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At least 289 records · Page 16

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DOE OSTI2010

A Hybrid Higgs

We construct composite Higgs models admitting a weakly coupled Seiberg dual description. We focus on the possibility that only the up-type Higgs is an elementary field, while the down-type Higgs arises as a composite hadron. The model, based on a confining SQCD theory, breaks supersymmetry and electroweak symmetry dynamically and calculably. This simultaneously solves the {mu}/B{sub {mu}} problem and explains the smallness of the bottom and tau masses compared to the top mass. The proposal is then applied to a class of models where the same confining dynamics is used to generate the Standard Model flavor hierarchy by quark and lepton compositeness. This provides a unified framework for flavor, supersymmetry breaking and electroweak physics. The weakly coupled dual is used to explicitly compute the MSSM parameters in terms of a few microscopic couplings, giving interesting relations between the electroweak and soft parameters. The RG evolution down to the TeV scale is obtained and salient phenomenological predictions of this class of 'single-sector' models are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2016

Determining the vulnerability of multi-threaded program code to soft errors

The described embodiments include a program code testing system that determines the vulnerability of multi-threaded program code to soft errors. For multi-threaded program code, two to more threads from the program code may access shared architectural structures while the program code is being executed. The program code testing system determines accesses of architectural structures made by the two or more threads of the multi-threaded program code and uses the determined accesses to determine a time for which the program code is exposed to soft errors. From this time, the program code testing system determines a vulnerability of the program code to soft errors.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Exact enforcement of temporal continuity in sequential physics-informed neural networks

The use of deep learning methods in scientific computing represents a potential paradigm shift in engineering problem solving. One of the most prominent developments is Physics-Informed Neural Networks (PINNs), in which neural networks are trained to satisfy partial differential equations (PDEs). While this method shows promise, the standard version has been shown to struggle in accurately predicting the dynamic behavior of time-dependent problems. To address this challenge, methods have been proposed that decompose the time domain into multiple segments, employing a distinct neural network in each segment and directly incorporating continuity between them in the loss function of the minimization problem. In this work we introduce a method to exactly enforce continuity between successive time segments via a solution ansatz. This hard constrained sequential PINN (HCS-PINN) method is simple to implement and eliminates the need for any loss terms associated with temporal continuity. The method is tested for a number of benchmark problems involving both linear and non-linear PDEs. Examples include various first order time dependent problems in which traditional PINNs struggle, namely advection, Allen–Cahn, and Korteweg–de Vries equations. Furthermore, second and third order time-dependent problems are demonstrated via wave and Jerky dynamics examples, respectively. Notably, the Jerky dynamics problem is chaotic, making the problem especially sensitive to temporal accuracy. Finally, the numerical experiments conducted with the proposed method demonstrated superior convergence and accuracy over both traditional PINNs and the soft-constrained counterparts.

42 ENGINEERING↗

DOE OSTI2015

Phase-contrast Hounsfield units of fixated and non-fixated soft-tissue samples

X-ray phase-contrast imaging is a novel technology that achieves high soft-tissue contrast. Although its clinical impact is still under investigation, the technique may potentially improve clinical diagnostics. In conventional attenuation-based X-ray computed tomography, radiological diagnostics are quantified by Hounsfield units. Corresponding Hounsfield units for phase-contrast imaging have been recently introduced, enabling a setup-independent comparison and standardized interpretation of imaging results. Thus far, the experimental values of few tissue types have been reported; these values have been determined from fixated tissue samples. This study presents phase-contrast Hounsfield units for various types of non-fixated human soft tissues. A large variety of tissue specimens ranging from adipose, muscle and connective tissues to liver, kidney and pancreas tissues were imaged by a grating interferometer with a rotating-anode X-ray tube and a photon-counting detector. In addition, we investigated the effects of formalin fixation on the quantitative phase-contrast imaging results.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2020

Collective mode Brownian dynamics: A method for fast relaxation of statistical ensembles

Sampling equilibrium configurations of correlated systems of particles with long relaxation times (e.g., polymeric solutions) using conventional molecular dynamics and Monte Carlo methods can be challenging. This is especially true for systems with complicated, extended bond network topologies and other interactions that make the use and design of specialized relaxation protocols infeasible. We introduce a method based on Brownian dynamics simulations that can reduce the computational time it takes to reach equilibrium and draw decorrelated samples. Importantly, the method is completely agnostic to the particle configuration and the specifics of interparticle forces. In particular, we develop a mobility matrix that excites non-local, collective motion of N particles and can be computed efficiently in $\mathcal{O}(N)$ time. Particle motion in this scheme is computed by integrating the overdamped Langevin equation with an Euler–Maruyama scheme, in which Brownian displacements are drawn efficiently using a low-rank representation of the mobility matrix in position and wave space. We demonstrate the efficacy of the method with various examples from the realm of soft condensed matter and release a massively parallel implementation of the code as a plugin for the open-source package HOOMD-blue [J. A. Anderson et al., J. Comput. Phys. 227, 5342 (2008) and J. Glaser et al., Comput. Phys. Commun. 192, 97 (2015)] which runs on graphics processing units

