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At least 235 records · Page 13

Efficient Simulation of Cascading Outages Using an Energy Function-Embedded Quasi-Steady-State Model

Here, this paper proposed an energy function-embedded quasi-steady-state model for efficient simulation of cascading outages on a power grid while addressing transient stability concerns. Compared to quasi-steady-state models, the proposed model incorporates short-term dynamic simulation and an energy function method to efficiently evaluate the transient stability of a power grid together with outage propagation without transient stability simulation. Cascading outage simulation using the proposed model conducts three steps for each disturbance such as a line outage. First, it performs time-domain simulation for a short term to obtain a post-disturbance trajectory. Second, along the trajectory, the system state with the local maximum potential energy is found and used as the initial point to search for a relevant unstable equilibrium by Newton's method. Third, the transient energy margin is estimated based on this unstable equilibrium to predict an out-of-step condition with generators. The proposed energy function-embedded quasi-steady-state model is tested in terms of its accuracy and time performance on an NPCC 140-bus power system and compared to a quasi-steady-state model embedding transient stability simulation.

Guo, Zhenping [Univ. of Tennessee, Knoxville, TN (↗

Collisional excitation of C2H− by H2: New interaction potential and scattering calculations

Interstellar anions play an important role in astrochemistry as being tracers of the physical and chemical conditions in cold molecular clouds and circumstellar gas. The local thermodynamic equilibrium is generally not fulfilled in media where anions are detected and radiative and collisional data are required to model the observed lines. The C2H− anion has not yet been detected in the interstellar medium; however, collisional data could be used for non-LTE models that would help in identifying the most intense lines. For this purpose, we have computed the first 4D potential energy surface (PES) of the C2H−–H2 complex using an explicitly correlated coupled-cluster approach. The PES is characterized by a single deep minimum with a well-depth of 924.96 cm−1. From this interaction potential, we derived excitation cross sections and rate coefficients of C2H− induced by collisions with para- and ortho-H2. The results obtained for collisions with para-H2 are compared to previous calculations performed using a 2D-PES obtained from an average over H2 rotations.

Chemistry↗

Elastic forces drive nonequilibrium pattern formation in a model of nanocrystal ion exchange

The widely used process of nanocrystal ion exchange operates out of thermodynamic equilibrium and can require mixing components of varying sizes. Here we use theory and computer simulation to study a simple model which captures these two basic features of ion exchange reactions. We show that a strong driving force for exchange among different-sized species creates nonequilibrium patterns within model nanocrystals. We further demonstrate that such patterns can be thermodynamically stable within core/shell nanocrystals. These results help us understand the heterostructures formed in ion-exchanged nanocrystals and suggest strategies for leveraging elasticity to design patterns in nanoscale materials. Chemical transformations, such as ion exchange, are commonly employed to modify nanocrystal compositions. Yet the mechanisms of these transformations, which often operate far from equilibrium and entail mixing diverse chemical species, remain poorly understood. Here we explore an idealized model for ion exchange in which a chemical potential drives compositional defects to accumulate at a crystal’s surface. These impurities subsequently diffuse inward. We find that the nature of interactions between sites in a compositionally impure crystal strongly impacts exchange trajectories. In particular, elastic deformations which accompany lattice-mismatched species promote spatially modulated patterns in the composition. These same patterns can be produced at equilibrium in core/shell nanocrystals, whose structure mimics transient motifs observed in nonequilibrium trajectories. Moreover, the core of such nanocrystals undergoes a phase transition—from modulated to unstructured—as the thickness or stiffness of the shell is decreased. Our results help explain the varied patterns observed in heterostructured nanocrystals produced by ion exchange and suggest principles for the rational design of compositionally patterned nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimized utilization of COMB3 reactive potentials in LAMMPS

