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At least 127 records · Page 7

A method for bounding high-order finite element functions: Applications to mesh validity and bounds-preserving limiters

We introduce a novel method for bounding high-order multi-dimensional polynomials in finite element approximations. The method involves precomputing optimal piecewise-linear bounding boxes for polynomial basis functions, which can then be used to locally bound any combination of these basis functions. This approach can be applied to any element/basis type at any approximation order, can provide local (i.e., subcell) extremum bounds to a desired level of accuracy, and can be evaluated efficiently on-the-fly in simulations. Furthermore, we show that this approach generally yields more accurate bounds in comparison to traditional methods based on convex hull properties (e.g., Bernstein polynomials). Furthermore, the efficacy of this technique is shown in applications such as mesh validity checks and optimization for high-order curved meshes, where positivity of the element Jacobian determinant can be ensured throughout the entire element, and continuously bounds-preserving limiters for hyperbolic systems, which can enforce maximum principle bounds across the entire solution polynomial.

Bounding box↗

Understanding the Effect of Lead Iodide Excess on the Performance of Methylammonium Lead Iodide Perovskite Solar Cells

The presence of unreacted lead iodide in organic-inorganic lead halide perovskite solar cells is widely correlated with an increase in power conversion efficiency. We investigate the mechanism for this increase by identifying the role of surfaces and interfaces present between methylammonium lead iodide perovskite films and excess lead iodide. We show how type I and II band alignments arising under different conditions result in either passivation of surface defects or hole injection. Through first-principles simulations of solid-solid interfaces, we find that lead iodide captures holes from methylammonium lead iodide and modulates the formation of defects in the perovskite, affecting recombination. Using surface-sensitive optical spectroscopy techniques, such as transient reflectance and time-resolved photoluminescence, we show how excess lead iodide affects the diffusion and surface recombination velocity of charge carriers in methylammonium lead iodide films. Our coupled experimental and theoretical results elucidate the role of excess lead iodide in perovskite solar cells.

14 SOLAR ENERGY↗

Vibronic coupling in energy transfer dynamics and two-dimensional electronic–vibrational spectra

We introduce a heterodimer model in which multiple mechanisms of vibronic coupling and their impact on energy transfer can be explicitly studied. We consider vibronic coupling that arises through either Franck-Condon activity in which each site in the heterodimer has a local electron-phonon coupling or Herzberg-Teller activity in which the transition dipole moment coupling the sites has an explicit vibrational mode-dependence. We have computed two-dimensional electronic-vibrational (2DEV) spectra for this model while varying the magnitude of these two effects and find that 2DEV spectra contain static and dynamic signatures of both types of vibronic coupling. Franck-Condon activity emerges through a change in the observed excitonic structure, while Herzberg-Teller activity is evident in the appearance of significant side-band transitions that mimic the lower-energy excitonic structure. A comparison of quantum beating patterns obtained from analysis of the simulated 2DEV spectra shows that this technique can report on the mechanism of energy transfer, elucidating a means of experimentally determining the role of specific vibronic coupling mechanisms in such processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advancing Cyber-Attack Detection in Power Systems: A Comparative Study of Machine Learning and Graph Neural Network Approaches

This paper explores the detection and localization of cyber-attacks on power systems, focusing on comparing conventional machine learning (ML) and deep learning methods, and graph neural network (GNN)-based techniques. We assess the detection accuracy of these approaches and their potential to pinpoint the locations of specific buses under attack. Given the demonstrated success of GNNs in other time series anomaly detection applications, we aim to evaluate their performance within the context of power systems cyber-attack. Utilizing the IEEE 68-bus system, we simulated four types of attacks to test the selected approaches. Our results indicate that GNN-based methods outperform conventional machine learning and deep learning models in detection. Additionally, GNNs show promise in accurately localizing attacks for simple scenarios, although they still face challenges in more complex cases.

artificial intelligence↗

OpenSn: A massively parallel, open-source simulation environment for discrete ordinates radiation transport

