Universality, Scaling, and Collapse in Supercritical Fluids

Self-assembly prediction of architecture-controlled bottlebrush copolymers in solution using graph convolutional networks

The investigation of bottlebrush copolymer self-assembly in solution involves a comprehensive approach integrating simulation and experimental research, due to their unique physical characteristics. However, the intricate architecture of bottlebrush copolymers and the diverse solvent conditions introduce a wide range of parameter spaces. In this study, we investigated the solution self-assembly behavior of bottlebrush copolymers by combining dissipative particle dynamics (DPD) simulation results and machine learning (ML) including graph convolutional networks (GCNs). The architecture of bottlebrush copolymers is encoded by graphs including connectivity, side chain length, bead types, and interaction parameters of DPD simulation. Using GCN, we accurately predicted the single chain properties of bottlebrush copolymers with over 95% accuracy. Furthermore, phase behavior was precisely predicted using these single chain properties. Shapley additive explanations (SHAP) values of single chain properties to the various self-assembly morphologies were calculated to investigate the correlation between single chain properties and morphologies. In addition, we analyzed single chain properties and phase behavior as a function of DPD interaction parameters, extracting relevant physical properties for vesicle morphology formation. This work paves the way for tailored design in solution of self-assembled nanostructures of bottlebrush copolymers, offering a GCN framework for precise prediction of self-assembly morphologies under various chain architectures and solvent conditions.

The Local Electronic Structure of Supercritical CO2 from X-ray Raman Spectroscopy and Atomistic-Scale Modeling

Supercritical CO₂ is encountered in several technical and natural systems related to biology, geophysics, and engineering. While the structure of gaseous CO₂ has been studied extensively, the properties of supercritical CO₂, particularly close to the critical point, are not well-known. In this work, we combine X-ray Raman spectroscopy, molecular dynamics simulations, and first-principles density functional theory (DFT) calculations to characterize the local electronic structure of supercritical CO₂ at conditions around the critical point. The X-ray Raman oxygen K-edge spectra manifest systematic trends associated with the phase change of CO₂ and the intermolecular distance. Extensive first-principles DFT calculations rationalize these observations on the basis of the 4sσ Rydberg state hybridization. X-ray Raman spectroscopy is found to be a sensitive tool for characterizing electronic properties of CO₂ under challenging experimental conditions and is demonstrated to be a unique probe for studying the electronic structure of supercritical fluids.

Inhomogeneity Effects on Reactions in Supercritical Fluids: A Computational Study on the Pyrolysis of n-Decane

Supercritical fluids exhibit peculiar inhomogeneity, which strongly affects reaction behaviors in them. However, explanations for inhomogeneity and its effect on reactions are both ambiguous so far. Here, we provide an atomic-level understanding of inhomogeneity effects on reactions via the computational method, with the example of n-decane pyrolysis under supercritical conditions. We describe the characteristic pyrolysis behaviors through collective variable-driven hyperdynamics (CVHD) simulations and explain the inhomogeneity of supercritical n-decane as the coexistence of gas-like and liquid-like atoms by a trained machine learning classifier. Due to their specific local environment, the appearance of liquid-like atoms under supercritical conditions significantly increases the type and frequency of bimolecular reactions and eventually causes changes in product distributions. Future research with this method is expected to extend the effect of inhomogeneity on other reactions under supercritical conditions or other condensed phases.

The Phonon Theory of Liquids and Biological Fluids: Developments and Applications

Among the three basic states of matter (solid, liquid, and gas), the liquid state has always eluded general theoretical approaches for describing liquid energy and heat capacity. In this Viewpoint, we derive the phonon theory of liquids and biological fluids stemming from Frenkel's microscopic picture of the liquid state. Specifically, the theory predicts the existence of phonon gaps in vibrational spectra of liquids and a thermodynamic boundary in the supercritical state. Direct experimental evidence reaffirming these theoretical predictions was achieved through a combination of techniques using static compression X-ray diffraction and inelastic X-ray scattering on deeply supercritical argon in a diamond anvil cell. Furthermore, these findings inspired and then led to the discovery of phonon gaps in liquid crystals (mesogens), block copolymers, and biological membranes. Importantly, phonon gaps define viscoelastic crossovers in cellular membranes responsible for lipid self-diffusion, lateral molecular-level stress propagation, and passive transmembrane transport of small molecules and solutes. Finally, molecular interactions mediated by external stimuli result in synaptic activity controlling biological membranes' plasticity resulting in learning and memory. Therefore, we also discuss learning and memory effects─equally important for neuroscience as well as for the development of neuromorphic devices─facilitated in biological membranes by external stimuli.

Gas–liquid crossover in the Lennard-Jones system

It is demonstrated that the crossover between gas- and liquid-like regions on the phase diagram of the Lennard-Jones system occurs at a fixed value of the density divided by its value at the freezing point, ρ/ ρfr ≃ 0.35. This definition is consistent with other definitions proposed recently. As a result, a very simple practical expression for the gas-to-liquid crossover line emerges.

Distinct molecular dynamics dividing liquid-like and gas-like supercritical hydrogens

Understanding how a supercritical fluid is related to normal liquid and gas and separating it into liquid-like and gas-like regions are of fundamental and practical importance. Despite the usefulness of hydrogen storage, molecular dynamics images on supercritical hydrogens exhibiting strong nuclear quantum effects are scarce. Taking advantage of the non-empirical ab initio molecular dynamics method for hydrogen molecules, we found that, while radial distribution functions and diffusion show a monotonic change along the density, van Hove time correlation functions and intramolecular properties such as bond length and vibrational frequency exhibit the anomalous order crossing the Widom line. By demonstrating that the anomalous order stemmed from the largest deviations between liquid-like and gas-like solvations formed around the Widom line, we concluded that this supercritical fluid is a mixture of liquid and gas possessing heterogeneity. The obtained physical insights can be an index to monitor the supercriticality and to identify distinct liquid-like and gas-like supercritical fluids.