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Nondestructively Visualizing and Understanding the Mechano-Electro-chemical Origins of “Soft Short” and “Creeping” in All-Solid-State Batteries

All-solid-state Li-metal batteries (ASLMBs) represent a significant breakthrough in the quest to overcome limitations associated with traditional Li-ion batteries, particularly in energy density and safety aspects. However, widespread implementation is stymied due to a lack of profound understanding of the complex mechano-electro-chemical behavior of Li metal in the ASLMBs. Herein, operando neutron imaging and X-ray computed tomography (XCT) are leveraged to nondestructively visualize Li behaviors within ASLMBs. This approach offers real-time observations of Li evolutions, both pre- and post- occurrence of a “soft short”. The coordination of 2D neutron radiography and 3D neutron tomography enables charting of the terrain of Li metal deformation operando. Concurrently, XCT offers a 3D insight into the internal structure of the battery following a “soft short”. Despite the manifestation of a “soft short”, the persistence of Faradaic processes is observed. To study the elusive “soft short”, phase field modeling is coupled with electrochemistry and solid mechanics theory. The research unravels how external pressure curbs dendrite growth, potentially leading to dendrite fractures and thus uncovering the origins of both “soft” and “hard” shorts in ASLMBs. Furthermore, by harnessing finite element modeling, it dive deeper into the mechanical deformation and the fluidity of Li metal.

25 ENERGY STORAGE↗

DOE OSTI2026

Molecular concentration field design using closed-form steady-state solutions

Control over spatial concentration fields represents a fundamental challenge in designing synthetic biological systems and programmable soft materials. While nature creates morphogen gradients that orchestrate complex developmental processes, synthetic approaches have largely relied on empirical optimization and computationally intensive simulations. Here, we present an analytical framework for steady-state concentration fields generated by finite-sized localized sources in diffusion–degradation systems and derive closed-form solutions for one-, two-, and three-dimensional geometries. By expressing these solutions in dimensionless form, we show that gradient steepness and spatial structure are organized by the Thiele modulus, which captures the competition between diffusion and degradation length scales. The analysis reveals distinct design regimes: in degradation-dominated systems, gradient shape is governed by exponential decay and becomes dimension-independent, whereas in diffusion-dominated systems, gradient magnitude and extent follow dimension-dependent power-law scaling. Building on these results, we introduce a quantitative design strategy that uses threshold-based criteria to program concentration ranges by tuning physically accessible parameters, most directly the production rate, while holding transport and degradation properties fixed. Comparisons with numerical solutions and reported experimental systems demonstrate consistency with the predicted scaling behavior. Together, this work provides a generalizable and physically transparent framework for designing steady-state concentration fields in synthetic biological and soft matter systems, enabling predictive control of gradient-mediated organization without reliance on extensive numerical optimization.

Kim, Dong Woo [Johns Hopkins University, Baltimore↗

DOE OSTI2023

Ultrafast X-ray Spectroscopy of Intersystem Crossing in Hexafluoroacetylacetone: Chromophore Photophysics and Spectral Changes in the Face of Electron-Withdrawing Groups

Intersystem crossings between singlet and triplet states represent a crucial relaxation pathway in photochemical processes. Herein, we probe the intersystem crossing in hexafluoro-acetylacetone with ultrafast X-ray transient absorption spectroscopy at the carbon K-edge. In this study, we observe the excited state dynamics following excitation with 266 nm UV light to the 1 ππ* (S 2 ) state with element and site-specificity using a broadband soft X-ray pulse produced by high harmonic generation. These results are compared to X-ray spectra computed from orbital optimized density functional theory methods. It is found that the electron-withdrawing fluorine atoms decongest the X-ray absorption spectrum by enhancing separation between features originating from different carbon atoms. This facilitates the elucidation of structural and electronic dynamics at the chromophore. The evolution of the core-to-valence resonances at the carbon K-edge reveals an ultrafast population transfer between the 1 nπ* (S 1 ) and 3 ππ* (T 1 ) states on a 1.6 ± 0.4 ps time scale, which is similar to the 1.5 ps time scale earlier observed for acetylacetone [ J. Am. Chem. Soc. 2017, 139, 16576—16583, DOI: 10.1021/jacs.7b07532]. It therefore appears that terminal fluorination has little influence on the intersystem crossing rate of the acetylacetone chromophore. In addition, the significant role of hydrogen-bond opened and twisted rotational isomers is elucidated in the excited state dynamics by comparison of the experimental transient X-ray spectra with theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Response of a fluid-immersed microcantilever close to a deformable body