OpenSn is an open-source, massively parallel deterministic radiation transport code for solving the discrete-ordinates ( S N ) form of the Boltzmann transport equation on unstructured, arbitrary polyhedral meshes. It supports high-fidelity simulations involving steady-state, eigenvalue, and adjoint problems for neutral particles (e.g., neutrons, photons, multi-particles), using the multigroup approximation in energy. OpenSn combines angular discretization via discrete ordinates with a discontinuous Galerkin finite element method (DGFEM) in space, enabling accurate resolution of transport physics on arbitrary polyhedral cells, included locally refined spatial grids. It includes multiple angular quadrature types, including locally refined angular quadratures. Written in modern C++ with a Python API, OpenSn runs efficiently on platforms ranging from laptops to supercomputers. The transport sweep algorithm is implemented using a task-based, directed-acyclic-graph (DAG) approach for each angle and supports asynchronous parallelism across thousands of MPI ranks. Group-set aggregation improves compute intensity, and synthetic acceleration techniques (e.g., diffusion synthetic acceleration, second-moment method) enhance solver convergence. OpenSn has been verified on reactor physics problems and demonstrated excellent weak and strong scaling performance on more than 32,768 processes, making it a versatile and robust platform for large-scale transport simulations in complex geometries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Applicability of 1D site response analysis to shallow sedimentary basins: A critical evaluation through physics-based 3D ground motion simulations

One-dimensional site response analysis (1D SRA) remains the standard practice in considering the effect of local soil deposits and predicting site-specific ground motions, although its range of applicability to realistic seismic wavefields is still in question. In this 1D approach, horizontal and vertical ground shaking are assumed to be induced by vertically propagating shear and compressional waves, respectively. A recent study based on analytical two-dimensional (2D) plane waves and simple point source earthquake simulations has shown two mechanistic limitations in this 1D modelling technique for general inclined seismic waves, that is, systematic over-prediction of the vertical motion and wave trapping in the 1D soil column. In this article, we evaluate in detail the applicability of this 1D modelling approach to realistic three-dimensional (3D) simulated seismic wavefields in shallow sedimentary basins. Linear-viscoelastic 1D SRA predictions using two types of input motions that are commonly used in practice—rock outcrop and in-column motions, are compared with the reference true site response results from 3D earthquake simulations in terms of various measures in the frequency and time domain. It is shown that the horizontal motion in the 3D seismic wavefield exhibits dominant shear wave propagation phenomenon, while the vertical motion is a combined effect of compressional and shear waves and can be over-predicted by the 1D approach when the incident seismic waves are inclined. Direct evidence of the wave refraction process that leads to the vertical motion over-prediction is provided. 1D SRA with in-column inputs can yield motions that have significantly longer duration compared to the true 3D site response solution due to trapped waves, casting in doubt the frequent need for increased soil damping in existing site studies to compensate for wave attenuation due to scattering alone. Sensitivity investigation on the increase of soil profile damping by a multiplier D mul shows D mul values compatible with those found in the literature for both horizontal and vertical motions. It is shown that the level of D mul optimized for a best match of the spectral acceleration is dependent on the characteristic of the input motion and a larger D mul is typically required for the vertical component. In contrast, 1D SRA with outcrop motions predicts motions with shorter significant duration due to its inability to capture the basin-edge generated surface waves. A suite of ground motion simulations was performed to assess the sensitivity of the observations to the basin geologic structure including the velocity gradient, rock-basin impedance contrast and basin depth. The analysis results show that the accuracy of the simplified 1D procedure is dependent on the wavefield composition of both the input motions and the true 3D site response solution. While the horizontal motions in shallow sedimentary basins can, to the first order, be reasonably captured by the simplified 1D approach, 1D SRA for the vertical component is in general not reliable and contributions from inclined shear waves should be accounted for in site-specific evaluation of the vertical design ground motion.