An investigation to optimize the application of the third-generation charge optimized many-body (COMB3) interatomic potential and associated input parameters was carried out through the study of solid–liquid interactions in classical molecular dynamics simulations. The rates of these molecular interactions are understood through the wetting rates of water nano-droplets on a bare copper (111) surface. Implementing the Langevin thermostat, the influence of simulation time step, the number of atoms in the system, the frequency at which charge equilibration is performed, and the temperature relaxation rate are all examined. The results indicate that time steps of 0.4 fs are possible when using longer relaxation times for the system temperature, which is almost double the typical time step used for reactive potentials. Additionally, the use of the charge equilibration allows for a fewer atomic layers to be used in the Cu slab. In addition, charge equilibrium schemes do not need to be performed every time step to ensure accurate charge transfer. Interestingly, the rate of wetting for the nanodroplets is dominantly dependent on the temperature relaxation time, which is predicted to significantly change the viscosity of the water droplets. This work provides a pathway for optimizing simulations using the COMB3 reactive interatomic potential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational thermodynamics and its applications

Thermodynamics is a science concerning the state of a system, whether it is stable, metastable or un- stable, when interacting with the surroundings. In this overview, fundamentals of thermodynamics are briefly reviewed through the combination of first and second laws of thermodynamics for open and nonequilibrium systems to demonstrate that the reversible equilibrium and irreversible nonequilibrium thermodynamics can be integrated to enhance the power and utilities of thermodynamics. The recent progresses in computational thermodynamics, the remaining challenges, and potential impacts in broad scientific fields are discussed here. It is shown that computational thermodynamics enables the modeling of thermodynamics of a state as a function of both external and internal variables and quantitative calculations of a broad range of properties of a multicomponent system in terms of first and second derivatives of energy, including not only equilibrium states when there are no driving forces for any internal processes and but also non-equilibrium states with driving forces for internal processes. Consequently, external constraints such as fixed strain and internal degree of freedoms such as ordering and defects can be described in a coherent framework and applied to materials design. Furthermore, two important but largely overlooked aspects in thermodynamics will be discussed, i.e. the rigorous application of statistical thermodynamics with the probability of configurations and their contributions to system properties, and the applications of second derivatives of energy with respect to either two extensive variables or two potentials or a mixture of them in terms of understanding and predicting emergent behaviors, critical phenomena, kinetic coefficients, and mechanical properties.

36 MATERIALS SCIENCE↗

First-principles investigation of cerium and neodymium diffusion in BCC chromium and vanadium via vacancy-mediated transport

Lanthanide transport plays a crucial role in the performance and longevity of metallic nuclear fuels. This study examines the diffusion behavior of Ce and Nd—two major fission products—in body-centered cubic (BCC) Cr and V, which are potential liner or coating materials for mitigating fuel-cladding chemical interactions (FCCI). Using density functional theory (DFT) calculations and self-consistent mean-field (SCMF) analysis, the vacancy-mediated diffusion coefficients are evaluated. Our findings reveal that Ce and Nd act as oversized solutes and are strongly bound to vacancies in BCC Cr and V, with diffusivities in Cr significantly lower than in V and in hexagonal closed-packed (HCP) Zr, as investigated in our previous work. The activation energies for Ce and Nd diffusion are 3.39 and 3.32 eV, respectively, in BCC Cr, and 2.56 and 2.33 eV, respectively, in BCC V. Analysis of vacancy drag and partial diffusion coefficient ratios indicates a strong tendency for lanthanide enrichment at vacancy sinks in BCC Cr, and to a lesser extent in BCC V, with this effect persisting up to the melting point in Cr and remaining substantial for Nd in V at high temperatures. Under irradiation, the increase in vacancy concentration is expected to enhance lanthanide transport, potentially accelerating interactions at liner-cladding interfaces. Although BCC Cr exhibits relatively low lanthanide diffusivities under equilibrium conditions, the expected segregation tendencies under irradiation suggest that Zr liners may be a more favorable option. Further investigations using rate theory, cluster dynamics, and phase-field modeling are required to quantitatively assess the performance of these materials in reactor environments.

