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At least 19 records

Non-local model for surface tension in fluid-fluid simulations

We propose a non-local model for surface tension obtained in the form of an integral of a molecular-force-like function with support 3.5e added to the Navier-Stokes momentum conservation equation. We demonstrate analytically and numerically that with the non-local model interfaces with a radius of curvature larger than the support length behave macroscopically and microscopically, otherwise. For static droplets, the pressure difference Pe,in - Pe,out satisfies the Young-Laplace law for droplet radius greater than 3.5e and other- wise deviates from the Young-Laplace law. The latter indicates that the surface tension in the proposed model decreases with decreasing radius of curvature, which agrees with molecular dynamics and experimental studies of nanodroplets. Using the non-local model we perform numerical simulations of droplets under dynamic conditions, including a rising droplet, a droplet in shear flow, and two colliding droplets in shear flow, and compare results with a standard Navier-Stokes model subject to the Young-Laplace boundary condition at the fluid-fluid interface implemented via the Conservative Level Set (CLS) method. We find good agreement with existing numerical methods and analytical results for a rising macroscopic droplet and a droplet in a shear flow. For colliding droplets in shear flow, the non- local model converges (with respect to the grid size) to the correct behavior, including sliding, coalescence, and merging and breaking of two droplets depending on the capillary number. In contrast, we find that the results of the CLS model are highly grid-size dependent.

Howard, Amanda A.↗

Designing slippery rough surfaces to enhance dropwise condensation of low surface tension fluid

Enhancing low surface tension liquid condensation is critical for achieving high energy efficiency and reducing the size of thermal energy systems. Extensive research has focused on promoting dropwise condensation of these liquids using state-of-the-art coatings on plain surfaces. However, maintaining dropwise condensation with low surface tension fluids is challenging due to rivulet formation, resulting in wetted tails that transition to filmwise condensation at elevated heat fluxes. Here, to address this issue, we uncover the role of surface structures and surface chemistry in the dropwise condensation of low surface tension ethanol on slippery rough surfaces (SRS). High-performance dropwise condensation has been achieved on slippery microchannels grafted with perfluoropolyether. The SRS uniquely facilitates rapid lateral droplet removal, enabling faster directional droplet shedding without rivulet formation. The resulting higher droplet removal frequency on SRS leads to heat transfer coefficients 100 % and 500 % higher than conventional dropwise and filmwise condensation on plain surfaces, respectively. Our findings uncover the pivotal role of rapid droplet removal through slippery microchannels in sustaining dropwise condensation of low surface tension liquids. This study introduces a new paradigm for promoting dropwise condensation using engineered SRS that incorporates surface structure and surface chemistry. The work will provide fundamental design guidelines to design efficient and compact condensers that use costly or flammable low global warming potential refrigerants in future refrigeration systems.

Dropwise condensation↗

Patterned Quasi-Liquid Surfaces for Condensation of Low Surface Tension Fluids

Extensive research concerns dropwise condensation of low surface tension fluids to promote energy efficiency and decarbonization in thermal energy systems. However, it is challenging as these fluids typically result in filmwise condensation. Drawing inspiration from the Namib desert beetle that enhances condensation through patterned wettability, conventional beetle-inspired surfaces excel in water condensation but flood when condensing low surface tension fluids. In this work, a patterned quasi-liquid surface is reported that achieves exceptional dropwise condensation of low surface tension fluids. The surface consists of alternating stripes with low surface energy, that is, a perfluoropolyether (PFPE) and fluorinated quasi-liquid surface (FQLS), that shows ultralow contact angle hysteresis for ethanol and hexane. Further, the PFPE stripes are slightly more slippery, acting as slippery bridges that accelerate droplet coalescence and removal. It is experimentally demonstrated that the striped PFPE-FQLS pattern exhibits a heat transfer coefficient 85%, 330%, and 550% higher than that of PFPE, fluorinated silane, and filmwise condensation, respectively. This study reveals that a high contact angle is desired to sustain dropwise condensation, irrespective of contact angle hysteresis. These findings provide a new paradigm for promoting the dropwise condensation of low surface tension fluids and offer valuable insights into surface design for energy sustainability.

