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Under isothermal conditions, phase transitions occur through a nucleation event when conditions are sufficiently close to coexistence. The formation of a nucleus of the new phase requires the system to overcome a free energy barrier of formation, whose height rapidly rises as supersaturation decreases. This phenomenon occurs both in the bulk and under confinement and leads to a very slow kinetics for the transition, ultimately resulting in hysteresis, where the system can remain in a metastable state for a long time. This has broad implications, for instance, when using simulations to predict phase diagrams or screen porous materials for gas storage applications. Here, we leverage simulations in an adiabatic statistical ensemble, known as adiabatic grand-isochoric ensemble (μ, V, L) ensemble, to reach equilibrium states with a greater efficiency than its isothermal counterpart, i.e., simulations in the grand-canonical ensemble. For the bulk, we show that at low supersaturation, isothermal simulations converge slowly, while adiabatic simulations exhibit a fast convergence over a wide range of supersaturation. We then focus on adsorption and desorption processes in nanoporous materials, assess the reliability of (μ, V, L) simulations on the adsorption of argon in IRMOF-1, and demonstrate the efficiency of adiabatic simulations to predict efficiently the equilibrium loading during the adsorption and desorption of argon in MCM-41, a system that exhibits significant hysteresis. We provide quantitative measures of the increased rate of convergence when using adiabatic simulations. Adiabatic simulations explore a wide temperature range, leading to a more efficient exploration of the configuration space. [ABSTRACT FROM AUTHOR]

The entropy change that occurs upon mixing two fluids has remained an intriguing topic since the dawn of statistical mechanics. In this work, we generalize the grand-isobaric ensemble to mixtures and develop a Monte Carlo algorithm for the rapid determination of entropy in these systems. A key advantage of adiabatic ensembles is the direct connection they provide with entropy. Here, we show how the entropy of a binary mixture A–B can be readily obtained in the adiabatic grand-isobaric (μA, μB, P, R) ensemble, in which μA and μB denote the chemical potential of components A and B, respectively, P is the pressure, and R is the heat (Ray) function, that corresponds to the total energy of the system. This, in turn, allows for the evaluation of the entropy of mixing and the Gibbs free energy of mixing. We also demonstrate that our approach performs very well both on systems modeled with simple potentials and with complex many-body force fields. Finally, this approach provides a direct route to the determination of the thermodynamic properties of mixing and allows for the efficient detection of departures from ideal behavior in mixtures. [ABSTRACT FROM AUTHOR]

Dissipative systems often exhibit novel and unexpected properties. This is, for instance, the case of simple liquids, which, when subjected to shear and after reaching a steady state, can exhibit a negative entropy production over finite length scales and timescales. This result, among others, is captured by nonequilibrium relations known as fluctuation theorems. Using nonequilibrium molecular dynamics simulations, we examine how, by fine-tuning the properties of the components of a complex fluid, we can steer the nonequilibrium response of the fluid. More specifically, we show how we control the nonequilibrium probability distribution for the shear stress and, in turn, how often states with a negative entropy production can occur. To achieve this, we start by characterizing how the size for the liquid matrix impacts the probability of observing negative entropy states, as well as the timescale over which these can be observed. We then measure how the addition of larger particles to this liquid matrix, i.e., simulating a model colloidal suspension, results in an increase in the occurrence of such states. This suggests how modifications in the composition of the mixture and in the properties of its components lead to an increase in the probability of observing states of negative entropy production and, thus, for the system to run in reverse. [ABSTRACT FROM AUTHOR]

Entropy has become increasingly central to characterize, understand, and even guide assembly, self-organization, and phase transition processes. In this work, we build on the analogous role of partition functions (or free energies) in isothermal ensembles and that of entropy in adiabatic ensembles. In particular, we show that the grand-isobaric adiabatic (μ, P, R) ensemble, or Ray ensemble, provides a direct route to determine the entropy. This allows us to follow the variations of entropy with the thermodynamic conditions and thus explore phase transitions. We test this approach by carrying out Monte Carlo simulations on argon and copper in bulk phases and at phase boundaries. We assess the reliability and accuracy of the method through comparisons with the results from flat-histogram simulations in isothermal ensembles and with the experimental data. Advantages of the approach are multifold and include the direct determination of the μ–P relation, without any evaluation of pressure via the virial expression, the precise control of the system size (number of atoms) via the input value of R, and the straightforward computation of enthalpy differences for isentropic processes, which are key quantities to determine the efficiency of thermodynamic cycles. A new insight brought by these simulations is the highly symmetric pattern exhibited by both systems along the transition, as shown by scaled temperature–entropy and pressure–entropy plots. [ABSTRACT FROM AUTHOR]