36 - MATERIALS SCIENCE↗

Zonally dominated dynamics and Dimits threshold in curvature-driven ITG turbulence

The saturated state of turbulence driven by the ion-temperature-gradient instability is investigated using a two-dimensional long-wavelength fluid model that describes the perturbed electrostatic potential and perturbed ion temperature in a magnetic field with constant curvature (a $Z$ -pinch) and an equilibrium temperature gradient. Numerical simulations reveal a well-defined transition between a finite-amplitude saturated state dominated by strong zonal-flow and zonal temperature perturbations, and a blow-up state that fails to saturate on a box-independent scale. We argue that this transition is equivalent to the Dimits transition from a low-transport to a high-transport state seen in gyrokinetic numerical simulations (Dimits et al. , Phys. Plasmas , vol. 7, 2000, 969). A quasi-static staircase-like structure of the temperature gradient intertwined with zonal flows, which have patch-wise constant shear, emerges near the Dimits threshold. The turbulent heat flux in the low-collisionality near-marginal state is dominated by turbulent bursts, triggered by coherent long-lived structures closely resembling those found in gyrokinetic simulations with imposed equilibrium flow shear (van Wyk et al. , J. Plasma Phys. , vol. 82, 2016, 905820609). The breakup of the low-transport Dimits regime is linked to a competition between the two different sources of poloidal momentum in the system – the Reynolds stress and the advection of the diamagnetic flow by the $\boldsymbol {E}\times \boldsymbol {B}$ flow. By analysing the linear ion-temperature-gradient modes, we obtain a semi-analytic model for the Dimits threshold at large collisionality.

Physics↗

Spontaneous formation of anisotropic microrods from paraffin wax in an aqueous environment

The construction of functional nano-/micro-architectures through self-assembly and self-organization of organic molecules and polymeric materials plays an important role in the development of many technologies. In this study, we report the spontaneous formation of uniform polymer microrods with lengths of up to a few tens of micrometers from paraffin wax. Through a solvent attrition approach, colloidal structures of paraffin wax are introduced into water. After the initial growth stage, the microrods undergo morphological transformation and end-to-end aggregation, processes likely driven by thermodynamics to create equilibrium structures with minimal interfacial energies. Here, the polymer microrods can effectively absorb hydrophobic nanoparticles, indicating their potential to serve as host materials for functional components. The formation of polymer microrods from paraffin wax and their spontaneous growth mechanism discovered in this study may provide new insights to the self-assembly of microstructures.

36 MATERIALS SCIENCE↗

W7-X and the sawtooth instability: towards realistic simulations of current-driven magnetic reconnection

Magnetic reconnection in W7-X is studied by means of global numerical simulations in a series of models of increasing complexity. The magnetic geometry ranges from that of a cylinder to the full three-dimensional field of W7-X, and the equations solved range from ideal magnetohydrodynamics (MHD) to gyrokinetics. We simulate plasmas from the first operation phase with electron cyclotron current drive (ECCD). These are characterized by an equilibrium magnetic field featuring an ECCD-distorted 'humped' profile of the rotational transform ι, with ι = 1 in two radial locations. Such plasmas generally show sawtooth activity, hence motivating the present study. We pay particular attention to the role of equilibrium current density gradients in the destabilization of reconnecting modes. When the equilibrium temperature and density gradients are artificially suppressed (to eliminate the pressure gradient drive), the perturbed electrostatic potential is radially localized between the locations at which ι = 1. This is shown with a purely collisionless gyrokinetic model, in cylindrical geometry. In the real toroidal geometry of W7-X, for a non-ideal MHD model including a uniform resistivity, electron inertia and (numerical) viscosity, the same qualitative behaviour is observed. In particular, even if a resonant (m, n) = (1, -1) perturbation is initialized, the most unstable mode is the (m, n) = (-4, 4), where m and n are the poloidal and toroidal mode numbers, respectively. Other modes are destabilized due to geometric coupling. The growth rate of this instability scales as η 1/3 , where η is the plasma resistivity, thus suggesting that ECCD drives ideal MHD stable W7-X plasmas towards non-ideal marginality. An ideal magnetohydrodynamic analysis confirms the result. A fluid-kinetic hybrid version of the EUTERPE code shows that gyrokinetic ions have a stabilizing effect on these modes. For W7-X relevant collisionalities, the growth rate scales linearly with the electron skin depth, d e . Implications of our results for sawtoothing W7-X operation are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Integrating subsystem embedding subalgebras and coupled cluster Green’s function: a theoretical foundation for quantum embedding in excitation manifold