The importance of hydrodynamics upon the response of a microcantilever immersed in a viscous fluid has been well established [J. E. Sader, J. Appl. Phys. 84, 64 (1998); C. A. Eysden and J. E. Sader, J. Appl. Phys. 101, 044908 (2007)]. It has previously been shown that the presence of a nearby rigid planar surface can significantly alter a microcantilever's non-contact response, through microcantilever–surface hydrodynamic interactions [C. P. Green and J. E. Sader, Phys. Fluids 17, 073102 (2005); C. P. Green and J. E. Sader, J. Appl. Phys. 98, 114913 (2005); R. J. Clarke et al., J. Fluid Mech. 545, 397426 (2005); R. J. Clarke et al., Phys. Rev. Lett. 96, 050801 (2006).]. In cases where the nearby surface is a finite-sized deformable body, such as in noncontact microrheology measurements, we expect to see further changes in the microcantilever's response. Hence, we here compute the thermal spectra of several microcantilevers in the presence of different compliant samples that have the characteristics of soft biological fibres. Our findings demonstrate that the elastohydrodynamic regime can substantially dictate the extent to which the compliance of a given body is evident in the microcantilever's thermal spectra, and suggest that certain nondimensional quantities should lie within particular, ranges for this to be the case. We expect these findings to be of interest in areas such as Atomic Force Microscopy, microsensing, and non-contact microrheology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Bootstrapping rapidity anomalous dimensions for transverse-momentum resummation

Soft function relevant for transverse-momentum resummation for Drell-Yan or Higgs production at hadron colliders are computed through to three loops in the expansion of strong coupling, with the help of bootstrap technique and supersymmetric decomposition. The corresponding rapidity anomalous dimension is extracted. Furthermore, an intriguing relation between anomalous dimensions for transverse-momentum resummation and threshold resummation is found.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2013

A full-spectral Bayesian reconstruction approach based on the material decomposition model applied in dual-energy computed tomography

Purpose: Dual-energy computed tomography (DECT) makes it possible to get two fractions of basis materials without segmentation. One is the soft-tissue equivalent water fraction and the other is the hard-matter equivalent bone fraction. Practical DECT measurements are usually obtained with polychromatic x-ray beams. Existing reconstruction approaches based on linear forward models without counting the beam polychromaticity fail to estimate the correct decomposition fractions and result in beam-hardening artifacts (BHA). The existing BHA correction approaches either need to refer to calibration measurements or suffer from the noise amplification caused by the negative-log preprocessing and the ill-conditioned water and bone separation problem. To overcome these problems, statistical DECT reconstruction approaches based on nonlinear forward models counting the beam polychromaticity show great potential for giving accurate fraction images.Methods: This work proposes a full-spectral Bayesian reconstruction approach which allows the reconstruction of high quality fraction images from ordinary polychromatic measurements. This approach is based on a Gaussian noise model with unknown variance assigned directly to the projections without taking negative-log. Referring to Bayesian inferences, the decomposition fractions and observation variance are estimated by using the joint maximum a posteriori (MAP) estimation method. Subject to an adaptive prior model assigned to the variance, the joint estimation problem is then simplified into a single estimation problem. It transforms the joint MAP estimation problem into a minimization problem with a nonquadratic cost function. To solve it, the use of a monotone conjugate gradient algorithm with suboptimal descent steps is proposed.Results: The performance of the proposed approach is analyzed with both simulated and experimental data. The results show that the proposed Bayesian approach is robust to noise and materials. It is also necessary to have the accurate spectrum information about the source-detector system. When dealing with experimental data, the spectrum can be predicted by a Monte Carlo simulator. For the materials between water and bone, less than 5% separation errors are observed on the estimated decomposition fractions.Conclusions: The proposed approach is a statistical reconstruction approach based on a nonlinear forward model counting the full beam polychromaticity and applied directly to the projections without taking negative-log. Compared to the approaches based on linear forward models and the BHA correction approaches, it has advantages in noise robustness and reconstruction accuracy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

Domain knowledge-informed, process-mapping AI graph for designing Fe-based alloys

