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At least 19 records

Bayes Inference Engine (BIE) Test Plan: TiltConeBeamCombo

The Bayes Inference Engine (BIE) is a general software tool intended to be used primarily in the analysis of radiographic data for density. An analysis is set up in the BIE by representing the problem as a collection of modules called glyphs. All glyphs to be used in creating the forward model of the experiment will be tested separately for a range of inputs. The testing of the adjoint code is performed in a separate document.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Bayes Inference Engine (BIE) Test Plan: TiltConeBeamComboDMLinear

The Bayes Inference Engine (BIE) is a general software tool intended to be used primarily in the analysis of radiographic data for density. An analysis is set up in the BIE by representing the problem as a collection of modules called glyphs. All glyphs to be used in creating the forward model of the experiment will be tested separately for a range of inputs.

97 MATHEMATICS AND COMPUTING↗

Bayes Inference Engine (BIE) Test Plan: TiltConeBeamComboDMGeometric

The Bayes Inference Engine (BIE) is a general software tool intended to be used primarily in the analysis of radiographic data for density. An analysis is set up in the BIE by representing the problem as a collection of modules called glyphs. All glyphs to be used in creating the forward model of the experiment will be tested separately for a range of inputs.

97 MATHEMATICS AND COMPUTING↗

Bayes Inference Engine (BIE) Test Plan: TiltConeBeamFVT

The Bayes Inference Engine (BIE) is a general software tool intended to be used primarily in the analysis of radiographic data for density. An analysis is set up in the BIE by representing the problem as a collection of modules called glyphs. All glyphs to be used in creating the forward model of the experiment will be tested separately for a range of inputs. The testing of the adjoint code is performed in a separate document.

97 MATHEMATICS AND COMPUTING↗

Dynamic Behavior of Bound Interlayer Excitons in Interlayer-Doped Cs 3 Bi 2 Br 9 Vacancy-Ordered Perovskite

Interlayer doping of the vacancy-ordered 2D perovskite Cs 3 Bi 2 Br 9 (CBB) enables the formation of bound interlayer excitons (BIEs), a unique charge-transfer excited state within the layered solid. BIEs previously reported with silver (Ag + ) as an interlayer dopant exhibited bright broadband photoluminescence (PL) with prolonged lifetime at room temperature, offering potential applications in efficient white light emission, photocatalysis, and optoelectronics. However, the dynamic behavior of radiation and excited carriers remains poorly understood due to the limitations of ensemble spectroscopic measurements. Here, we investigate the temperature-dependent dynamics of Ag-doped Cs 3 Bi 2 Br 9 (Ag-CBB) using single-particle time-resolved PL spectroscopy and ultrafast transient absorption imaging. Single-particle PL measurements reveal three distinct emission regimes across temperature: (i) BIE-dominant emission at high temperatures, (ii) a mixture of radiation from BIEs and self-trapped excitons (STEs) at intermediate temperatures, and (iii) STE-dominant emission below 100 K. Rapid transient absorption mapping using Parallel Rapid Imaging with Spectroscopic Mapping (PRISM) reveals subpicosecond STE formation in pristine CBB and long-lived photoinduced absorption by BIEs, consistent with electron–hole separation and suppressed STE transfer. The spatial uniformity of these signals confirms homogeneous Ag doping across single crystals. These findings highlight the role of Ag interlayer dopants in governing the BIE dynamics.

bound interlayer exciton↗

Ag Intercalation in Layered Cs 3 Bi 2 Br 9 Perovskite for Enhanced Light Emission with Bound Interlayer Excitons