Using nonequilibrium molecular dynamics simulations, we study the properties of supercooled liquids of Si under shear at T = 1060 K over a range of densities encompassing the low-density liquid (LDL) and high-density liquid (HDL) forms. This enables us to generate nonequilibrium steady-states of the LDL and HDL polymorphs that remain stabilized in their liquid forms for as long as the shear is applied. This is unlike the LDL and HDL forms at rest, which are metastable under those conditions and, when at rest, rapidly undergo a transition toward the crystal, i.e., the thermodynamically stable equilibrium phase. In particular, through a detailed analysis of the structural and energetic features of the liquids under shear, we identify the range of densities, as well as the range of shear rates, which give rise to the two forms. We also show how the competition between shear and tetrahedral order impacts the two-body entropy in steady-states of Si under shear. These results open the door to new ways of utilizing shear to stabilize forms that are metastable at rest and can exhibit unique properties, since, for instance, experiments on Si have shown that HDL is metallic with no bandgap, while LDL is semimetallic with a pseudogap. [ABSTRACT FROM AUTHOR]

The liquid-liquid hypothesis, which states that a pure substance can exhibit two liquid forms (or poly- morphs), has drawn considerable interest in recent years. The appeal of this theory is that it provides the basis for a deeper understanding of the properties of supercooled liquids. However, the study of this phenomenon is extremely challenging and a complete understanding of its impact on fluid properties has remained elusive so far, since the low-temperature liquid form is generally not stable and undergoes rapid crystallization. Using a coarse-grained model for methanol, we show that methanol under shear can exhibit, in the steady state, two liquid forms that respond differently to the applied shear. Using molecular simulations, we show that the difference in dynamical response is correlated with structural differences between the two liquid forms. This establishes the existence of liquid polymorphism for systems driven out-of-equilibrium. Our findings also show how, by varying the pressure or the shear stress applied to the system, liquid-liquid transitions can be triggered and how a control of liquid polymorphism can be achieved. The resulting solid-liquid-liquid nonequilibrium phase diagram leads us to identify new ways for the stabilization and study of liquid polymorphism. [ABSTRACT FROM AUTHOR]

Recent force microscopy experiments have shed light on new possible molecular structures for asphaltenes, which are key compounds for the oil industry. These studies have revealed the significance of asphaltenes with an island molecular architecture, i.e., composed of a large polycyclic aromatic hydrocarbon (PAH) core and alkyl side chains. In this work, we carry out molecular simulations based on a Wang-Landau sampling of the isothermal-isobaric ensemble to determine the thermodynamic properties of island-type asphaltenes at the vapor-liquid coexistence. We first parameterize a coarse-grained force field for these systems, focusing on compounds with a PAH core containing fluorene, fluoranthene, and dibenzothiophene motifs. Then, using this coarse-grained force field, we predict the entire phase envelope, including the boiling points and the critical parameters for a series of island-type asphaltenes. [ABSTRACT FROM AUTHOR]

Using molecular simulation, we analyze the capillary condensation and evaporation processes for argon confined in a cylindrical nanopore. For this purpose, we define the entropy of the adsorbed fluid as a reaction coordinate and determine the free energy associated with both processes along entropic pathways. For capillary condensation, we identify a complex free energy profile resulting from the multi-stage nature of this phenomenon. We find capillary condensation to proceed through the nucleation of a liquid bridge across the nanopore, followed by its expansion throughout the pore to give rise to the stable phase of high density. In the case of capillary evaporation, the free energy profile along the entropy pathway also exhibits different regimes, corresponding to the initial destabilization of the layered structure of the fluid followed by the formation, and subsequent expansion, of a bubble across the nanopore. [ABSTRACT FROM AUTHOR]

We review recent advances in the design, synthesis, and modeling of active fluids. Active fluids have been at the center of many technological innovations and theoretical advances over the past two decades. Research on this new class of fluids has been inspired by the fascinating and remarkably efficient strategies that biological systems employ, leading to the development of biomimetic nano- and micro-machines and swimmers. The review encompasses active fluids on both the nano- and micro-scale. We start with examples of biological active systems before we discuss how experimentalists leverage novel propulsion mechanisms to power nano- and micro-machines. We then examine how the study of these far-from-equilibrium systems has prompted the development of new simulation methods and theoretical models in nonequilibrium physics to account for their mechanical, thermodynamic, and emergent properties. Recent advances in the field have paved the way for the design, synthesis, and modeling of autonomous systems at the nano- and micro-scale and opened the door to the development of soft matter robotics. [ABSTRACT FROM AUTHOR]