1D assumption↗

Stable Element Doping of Sol-gel Toward Simulating Environmental Matrix in Surrogate Explosive Nuclear Debris

Training nuclear forensic analysis personnel in post-detonation scenarios is of critical importance to nuclear threat response capabilities. Thus, realistic nuclear debris simulants which resemble the size, color, elemental composition, and radionuclide content of actual nuclear fallout from a recent detonation would be valuable for training nuclear first responders in realistic scenarios. As nuclear fallout types vary significantly in each of these parameters based on detonation environment (rural, urban, maritime etc.) and collection location, the ability to tailor each of these parameters accurately in simulated debris would be of immense benefit to the post-detonation analysis community for training both in-field collections and triage and the validation of laboratory level nuclear forensic techniques. Sol-gel synthesis techniques can provide the tunability of size, shape and composition required for producing surrogate nuclear debris of a wide variety. The sol-gel process consists of forming a metal oxide material, often silica, through polymerization of a metal-alkoxy precursor. In this work, we characterize the ability to load the sol-gel particles with secondary elemental components such as iron, aluminum, and calcium toward approximating the elemental composition of debris from various detonation environments and demonstrate the ability to produce particles with controllable size, shape, and color. We also demonstrate quantitative radionuclide encapsulation toward reproducing the radionuclide content of actual fallout from a recent detonation. Finally, we then employ these techniques in producing simulated aerodynamic debris samples with realistic elemental matrix composition and radionuclide content simulating a recent uranium-fueled detonation taking place in a rural desert environment and compare it to historic fallout from the Nevada Nuclear Security Site.

36 MATERIALS SCIENCE↗

Stable Element Doping of Sol-gel Toward Simulating Environmental Matrix in Surrogate Explosive Nuclear Debris

Training nuclear forensic analysis personnel in post-detonation scenarios is of critical importance to nuclear threat response capabilities. Thus, realistic nuclear debris simulants which resemble the size, color, elemental composition, and radionuclide content of actual nuclear fallout from a recent detonation would be valuable for training nuclear first responders in realistic scenarios. As nuclear fallout types vary significantly in each of these parameters based on detonation environment (rural, urban, maritime etc.) and collection location, the ability to tailor each of these parameters accurately in simulated debris would be of immense benefit to the post-detonation analysis community for training both in-field collections and triage and the validation of laboratory level nuclear forensic techniques. Sol-gel synthesis techniques can provide the tunability of size, shape and composition required for producing surrogate nuclear debris of a wide variety. The sol-gel process consists of forming a metal oxide material, often silica, through polymerization of a metal-alkoxy precursor. In this work, we characterize the ability to load the sol-gel particles with secondary elemental components such as iron, aluminum, and calcium toward approximating the elemental composition of debris from various detonation environments and demonstrate the ability to produce particles with controllable size, shape, and color. We also demonstrate quantitative radionuclide encapsulation toward reproducing the radionuclide content of actual fallout from a recent detonation. Finally, we then employ these techniques in producing simulated aerodynamic debris samples with realistic elemental matrix composition and radionuclide content simulating a recent uranium-fueled detonation taking place in a rural desert environment and compare it to historic fallout from the Nevada Nuclear Security Site.

36 MATERIALS SCIENCE↗

Vertical van der Waals heterojunction diodes comprising 2D semiconductors on 3D β-Ga 2 O 3

Wide bandgap semiconductors such as gallium oxide (Ga 2 O 3 ) have attracted much attention for their use in next-generation high-power electronics. Although single-crystal Ga 2 O 3 substrates can be routinely grown from melt along various orientations, the influence of such orientations has been seldom reported. Further, making rectifying p–n diodes from Ga 2 O 3 has been difficult due to lack of p-type doping. In this study, we fabricated and optimized 2D/3D vertical diodes on β-Ga 2 O 3 by varying the following three factors: substrate planar orientation, choice of 2D material and metal contacts. Furthermore, the quality of our devices was validated using high-temperature dependent measurements, atomic-force microscopy (AFM) techniques and technology computer-aided design (TCAD) simulations. Our findings suggest that 2D/3D β-Ga 2 O 3 vertical heterojunctions are optimized by substrate planar orientation (–201), combined with 2D WS 2 exfoliated layers and Ti contacts, and show record rectification ratios (>10 6 ) concurrently with ON-Current density (>10 3 A cm –2 ) for application in power rectifiers.

