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At least 235 records · Page 13

Thermodynamics of high-pressure ice phases explored with atomistic simulations

Most experimentally known high-pressure ice phases have a body-centred cubic (bcc) oxygen lattice. Our large-scale molecular-dynamics simulations with a machine-learning potential indicate that, amongst these bcc ice phases, ices VII, VII' and X are the same thermodynamic phase under different conditions, whereas superionic ice VII" has a first-order phase boundary with ice VII'. Moreover, at about 300 GPa, the transformation between ice X and the Pbcm phase has a sharp structural change but no apparent activation barrier, whilst at higher pressures the barrier gradually increases. Our study thus clarifies the phase behaviour of the high-pressure ices and reveals peculiar solid–solid transition mechanisms not known in other systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Tuning of electronic properties in highly lattice-mismatched epitaxial SmN

Here, we establish the relationship between native N vacancies, introduced through varying growth parameters, and the structural and transport properties in SmN thin films grown via molecular beam epitaxy grown on MgO(001). The varying levels of N vacancies introduced by varying the ratio of Sm to N atoms during deposition creates excess carriers that radically transform the electrical behavior of the film, over a range of five orders of magnitude, from highly resistive to highly conductive, and unlocking a phase transition evidenced by the presence of a ferromagnetic feature in resistivity. X-ray photoelectron spectroscopy results show that this effect is much less pronounced when varying the available nitrogen species. These samples retain a highly crystal quality despite being grown on a substrate with a lattice mismatch of 20%, alleviating the strain by forming a highly strained SmO oxide layer. The integration between SmN and several transition metal nitride compounds has the potential to unlock new architectures for Josephson junction devices.

36 - MATERIALS SCIENCE↗

Fast and scalable quantum Monte Carlo simulations of electron-phonon models

We introduce methodologies for highly scalable quantum Monte Carlo simulations of electron-phonon models, and report benchmark results for the Holstein model on the square lattice. The determinant quantum Monte Carlo (DQMC) method is a widely used tool for simulating simple electron-phonon models at finite temperatures, but incurs a computational cost that scales cubically with system size. Alternatively, near-linear scaling with system size can be achieved with the hybrid Monte Carlo (HMC) method and an integral representation of the Fermion determinant. Here, we introduce a collection of methodologies that make such simulations even faster. To combat "stiffness" arising from the bosonic action, we review how Fourier acceleration can be combined with time-step splitting. To overcome phonon sampling barriers associated with strongly-bound bipolaron formation, we design global Monte Carlo updates that approximately respect particle-hole symmetry. To accelerate the iterative linear solver, we introduce a preconditioner that becomes exact in the adiabatic limit of infinite atomic mass. Finally, we demonstrate how stochastic measurements can be accelerated using fast Fourier transforms. Here, these methods are all complementary and, combined, may produce multiple orders of magnitude speedup, depending on model details.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

16 O Electroweak Response Functions from First Principles

We present calculations of various electroweak response functions for the 16 O nucleus obtained using coupled-cluster theory in conjunction with the Lorentz integral transform method. We employ nuclear forces derived at next-to-leading order and next-to-next-to-leading order in chiral effective field theory and perform a Bayesian analysis to assess uncertainties. Our results are in good agreement with available electron-scattering data at |𝐪|≈326 MeV/c. Additionally, we provide several predictions for the weak response functions in the quasielastic peak region at |𝐪| =300 and 400 MeV/c, which are critical for long-baseline neutrino experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Metallization of colloidal crystals

Colloidal crystals formed by size-asymmetric binary particles coassemble into a wide variety of colloidal compounds with lattices akin to ionic crystals. Recently, a transition from a compound phase with a sublattice of small particles to a metal-like phase in which the small particles are delocalized has been predicted computationally and observed experimentally. In this colloidal metallic phase, the small particles roam the crystal maintaining the integrity of the lattice of large particles, as electrons do in metals. A similar transition also occurs in superionic crystals, termed sublattice melting. Here, we use energetic principles and a generalized molecular dynamics model of a binary system of functionalized nanoparticles to analyze the transition to sublattice delocalization in different coassembled crystal phases as a function of temperature (T), number of grafted chains on the small particles, and number ratio between the small and large particles n s : n l . Here we find that n s : n l is the primary determinant of crystal type due to energetic interactions and interstitial site filling, while the number of grafted chains per small particle determines the stability of these crystals. We observe first-order sublattice delocalization transitions as T increases, in which the host lattice transforms from low- to high-symmetry crystal structures, including A20 → bct → bcc, A d → bct → bcc, and bcc → bcc/fcc → fcc transitions and lattices. Analogous sublattice transitions driven primarily by lattice vibrations have been seen in some atomic materials exhibiting an insulator-metal transition also referred to as metallization. We also find minima in the lattice vibrations and diffusion coefficient of small particles as a function of n s : n l , indicating enhanced stability of certain crystal structures for n s : n l values that form compounds.