36 MATERIALS SCIENCE↗

Impact of carbamate formation on the surface tension of epoxy‐amine curing systems

Abstract Epoxy‐amine reactive systems, including their surface tension, have been studied due to their use and importance in composites and adhesives in laboratory and industrial applications. Understanding how the system's surface tension changes during curing could help target applications for tailored composites. Using the Wilhelmy plate method, surface tensions for epoxy‐curing agent systems were investigated under different environments. While the epoxy exhibited an expected negative temperature coefficient of −0.096 mN/m/°C, the curing agent exhibited a positive temperature coefficient of 0.073 mN/m/°C, which is due to the curing agent reacting with atmospheric CO 2 to form carbamate through a zwitterion pathway and functional groups accumulating at the surface of the reacting systems. Carbamate formation results in a surface tension below that of the individual constituents in the epoxy‐amine curing agent system. Fourier transform infrared (FTIR) spectroscopy was used to verify in situ formation of carbamate, and by reducing the system's temperature, it was demonstrated that the system surface tension profiles displayed micellar surfactant‐like characteristics. FTIR was used to explore the difference in composition between the surface and the bulk, in particular carbamate formation at the surface, resulting in a lowering of the surface tension of reacting systems.

Shenk, Timothy M.↗

Comparison of Surface Tension Generation Methods in Smoothed Particle Hydrodynamics for Dynamic Systems

Developing robust numerical models of dynamic surface tension dominated multiphase systems is an ongoing challenge, especially in scenarios with large density and viscosity ratios. This is critical to the design and understanding of various physical and engineering systems, such as fluidized beds, fuel injectors, and drug delivery schemes. Much of the computational work in surface tension dominated multiphase flows has employed the continuum surface force method (CSF) of Brackbill et al. [1], which recasts surface tension from a surface force to a volumetric force that can be imposed in the vicinity of an interface. The CSF method produces accurate results across a variety of systems, however it relies on the identication of surface normals, which can be unreliable under certain conditions. Alternative methods of simulating surface tension have been proposed. Here the advantages and disadvantages of the CSF method in comparison to a pairwise forces (PF) method proposed by Tartakovsky and Panchenko [2] are explored. The CSF and PF methods are used in a smoothed particle hydrodynamics (SPH) framework to model dynamic systems. Results are compared to existing test cases from the literature and to analytic solutions derived from fundamental normal mode behavior of bubbles and droplets. A physical system for which the PF method is more stable and physically appropriate than the CSF method is identied.

smoothed particle hydrodynamics, multiphase flow↗

The importance of accounting for the Tolman correction to surface tension for nucleation and growth modeling of Fe clusters

Gibbs free energies of clusters are required for predictive modeling of cluster growth during condensation of a cooling vapor. Here, we present a straightforward method of calculating free energies of cluster formation using the data from molecular dynamics (MD) simulations. We apply this method to iron clusters having from 2 to 100 atoms. The energies obtained are verified by comparing to an MD-simulated equilibrium cluster size distribution in a sub-saturated vapor. We show that these free energies differ significantly from those obtained with a commonly used spherical cluster approximation, which relies on a surface tension coefficient of a flat surface, as it is used in the classical nucleation theory (CNT). We show that the spherical cluster approximation in CNT can be improved by using a cluster-size-dependent Tolman correction for the surface tension. The Tolman length and effective surface tension values were derived for iron clusters, and they significantly differ from the commonly used experimentally measured values. This improved approximation does not account for geometric magic number effects responsible for spikes and troughs in densities of neighbor cluster sizes. Nonetheless, it allows to more accurately model cluster formation from a cooling vapor. It better reproduces the condensation timeline, overall shape of the cluster size distribution, average cluster size, and the distribution width. In contrast, using a constant surface tension coefficient (as done in CNT) resulted in incorrect condensation dynamics and cluster size distributions. The analytical expression for cluster nucleation rate from CNT was updated to account for the size-dependence of cluster surface tension.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The mechanics of nucleation and growth and the surface tensions of active matter