Here, in this study, we introduce a novel approach to coupled-cluster Green's function (CCGF) embedding by seamlessly integrating conventional CCGF theory with the state-of-the-art sub-system embedding sub-algebras coupled cluster (SES-CC) formalism. This integration focuses primarily on delineating the characteristics of the sub-system and the corresponding segments of the Green's function, defined explicitly by active orbitals. Crucially, our work involves the adaptation of the SES-CC paradigm, addressing the left eigenvalue problem through a distinct form of Hamiltonian similarity transformation. This advancement not only facilitates a comprehensive representation of the interaction between the embedded sub-system and its surrounding environment but also paves the way for the quantum mechanical description of multiple embedded domains, particularly by employing the emergent quantum flow algorithms. Our theoretical underpinnings further set the stage for a generalization to multiple embedded sub-systems. This expansion holds significant promise for the exploration and application of non-equilibrium quantum systems, enhancing the understanding of system–environment interactions. In doing so, the research underscores the potential of SES-CC embedding within the realm of quantum computations and multi-scale simulations, promising a good balance between accuracy and computational efficiency.

97 MATHEMATICS AND COMPUTING↗

Within-Host Phenotypic Evolution and the Population-Level Control of Chronic Viral Infections by Treatment and Prophylaxis

Chronic viral infections can persist for decades spanning thousands of viral generations, leading to a highly diverse population of viruses with its own complex evolutionary history. We propose an expandable mathematical framework for understanding how the emergence of genetic and phenotypic diversity affects the population-level control of those infections by both non-curative treatment and chemo-prophylactic measures. Our frameworks allows both neutral and phenotypic evolution, and we consider the specific evolution of contagiousness, resistance to therapy, and efficacy of prophylaxis. We compute both the controlled and uncontrolled, population-level basic reproduction number accounting for the within-host evolutionary process where new phenotypes emerge and are lost in infected persons, which we also extend to include both treatment and prophylactic control efforts. We used these results to discuss the conditions under which the relative efficacy of prophylactic versus therapeutic methods of control are superior. Finally, we give expressions for the endemic equilibrium of these models for certain constrained versions of the within-host evolutionary model providing a potential method for estimating within-host evolutionary parameters from population-level genetic sequence data.

sensitivity analysis↗

Accelerating Thermochemical Equilibrium Calculations for Nuclear Reactor Applications

Thermochemical properties play a key role in modeling and simulation of several key phenomena in nuclear reactors. There has been an increasing interest in incorporating CALPHAD-based formulations in multiphysics simulations including for Molten Salt Reactors where knowledge of phase evolution of the salt and the chemical potentials of various elements are of utmost importance in source term analyses and redox control. However, the size of such simulations is often limited by the high computational cost of full thermodynamic equilibrium calculations. This work discusses the current efforts aimed at accelerating thermochemical equilibrium calculations for multiphysics simulations performed using the open-source finite element / finite volume code Multiphysics Object Oriented Simulation Environment (MOOSE) [1]. While several methods have been proposed for accelerating phase equilibrium calculations [2], most focus on relatively small systems and often rely on a- priori knowledge of the state-space of the system. Nuclear materials, however, are often multi-component systems owing to the evolution of composition under irradiation and an approach based on a-priori mapping of phase diagram is often not enough. This work is aimed at demonstrating an on-the-fly surrogate modeling framework that uses active learning to reduce the number of full equilibrium calculations that must be performed. By combining with efficient coupling approaches, the surrogate framework helps in reducing the computational cost of thermodynamic equilibrium informed multiphysics simulations of nuclear materials. The performance is benchmarked against full coupling with the thermochemistry library Thermochimica [3]. This work uses a machine learning based approach for constructing surrogate models to predict the stable phases in a multicomponent system. The surrogates were constructed using neural networks and Gaussian process classification. In this work, we compare the relative performance of the two methods. We also demonstrate the use of caching previous calculations by interpolating the values from nearest neighbors. References [1] Lindsay, A.D., et al. "2.0 – MOOSE: Enabling massively parallel multiphysics simulation", SoftwareX, 20 (2022): 101202. [2] Roos, W.A. and Zietsman J.H. "Accelerating complex chemical equilibrium calculations – A Review", Calphad, 77 (2022): 102380. [3] Piro, M.H.A., et al. "The thermochemistry library Thermochimica", Computational Materials Science, 67 (2013): 266-272.