36 MATERIALS SCIENCE↗

On the Impact of High-Order Harmonic Generation in Electrical Distribution Systems

The modern power grid has seen a rise in the integration of non-linear loads, presenting a significant concern for operators. These loads introduce unwanted harmonics, leading to potential issues such as overheating and improper functioning of circuit breakers. In pursuing a more sustainable grid, the adoption of electric vehicles (EVs) and photovoltaic (PV) systems in residential networks has increased. Understanding and examining the effects of high-order harmonic frequencies beyond $1.5$ kHz is crucial to understanding their impact on the operation and planning of electrical distribution systems under varying nonlinear loading conditions. This study investigates a diverse set of critical power electronic loads within a household modeled using PSCAD/EMTdc, analyzing their unique harmonic spectra. This information is utilized to run the time-series harmonic analysis program in OpenDSS on a modified IEEE 34 bus test system model. The impact of high-order harmonics is quantified using metrics that evaluate total harmonic distortion (THD), transformer harmonic-driven eddy current loss component, and propagation of harmonics from the source to the substation transformer.

Peerzada, Aaqib A. [BATTELLE (PACIFIC NW LAB)]↗

Distribution Market-Clearing and Pricing Considering Coordination of DSOs and ISO: An EPEC Approach

Distribution-level electricity market provides a platform for trading energy and grid services from large-amount of small-scale distributed energy resources (DERs) located on distribution grids. The behavior of the DERs in the distribution electricity market may ultimately impact the market-clearing and locational marginal prices (LMPs) in the wholesale market. This paper proposes a bi-level optimization model for distribution market clearing and distribution locational marginal pricing (DLMP) considering the interactions between distribution and transmission wholesale markets. In the proposed model, the upper-level model represents the distribution system operator (DSO) market-clearing and the lower-level model represents the wholesale market-clearing by the independent system operator (ISO). The LMP at the substation will impact the DER dispatch and power demands of the DSO as well as the DLMP. In turn, the power demands of the DSO will further impact the ISO market and its LMPs. The equilibrium problem with equilibrium constraints (EPEC) approach is applied to find the equilibria of multiple DSOs and the ISO. The EPEC problem is transformed into a single-level mixed-integer convex problem in order to allow for efficient solving. Finally, the effectiveness of the proposed model and solution method are demonstrated through case studies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Powder Diffraction Crystallography : 98 Years as Plan B?

A historical essay written in 2014 to accompany a talk in the Transactions Symposium "100 Years of Crystallography" at the 2014 American Crystallographic Association Annual Meeting (talk at https://history.amercrystalassn.org/h-brian-toby-videos). Abstract: Powder diffraction patterns were used for structure solution almost contemporaneously with the Bragg’s initial single-crystal determinations. Structures have continued to be determined from powders, in the subsequent century. There has been a nearly explosive growth in this technique since the 1970’s. This was initially driven by neutron diffraction, which prompted the invention of Rietveld analysis, but synchrotrons have gone on to have at least as large an impact. There is no apparent upper limit to the scale of systems that can be structurally studied with powder diffraction; novel protein structures have been determined. When short-range ordering or disordered regions of a material are of interest, the Fourier transform of a powder diffraction pattern, the pair distribution function can be modeled.

