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At least 127 records · Page 7

Forces from Stochastic Density Functional Theory under Nonorthogonal Atom-Centered Basis Sets

We develop a formalism for calculating forces on the nuclei within the linear-scaling stochastic density functional theory (sDFT) in a nonorthogonal atom-centered basis set representation (Fabian et al. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2019, 9, e1412, 10.1002/wcms.1412) and apply it to the Tryptophan Zipper 2 (Trp-zip2) peptide solvated in water. We use an embedded-fragment approach to reduce the statistical errors (fluctuation and systematic bias), where the entire peptide is the main fragment and the remaining 425 water molecules are grouped into small fragments. We analyze the magnitude of the statistical errors in the forces and find that the systematic bias is of the order of 0.065 eV/Å (~1.2 × 10 -3 E h / a 0 ) when 120 stochastic orbitals are used, independently of system size. This magnitude of bias is sufficiently small to ensure that the bond lengths estimated by stochastic DFT (within a Langevin molecular dynamics simulation) will deviate by less than 1% from those predicted by a deterministic calculation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An idealized model for collapse of a molecular core within a filament

Here, we present an analytic treatment of the self-similar collapse of a uniform density ellipsoid to linear order in the deviations from sphericity. First we obtain a self-consistent closed-form solution for the evolution of an isolated ellipsoid and then impose the effects of an external forcing. This model describes the evolution under gravity of a pre-stellar core of molecular gas embedded in a much larger and lower-density filament. We compare with numerical solutions for the collapse without the limitation of small deviations. These show how the external perturbing force producing the initial deviation from sphericity is eventually surpassed by the anisotropic forces generated by the collapsing ellipsoid itself. This model should be useful in interpreting the way in which environment shapes the evolution of pre-stellar cores.

79 ASTRONOMY AND ASTROPHYSICS↗

Fault-tolerant resource comparison of qudit and qubit encodings for diagonal quadratic operators

Finite local Hilbert-space truncations arise naturally in quantum simulations of lattice field theories and motivate qudit encodings, but their fault-tolerant advantage over qubit encodings remains unclear. We compare the non-Clifford cost of implementing quadratic diagonal evolutions, exemplified by 𝑈 = 𝑒$^{−𝑖⁢𝑡⁢𝜙^2_𝑥}$ in a uniform field-amplitude discretization of a real scalar field, using either one logical 𝑑-level qudit or 𝑛 𝑏 = ⌈log 2⁡ 𝑑⌉ logical qubits. We analyze two standard settings: product-formula simulation and linear combination of unitaries (LCU) per block encoding, taking the resource metric to be the number of non-Clifford gates after synthesis into a discrete logical gate set. Because tight synthesis bounds for general single-qudit rotations are not known, we express the qudit constructions in terms of embedded two-level SU⁡(2) rotations and derive explicit finite-𝑑 break-even conditions for their synthesis cost; these serve as compiler targets for when qudit encodings can outperform the qubit baseline. Within the constructive models studied here, product-formula implementations would require an exponentially stronger per-primitive synthesis advantage for qudits to win asymptotically, while in the LCU setting the qubit encoding is asymptotically cheaper in 𝑑. Nevertheless, the finite-𝑑 threshold analysis identifies low-dimensional regions in which qudits can yield meaningful constant-factor savings, particularly for LCU-based implementations. As a secondary analysis of the LCU construction, we use an idealized negligible-overhead qubit-qudit code-switching model to give an absolute 𝑇-count comparison and reinterpret the savings as an allowable per-switch overhead budget.