36 MATERIALS SCIENCE↗

Transferable Water Potentials Using Equivariant Neural Networks

Machine learning interatomic potentials (MLIPs) have emerged as a technique that promises quantum theory accuracy for reduced cost. It has been proposed [J. Chem. Phys. 2023, 158, 084111] that MLIPs trained on solely liquid water data cannot accurately transfer to the vapor–liquid equilibrium while recovering the many-body decomposition (MBD) analysis of gas-phase water clusters. This suggests that MLIPs do not directly learn the physically correct interactions of water molecules, limiting transferability. In this work, we show that MLIPs using equivariant architecture and trained on 3200 liquid water structures reproduces liquid-phase water properties (e.g., density within 0.003 g/cm 3 between 230 and 365 K), vapor–liquid equilibrium properties up to 550 K, the MBD analysis of gas-phase water cluster up to six-body interactions, and the relative energy and the vibrational density of states of ice phases. We show that potentials developed using equivariant MLIPs allow transferability for arbitrary phases of water that remain stable in nanosecond long simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Linearized Pair-Density Functional Theory for Vertical Excitation Energies

Multiconfiguration pair-density functional theory (MC-PDFT) is a computationally efficient method that computes the energies of electronic states in a state specific or state average framework via an on-top functional. However, MC-PDFT does not include state interaction among these states since the final energies do not come from the diagonalization of an effective model-space Hamiltonian. Recently, multistate extensions such as linearized PDFT (L-PDFT) have been developed to accurately model the potentials near conical intersections and avoided crossings. However, there has not been any systematic study evaluating their performance for predicting vertical excitations at the equilibrium geometry of a molecule, when the excited states are generally well separated. In this paper, we report the performance of L-PDFT on the extensive QUESTDB data set of vertical excitations using a database of automatically selected active spaces. We show that L-PDFT performs well on all these excitations and successfully reproduces the performance of MC-PDFT. These results further demonstrate the potential of L-PDFT, as its scaling is constant with the number of states included in the state-average manifold, whereas MC-PDFT scales linearly in this regard.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing the thermodynamics and kinetics of ethylene carbonate reduction at the electrode–electrolyte interface with molecular simulations

Understanding the formation of the solid-electrolyte interphase (SEI) in lithium-ion batteries (LIBs) is an ongoing area of research due to its high degree of complexity and the difficulties encountered by experimental studies. Herein, we investigate the initial stage of SEI growth, the reduction reaction of ethylene carbonate (EC), from both a thermodynamic and kinetic approach with theory and molecular simulation. We employed both the potential distribution theorem (PDT) and the SMD implicit solvent model to EC solvation for the estimation of reduction potentials of Li$^+$, EC, and Li$^+$-solvating EC (s-EC), as well as reduction rate constants of EC and s-EC. We find that solvation effects greatly influence these quantities of interest, particularly the Li$^+$/Li reference electrode potential in EC solvent. Further, we also compute the inner- and outer-sphere reorganization energies for both EC and s-EC at the interface of liquid EC and a hydroxyl-terminated graphite surface, where total reorganization energies are predicted to be 76.6 and 88.9 kcal/mol, respectively. With the computed reorganization energies, we estimate reduction rate constants across a range of overpotentials and show that EC has a larger electron transfer rate constant than s-EC at equilibrium, despite s-EC being more thermodynamically favorable. Furthermore, this manuscript demonstrates how ion solvation effects largely govern the prediction of reduction potentials and electron transfer rate constants at the electrode-electrolyte interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Equilibrium Separation of Siloxanes in Metal–Organic Frameworks

