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At least 487 records · Page 27

Coalescence and splashing threshold for head-on collisions of liquid metal nanodroplets

Head-on collisions of liquid metal nanodroplets in a vacuum are investigated through molecular dynamics simulations in order to determine the transition threshold between the coalescing and splashing regimes for six different materials (aluminum, calcium, cerium, gold, platinum, and tin). Droplets of various sizes and initial speeds are simulated, and it is found that the Reynolds and Ohnesorge numbers are able to predict the transition between the coalescing and splashing regimes. An energy balance for coalescing droplets shows that the initial energy is mainly converted to thermal energy increasing the temperature of the combined droplets by several hundred to several thousand kelvin depending on the material, and this result is confirmed in the simulations. Furthermore, when splashing occurs, the number of smaller droplets formed and the spreading rate are found to be dependent on the initial size and initial speed of the original droplets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Trapping and imaging dynamic battery nanointerfaces via electrified cryo-EM

The electrified interface between a liquid and a solid underpins diverse phenomena, from ion-transfer during battery operation to action potentials enabling biological communication. However, conventional tools are blind to the nanoscale dynamics of this metastable interface. Here, we leverage electrified cryo–electron microscopy (eCryo-EM), a technique that rapidly freezes and kinetically traps these dynamic, nonequilibrium states during battery operation for nanoscale characterization. Collective snapshots of the electrified interface at controlled time intervals quantifies early-stage growth kinetics of the solid electrolyte interphase (SEI), a passivation film that governs electron and ion transport. Unexpectedly, the diffusivity of charged species of the two SEI films with differing chemistry and performance are estimated to be within 10% of the other, indicated by the slope of their diffusion-limited SEI growth regimes. Instead, the slope of the reaction-limited SEI growth regimes differs by a factor of 3, suggesting that lowered reactivity of the high-performance electrolyte is largely responsible for its high coulombic efficiency.

Science & Technology - Other Topics↗

Ionic Contraction across the Lanthanide Series Decreases the Temperature-Induced Disorder of the Water Coordination Sphere

In liquid, temperature affects the structures of lanthanide complexes in multiple ways that depend upon complex interactions between ligands, anions, and solvent molecules. The relative simplicity of lanthanide aqua ions (Ln 3+ ) make them well suited to determine how temperature induces structural changes in lanthanide complexes. In this work, we performed a combination of ab initio molecular dynamics (AIMD) simulations and extended X-ray absorption fine structure (EXAFS) measurements, both at 25 and 90 °C, to determine how temperature affects the first- and second-coordination spheres of three Ln 3+ (Ce 3+ , Sm 3+ , and Lu 3+ ) aqua ions. AIMD simulations show first lanthanide coordination spheres that are similar at 25 and 90 °C, more so for the Lu 3+ ion that remains as eight-coordinate than for the Ce 3+ and Sm 3+ ions that change their preferred coordination number from nine (at 25 °C) to eight (at 90 °C). The measured EXAFS spectra are very similar at 25 and 90 °C, for the Ce 3+ , Sm 3+ , and Lu 3+ ions, suggesting that the dynamical disorder of the Ln 3+ ions in liquid water is sufficient such that temperature-induced changes do not clearly manifest changes in the structure of the three ions. Both AIMD simulations and EXAFS measurements show very similar structures of the first coordination sphere of the Lu 3+ ion at 25 and 90 °C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shadow molecular dynamics and atomic cluster expansions for flexible charge models