Godwood, Samuel [Univ. of Liverpool (United Kingdo↗

Multi‐scale simulation of rock compaction through breakage models with microstructure evolution

Abstract. Regional subsidence due to fluid depletion includes the interaction among multiple physical processes. Specifically, rock compaction is governed by coupled hydro-mechanical feedbacks involving fluid flow, effective stress change and pore collapse. Although poroelastic models are often used to explain the delay between depletion and subsidence, recent evidence indicates that inelastic effects could alter the rock microstructure, thus exacerbating coupling effects. Here, a constitutive law built within the framework of Breakage Mechanics is proposed to account for the inherent connection between rock microstructure, hydraulic conductivity, and pore compaction. Furthermore, it is embedded into a 1-D hydromechanical coupled finite element analysis (FEA) to explore the effects of micro-structure rearrangement on the development of reservoir compaction. Numerical examples with the proposed model are compared with simulations under constant hydraulic conductivity to illustrate the model capability to capture the non-linear processes of reservoir compaction induced by fluid depletion.

Buscarnera, Giuseppe↗

Room-temperature single-photon emitters in silicon nitride

Single-photon emitters are essential in enabling several emerging applications in quantum information technology, quantum sensing, and quantum communication. Scalable photonic platforms capable of hosting intrinsic or embedded sources of single-photon emission are of particular interest for the realization of integrated quantum photonic circuits. Here, we report on the observation of room-temperature single-photon emitters in silicon nitride (SiN) films grown on silicon dioxide substrates. Photophysical analysis reveals bright (>10 5 counts/s), stable, linearly polarized, and pure quantum emitters in SiN films with a second-order autocorrelation function value at zero time delay g (2) (0) below 0.2 at room temperature. We suggest that the emission originates from a specific defect center in SiN because of the narrow wavelength distribution of the observed luminescence peak. Single-photon emitters in SiN have the potential to enable direct, scalable, and low-loss integration of quantum light sources with a well-established photonic on-chip platform.

42 ENGINEERING↗

Deep Koopman Neural Network for Analyzing High-Energy-Density Simulations of Electrical Wire Explosions

Megaampere-scale electrical wire experiments (EWEs) provide a platform for studying magnetohydrodynamic (MHD) instability growth in magneto-inertial fusion (MIF) devices. Even when nonlinear simulations of these experiments can digitally reproduce much of the experimentally observed instability growth, interpreting the results and understanding mode growth and evolution can be non-trivial. As a first step toward providing better interpretation of these simulation features, this work investigates the use of a deep neural network that uses Koopman operator theory to analyze the dynamics of pulsed-power-driven explosions of EWEs. This deep neural network is trained on 1-D resistive MHD simulations of EWEs. This neural network learns to transform the nonlinear data into a lower-dimensional representation where the time dynamics are linear. Layers of this neural network are shown to learn features of the simulations, including the locations of shock waves and different physical regimes of the simulation. Using the learned features, the network can compress a time state of the simulation consisting of 5120 data point into a 36-parameter lower-dimensional latent space embedding. Furthermore, these embeddings are shown to be clustered in the latent space by initial radius and time state.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Model-based predictive control of multi-stage air-source heat pumps integrated with phase change material-embedded ceilings

This paper presents a model-based predictive control strategy to optimize the operations of phase change material (PCM) ceiling panels coupled with a multi-stage air-source heat pump. A three-stage prototype heat pump unit has been built and tested in the laboratory, with the low and medium stages designed for space heating/cooling and the high compression stage dedicated to charging of the PCM energy storage. To facilitate optimal control of the integrated heat pump system, a mixed-integer linear programming formulation is derived through linearization of the heat pump model and a mixed-integer reformulation of the PCM dynamic governing equations. A predictive control strategy is synthesized based on the resultant control formulation and implemented in a receding horizon scheme that optimizes the PCM charging and the zone temperature schedules simultaneously to leverage both the passive (associated with building construction materials) and active (PCM) storage capacities of a building. The control strategy has been tested along with three benchmarking control scenarios using a co-simulation platform for a prototypical detached house in Atlanta, GA. In this study, test results showed that application of the proposed control strategy to the PCM-integrated heat pump could provide 27.1% electricity cost savings while a fine tuned rule-based control strategy could achieve cost savings of 20.4%, compared to a baseline case without PCM storage, under a time-of-use rate tariff.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy amplification in plasma crystals due to multiple torsions