Homogeneous nucleation, a textbook transition path for phase transitions, is typically understood on thermodynamic grounds through the prism of classical nucleation theory. However, recent studies have suggested the applicability of classical nucleation theory to systems far from equilibrium. Here, in this article, we formulate a purely mechanical perspective of homogeneous nucleation and growth, elucidating the criteria for the properties of a critical nucleus without appealing to equilibrium notions. Applying this theory to active fluids undergoing motility-induced phase separation, we find that nucleation proceeds in a qualitatively similar fashion to equilibrium systems, with concepts such as the Gibbs–Thomson effect and nucleation barriers remaining valid. We further demonstrate that the recovery of such concepts allows us to extend classical theories of nucleation rates and coarsening dynamics to active systems upon using the mechanically derived definitions of the nucleation barrier and surface tensions. Three distinct surface tensions—the mechanical, capillary, and Ostwald tensions—play a central role in our theory. While these three surface tensions are identical in equilibrium, our work highlights the distinctive role of each tension in the stability of active interfaces and the nucleation and growth of motility-induced phases.

Capillary waves↗

Molten Halide Salt Surface Tension: Methods and Correlations

Here, this paper reviews various methods for studying surface tension and their applicability to fluoride and chloride molten salt systems, including a comparison of benefits and drawbacks. Such a comparison aids in experiment design based on desired factors such as scale, accuracy, and repeatability. A detailed review is presented for existing literature data regarding the surface tension of molten fluoride and chloride salts. These reference data were compiled and analyzed to determine cross-validated correlation equations for several alkali and alkaline earth fluoride and chloride salts as functions of temperature. These correlations are necessary for reliable multiphysics modeling approaches as well as accurate design and analysis of multiphase molten salt phenomena such as gas sparging and bubble formation/transport. This analysis supports the development of the thermophysical arm of the Molten Salt Thermal Properties Database (MSTDB-TP) managed by Oak Ridge National Laboratory.

Chloride↗

A small-volume, high-throughput approach for surface tension and viscosity measurements of liquid fuels

An ongoing effort looking at bioblendstocks to function as drop-in replacements or blending components for gasoline has identified a large number of candidate fuels. This work documents an approach for rapid screening of candidate fuels using relatively small sample sizes ($\mathcal{O}(\mu\,{\rm l})$) that targets two key physical properties of liquid fuels—surface tension and viscosity. The approach utilizes shape oscillation dynamics of single droplets generated by a piezo-electric device and their decay over time. Strobed imaging of the oscillation process is used along with image processing, edge detection, and data analysis to capture the decay of the oscillation over time. The time constant of the decay process along with oscillation frequency are then used to estimate viscosity and surface tension using a theory for small amplitude droplet oscillations. Measurements are obtained for primary reference fuels (isooctane and n-heptane) as well as candidate fuels from four bio-derived functional groups of interest. Measurement results for surface tension and viscosity are correlated with literature data as well as measurements from standard reference instruments. The measurement results show that the droplet oscillation based approach is capable of reproducing surface tension and viscosity values for the tested fuels within deviations of 7% and 13% respectively from literature data. Results are obtained using an average of 5 µl per fuel within about 20 s, thus demonstrating a small-volume, high-throughput approach that can be used for screening of candidate bioblendstock fuels.