A shadow molecular dynamics scheme for flexible charge models is presented, where the shadow Born-Oppenheimer potential is derived from a coarse-grained approximation of range-separated density functional theory. The interatomic potential, including the atomic electronegativities and the charge-independent short-range part of the potential and force terms, are modeled by the linear atomic cluster expansion (ACE), which provides a computationally efficient alternative to many machine learning methods. The shadow molecular dynamics scheme is based on extended Lagrangian (XL) Born-Oppenheimer molecular dynamics (BOMD) [Eur. Phys. J. B 94, 164 (2021)]. XL-BOMD provides a stable dynamics, while avoiding the costly computational overhead associated with solving an all-to-all system of equations, which normally is required to determine the relaxed electronic ground state prior to each force evaluation. To demonstrate the proposed shadow molecular dynamics scheme for flexible charge models using the atomic cluster expansion, we emulate the dynamics generated from self-consistent charge density functional tight-binding (SCC-DFTB) theory using a second-order charge equilibration (QEq) model. The charge-independent potentials and electronegativities of the QEq model are trained for a supercell of uranium oxide (UO2) and a molecular system of liquid water. The combined ACE + XL-QEq dynamics are stable over a wide range of temperatures both for the oxide and the molecular systems, and provide a precise sampling of the Born-Oppenheimer potential energy surfaces. Accurate ground Coulomb energies are produced by the ACE-based electronegativity model during an NVE simulation of UO 2 , predicted to be within 1 meV of those from SCC-DFTB on average during comparable simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗

Machine learning accelerated turbulence modeling of transient flashing jets

We report modeling the sudden depressurization of superheated liquids through nozzles is a challenge because the pressure drop causes rapid flash boiling of the liquid. The resulting jet usually demonstrates a wide range of structures, including ligaments and droplets, due to both mechanical and thermodynamic effects. As the simulation comprises increasingly numerous phenomena, the computational cost begins to increase. One way to moderate the additional cost is to use machine learning surrogacy for specific elements of the calculation. This study presents a machine learning-assisted computational fluid dynamics approach for simulating the atomization of flashing liquids accounting for distinct stages, from primary atomization to secondary breakup to small droplets using the Σ - Y model coupled with the homogeneous relaxation model. Notably, the models for thermodynamic non-equilibrium (HRM) and Σ - Y are coupled, for the first time, with a deep neural network that simulates the turbulence quantities, which are then used in the prediction of superheated liquid jet atomization. The data-driven component of this method is used for turbulence modeling, avoiding the solution of the two-equation turbulence model typically used for Reynolds-averaged Navier-Stokes simulations for these problems. Both the accuracy and speed of the hybrid approach are evaluated, demonstrating adequate accuracy and at least 25% faster computational fluid dynamics simulations than the traditional approach. This acceleration suggests that perhaps additional components of the calculation could be replaced for even further benefit. Published under an exclusive license by AIP Publishing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The influence of random packed column parameters on the liquid holdup and interfacial area

Abstract Carbon dioxide capture via solvent absorption in packed columns has emerged as a potential technology to mitigate coal‐fired power plant CO 2 emissions. Parameters, including packing types, solvent properties, and operating conditions, could potentially affect the packed column CO 2 capture efficiency. To understand the importance of those parameters and help packed column optimization, a design of experiments (DoEs) method was proposed to generate input parameter matrix. Combined with multiphase computational fluid dynamics (CFD), the random packed column parameter influence on the liquid holdup and interfacial area can be efficiently investigated. Surrogate‐based sensitivity analysis shows that the solvent flow rate and contact angle are key factors dictating liquid holdup and interfacial area. On the other hand, solvent viscosity has a marginal impact on the interfacial area. The sensitivity scores were calculated for each input parameter to guide the selection of dimensionless numbers for the liquid holdup and interfacial area correlation development.

42 ENGINEERING↗

Imaging Field–Driven Melting of a Molecular Solid at the Atomic Scale

Solid–liquid phase transitions are basic physical processes, but atomically resolved microscopy has yet to capture their full dynamics. A new technique is developed for controlling the melting and freezing of self–assembled molecular structures on a graphene field–effect transistor (FET) that allows phase–transition behavior to be imaged using atomically resolved scanning tunneling microscopy. This is achieved by applying electric fields to 2,3,5,6–tetrafluoro–7,7,8,8–tetracyanoquinodimethane–decorated FETs to induce reversible transitions between molecular solid and liquid phases at the FET surface. Nonequilibrium melting dynamics are visualized by rapidly heating the graphene substrate with an electrical current and imaging the resulting evolution toward new 2D equilibrium states. An analytical model is developed that explains observed mixed–state phases based on spectroscopic measurement of solid and liquid molecular energy levels. The observed nonequilibrium melting dynamics are consistent with Monte Carlo simulations.