Interacting torsions are examined within a two-dimensional monolayer crystal suspended in an argon complex plasma for 1–10 W discharge powers and pressures of 135–155 mTorr. Two torsions embedded in a lattice are shown to amplify the kinetic energy and range of motion of particles located between the torsions to nearly three times that observed in single torsion systems. It is also shown that multiple torsions can interact via amplified particle energy when separated by up to 14 interparticle distances (Δ). The torsion separation distance also showed a positive linear trend with power and a slightly positive correlation with the pressure. This amplification of energy is possible due to the fact that multiple torsions in a lattice increase the interparticle distance of the lattice by 16% more than single torsion systems, leading to additional freedom of motion in the lattice plane. These combined findings show that multiple torsions heat the lattice differently depending on their separation from the other torsion. The midpoint particles between torsions absorb the majority of energy from the two torsions, and energy addition at the midpoint is nonlinear. The addition of more torsions to the lattice may lead to melting of the plasma crystal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Precoder Design for Physical-Layer Security and Authentication in Massive MIMO UAV Communications

Supporting reliable and seamless wireless connectivity for unmanned aerial vehicles (UAVs) has recently become a critical requirement to enable various different use cases of UAVs. Due to their widespread deployment footprint, cellular networks can support beyond visual line of sight (BVLOS) communications for UAVs. In this paper, we consider cellular connected UAVs (C-UAVs) that are served by massive multiple input-multiple-output (MIMO) links to extend coverage range, while also improving physical layer security and authentication. Here, we consider Rician channel and propose a novel linear precoder design for transmitting data and artificial noise (AN). We derive the closed-form expression of the ergodic secrecy rate of CUAVs for both conventional and proposed precoder designs. In addition, we obtain the optimal power splitting factor that divides the power between data and AN by asymptotic analysis. Then, we apply the proposed precoder design in the fingerprint embedding authentication framework, where the goal is to minimize the probability of detection of the authentication tag at an eavesdropper. In simulation results, we show the superiority of the proposed precoder in both secrecy rate and the authentication probability considering moderate and large number of antenna massive MIMO scenarios.

99 GENERAL AND MISCELLANEOUS↗

Metal–Organic Framework–Polyacrylonitrile Composite Beads for Xenon Capture

Mechanically robust forms of HKUST-1 metal-organic frameworks (MOFs) were fabricated by embedding the MOF in a passive polyacrylonitrile (PAN) matrix at different MOF loadings of 10–90 mass%. Here, the PAN is highly porous and acts as a scaffold that holds the active MOF adsorbent in place for Xe capture. Data presented herein show that the PAN matrix does not notably interfere with the Xe capture process where the Xe capacities scale somewhat linearly with the increase in MOF loading in the composites. Radiation testing of the composites under a gamma flux revealed that they are highly tolerant to these types of radiation fields.

36 MATERIALS SCIENCE↗

PBX9502 PAGOSA/SURF Calibration for 100 µm Grid Size

There are two methods to calibrate the SURF reactive burn explosives model.The first is to calibrate using Pop plot data. Because there are only two main parameters in SURF, called A and B, there is just enough flexibility in SURF to determine the Pop plot line, i.e., equivalent information to a slope and a single point on the line. However, due to the linearity of the Pop plot being based on logarithmic scales, a slight deviation off the Pop plot (though the fit to the Pop plot might be very good overall) can make considerable difference when comparing with the velocity profile data. The second calibration method thusly focuses strongly on matching entire velocity profile data. This is to say that individual velocity profiles extracted from embedded gages (in the case of PBX 9502, we refer to R. Gustavsen’s experimental data) may fit poorly, while the overall fit to the Pop plot may seem reasonable. In addition, there are other factors that could produce slightly different calibrations for SURF, while leading to an overall acceptable fit to data. One of those may be the physics code used and here we use Pagosa. Another is mesh size dependence. A third one stems from fitting a reactive burn model being done in conjunction with an equation of state (EOS) of the reactants and one for the products – different EOS can result in slightly different parameterizations. Finally, there are several secondary material parameters in SURF, and the overall fit will depend on the entire parameterization. The goal of this report is to clarify some of our previously made statements about SURF calibration, as well as to redo a systematic calibration using 100 µm grid resolution.