36 MATERIALS SCIENCE↗

Two-color, intracavity pump–probe, cavity ringdown spectroscopy

Here, we report a proof-of-principle demonstration of intracavity pump–probe, cavity ringdown (CRD) detection in a three-mirror, traveling-wave cavity. With cavity-enhanced pump power and probe absorption path length, the technique is a generally applicable, high-sensitivity, high-selectivity detection method. In our experiments, the pump radiation is switched off during every other probe ringdown, which allows uncorrelated measurements of analyte and background cavity decay rates. The net, two-color signal from the difference between the pump-on and pump-off decay rates is immune to empty-CRD drifts and spectral overlaps from non-target molecular transitions. The immunity to the ringdown drifts allows longer signal-averaging and, thus, higher detection sensitivity. The ability to compensate for the background absorption enhances the detection selectivity in spectrally congested regions. Our technique is well-suited for trace-detection in the mid-IR region, where pump–probe schemes based on strong rovibrational transitions can be applied. In this work, two-color CRD detection is implemented on a ladder-type, three-level system based on the N 2 O, ν 3 = 1 ← 0, P(19) (pump) and ν 3 = 2 ← 1, R(18) (probe), rovibrational transitions. By frequency-locking two-quantum cascade lasers to the p-polarization (pump, Finesse = 5280) and s-polarization (probe, Finesse = 67 700) cavity modes, we achieve high intracavity pump power (36 W) and high probe ringdown rates (>2 kHz). The observed two-color spectra are simulated by a density-matrix, three-level system model that is solved under the constraints of the cavity resonance conditions. In addition to its background compensation capability, experimental flexibility in the selection of pump–probe schemes and signal insensitivity to intracavity laser power are further features that enhance the utility of our technique for mid-IR trace-detection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A new effective theory for stochastic relativistic hydrodynamics

Thermal fluctuations are a fundamental feature of dissipative systems that are essential for understanding physics near the expected critical point of QCD and in small systems. When such fluctuations are modeled naively in relativistic systems, strange features can appear such as negative self-correlation functions. We construct an effective theory for nonlinear stochastic relativistic hydrodynamics that ensure a well-posed mathematical formulation. Using Crooks fluctuation theorem, we derive a symmetry of the effective action that incorporates fluctuations through a suitable free energy functional. For divergence type theories, the action can then be fully specified using a single vector generating current. The equations of motion obtained using this procedure are guaranteed to be flux conservative and symmetric hyperbolic when the dynamics is causal. This ensures that these equations are well-posed (for suitable initial data) and are in a form that can easily be simulated, including with Metropolis techniques.

Mullins, Nicki [University of Illinois at Urbana-C↗

Blast from the past: constraining progenitor models of SN 1972E

ABSTRACT We present a novel technique to study Type Ia supernovae (SNe Ia) by constraining surviving companions of historical extragalactic SN by combining archival photographic plates and Hubble Space Telescope(HST) imaging. We demonstrate this technique for Supernova 1972E, the nearest known SN Ia in 125 yr. Some models of SNe Ia describe a white dwarf with a non-degenerate companion that donates enough mass to trigger thermonuclear detonation. Hydrodynamic simulations and stellar evolution models show that these donor stars will survive the explosion, and show increased luminosity for at least a 1000 yr. Thus, late-time observations of the exact location of a supernova can constrain the presence of a surviving donor star and progenitor models. We find the explosion site of SN 1972E by analysing 17 digitized photographic plates taken with the European Southern Observatory 1-m Schmidt and 1 plate taken with the Cerro Tololo Inter-American Observatory 1.5-m telescope. Using the Gaia eDR3 catalogue to determine Supernova 1972E’s location yields: α = 13h39m52${_{.}^{\rm s}}$708 ± 0${_{.}^{\rm s}}$004 and δ = −31°40’9${_{.}^{\prime\prime}}$00 ± 0${_{.}^{\prime\prime}}$04 (ICRS). In 2005, HST/ACS imaged the host galaxy of SN 1972E with the F435W, F555W, and F814W filters covering the explosion site. The nearest detected source is offset by 3.0 times our positional precision, and is inconsistent with the colours expected of a surviving donor star. Thus, the limiting magnitude of the HST observation (F555W > 28 mag) rules out all He star companion models and the most luminous main-sequence companion model currently in the literature. The remaining main-sequence companion models could be tested with a 10 orbit HST exposure in the F606W filter.