36 MATERIALS SCIENCE↗

Effect of interfacial vibrational coupling on surface wettability and water transport

Here, we report that the atomic-scale vibrational coupling at the solid-fluid interface can substantially alter the interfacial properties such as wettability and fluid slip. The wettability of water droplets on substrates subjected to various vibrational frequencies is studied using molecular dynamics simulation. The contact angle increases (i.e., becomes more hydrophobic) when the oscillation frequency of the substrate matches the intermolecular bending frequency of liquid water. We investigate the underlying mechanism by examining the dynamics of water molecules at the interface and find that the temporal contact between the solid and fluid is shorter when the frequencies match, resulting in weak solid-fluid adsorption. We further report that the vibrational match at the interface reduces wall-fluid friction and enhances water transport through the nanopore. Our findings demonstrate the importance of the atomic-scale vibrational coupling at the solid-fluid interface on the physicochemical behavior of nanodevices and biological nanochannels.

74 ATOMIC AND MOLECULAR PHYSICS↗

In Situ Chemical Monitoring and Imaging of Contents within Microfluidic Devices Having a Porous Membrane Wall Using Liquid Microjunction Surface Sampling Probe Mass Spectrometry

The ability to observe dynamic chemical processes (e.g., signaling, transport, etc.) in vivo or in situ using nondestructive chemical imaging opens a new door to understanding the complex dynamics of developing biological systems. With the advent of “biology-on-a-chip” devices has come the ability to monitor dynamic chemical processes in a controlled environment, using these engineered habitats to capture key features of natural systems while allowing visual observation of system development. Having the capability to spatially and temporally map the chemical signals within these devices may yield new insights into the forces that drive biosystem development. Here, a porous membrane sealed microfluidic device was designed to allow normal microfluidic operation while enabling continuous, location specific sampling and chemical characterization by liquid microjunction surface sampling probe mass spectrometry (LMJ-SSP MS). LMJ-SSP was used to extract fluids with nL-to-μL/min flow rates directly from selected areas of the microfluidic device without negatively impacting the device function. These extracts were subsequently characterized using MS. This technique was used to acquire MS images of the entirety of several multi-input microfluidic devices having different degrees of fluid mixing. LMJ-SSP MS imaging visualized the spatial distribution of chemical components within the microfluidic channels and could visualize chemical reactions occurring in the device. These microfluidic devices with a porous membrane wall are wholly compatible with the construction of biology-on-a-chip devices. This ultimately would enable correlation of biosystem physical structure with an evolving chemical environment

47 OTHER INSTRUMENTATION↗

Glaciation of mixed-phase clouds: insights from bulk model and bin-microphysics large-eddy simulation informed by laboratory experiment

Abstract. Mixed-phase clouds affect precipitation and radiation differently from liquid and ice clouds, posing greater challenges to their representation in numerical simulations. Recent laboratory experiments using the Pi Cloud Chamber explored cloud glaciation conditions based on increased injection of ice-nucleating particles. In this study, we use two approaches to reproduce the results of the laboratory experiments: a bulk scalar mixing model and large-eddy simulation (LES) with bin microphysics. The first approach assumes a well-mixed domain to provide an efficient assessment of the mean cloud properties for a wide range of conditions. The second approach resolves the energy-carrying turbulence, the particle size distribution, and their spatial distribution to provide more details. These modeling approaches enable a separate and detailed examination of liquid and ice properties, which is challenging in the laboratory. Both approaches demonstrate that, with an increased ice number concentration, the flow and microphysical properties exhibit the same changes in trends. Additionally, both approaches show that the ice integral radius reaches the theoretical glaciation threshold when the cloud is subsaturated with respect to liquid water. The main difference between the results of the two approaches is that the bulk model allows for the complete glaciation of the cloud. However, LES reveals that, in a dynamic system, the cloud is not completely glaciated as liquid water droplets are continuously produced near the warm lower boundary and subsequently mixed into the chamber interior. These results highlight the importance of the ice mass fraction in distinguishing the mixed-phase clouds and ice clouds.