Using molecular simulation, we study the nucleation of liquid droplets from binary mixtures and determine the free energy of nucleation along entropic pathways. To this aim, we develop the µ1µ2VT-S method, based on the grand-canonical ensemble modeling the binary mixture, and use the entropy of the system S as the reaction coordinate to drive the formation of the liquid droplet. This approach builds on the advantages of the grand-canonical ensemble, which allows for the direct calculation of the entropy of the system and lets the composition of the system free to vary throughout the nucleation process. Starting from a metastable supersaturated vapor, we are able to form a liquid droplet by gradually decreasing the value of S, through a series of umbrella sampling simulations, until a liquid droplet of a critical size has formed. The µ1µ2VT-S method also allows us to calculate the free energy barrier associated with the nucleation process, to shed light on the relation between supersaturation and free energy of nucleation, and to analyze the interplay between the size of the droplet and its composition during the nucleation process. [ABSTRACT FROM AUTHOR]

Using the entropy S as a reaction coordinate, we determine the free energy barrier associated with the formation of a liquid droplet from a supersaturated vapor for atomic and molecular fluids. For this purpose, we develop the µVT-SµVT-S simulation method that combines the advantages of the grand-canonical ensemble, that allows for a direct evaluation of the entropy, and of the umbrella sampling method, that is well suited to the study of an activated process like nucleation. Applying this approach to an atomic system such as Ar allows us to test the method. The results show that the µVT-S method gives the correct dependence on supersaturation of the height of the free energy barrier and of the size of the critical droplet, when compared to predictions from the classical nucleation theory and to previous simulation results. In addition, it provides insight into the relation between the entropy and droplet formation throughout this process. An additional advantage of the µVT-S approach is its direct transferability to molecular systems, since it uses the entropy of the system as the reaction coordinate. Applications of the µVT-S simulation method to N2 and CO2 are presented and discussed in this work, showing the versatility of the µVT-SµVT-S approach. [ABSTRACT FROM AUTHOR]

Using molecular simulation, we assess the impact of an electric field on the properties of water, modeled with the SPC/E potential, over a wide range of states and conditions. Electric fields of the order of 0.1 V/Å and beyond are found to have a significant impact on the grand-canonical partition function of water, resulting in shifts in the chemical potential at the vapor-liquid coexistence of up to 20%. This, in turn, leads to an increase in the critical temperatures by close to 7% for a field of 0.2 V/Å, to lower vapor pressures, and to much larger entropies of vaporization (by up to 35%). We interpret these results in terms of the greater density change at the transition and of the increased structural order resulting from the applied field. The thermodynamics of compressed liquids and of supercritical water are also analyzed over a wide range of pressures, leading to the determination of the Zeno line and of the curve of ideal enthalpy that span the supercritical region of the phase diagram. Rescaling the phase diagrams obtained for the different field strengths by their respective critical properties allows us to draw a correspondence between these systems for fields of up to 0.2 V/Å. [ABSTRACT FROM AUTHOR]

We extend Expanded Wang-Landau (EWL) simulations beyond classical systems and develop the EWL method for systems modeled with a tight-binding Hamiltonian. We then apply the method to determine the partition function and thus all thermodynamic properties, including the Gibbs free energy and entropy, of the fluid phases of Si. We compare the results from quantum many-body (QMB) tight binding models, which explicitly calculate the overlap between the atomic orbitals of neighboring atoms, to those obtained with classical many-body (CMB) force fields, which allow to recover the tetrahedral organization in condensed phases of Si through, e.g., a repulsive 3-body term that favors the ideal tetrahedral angle. Along the vapor-liquid coexistence, between 3000 K and 6000 K, the densities for the two coexisting phases are found to vary significantly (by 5 orders of magnitude for the vapor and by up to 25% for the liquid) and to provide a stringent test of the models. Transitions from vapor to liquid are predicted to occur for chemical potentials that are 10%-15% higher for CMB models than for QMB models, and a ranking of the force fields is provided by comparing the predictions for the vapor pressure to the experimental data. QMB models also reveal the formation of a gap in the electronic density of states of the coexisting liquid at high temperatures. Subjecting Si to a nanoscopic confinement has a dramatic effect on the phase diagram with, e.g. at 6000 K, a decrease in liquid densities by about 50% for both CMB and QMB models and an increase in vapor densities between 90% (CMB) and 170% (QMB). The results presented here provide a full picture of the impact of the strategy (CMB or QMB) chosen to model many-body effects on the thermodynamic properties of the fluid phases of Si. [ABSTRACT FROM AUTHOR]