We present an in silico assessment of metal–organic frameworks (MOFs) for the equilibrium separation of linear and cyclic siloxanes. Using a combination of configurational bias/continuous fractional component Monte Carlo (CB/CFCMC) simulations and Ideal Adsorbed Solution Theory (IAST), we investigated the adsorption of both equimolar and nonequimolar mixtures of linear and cyclic siloxanes in a selection of synthesizable MOFs with medium to large pore volumes. We showed that configurational entropy effects drive the preferential adsorption of linear siloxanes over cyclic siloxanes. Based on synthesizability metrics we identified ZIF-70 as a promising adsorbent for the separation of linear and cyclic siloxanes. Self-diffusivities of linear and cyclic siloxanes in ZIF-70 calculated from molecular dynamics simulations show that equilibrium can be reached on reasonable time scales. We explored vacuum-temperature swing adsorption (VTSA) as a potential method for the recovery of adsorbed linear siloxanes from ZIF-70, achieving a 75% reduction in adsorbed phase concentration. Additionally, we demonstrated that supercritical CO 2 offers an alternative desorption strategy by displacing adsorbed linear siloxanes in ZIF-70 at pressures above 200 bar driven by entropy effects.

Adsorption↗

The effects of introducing elasticity using different interpolation schemes to the grand potential phase field model

Introducing elastic energy in the phase field method has been shown to influence interfacial energy, depending on the elastic interpolation scheme. This study investigates the impact of the elastic energy when using a grand potential-based phase field method, comparing the result of Khachaturyan’s strain interpolation scheme (KHS) and Voight-Taylor’s elastic energy interpolation scheme (VTS). The KHS model leads to a decrease in the interfacial energy, while the VTS model leads to an increase. The change in interfacial energy is greater with the VTS model than the KHS model, which suggests that the KHS model is more appropriate to limit the artificial impact of the elastic energy on the interfacial energy. When the contribution at the interface is not negligible, it is shown that both the microstructure evolution kinetics and the equilibrium microstructure can be influenced by the choice of the elastic scheme being used. In addition, this paper shows that the grand potential model might not be appropriate when the system requires the introduction of a composition-dependent term in the elastic energy contribution. This limitation is due to the need for an explicit and invertible relation between the total potential and the composition.

36 MATERIALS SCIENCE↗

Platinum Graphene Catalytic Condenser for Millisecond Programmable Metal Surfaces

Accelerating catalytic chemistry and tuning surface reactions require precise control of the electron density of metal atoms. In this work, nanoclusters of platinum were supported on a graphene sheet within a catalytic condenser device that facilitated electron or hole accumulation in the platinum active sites with negative or positive applied potential, respectively. The catalytic condenser was fabricated by depositing on top of a p-type Si wafer an amorphous HfO 2 dielectric (70 nm), on which was placed the active layer of 2–4 nm platinum nanoclusters on graphene. A potential of ±6 V applied to the Pt/graphene layer relative to the silicon electrode moved electrons into or out of the active sites of Pt, attaining charge densities more than 1% of an electron or hole per surface Pt atom. At a level of charge condensation of ±10% of an electron per surface atom, the binding energy of carbon monoxide to a Pt(111) surface was computed via density functional theory to change 24 kJ mol –1 (0.25 eV), which was consistent with the range of carbon monoxide binding energies determined from temperature-programmed desorption (ΔBE CO of 20 ± 1 kJ mol –1 or 0.19 eV) and equilibrium surface coverage measurements (ΔBE CO of 14 ± 1 kJ mol –1 or 0.14 eV). Impedance spectroscopy indicated that Pt/graphene condensers with potentials oscillating at 3000 Hz exhibited negligible loss in capacitance and charge accumulation, enabling programmable surface conditions at amplitudes and frequencies necessary to achieve catalytic resonance.

Inorganic carbon compounds↗