Toby, Brian H.↗

Uncertainties in ab initio nuclear structure calculations with chiral interactions

We present theoretical ground state energies and their uncertainties for p -shell nuclei obtained from chiral effective field theory internucleon interactions as a function of chiral order, fitted to two- and three-body data only. We apply a Similary Renormalization Group transformation to improve the numerical convergence of the many-body calculations, and discuss both the numerical uncertainties arising from basis truncations and those from omitted induced many-body forces, as well as chiral truncation uncertainties. With complete Next-to-Next-to-Leading (N 2 LO) order two- and three-body interactions, we find significant overbinding for the ground states in the upper p -shell, but using higher-order two-body potentials, in combination with N 2 LO three-body forces, our predictions agree with experiment throughout the p -shell to within our combined estimated uncertainties. The uncertainties due to chiral order truncation are noticeably larger than the numerical uncertainties, but they are expected to become comparable to the numerical uncertainties at complete N 3 LO.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Monte Carlo MP2-F12 for Noncovalent Interactions: The C 60 Dimer

A scalable stochastic algorithm is presented that can evaluate explicitly correlated (F12) second-order many-body perturbation (MP2) energies of weak, noncovalent, intermolecular interactions. It first transforms the formulas of the MP2 and F12 energy differences into a short sum of high-dimensional integrals of Green’s functions in real space and imaginary time. Furthermore, these integrals are then evaluated by the Monte Carlo method augmented by parallel execution, redundant-walker convergence acceleration, direct-sampling autocorrelation elimination, and control-variate error reduction. By sharing electron-pair walkers across the supermolecule and its subsystems spanned by the joint basis set, the statistical uncertainty is reduced by one to 2 orders of magnitude in the MP2 binding energy corrected for the basis-set incompleteness and superposition errors. The method predicts the MP2-F12/aug-cc-pVDZ binding energy of 19.1 ± 4.0 kcal mol –1 for the C 60 dimer at the center distance of 9.748 Å.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning based rate optimization under geologic uncertainty

We propose a novel approach for rate optimization during a waterflood under geologic uncertainty in reservoir properties such as permeability and porosity. The traditional approach typically involves several runs of the forward simulator. This may not scale well when the optimization is to be performed at the full field-level and over multiple geologic realizations. A machine-learning (ML) based approach which is quick and scalable for rate optimization over multiple geologic realizations is proposed instead. The training data for the model is generated by running the forward simulator with randomly assigned well rates using multiple geologic realizations. A reduced order representation of the permeability heterogeneity in each of the realizations is derived using a grid connectivity transformation (GCT). This step involves finding basis functions corresponding to the different modal frequencies of the grid connectivity represented by the grid Laplacian. The projection of the heterogeneous property field along these basis functions gives the basis coefficients that form the reduced order representation. Subsequently, for each training datapoint, streamlines are traced and the minimum time of flight (TOF) representing the tracer breakthrough time at each producer is recorded. The basis coefficients and well rates are fed to a machine learning model as input and the minimum TOF at the producers forms the output of the model. This trained model can then be used along with an optimizer for computing the optimal injection rates to maximize the injection sweep efficiency. This corresponds to minimizing the variance in the minimum TOF within each well group. Different architectures of neural network are tested using 5-fold cross validation to decide the best ML model to compute the streamline time of flight. The trained model is used to perform well rate optimization over multiple realizations of geology by using a risk tolerance penalty. The optimal well rates thus obtained are compared with two cases: a) equal well rates assigned to all injectors and producers and b) well rates obtained by optimizing over a single realization without considering the uncertainty in geology. The optimal well rates are seen to offer better oil recovery and sweep efficiency than both cases.

02 PETROLEUM↗

Impact of the d 0 transition metal on local structural transformations in disordered rock salt cathodes