Combining rules, such as the Lorentz-Berthelot rules, are routinely used to calculate the thermodynamic properties of mixtures using molecular simulations. Here we extend the expanded Wang-Landau simulation approach to determine the impact of the combining rules on the value of the partition function of binary systems, and, in turn, on the phase coexistence and thermodynamics of these mixtures. We study various types of mixtures, ranging from systems of rare gases to biologically and technologically relevant mixtures, such as water-urea and water-carbon dioxide. Comparing the simulation results to the experimental data on mixtures of rare gases allows us to rank the performance of combining rules. We find that the widely used Lorentz-Berthelot rules exhibit the largest deviations from the experimental data, both for the bulk and at coexistence, while the Kong and Waldman-Hagler provide much better alternatives. In particular, in the case of aqueous solutions of urea, we show that the use of the Lorentz-Berthelot rules has a strong impact on the Gibbs free energy of the solute, overshooting the value predicted by the Waldman-Hagler rules by 7%. This result emphasizes the importance of the combining rule for the determination of hydration free energies using molecular simulations. [ABSTRACT FROM AUTHOR]

We propose to apply expanded Wang-Landau simulations to study the adsorption of atomic and molecular fluids in porous materials. This approach relies on a uniform sampling of the number of atoms and molecules adsorbed. The method consists in determining a high-accuracy estimate of the grand-canonical partition function for the adsorbed fluids. Then, using the formalism of statistical mechanics, we calculate absolute and excess thermodynamic properties relevant to adsorption processes. In this paper, we examine the adsorption of argon and carbon dioxide in the isoreticular metal-organic framework (IRMOF-1). We assess the reliability of the method by showing that the predicted adsorption isotherms and isosteric heats are in excellent agreement with simulation results obtained from grand-canonical Monte Carlo simulations. We also show that the proposed method is very efficient since a single expanded Wang-Landau simulation run at a given temperature provides the whole adsorption isotherm. Moreover, this approach provides a direct access to a wide range of thermodynamic properties, such as, e.g., the excess Gibbs free energy and the excess entropy of adsorption. [ABSTRACT FROM AUTHOR]

The Wang-Landau sampling is a powerful method that allows for a direct determination of the density of states. However, applications to the calculation of the thermodynamic properties of realistic fluids have been limited so far. By combining the Wang-Landau method with expanded grand-canonical simulations, we obtain a high-accuracy estimate for the grand-canonical partition function for atomic and molecular fluids. Then, using the formalism of statistical thermodynamics, we are able to calculate the thermodynamic properties of these systems, for a wide range of conditions spanning the single-phase regions as well as the vapor-liquid phase boundary. Excellent agreement with prior simulation work and with the available experimental data is obtained for argon and CO2, thereby establishing the accuracy of the method for the calculation of thermodynamic properties such as free energies and entropies. [ABSTRACT FROM AUTHOR]

Using molecular simulation, we study the molecular mechanisms underlying the nucleation and growth of C60 nanoparticles from the supersaturated vapor and from the undercooled liquid. We show that in both cases, nucleation proceeds through the formation of small clusters composed of the metastable hexagonal close-packed (HCP) polymorph. This observation differs from the nucleation pathway of simple systems (e.g., modeled by Lennard-Jones potential) in which the nucleation proceeds through the metastable body-centered cubic polymorph. We rationalize this observation in terms of the relative steepness of the repulsion for the different potential models. Finally, we observe two different types of growth leading either to crystallites dominated by the metastable HCP polymorph or to crystallites whose structure is predominantly that of the stable face-centered cubic (FCC) polymorph. This finding is consistent with experiments on the crystallization of C60 from the vapor, which reported the formation of FCC and HCP crystals. [ABSTRACT FROM AUTHOR]

In recent years, powerful and accurate methods, based on a Wang–Landau sampling, have been developed to determine phase equilibria. However, while these methods have been extensively applied to study the phase behavior of model fluids, they have yet to be applied to molecular systems. In this work, we show how, by combining hybrid Monte Carlo simulations in the isothermal-isobaric ensemble with the Wang–Landau sampling method, we determine the vapor-liquid equilibria of various molecular fluids. More specifically, we present results obtained on rigid molecules, such as benzene, as well as on flexible chains of n-alkanes. The reliability of the method introduced in this work is assessed by demonstrating that our results are in excellent agreement with the results obtained in previous work on simple fluids, using either transition matrix or conventional Monte Carlo simulations with a Wang–Landau sampling, and on molecular fluids, using histogram reweighting or Gibbs ensemble Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