54 ENVIRONMENTAL SCIENCES↗

Stabilized Electrode/Electrolyte Interphase by a Saturated Ionic Liquid Electrolyte for High-Voltage NMC532/Si-Graphite Cells

Nonaqueous electrolyte has become one of the technical barriers in enabling Li-ion battery comprising of a high voltage cathode and high capacity anode. Here, we demonstrate a saturated piperidinum bis(fluorosulfonyl)imide ionic liquid (IL) with a LiFSI salt not only supports the redox reaction on the cathode at high voltages, but also shows exceptional kinetic stability on the lithiated anode as evidenced by its improved cycling performance in a NMC532/Si-graphite full cells cycled between 4.6 and 3.0 V. On the basis of the spectroscopic/microscopic analysis and molecular dynamics (MD) simulations, the superior performance of the cells is attributed to the formation of solid-electrolyte-interphase on both electrode as well as unique solvation structure where a deadlocked coordination network is established at the saturated state, which prevents transition metal dissolution into the electrolyte via a solvation process.

25 ENERGY STORAGE↗

A review of the application of 2D isotropic-anisotropic correlation NMR spectroscopy in structural studies of chalcogenide glasses

The application of solid-state high-resolution NMR spectroscopy in the structural investigation of chalcogenide glasses in Ge/As/P/Si-X (X = S, Se,Te) systems has remained challenging even for the spin-1/2 nuclides ( 29 Si, 31 P, 77 Se, 125 Te), owing to their low natural abundance (except for 31 P), slow spin-lattice relaxation rate and large CSA and chemical shift distribution induced line broadening effects. However, most of these deleterious effects can be successfully overcome in two-dimensional (2D) isotropic-anisotropic correlation NMR experiments, especially when performed at high magnetic field and in conjunction with the Car-Purcell-Meiboom-Gill (CPMG) echo train acquisition. Here, we present a short introduction to the basic principles of such experiments and review their applications over the last decade in deciphering various short- and intermediate- range structural characteristics of chalcogenide glasses in S-Se, Se-Te, Ge-Se, As-Se and Si-Se systems as well as in investigating the molecular dynamics in a P-Se supercooled liquid. We anticipate possible future applications of these 2D isotropic-anisotropic correlation NMR experiments, particularly in conjunction with density functional theory-based calculations of NMR chemical shift tensor parameters and additional signal enhancement schemes, in addressing complex structural correlations and distributions in chalcogenide glasses.

2D NMR↗

Artificial neural network potentials for mechanics and fracture dynamics of two-dimensional crystals **

Understanding the mechanics and failure of materials at the nanoscale is critical for their engineering and applications. The accurate atomistic modeling of brittle failure with crack propagation in covalent crystals requires a quantum mechanics-based description of individual bond-breaking events. Artificial neural network potentials (NNPs) have emerged to overcome the traditional, physics-based modeling tradeoff between accuracy and accessible time and length scales. Previous studies have shown successful applications of NNPs for describing the structure and dynamics of molecular systems and amorphous or liquid phases of materials. However, their application to deformation and failure processes in materials is still uncommon. In this study, we discuss the apparent limitations of NNPs for the description of deformation and fracture under loadings and propose a way to generate and select training data for their employment in simulations of deformation and fracture simulations of crystals. We applied the proposed approach to 2D crystalline graphene, utilizing the density-functional tight-binding method for more efficient and extensive data generation in place of density functional theory. Then, we explored how the data selection affects the accuracy of the developed artificial NNPs. It revealed that NNP’s reliability should not only be measured based on the total energy and atomic force comparisons for reference structures but also utilize comparisons for physical properties, e.g. stress–strain curves and geometric deformation. In sharp contrast to popular reactive bond order potentials, our optimized NNP predicts straight crack propagation in graphene along both armchair and zigzag (ZZ) lattice directions, as well as higher fracture toughness of ZZ edge direction. Our study provides significant insight into crack propagation mechanisms on atomic scales and highlights strategies for NNP developments of broader materials.