09 BIOMASS FUELS↗

Deep Learning Approaches for Predicting the Surface Tension of Ionic Liquids

Ionic liquids (ILs) are a novel class of solvents that have attracted significant attention due to their unique and tunable properties. Among their physiochemical characteristics, surface tension plays a critical role in various industrial applications including electrolytes, heat transfer fluids, and separation processes. However, because of the exploratory nature of IL design and the vast combinatorial space of possible anion–cation pairs, the experimental determination of these properties is often impractical, being both time-consuming and costly. To overcome these challenges, computational approaches are increasingly employed to develop accurate predictive models that can accelerate IL discovery and design. In this study, we present two deep learning (DL) models for predicting the surface tension of ILs across a broad temperature range at a constant pressure. The models use simplified molecular input line entry system, SMILES, representations of ILs to extract molecular features as inputs. Both DL models demonstrate excellent agreement with experimental data, achieving an R 2 value of 0.990 and a root-mean-square error of 0.792 mN/m. In conclusion, these results offer valuable insights for the rapid screening and rational design of ILs with tailored surface tension values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predictive understanding of the surface tension and velocity of sound in ionic liquids using machine learning

Knowledge of the physical properties of ionic liquids (ILs), such as the surface tension and speed of sound, is important for both industrial and research applications. Unfortunately, technical challenges and costs limit exhaustive experimental screening efforts of ILs for these critical properties. Previous work has demonstrated that the use of quantum-mechanics-based thermochemical property prediction tools, such as the conductor-like screening model for real solvents, when combined with machine learning (ML) approaches, may provide an alternative pathway to guide the rapid screening and design of ILs for desired physiochemical properties. However, the question of which machine-learning approaches are most appropriate remains. In the present study, we examine how different ML architectures, ranging from tree-based approaches to feed-forward artificial neural networks, perform in generating nonlinear multivariate quantitative structure–property relationship models for the prediction of the temperature- and pressure-dependent surface tension of and speed of sound in ILs over a wide range of surface tensions (16.9–76.2 mN/m) and speeds of sound (1009.7–1992 m/s). The ML models are further interrogated using the powerful interpretation method, shapley additive explanations. We find that several different ML models provide high accuracy, according to traditional statistical metrics. The decision tree-based approaches appear to be the most accurate and precise, with extreme gradient-boosting trees and gradient-boosting trees being the best performers. However, our results also indicate that the promise of using machine-learning to gain deep insights into the underlying physics driving structure–property relationships in ILs may still be somewhat premature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measuring the density, viscosity, and surface tension of molten titanates using electrostatic levitation in microgravity

Rare earth and barium titanates are useful as ferroelectric, dielectric, and optical materials. Measurements of their thermophysical properties in the liquid state can help guide melt processing technologies for their manufacture and advance understanding of fragile liquids' behavior and glass formation. Here, we report the density, thermal expansion, viscosity, and surface tension of molten BaTi 2 O 5 , BaTi 4 O 9 , and 83TiO 2 -17RE 2 O 3 (RE = La or Nd). Measurements were made using electrostatic levitation and droplet oscillation techniques in microgravity, which provide access to quiescent liquid droplets and deep supercooling of 510–815 K below the equilibrium melting points. Densities were measured over 900–2400 K. Viscosities were similar for all four compositions, increasing from ~10 mPa s near 2100 K to ~30 mPa s near 1750 K. Surface tensions were 450–490 dyn cm -1 for the rare earth titanates and 383–395 dyn cm -1 for the barium titanates; surface tensions of all compositions had small or negligible temperature dependence over 1700–2200 K. In conclusion, for solids recovered after melt quenching, x-ray microtomography revealed the fracture mechanics in crystalline products and minimal internal porosity in glass products, likely arising from entrapped gas bubbles. Internal microstructures were generally similar for products processed either in microgravity or in a terrestrial aerodynamic levitator.

42 ENGINEERING↗

Implementation of Surface Tension on a Reacting Flow Solver, PeleLM: Preprint

In liquid rocket engines, the fuel is supplied to the combustion chamber in the liquid state though injectors. Such fuel undergoes atomization, vaporization, and combustion processes. To design reliable and efficient injectors, it is required to understand the full processes. This research is part of an effort to develop a full atomization-vaporization-combustion solver from first principles. As an initial step to tackle the atomization process, a multiphase flow solver is under development. For the development, a library of the volume of fluid scheme for multiphase, IRL is coupled with a reacting Navier-Stokes equation solver, PeleLM. Furthermore, as the surface tension has considerable effects on spray breakup. surface tension is implemented in the momentum equation using the continuum surface force model and the improved height function technique.