We report on nonequilibrium molecular dynamics (NEMD) simulations results on the shear viscosity of liquid copper, modeled by a many-body embedded-atoms model potential. Because conventional NEMD methods are restricted to very high shear rates (at least of the order of 1010 s-1, that is several orders of magnitude larger than those accessible by experiment), previous work only provided access to the response of the fluid in the shear-thinning regime. Using the transient-time correlation function formalism, we show how NEMD simulations can be extended to study the rheological properties of liquid copper subjected to low, experimentally accessible, shear rates. Our results provide a full picture of the rheology of the system, in the Newtonian regime as well as in the shear-thinning regime. [ABSTRACT FROM AUTHOR]

We report hybrid Monte Carlo molecular simulation results on the crystallization of aluminum from the supercooled liquid. We simulate the entire crystallization process at P=1 atm and at temperatures 20% and 15% below the melting temperature. We demonstrate that crystallization takes place according to the same mechanism for the two degrees of supercooling considered in this work. We show that both nucleation and growth proceed into a random mixing of the hexagonal close packed structure and of the face centered cubic (fcc) phase, with a predominance of the stable fcc form. The concentration of icosahedral (Ih)-like atoms in the supercooled liquid is found to remain constant throughout nucleation and growth, showing that Ih-like atoms do not play an active role in the crystallization process. We also find that the crystallization mechanism of aluminum differs from that observed for simple fluids. While nucleation of simple fluids first proceeds into the metastable body centered cubic (bcc) phase, the fraction of bcc-like atoms in aluminum crystallites always remains very low. [ABSTRACT FROM AUTHOR]

Using molecular-dynamics simulations, we study the crystallization of supercooled liquids of charge-stabilized colloidal suspensions, modeled by the Yukawa (screened-Coulomb) potential. By modifying the value of the screening parameter λ, we are able to invert the stability of the body-centered cubic (bcc) and face-centered cubic (fcc) polymorphs and study the crystal nucleation and growth in the domain of stability of each polymorph. We show that the crystallization mechanism strongly depends on the value of λ. When bcc is the stable polymorph (λ=3), the crystallization mechanism is straightforward. Both kinetics and thermodynamics favor the formation of the bcc particles and polymorph selection takes place early during the nucleation step. When fcc is the stable polymorph (λ=10), the molecular mechanism is much more complex. First, kinetics favor the formation of bcc particles during the nucleation step. The growth of the post-critical nucleus proceeds through the successive cross-nucleation of the stable fcc polymorph on the metastable hcp polymorph as well as of the hcp polymorph on the fcc polymorph. As a result, polymorph selection occurs much later, i.e., during the growth step, than for λ=3. We then extend our findings established in the case of homogeneous crystal nucleation to a situation of practical interest, i.e., when a seed of the stable polymorph is used. We demonstrate that the growth from the (111) face of a perfect fcc crystal into the melt proceeds through the same mechanisms. [ABSTRACT FROM AUTHOR]

The integration of nanomaterials with biomolecules has recently led to the development of new ways of designing biosensors, and through their assembly, to new hybrid structures for novel and exciting applications. In this work, we develop a coarse-grained model for nanoparticles grafted with antibody molecules and their binding with antigens. In particular, we isolate two possible states for antigen-antibody pairs during the binding process, termed as recognition and anchoring states. Using molecular simulation, we calculate the thermodynamic and structural features of three possible crystal structures or polymorphs, the body-centered cubic, simple cubic, and face-centered cubic phases, and of the melt. This leads us to determine the domain of stability of the three solid phases. In particular, the role played by the switching process between anchoring and recognition states during melting is identified, shedding light on the complex microscopic mechanisms in these systems. [ABSTRACT FROM AUTHOR]

Using machine learning (ML), we predict the partition functions and, thus, all thermodynamic properties of atomic and molecular fluids over a wide range of temperatures and pressures. Our approach is based on training neural networks using, as a reference, the results of a few flat-histogram simulations. The neural network weights so obtained are then used to predict fluid properties that are shown to be in excellent agreement with the experiment and with simulation results previously obtained on argon, carbon dioxide, and water. In particular, the ML predictions for the Gibbs free energy, Helmholtz free energy, and entropy are shown to be highly accurate over a wide range of conditions and states for bulk phases as well as for the conditions of phase coexistence. Our ML approach thus provides access instantly to G, A, and S, thereby eliminating the need to carry out any additional simulations to explore the dependence of the fluid properties on the conditions of temperature and pressure. This is of particular interest, for e.g., the screening of new materials, as well as in the parameterization of force fields, for which this ML approach provides a rapid way to assess the impact of new sets of parameters on the system properties.