Cesium bismuth bromide (CBB) has garnered considerable attention as a vacancy-ordered layered perovskite with notable optoelectronic applications. However, its use as a light source has been limited due to its weak photoluminescence (PL). Here, we demonstrate metal intercalation as a novel approach to engineer the room-temperature PL of CBB using experimental and computational methods. Ag, when introduced into CBB, occupies vacant sites in the spacer region, forming octahedral coordination with surrounding Br anions. First-principles density functional theory calculations reveal that intercalated Ag represents the most energetically stable Ag species compared to other potential forms, such as Ag substituting Bi. The intercalated Ag forms a strong polaronic trap state close to the conduction band minimum and quickly captures photoexcited electrons with holes remaining in CBB layers, leading to the formation of a bound interlayer exciton, or BIE. The radiative recombination of this BIE exhibits bright room-temperature PL at 600 nm and a decay time of 38.6 ns, 35 times greater than that of free excitons, originating from the spatial separation of photocarriers by half a unit cell separation distance. The BIE as a new form of interlayer exciton is expected to inspire new research directions for vacancy-ordered perovskites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Neural Network-Based Electric Vehicle Range Prediction for Smart Charging Optimization

Range prediction is a standard feature in most modern road vehicles, allowing drivers to make informed decisions about when to refuel. Most vehicles make range predictions through data- or model-driven means, monitoring the average fuel consumption rate or using a tuned vehicle model to predict fuel consumption. The uncertainty of future driving conditions makes the range prediction problem challenging, particularly for less pervasive battery electric vehicles (BEV). Most contemporary machine learning-based methods attempt to forecast the battery SOC discharge profile to predict vehicle range. In this work, we propose a novel approach using two recurrent neural networks (RNNs) to predict the remaining range of BEVs and the minimum charge required to safely complete a trip. Each RNN has two outputs that can be used for statistical analysis to account for uncertainties; the first loss function leads to mean and variance estimation (MVE), while the second results in bounded interval estimation (BIE). These outputs of the proposed RNNs are then used to predict the probability of a vehicle completing a given trip without charging, or if charging is needed, the remaining range and minimum charging required to finish the trip with high probability. Training data was generated using a low-order physics model to estimate vehicle energy consumption from historical drive cycle data collected from medium-duty last-mile delivery vehicles. Here, the proposed method demonstrated high accuracy in the presence of day-to-day route variability, with the root-mean-square error (RMSE) below 6% for both RNN models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Learning Only on Boundaries: A Physics-Informed Neural Operator for Solving Parametric Partial Differential Equations in Complex Geometries

Recently, deep learning surrogates and neural operators have shown promise in solving partial differential equations (PDEs). However, they often require a large amount of training data and are limited to bounded domains. In this work, we present a novel physics-informed neural operator method to solve parameterized boundary value problems without labeled data. By reformulating the PDEs into boundary integral equations (BIEs), we can train the operator network solely on the boundary of the domain. This approach reduces the number of required sample points from $O(N^d)$ to $O(N^{d-1}$), where $d$ is the domain’s dimension, leading to a significant acceleration of the training process. Additionally, our method can handle unbounded problems, which are unattainable for existing physics-informed neural networks (PINNs) and neural operators. Finally, our numerical experiments show the effectiveness of parameterized complex geometries and unbounded problems.

97 MATHEMATICS AND COMPUTING↗

Penetrating power in radiography of high-Z materials as a function of bremsstrahlung spectrum endpoint energy

A modified radiographer’s equation is derived and fitted to simulation data so as to describe the increase in radiographic signal that comes with increasing bremsstrahlung spectrum endpoint energy. The dose contained in the incident spectrum follows an E28 power law, as often cited. However, the direct flux penetrating through a heavy, high-Z material, obeys a weaker scaling due to hardening of the radiation. The resultant expression depends on the thickness of the scene being radiographed, the composition of high-Z materials in the scene, and any filtering by other low-Z materials, such as Al or Be. The expression exhibits two asymptotic limits: a ‘thick’ limit at which radiation is extremely hardened and only a weak benefit to increasing endpoint energy is observed (also the most attenuating limit and therefore of dubious physical significance), and a ‘thin’ limit at which a minimum of high-Z material is present and the penetrating dose exhibits the 2.8 power scaling inherent in the incident spectrum. Behavior for intermediate thicknesses of W and Al are obtained by modeling incident and attenuated dose using the DOSECALC code and the Bayes’ Inference Engine (BIE). These data guide the optimization of MeV radiography over a wide range of energies where pair production plays a significant role in photon scattering.