42 ENGINEERING↗

High-Fidelity Large-Signal Order Reduction Approach for Composite Load Model

With the increasing penetration of electronic loads and distributed energy resources, conventional load models cannot capture their dynamics. Therefore, a new comprehensive composite load model is developed by Western Electricity Coordinating Council (WECC). However, this model is a complex high-order non-linear system with multi-time-scale property, which poses challenges on power system studies with heavy computational burden. In order to reduce the model complexity, the authors firstly develop a large-signal order reduction (LSOR) method using singular perturbation theory. In this method, the fast dynamics are integrated into the slow ones to preserve transient characteristics of the former. Then, accuracy assessment conditions are proposed and embedded into the LSOR to improve and guarantee the accuracy of reduced-order model. Finally, the reduced-order WECC composite load model is derived by using the proposed algorithm. Overall, simulation results show that the reduced-order large-signal model significantly alleviates the computational burden while maintaining similar dynamic responses as the original composite load model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Flexocaloric effect near a ferroelastic transition

A Ginzburg-Landau model embedded into a vibrational model is used to study the flexocaloric effect in a beam near a ferroelastic transition. The caloric response upon bending is characterized by the isothermal entropy change and the adiabatic temperature change of the beam. Here, we obtain a larger response relative to the strength of the applied forces at temperatures slightly above the transition temperature. It is also obtained that the maximum caloric response is almost linear with the bending angle of the beam, whereas the relation between the bending angle and the applied forces is highly nonlinear. Small hysteresis associated with the phase transition is obtained for sufficiently large bending forces due to the existence of a critical point in the temperature-stress phase diagram of the ferroelastic material. Finally, the microstructure changes with bending in the beam are consistent with previous experimental observations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution

Recent works exploring deep learning application to dynamical systems modeling have demonstrated that embedding physical priors into neural networks can yield more effective, physically-realistic, and data-efficient models. However, in the absence of complete prior knowledge of a dynamical system's physical characteristics, determining the optimal structure and optimization strategy for these models can be difficult. In this work, we explore methods for discovering neural state space dynamics models for system identification. Starting with a design space of block-oriented state space models and structured linear maps with strong physical priors, we encode these components into a model genome alongside network structure, penalty constraints, and optimization hyperparameters. Demonstrating the overall utility of the design space, we employ an asynchronous genetic search algorithm that alternates between model selection and optimization and obtains accurate physically consistent models of three physical systems: an aerodynamics body, a continuous stirred tank reactor, and a two tank interacting system.

genetic algorithms, neural architecture search, ne↗

Kondo screening in a Majorana metal

Kondo impurities provide a nontrivial probe to unravel the character of the excitations of a quantum spin liquid. In the S = 1/2 Kitaev model on the honeycomb lattice, Kondo impurities embedded in the spin-liquid host can be screened by itinerant Majorana fermions via gauge-flux binding. Here, we report experimental signatures of metallic-like Kondo screening at intermediate temperatures in the Kitaev honeycomb material α-RuCl 3 with dilute Cr 3+ (S = 3/2) impurities. The static magnetic susceptibility, the muon Knight shift, and the muon spin-relaxation rate all feature logarithmic divergences, a hallmark of a metallic Kondo effect. Concurrently, the linear coefficient of the magnetic specific heat is large in the same temperature regime, indicating the presence of a host Majorana metal. This observation opens new avenues for exploring uncharted Kondo physics in insulating quantum magnets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A multivariate library of zirconia metal–organic frameworks with dissolved p -nitroaniline dipoles and concentration-dependent optical and dielectric response

In this work, we show how the combination of soluble non-polar and polar links allows for the preparation of multivariate metal–organic frameworks (MTV MOFs) that exhibit dipolar solid-solution behavior. We prepared a library of PIZOF-2 MOFs with varied concentrations of p -nitroaniline (PNA)-containing moiety embedded within the MTV links. This library forms a partial solid solution up to 30 mol% with input/output composition ratio of 0.536 ± 0.018. MOFs with x > 5 mol% PNA show concentration-dependent hypsochromic dipole–dipole coupling (H-coupling) in the solid-state UV-visible spectra. The MTV library also exhibits a dielectric relaxation event in the broadband dielectric spectra with activation enthalpies and entropies that vary with temperature and PNA content and follow linear Meyer–Neldel compensation relations.