Do, Aaron↗

Screening Cu-Zeolites for Methane Activation Using Curriculum-Based Training

Machine learning (ML), when used synergistically with atomistic simulations, has recently emerged as a powerful tool for accelerated catalyst discovery. However, the application of these techniques has been limited by the lack of interpretable and transferable ML models. In this work, we propose a curriculum-based training (CBT) philosophy to systematically develop reactive machine learning potentials (rMLPs) for high-throughput screening of zeolite catalysts. Our CBT approach combines several different types of calculations to gradually teach the ML model about the relevant regions of the reactive potential energy surface. The resulting rMLPs are accurate, transferable, and interpretable. We further demonstrate the effectiveness of this approach by exhaustively screening thousands of [CuOCu] 2+ sites across hundreds of Cu-zeolites for the industrially relevant methane activation reaction. Specifically, this large-scale analysis of the entire International Zeolite Association (IZA) database identifies a set of previously unexplored zeolites (i.e., MEI, ATN, EWO, and CAS) that show the highest ensemble-averaged rates for [CuOCu] 2+ -catalyzed methane activation. We believe that this CBT philosophy can be generally applied to other zeolite-catalyzed reactions and, subsequently, to other types of heterogeneous catalysts. Thus, this represents an important step toward overcoming the long-standing barriers within the computational heterogeneous catalysis community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of APCVD BSG and POCl 3 Codiffusion Process for Double-Side TOPCon Solar Cell Precursor Fabrication

This paper presents a commercially viable process for fabricating a high-quality double-side tunnel oxide passivating contact (DS-TOPCon) cell precursor using APCVD-deposited boron silicate glass and ex-situ POCl 3 diffusion in a single high-temperature step, eliminating the need for additional masking and diffusion processes. A two-tier temperature profile was developed, involving a pre-annealing at above 900°C in nitrogen (N2) ambient followed by POCl 3 diffusion at 840°C. We investigated the effect of varying pre-annealing temperatures, ranging from 875°C to 950°C, on the passivation quality and metal-Si contact properties of both n-TOPCon and p-TOPCon layers. The resultant DS-TOPCon cell precursor after silicon nitride (SiNX) passivation exhibited an excellent iV OC of close to 730 mV. In addition, a rapid asymmetric poly-Si thinning technique, developed in this work, enabled adjustment of the front n + poly-Si thickness while maintaining the rear p + poly-Si thickness. Two types of DS-TOPCon cell architectures can be fabricated: i) full-area thin (≈40nm) n-TOPCon layer on the front and ii) selective-area thick (≈200nm) n-TOPCon fingers underneath the metal grid. Device simulations suggest that full-area DS-TOPCon cell with 40 nm n + poly-Si and selective-area DS-TOPCon cell with 200 nm n + poly fingers on the front, fabricated from our current DS-TOPCon cell precursor, can achieve cell efficiencies of 22.1 and 23.5%, respectively. Detailed power loss analysis and device simulation reveal that further improvements in material and device parameters have potential to push the cell efficiencies of DS-TOPCon cell structure beyond 25%, making it a promising alternative to fabricate a high-efficiency next-generation solar cells at low cost.

14 SOLAR ENERGY↗

Information-Theoretic Exploration of Multivariate Time-Varying Image Databases

Modern scientific simulations produce very large datasets, making interactive exploration of such data computationally prohibitive. An increasingly common data reduction technique is to store visualizations and other data extracts in a database. The Cinema project is one such approach, storing visualizations in an image database for post hoc exploration and interactive image-based analysis. This work focuses on developing efficient algorithms that can quantify various types of multivariate dependencies existing within multi-variable datasets. It applies specific mutual information measures for the quantification of salient regions from multivariate image data. Here, using such information measures, the opacity of the images is modulated so that the salient regions are automatically highlighted and the domain scientists can interactively explore the most relevant regions for scientific discovery.