36 MATERIALS SCIENCE↗

Overview of the LANL Multi-Probe Radiography Project [Slides]

Future radiographic facilities for the U.S. defense program will be required to provide more information as simulation codes improve in both physics’ fidelity and resolution. A possible approach is to use more types of probe beams in addition to, or instead of X-rays, generated by 20-MeV electron accelerators from a small number of directions. High power short-pulse laser systems can generate beams of protons, neutrons and electrons, as well as X-rays. The cost of these systems is falling rapidly. So, it can be imagined that deploying multiple short-pulse lasers along with other, more traditional probes, will become feasible. In this project, we are following three paths to determine if such an approach will succeed for cm-scale objects. The first is an experimental one to determine if the presence of multiple short-pulse probes cause interference with each other, especially while radiographing dynamic objects. The second leg of this project is to determine if having multiple types of probes really does give more information on composition. Finally, an overall assessment of the viability of this approach will be made. Examples from recent experiments at the Omega EP laser will be presented. The initial approach to evaluating radiographs with multiple probes using the Bayesian Inference Engine (BIE) also will be given.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Machine learning and algebraic approaches towards complete matter spectra in 4d F-theory

Motivated by engineering vector-like (Higgs) pairs in the spectrum of 4d F-theory compactifications, we combine machine learning and algebraic geometry techniques to analyze line bundle cohomologies on families of holomorphic curves. To quantify jumps of these cohomologies, we first generate 1.8 million pairs of line bundles and curves embedded in dP 3 , for which we compute the cohomologies. A white-box machine learning approach trained on this data provides intuition for jumps due to curve splittings, which we use to construct additional vector-like Higgs-pairs in an F-Theory toy model. We also find that, in order to explain quantitatively the full dataset, further tools from algebraic geometry, in particular Brill-Noether theory, are required. Using these ingredients, we introduce a diagrammatic way to express cohomology jumps across the parameter space of each family of matter curves, which reflects a stratification of the F-theory complex structure moduli space in terms of the vector-like spectrum. Furthermore, these insights provide an algorithmically efficient way to estimate the possible cohomology dimensions across the entire parameter space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Brill-Noether-general limit root bundles: absence of vector-like exotics in F-theory Standard Models

Root bundles appear prominently in studies of vector-like spectra of 4d F-theory compactifications. Of particular importance to phenomenology are the Quadrillion F-theory Standard Models (F-theory QSMs). In this work, we analyze a superset of the physical root bundles whose cohomologies encode the vector-like spectra for the matter representations ($3$, $2$) 1/6 , ($\overline{3}$, $1$) -2/3 and ($1$, $1$) 1 . For the family B 3 (Δ$^{°}_{4}$) consisting of $\mathcal{O}$(10 11 ) F-theory QSM geometries, we argue that more than 99.995% of the roots in this superset have no vector-like exotics. This indicates that absence of vector-like exotics in those representations is a very likely scenario in the O(10 11 ) QSM geometries B 3 (Δ$^{°}_{4}$). The QSM geometries come in families of toric 3-folds B 3 (Δ°) obtained from triangulations of certain 3-dimensional polytopes Δ°. The matter curves in X Σ $\large{ϵ}$ B 3 (Δ°) can be deformed to nodal curves which are the same for all spaces in B 3 (Δ°). Therefore, one can probe the vector-like spectra on the entire family B 3 (Δ°) from studies of a few nodal curves. We compute the cohomologies of all limit roots on these nodal curves. In our applications, for the majority of limit roots the cohomologies are determined by line bundle cohomology on rational tree-like curves. For this, we present a computer algorithm. The remaining limit roots, corresponding to circuit-like graphs, are handled by hand. The cohomologies are independent of the relative position of the nodes, except for a few circuits. On these jumping circuits, line bundle cohomologies can jump if nodes are specially aligned. This mirrors classical Brill-Noether jumps. B 3 (Δ°) admits a jumping circuit, but the root bundle constraints pick the canonical bundle and no jump happens.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Improved Statistics for F-theory Standard Models