Although it is widely accepted that the long-range (average) crystal structure plays a critical role in determining the electrochemical performance of battery materials, the relationship between local structural features and electrochemical performance is rarely studied. Disordered rock salt oxides (DRX), which have become serious contenders for next generation Li-ion electrode materials, provide an ideal platform for exploring correlations between local structure and electrochemical performance as they exhibit a simple face-centered cubic structure and combine long-range disorder and short-range order on the cation sublattice. This work examines the Li 1.1 Mn 0.7 Zr 0.2−x Ti x O 2 series of DRX cathodes and investigates the links between local structure rearrangements and capacity activation. The end-member Li 1.1 Mn 0.7 Zr 0.2 O 2 compound exhibits a low capacity in the as-synthesized state, attributed to unfavorable short-range order that hinders Li-ion transport, yet its capacity increases seven-fold, from 20 to 140 mAh g −1 , after chemical delithiation followed by a 400 °C heat treatment. Capacity activation is associated with the appearance of local spinel-like structural features that depart from the short-range order originally present in the material, without significant change to the bulk composition and average crystal structure. Investigation of a series of Li 1.1 Mn 0.7 Zr 0.2−x Ti x O 2 (x ≤ 0.2) DRX compounds reveals that the correlation length of the spinel-like ordering that emerges during the heat treatment strongly depends on the Zr : Ti ratio. Yet, dramatic capacity activation and electrochemical (pseudo-)plateaus reminiscent of Mn-based spinel cathodes are observed for all compounds irrespective of the size of the ordered domains. To explain this phenomenon, we propose that the DRX phase undergoes a complete transformation to a spinel-like domain structure, which improves bulk Li-ion transport regardless of domain size.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Direct observations of transient weakening during phase transformations in quartz and olivine

Phase transformations are widely invoked as a source of rheological weakening during subduction, continental collision, mantle convection and various other geodynamic phenomena. However, despite more than half a century of research, the likelihood and magnitude of such weakening in nature remain poorly constrained. Here we use experiments performed on a synchrotron beamline to reveal transient weakening of up to three orders of magnitude during the polymorphic quartz to coesite (SiO 2 ) and olivine to ringwoodite (Fe 2 SiO 4 ) phase transitions. Weakening becomes increasingly prominent as the transformation outpaces deformation. We suggest that this behaviour is broadly applicable among silicate minerals undergoing first-order phase transitions and examine the likelihood of weakening due to the olivine-spinel, (Mg,Fe) 2 SiO 4 , transformation during subduction. Modelling suggests that cold, wet slabs are most susceptible to transformational weakening, consistent with geophysical observations of slab stagnation in the mantle transition zone beneath the western Pacific. In conclusion, our study highlights the importance of incorporating transformational weakening into geodynamic simulations and provides a quantitative basis for doing so.

Cross, Andrew J. [Woods Hole Oceanographic Institu↗

Chiral properties of the nucleon interpolating current and θ-dependent observables

We revisit the chiral properties of nucleon interpolating currents, and show that of the two leading order currents j 1 and j 2 , only two linear combinations j 1 ± j 2 transform covariantly under the anomalous U⁢(1) A symmetry. As a result, calculations of quantities which vanish by symmetry in the chiral limit may produce unphysical results if carried out with different linear combinations of the currents. This includes observables such as electric dipole moments, induced by the quantum chromodynamics (QCD) parameter θ, and the θ-dependence of the nucleon mass. For completeness, we also exhibit the leading order results for nucleon electric dipole moments (d n,p ) induced by θ, and the nucleon magnetic moments (μ n,p ), when calculated using QCD sum rules for both the covariant choices of the nucleon interpolating current. The results in each channel, conveniently expressed as the ratios, d n,p /μ n,p , are numerically consistent, and reflect the required physical dependence on θ.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Comparison of short-range order in irradiated dysprosium titanates

Abstract The structural response of Dy 2 TiO 5 oxide under swift heavy ion irradiation (2.2 GeV Au ions) was studied over a range of structural length scales utilizing neutron total scattering experiments. Refinement of diffraction data confirms that the long-range orthorhombic structure is susceptible to ion beam-induced amorphization with limited crystalline fraction remaining after irradiation to 8 × 10 12 ions/cm 2 . In contrast, the local atomic arrangement, examined through pair distribution function analysis, shows only subtle changes after irradiation and is still described best by the original orthorhombic structural model. A comparison to Dy 2 Ti 2 O 7 pyrochlore oxide under the same irradiation conditions reveals a different behavior: while the dysprosium titanate pyrochlore is more radiation resistant over the long-range with smaller degree of amorphization as compared to Dy 2 TiO 5 , the former involves more local atomic rearrangements, best described by a pyrochlore-to-weberite-type transformation. These results highlight the importance of short-range and medium-range order analysis for a comprehensive description of radiation behavior.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Direct neutron-diffraction-based measurement of magnetic order in brownmillerite SrCoO 2.5 and La 0.5 Sr 0.5 CoO 2.5 thin films