Langlois, Kyle R. [Univ. of Central Florida, Orlan↗

Review on the growth, properties and applications of self-assembled oxide–metal vertically aligned nanocomposite thin films—current and future perspectives

Self-assembled oxide–metal nanocomposite thin films have aroused great research interest owing to their wide range of functionalities, including metamaterials with plasmonic and hyperbolic optical properties, and ferromagnetic, ferroelectric and multiferroic behaviors. Oxide–metal nanocomposites typically self-assemble as metal particles in an oxide matrix or as a vertically aligned nanocomposite (VAN) with metal nanopillars embedded in an oxide matrix. Among them, the VAN architecture is particularly interesting due to the vertical strain control and highly anisotropic structure, enabling the epitaxial growth of materials with large lattice mismatch. In this review, the driving forces behind the formation of self-assembled oxide–metal VAN structures are discussed. Specifically, an updated in-plane strain compensation model based on the areal strain compensation concept has been proposed in this review, inspired by the prior linear strain compensation model. It provides a guideline for material selection for designing VAN systems, especially those involving complex orientation matching relationships. Based on the model, several case studies are discussed, comparing the microstructure and morphology of different oxide–metal nanocomposites by varying the oxide phase. Specific examples highlighting the coupling between the electrical, magnetic and optical properties are also discussed in the context of oxide–metal nanocomposites. Finally, future research directions and needs are also discussed.

36 MATERIALS SCIENCE↗

Linker-Free Magnetite-Decorated Gold Nanoparticles (Fe3O4-Au): Synthesis, Characterization, and Application for Electrochemical Detection of Arsenic (III)

Linker-free magnetite nanoparticles (Fe3O4NPs)-decorated gold nanoparticles (AuNPs) were grown using a new protocol that can be used as a new platform for synthesis of other intact metal–metal oxide nanocomposites without the need for linkers. This minimizes the distance between the metal and metal oxide nanoparticles and ensures the optimum combined effects between the two material interfaces. X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy confirmed the successful synthesis of the Fe3O4-Au nanocomposite, without any change in the magnetite phase. Characterization, using transmission electron microscopy (TEM), scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) spectroscopy, revealed the composite to consist of AuNPs of 70 ± 10 nm diameter decorated with tiny 10 ± 3 nm diameter Fe3O4NPs in Au:Fe mass ratio of 5:1. The prepared Fe3O4-Au nanocomposite was embedded in ionic liquid (IL) and applied for the modification of glassy carbon electrode (GCE) for the electrochemical detection of As(III) in water. By combining the excellent catalytic properties of the AuNPs with the high adsorption capacity of the tiny Fe3O4NPs towards As(III), as well as the good conductivity of IL, the Fe3O4-Au-IL nanocomposite showed excellent performance in the square wave anodic stripping voltammetry detection of As(III). Under the optimized conditions, a linear range of 1 to 100 μg/L was achieved with a detection limit of 0.22 μg/L (S/N = 3), and no interference from 100-fold higher concentrations of a wide variety of cations and anions found in water. A very low residual standard deviation of 1.16% confirmed the high precision/reproducibility of As(III) analysis and the reliability of the Fe3O4-Au-IL sensing interface. Finally, this proposed sensing interface was successfully applied to analyzing synthetic river and wastewater samples with a 95–101% recovery, demonstrating excellent accuracy, even in complex synthetic river and wastewater samples containing high concentrations of humic acid without any sample pretreatments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