Much of the analysis of F-theory-based Standard Models boils down to computing cohomologies of line bundles on matter curves. By varying parameters one can degenerate such matter curves to singular ones, typically with many nodes, where the computation is combinatorial and straightforward. The question remains to relate the (a priori possibly smaller) value on the original curve to the singular one. In this work, we introduce some elementary techniques (pruning trees and removing interior edges) for simplifying the resulting nodal curves to a small collection of terminal ones that can be handled directly. When applied to the QSMs, these techniques yield optimal results in the sense that obtaining more precise answers would require currently unavailable information about the QSM geometries. This provides us with an opportunity to enhance the statistical bounds established in earlier research regarding the absence of vector-like exotics on the quark-doublet curve.

Bies, Martin↗

Direct observation on supersonic microprojectile penetration of carbon fiber composites with ultrafast synchrotron X-ray phase contrast imaging

High-speed penetration into carbon fiber composites is of fundamental importance to materials science and impact engineering, but research along this line suffers considerably from the lack of direct experimental observations. Here we investigate such penetration dynamics of a unidirectional carbon fiber reinforced epoxy (UCFRE) composite, with a combination of in situ, ultrafast, synchrotron phase contrast imaging and finite element (FE) analysis. The experiments yield the first direct observation on projectile trajectories and fiber-scale deformation and damage in the UCFRE composites during supersonic microprojectile penetration, for different fiber orientations (0 degrees - 90 degrees from the impact direction) and projectile velocities (600 - 850 m.s -1 ), at unprecedented temporal (~ 100 ps) and spatial (5 μm) resolutions. The maximum penetration depth decreases with increasing fiber orientation angles, as a result of anisotropic damage evolution in the composite sample. Strain localizations are prone to develop along a direction perpendicular to the fiber orientation, while the damage or cavity region, along the fiber direction. FE modeling with a three-dimensional Hashin criterion yields consistent projectile trajectory and cavity morphology with the experimental results. Finally, with increasing fiber orientation angles, damage analyses show a transition in the damage mode from fiber compression to matrix compression damage, in line with the increasing maximum penetration depth.

36 MATERIALS SCIENCE↗

Rate-dependent strength and deformation heterogeneity of B4C-reinforced Al composite: Time-resolved imaging with synchrotron X-rays

Dynamic (up to 5500 s -1 ) and quasi-static compression tests are conducted on a 15 wt% B4C particle-reinforced Al (B 4 C/Al) composite. In situ, high-speed synchrotron X-ray phase contrast imaging and digital image correlation are employed to map mesoscale deformation fields at μm and μs scales. The bulk stress–strain curves show significant strain and strain-rate hardening under dynamic compression. The strain-rate sensitivity exponent is an order of magnitude higher at high strain rates (> 10 3 s -1 ) than that at low strain rates (< 10 -2 s -1 ). Strain field mapping demonstrates distinct compressive strain localizations for both quasi-static and dynamic loading. Nevertheless, compressive strain localizations appear denser in spacing under dynamic loading, owing to spontaneous dislocation nucleation in both weak and strong zones. This results in a higher density of geometrically necessary dislocations, which contributes to the higher strain and strain-rate hardening of B 4 C/Al under dynamic loading. Additionally, the ratio of the maximum local strain to the bulk average is 1.5, and the local strain-rate enhancement cannot explain the increased rate sensitivity of B 4 C/Al under dynamic loading. Therefore, the rate-dependent deformation heterogeneity dominates the strain-rate hardening of B 4 C/Al. Postmortem analyses help correlate deformation features to particle- and grain-scale microstructures, yielding consistent results with mesoscale strain fields.

36 MATERIALS SCIENCE↗