Structural Markers of the Frenkel Line in the Proximity of Widom Lines

We have performed a neutron scattering experiment on supercritical fluid nitrogen at 160 K (1.27 T_C) over a wide pressure range (7.8 MPa/0.260 g/mL-125 MPa/0.805 g/mL). This has enabled us to study the process by which nitrogen changes from a fluid that exhibits gaslike behavior to one that exhibits rigid liquidlike behavior at a temperature close to, but above, the critical temperature by crossing the Widom lines followed by the Frenkel line on pressure (density) increase. We find that the Frenkel line transition is indicated by a transition to a regime of rigid liquidlike behavior in which the coordination number remains constant within error, in agreement with our previous work at 300 K. The Frenkel line transition takes place at approximately the same density at 160 and 300 K. The data do not conclusively show an additional transition at the location of the known Widom lines. We find that behavior remains gaslike until the Frenkel line is crossed and our data support the hypothesis that Widom line transitions are density increase-driven.

Dynamic Crossover in Fluids: From Hard Spheres to Molecules

We propose a simple and generic definition of a demarcation reconciling structural and dynamic frameworks when combined with the entropy scaling framework. This crossover line between gas- and liquid-like behaviors is defined as the curve for which an individual property, the contribution to viscosity due to molecules' translation, is exactly equal to a collective property, the contribution to viscosity due to molecular interactions. Such a definition is shown to be consistent with the one based on the minima of the kinematic viscosity. For the hard sphere, this is shown to be an exact solution. For Lennard-Jones spheres and dimers and for some simple real fluids, this relation holds very well. This crossover line passes nearby the critical point, and for all studied fluids, it is well captured by the critical excess entropy curve for atomic fluids, emphasizing the link between transport properties and local structure.

Understanding simple liquids through statistical and deep learning approaches

Statistical and deep learning-based methods are employed to obtain insights into the quasi-universal properties of simple liquids. In the first part, a statistical model is employed to provide a probabilistic explanation for the similarity in the structure of simple liquids interacting with different pair potential forms, collectively known as simple liquids. The methodology works by sampling the radial distribution function and the number of interacting particles within the cutoff distance, and it produces the probability density function of the net force. We show that matching the probability distribution of the net force can be a direct route to parameterize simple liquid pair potentials with a similar structure, as the net force is the main component of the Newtonian equations of motion. The statistical model is assessed and validated against various cases. In the second part, we exploit DeepILST [A. Moradzadeh and N. R. Aluru, J. Phys. Chem. Lett. 10, 1242-1250 (2019)], a data-driven and deep-learning assisted framework to parameterize the standard 12-6 Lennard-Jones (LJ) pair potential, to find structurally equivalent/isomorphic LJ liquids that identify constant order parameter [τ=∫₀ ^ξ_cf gξ-1ξ²dξ, where gξ and ξ(=rρ¹³) are the reduced radial distribution function and radial distance, respectively] systems in the space of non-dimensional temperature and density of the LJ liquids. We also investigate the consistency of DeepILST in reproducibility of radial distribution functions of various quasi-universal potentials, e.g., exponential, inverse-power-law, and Yukawa pair potentials, quantified based on the radial distribution functions and Kullback-Leibler errors. Our results provide insights into the quasi-universality of simple liquids using the statistical and deep learning methods.

Thermodynamics and Dynamics of Supercritical Water Pseudo-Boiling

Supercritical fluid pseudo-boiling (PB), recently brought to the attention of the scientific community, is the phenomenon occurring when fluid changes its structure from liquid-like (LL) to gas-like (GL) states across the Widom line. This work provides the first quantitative analysis on the thermodynamics and the dynamics of water's PB, since the understanding of this phase transition is mandatory for the successful implementation of technologies using supercritical water (scH2O) for environmental, energy, and nanomaterial applications. The study combines computational techniques with in situ neutron imaging measurements. The results demonstrate that, during isobaric heating close to the critical point, while water density drops by a factor of three in the PB transitional region, the system needs >16 times less energy to increase its temperature by 1 K than to change its structure from LL to GL phase. Above the PB-Widom line, the structure of LL water consists mainly of tetramers and trimers, while below the line mostly dimers and monomers form in the GL phase. At atomic level, the PB dynamics are similar to those of the subcritical water vaporization. This fundamental knowledge has great impact on water science, as it helps to establish the structure-properties relationship of scH2O.

Decelerated Liquid Dynamics Induced by Component-Dependent Supercooling in Hydrogen and Deuterium Quantum Mixtures

Isotopic mixtures of p-H₂ and o-D₂ molecules have been an attractive binary system because they include two kinds of purely isotopic molecules which possess the same electronic potential but the twice different mass inducing differently pronounced nuclear quantum effects (NQEs). Accessing details of structures and dynamics in such quantum mixtures combining complex molecular dynamics with NQEs of different strengths remains a challenging problem. Taking advantage of the nonempirical molecular dynamics method which describes p-H₂ and o-D₂ molecules, we found that the liquid dynamics slows down at a specific mixing ratio, which can be connected to the observed anomalous slowdown of crystallization in the quantum mixtures. We attributed the decelerated dynamics to the component-dependent supercooling of p-H₂ taking place in the mixtures, demonstrating that there is an optimal mixing ratio to hinder crystallization. The obtained physical insights will help in experimentally controlling and achieving unknown quantum mixtures including superfluid.