2D materials↗

Reconfigurable structure and tunable transport in synchronized active spinner materials

Ensembles of actuated colloids are excellent model systems to explore emergent out-of-equilibrium structures, complex collective dynamics, and design rules for the next generation materials. Here, we demonstrate that ferromagnetic microparticles suspended at an air-water interface and energized by an external rotating magnetic field spontaneously form dynamic ensembles of synchronized spinners in a certain range of the excitation field parameters. Each spinner generates strong hydrodynamic flows, and collective interactions of the multiple spinners promote a formation of dynamic lattices. On the basis of experiments and simulations, we reveal structural transitions from liquid to nearly crystalline states in this novel active spinner material and demonstrate that dynamic spinner lattices are reconfigurable, capable of self-healing behavior and that the transport of embedded inert cargo particles can be remotely tuned by the parameters of the external excitation field. Our findings provide insights into the behavior of active spinner materials with reconfigurable structural order and tunable functionalities.

36 MATERIALS SCIENCE↗

Large-Scale Atomistic Simulations: Investigating Free Expansion

The experiment investigates free expansion of a supercritical fluid into a two-phase liquid-vapor coexistence region. A huge molecular dynamics simulation (6 billion Lennard-Jones atoms) was run on 5760 GPUs (33% of LLNL Sierra) using LAMMPS/Kokkos software. This improved visualization workflow and started preliminary simulations of aluminum using SNAP machine learning potential.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The role of defects and solid/liquid interfacial interactions on controlling anisotropic growth of novel two-dimensional materials

Atomic-scale understanding about how interfacial properties are modified in the presence of defects and how they are correlated to the properties of nucleation and growth is critical for controlled materials growth on solid/liquid interfaces. The goal of this proposal is to establish preliminary data on the critical role of surface defects and chemical compositions of solvent on the structure, dynamics, reactivity, and free energetics at graphene/ionic liquid (IL) interfaces and their impact on two-dimensional (2D) growth of transition metal oxides on the surface. This study aims to develop generalized physical/chemical principles for directional growth at solid/liquid interfaces to achieve atomic-level control of two-dimensional materials synthesis. The proposed study of the effects of surface defects on the interfacial structure and reactivity will improve our understanding of the critical roles of heterogeneity, disorder, and solvents on 2D materials synthesis and lead to better control of directional growth of materials at solid/liquid interfaces.

36 MATERIALS SCIENCE↗

Spinon mediation of witness spin dynamics in herbertsmithite

The kagome lattice of spin-1/2 copper atoms in herbertsmithite is conjectured to sustain a quantum spin liquid state with spinon quasiparticles. Ideally, the kagome crystal planes are each separated by a plane of spinless zinc atoms. However, in real crystals, some spin-1/2 copper atoms substitute randomly onto these inter-kagome zinc sites. Here we reconceptualize such ‘impurity’ atoms as quantum witness spins whose dynamics is designed to probe the spin liquid state. We then introduce spin noise spectroscopy to measure the frequency and temperature dependence of witness spin dynamics, demonstrating that their phenomenology is consistent with extensive interactions between witness spins mediated by propagation of spinons through a quantum spin liquid. Ultimately, a sharp transition occurs at around 260 mK, below which the properties of both spin noise and magnetic susceptibility suggest that the witness spins form a spin glass phase. Among the theoretical models considered, we demonstrate that our observations are only consistent with spinon-mediated interactions between witness spins by either a Z 2 or U(1) quantum spin liquid, with the former model more closely matching the data. Our work demonstrates that quantum mechanical witness spins may now conceivably be used as a widely applicable probe of quantum spin liquid physics.

Takahashi, Hiroto [University of Oxford (United Ki↗

Matlab implementation of a novel semi-structured kinetic model for methanotroph-photoautotroph cocultures

This paper presents the MatLab implementation details of a novel semi-structured kinetic model for methanotroph-photoautotroph cocultures. This includes the parameterization of the modeling equations, and the initialization of the simulation based on experimental conditions. More importantly, it provides details on how the differential equations governing mass balances in both gas and liquid phases are integrated together to simulate the system dynamics over time. The semi-structured kinetic model for methanotroph-photoautotroph coculture is validated using a wide range of experimental conditions. The model: Accurate predicts both the coculture growth in liquid phase and the gas composition changes in head space over time; Explicitly models the exchange of in situ produced O 2 and CO 2 within the coculture; Considers the self-shading effect on the growth of photoautotroph.

42 ENGINEERING↗