster morphology, whereas long-range repulsion can be used to tune cluster size and polydispersity. The extracted principles provide a causal road-map for engineering self-assembled materials and a set of basic physical concepts for interpreting the complex phase behavior of biomolecular condensates.

In this work, we performed all-atom molecular dynamics simulations of the ionic liquids choline chloride (ChCl) and 1-ethyl-3-methylimidazolium chloride, as well as their mixtures with ethylene glycol (ETG) and urea (UR), to obtain deep eutectic solvents (DESs). We calculated the structural and transport properties of all systems studied to explore the differences between pure ILs and DESs. From these results, we discuss the ability of ETG and UR to orient themselves along the ionic electric field, similarly to water in classical electrolytes. This orientational behavior promotes an effective reduction of the electrostatic interactions (usually called "screening" within the context of classical electrolytes). We found that, similar to inorganic salts dissolved in water, the hydrogen-bond donors reduce electrostatic interactions between ions, leading to significant changes in their structural and transport properties.

Penning electron detachment is a process in which an electronically excited neutral species collides with an anion and detaches an electron from it by transferring its excitation energy, viz., A- + N* → A + N + e-. While there have been theoretical studies relating to the mechanism of Penning detachment, there have been few experimental investigations of this fundamental process. In this work, Penning electron detachment of sulfur pentafluoride anions by potassium atoms, which had been selectively excited to high Rydberg electronic states, was investigated by directly observing its occurrence via the depletion of the SF5- anion signal in mass spectra, viz., SF5- + K** → SF5 + K + e-. Scanning the excited states of potassium in the range of 8d-32d and 10s-33s (excitation energy 4.11-4.33 eV) showed a significant dependence of the Penning detachment cross section on the excitation energy of potassium. Combining quantitative Penning detachment results with the electron affinity of SF5 (4.4 eV), which we had determined using anion photoelectron spectroscopy, demonstrated that Penning detachment occurred when the total available energy, that is, the SF5- + K** collision energy + the K** excitation energy, exceeded the electron affinity of SF5.

A simple fourth-order propagator [Ture and Jang, J. Phys. Chem. A 128, 2871 (2024)] based on the Magnus expansion is extended to the Liouville space for both closed-system and Lindbladian open-system quantum dynamics. For both dynamics, commutator free versions of fourth-order propagators are provided as well. These propagators are then applied to the dynamics of a driven Λ-system, where Lindblad terms represent the effect of a photonic bath. For both dynamics, the accuracy of the rotating wave approximation (RWA) for the matter-radiation interaction is assessed. We confirmed reasonable performance of RWA for weak and resonant fields. However, small errors appear for moderate fields and substantial errors can be found for strong fields where coherent population trapping can still be expected. We also found that the presence of bath for open-system quantum dynamics consistently reduces the errors of the RWA. These results provide quantitative information on how the RWA breaks down beyond weak field or for non-resonant cases. Major results are benchmarked against results of our sixth-order ME-based propagator. We also provide numerical comparison of our algorithms with other fourth-order algorithms for the Λ-system. These confirm reasonable performance of our simple propagators and the improvement gained through commutator-free expressions.

Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density functional theory (DFT) code's grid-decomposition approach scales nearly linearly with the number of graphics processing units (GPUs), even for simulations exceeding thousands of atoms. This scalability makes RMG a compelling tool for high-throughput DFT studies of materials that would otherwise be bottlenecked in other codes (for example, by global fast Fourier transforms in plane-wave DFT). However, the limited workflow infrastructure for RMG has thus far constrained its adoption to a small user community. In this work, we present pyRMG, a Python package designed to streamline the setup and execution of RMG DFT calculations. Built on the pymatgen and ASE (Atomic Simulation Environment) computational materials science Python packages, pyRMG automates input generation and convergence checking, and it integrates with modern job schedulers (e.g., Flux) on leadership-class platforms such as Frontier and Perlmutter. We demonstrate pyRMG for a high-throughput study of strain effects in 2D 2L-Bi2Se3/2L-NbSe2 heterostructures, which offers chemical insights into this system and shows that RMG-based workflows can converge with limited user intervention.