97 MATHEMATICS AND COMPUTING↗

Non-intrusive nonlinear model reduction via machine learning approximations to low-dimensional operators

Abstract Although projection-based reduced-order models (ROMs) for parameterized nonlinear dynamical systems have demonstrated exciting results across a range of applications, their broad adoption has been limited by their intrusivity: implementing such a reduced-order model typically requires significant modifications to the underlying simulation code. To address this, we propose a method that enables traditionally intrusive reduced-order models to be accurately approximated in a non-intrusive manner. Specifically, the approach approximates the low-dimensional operators associated with projection-based reduced-order models (ROMs) using modern machine-learning regression techniques. The only requirement of the simulation code is the ability to export the velocity given the state and parameters; this functionality is used to train the approximated low-dimensional operators. In addition to enabling nonintrusivity, we demonstrate that the approach also leads to very low computational complexity, achieving up to $$10^3{\times }$$ 10 3 × in run time. We demonstrate the effectiveness of the proposed technique on two types of PDEs. The domain of applications include both parabolic and hyperbolic PDEs, regardless of the dimension of full-order models (FOMs).

42 ENGINEERING↗

Development of fast-running eighth core nodal solution

A fast-running, eighth-core solution technique has been developed for the quick core calculations in ANC, the Westinghouse core analysis code based on the nodal expansion method, and the BEACON{sup TM} Core Monitoring System (BEACON). This technique, referred to as 'Fast Eighth' (Fast8), enables users to obtain satisfactory macroscopic core calculation results such as reactivity, axial offset and assembly power much more quickly than calculations performed in the standard full-core or quarter-core geometry. Fast8 uses three techniques: folding the radial geometry into eighth-core geometry, reducing the axial geometry into a coarse axial mesh geometry, and smearing the spacer grids into nodes on-the-fly after the first calculation in the standard geometry. These geometry adjustments in Fast8 contribute to the reduction of the number of neutronic and material nodes while maintaining the reaction rates in each node. The axial mesh condition dependency in Fast8 is investigated in a xenon transient calculation in single assembly geometry, and the Fast8 maximum axial mesh size is determined based on these results. Fast8 is then applied to the load swing calculation, and the results are compared with the reference, full-core geometry, solution. The critical boron concentration and axial offset of Fast8 show good agreement with the reference solutions, and that Fast8 is a good technique for obtaining macroscopic core calculation results in significantly shorter time. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Sub‐5 Ångstrom Porosity Tuning in Calixarene‐Derived Porous Liquids via Supramolecular Complexation Construction

Abstract Sub‐Ångstrom‐level porosity engineering, which is appealing in gas separations, has been demonstrated in solid carbon, polymer, and framework materials but rarely achieved in the liquid phase. In this work, a gas molecular sieving effect in the liquid phase at sub‐5 Ångstrom scale is created via sophisticated porosity tuning in calixarene‐derived porous liquids (PLs). Type II PLs are constructed via supramolecular complexation between the sodium salts of calixarene derivatives and crown ether solvents. The chemical structure variation and assembly behavior of the porous host upon PL construction are monitored by spectroscopy‐, X‐ray‐, and neutron‐scattering techniques. The presence of permanent porosity in calixarene‐derived PLs is verified by pressure swing gas uptake, altered CO 2 physisorption behavior, and molecular simulations. Sub‐5 Ångstrom porosity tuning within the PL phase is achieved by introducing bulky substituted groups on the benzene ring of the calixarene host, which then greatly affects the dynamic motion and transport behavior of CO 2 molecules and the Xe uptake performance. The approach being demonstrated in this work represents a promising pathway to tune and leverage the porosity effect for enhanced gas uptake capacity and selectivity in liquid sorbents.

Li, Errui [Department of Chemistry University of T↗