height function↗

Quantum Chemistry-Driven Machine Learning Approach for the Prediction of the Surface Tension and Speed of Sound in Ionic Liquids

Ionic liquids (ILs) have unique solvent properties and have thus garnered significant interest. However, exhaustive experimental determination of the physicochemical properties of ILs is unrealistic due to the large structural diversity of anions and cations, their high cost, the requirements of elevated temperature and pressure, and the time required. To circumvent these experimental costs, computational approaches to accurately calculate these properties have emerged. Here in the present study, we present a demonstration of two machine learning (ML) models for the prediction of two critical IL physical properties, the surface tension and the speed of sound, across a wide range of temperatures and pressures. The models make use of molecular descriptors derived from the COSMO-RS, a quantum chemical-based model. The ML models show excellent agreement with experimental observations, with an R2 value of 0.96–0.99 and RMSE of 1.71 mN/m and 16.12 m/s for the surface tension and speed of sound, respectively. This work paves the way for the development of COSMO-RS-informed ML models for the prediction of IL properties which can help to further optimize and accelerate technology development for ILs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface Tension of Dielectric–Air Interfaces

Analytical and semianalytical expressions for the surface tension of dielectric–air interfaces are presented after considering local and nonlocal dielectric effects near interfaces. It is shown that the nonlocal effects of dielectrics are significant for highly polar dielectric fluids such as water. Far from the interface, nonlocal dielectric effects are shown to cause not only the oscillatory potential of the mean force but also a reversal of sign at intermediate distances.

42 ENGINEERING↗

Optimal surface-tension isotropy in the Rothman-Keller color-gradient lattice Boltzmann method for multiphase flow

The Rothman-Keller color-gradient (CG) lattice Boltzmann method is a popular method to simulate two-phase flow because of its ability to deal with fluids with large viscosity contrasts and a wide range of interfacial tensions. Here, two fluids are labeled red and blue, and the gradient in the color difference is used to compute the effect of interfacial tension. It is well known that finite-difference errors in the color-gradient calculation lead to anisotropy of interfacial tension and errors such as spurious currents. Here, we investigate the accuracy of the CG calculation for interfaces between fluids with several radii of curvature and find that the standard CG calculations lead to significant inaccuracy. Specifically, we observe significant anisotropy of the color gradient of order 7% for high curvature of an interface such as when a pinchout occurs. We derive a second order accurate color gradient and find that the diagonal nearest neighbors can be weighted differently than in the usual color-gradient calculation such that anisotropy is minimized to a fraction of a percent. The optimal weights that minimize anisotropy for the smallest radius of curvature interface are found to be w = (0.298, 0.284, 0.275) for diagonal nearest neighbors for the cases of the interface smoothing parameter β = (0.5, 0.7, 0.99), somewhat higher than the w = 0.25 value derived by Leclaire et al. [Leclaire, Reggio, and Trepanier, Computers and Fluids 48, 98 (2011)] based on obtaining isotropic errors to second order. We find that use of these optimal w values yields over a factor of 10 decrease in anisotropy and over a factor of 30 decrease in mean anisotropy relative to using the standard w = 1 value. And we find a factor of about 2 decrease in the anisotropic error and up to factor 15 decrease in mean anisotropic error relative to the choice of w = 0.25 for small radius of curvature interfaces. The improved CG calculations will allow the method to be more reliably applied to studies of phenomenology and pore scale processes such as viscous and capillary fingering, and droplet formation where surface-tension isotropy of narrow fingers and small droplets plays a crucial role in correctly capturing phenomenology. We present an example illustrating how different phenomena can be captured using the improved color-gradient method. Namely, we present simulations of a wetting fluid invading a fluid filled pipe where the viscosity ratio of fluids is unity in which droplets form at the transition to fingering using the improved CG calculations that are not captured using the standard CG calculations. We present an explanation of why this is so which relates to anisotropy of the surface tension, which inhibits the pinchouts needed to form droplets.

58 GEOSCIENCES↗