Epitaxial cobaltites have emerged as exemplary materials for electrochemical gating, in large part due to their topotactic perovskite (P) ↔ brownmillerite (BM) transformations. SrCoO 3-δ , for example, can be cycled between metallic ferromagnetic P SrCoO 3 and insulating BM SrCoO 2.5 , realizing exceptional modulation of electronic, thermal, and optical properties. It is often presumed that such cycling also generates ferromagnetic–antiferromagnetic (F-AF) modulation due to the G-type AF order in bulk SrCoO 2.5 . Little is understood about magnetism in thin-film BM SrCoO 2.5 , however, meaning that the true magnetic property modulation is unclear. We address this here through a neutron diffraction study of BM La 1-x Sr x CoO 2.5 films at x = 0.5 and 1.0. Lightly compressively strained SrCoO 2.5 films are shown to retain G-type AF order, albeit with suppressed Néel temperature (~340 K). Of high interest for AF spintronics, room-temperature F–AF cycling is thus possible across the SrCoO 3-δ P ↔ BM transformation. At x = 0.5, however, BM La 0.5 Sr 0.5 CoO 2.5 films are found to exhibit no detectable G-type AF order but instead weak F order (Curie temperature ~115 K), unveiling a La 0.5 Sr 0.5 CoO 3-δ phase diagram with two distinct F phases. These results thus uncover new, unanticipated magnetic phase behavior in these materials, in addition to being directly relevant to cobaltite-based magnetoionics.

36 MATERIALS SCIENCE↗

Unprecedented generation of 3D heterostructures by mechanochemical disassembly and re-ordering of incommensurate metal chalcogenides

Three-dimensional heterostructures are usually created either by assembling two-dimensional building blocks into hierarchical architectures or using stepwise chemical processes that sequentially deposit individual monolayers. Both approaches suffer from a number of issues, including lack of suitable precursors, limited reproducibility, and poor scalability of the preparation protocols. Therefore, development of alternative methods that enable preparation of heterostructured materials is desired. We create heterostructures with incommensurate arrangements of well-defined building blocks using a synthetic approach that comprises mechanical disassembly and simultaneous reordering of layered transition-metal dichalcogenides, MX 2 , and non-layered monochalcogenides, REX, where M = Ta, Nb, RE = Sm, La, and X = S, Se. We show that the discovered solid-state processes are rooted in stochastic mechanochemical transformations directed by electronic interaction between chemically and structurally dissimilar solids toward atomic-scale ordering, and offer an alternative to conventional heterostructuring. Details of composition–structure–properties relationships in the studied materials are also highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hutchinson Trace Estimation for high-dimensional and high-order Physics-Informed Neural Networks

Physics-Informed Neural Networks (PINNs) have proven effective in solving partial differential equations (PDEs), especially when some data are available by seamlessly blending data and physics. However, extending PINNs to high-dimensional and even high-order PDEs encounters significant challenges due to the computational cost associated with automatic differentiation in the residual loss function calculation. Herein, we address the limitations of PINNs in handling high-dimensional and high-order PDEs by introducing the Hutchinson Trace Estimation (HTE) method. Starting with the second-order high-dimensional PDEs, which are ubiquitous in scientific computing, HTE is applied to transform the calculation of the entire Hessian matrix into a Hessian vector product (HVP). This approach not only alleviates the computational bottleneck via Taylor-mode automatic differentiation but also significantly reduces memory consumption from the Hessian matrix to an HVP’s scalar output. We further showcase HTE’s convergence to the original PINN loss and its unbiased behavior under specific conditions. Comparisons with the Stochastic Dimension Gradient Descent (SDGD) highlight the distinct advantages of HTE, particularly in scenarios with significant variability and variance among dimensions. We further extend the application of HTE to higher-order and higher-dimensional PDEs, specifically addressing the biharmonic equation. By employing tensor-vector products (TVP), HTE efficiently computes the colossal tensor associated with the fourth-order high-dimensional biharmonic equation, saving memory and enabling rapid computation. The effectiveness of HTE is illustrated through experimental setups, demonstrating comparable convergence rates with SDGD under memory and speed constraints. Additionally, HTE proves valuable in accelerating the Gradient-Enhanced PINN (gPINN) version as well as the Biharmonic equation. Overall, HTE opens up a new capability in scientific machine learning for tackling high-order and high-dimensional PDEs.

Curse of dimensionality↗