<span style="font-family: Calibri, sans-serif; font-size: 12pt;">Continuous improvement in efficiency of a power plant relies on designing materials for use at increasingly higher temperature and/or pressure, for 100,000s hours of operation. Due to complexity, non-linearity and high-dimensionality of the problem, traditional Machine Learning (ML) approaches require unreasonably large datasets for the data-driven model development. Science-based material and process engineering complements hard data with, sometimes soft and intuitive, empirical domain knowledge. Artificial Intelligence (AI) was used in this study to incorporate such knowledge into computational graph architecture (process-mimicking artificial neuron design, causal layer and graph structures, ensemble modeling of latent states) and learning procedures (variable transformation, fuzzy physics pre-training and freezing of deep layers, virtual microstructure representation, and adversarial multi-objective optimization). The first alloys design pathways suggested by the AI tool (pyroMind) passed a preliminary engineering review on soundness and transparency.</span>

Romanov, Vyacheslav↗

DOE OSTI2014

Statistics of reversible transitions in two-state trajectories in force-ramp spectroscopy

A possible way to extract information about the reversible dissociation of a molecular adhesion bond from force fluctuations observed in force ramp experiments is discussed. For small loading rates the system undergoes a limited number of unbinding and rebinding transitions observable in the so-called force versus extension (FE) curves. The statistics of these transient fluctuations can be utilized to estimate the parameters for the rebinding rate. This is relevant in the experimentally important situation where the direct observation of the reversed FE-curves is hampered, e.g., due to the presence of soft linkers. I generalize the stochastic theory of the kinetics in two-state models to the case of time-dependent kinetic rates and compute the relevant distributions of characteristic forces. While for irreversible systems there is an intrinsic relation between the rupture force distribution and the population of the free-energy well of the bound state, the situation is slightly more complex if reversible systems are considered. For a two-state model, a “stationary” rupture force distribution that is proportional to the population can be defined and allows to consistently discuss quantities averaged over the transient fluctuations. While irreversible systems are best analyzed in the soft spring limit of small pulling device stiffness and large loading rates, here I argue to use the stiffness of the pulling device as a control parameter in addition to the loading rate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Cr/B{sub 4}C multilayer mirrors: Study of interfaces and X-ray reflectance

We present an experimental study of the effect of layer interfaces on the x-ray reflectance in Cr/B{sub 4}C multilayer interference coatings with layer thicknesses ranging from 0.7 nm to 5.4 nm. The multilayers were deposited by magnetron sputtering and by ion beam sputtering. Grazing incidence x-ray reflectometry, soft x-ray reflectometry, and transmission electron microscopy reveal asymmetric multilayer structures with a larger B{sub 4}C-on-Cr interface, which we modeled with a 1–1.5 nm thick interfacial layer. Reflectance measurements in the vicinity of the Cr L{sub 2,3} absorption edge demonstrate fine structure that is not predicted by simulations using the currently tabulated refractive index (optical constants) values for Cr.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2013

Low delay and area efficient soft error correction in arbitration logic

There is provided an arbitration logic device for controlling an access to a shared resource. The arbitration logic device comprises at least one storage element, a winner selection logic device, and an error detection logic device. The storage element stores a plurality of requestors' information. The winner selection logic device selects a winner requestor among the requestors based on the requestors' information received from a plurality of requestors. The winner selection logic device selects the winner requestor without checking whether there is the soft error in the winner requestor's information.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Physics augmented machine learning discovery of composition-dependent constitutive laws for 3D printed digital materials

Multi-material 3D printing, particularly through polymer jetting, enables the fabrication of digital materials by mixing distinct photopolymers at the micron scale within a single build to create a composite with tunable mechanical properties. Here, this work presents an integrated experimental and computational investigation into the composition-dependent mechanical behavior of 3D printed digital materials. We experimentally characterize five formulations, combining soft and rigid UV-cured polymers under uniaxial tension and torsion across three strain and twist rates. The results reveal nonlinear and rate-dependent responses that strongly depend on composition. To model this behavior, we develop a physics-augmented neural network (PANN) that combines a partially input convex neural network (pICNN) for learning the composition-dependent hyperelastic strain energy function with a quasi-linear viscoelastic (QLV) formulation for time-dependent response. The pICNN ensures convexity with respect to strain invariants while allowing non-convex dependence on composition. To enhance interpretability, we apply $L_0$ sparsification. For the time-dependent response, we introduce a multilayer perceptron (MLP) to predict viscoelastic relaxation parameters from composition. The proposed model accurately captures the nonlinear, rate-dependent behavior of 3D printed digital materials in both uniaxial tension and torsion, achieving high predictive accuracy for interpolated material compositions. This approach provides a scalable framework for automated, composition-aware constitutive model discovery for multi-material 3D printing.

Constitutive modeling↗

DOE OSTI2022

Insights into the possible existence of a soft dipole mode in He 8

With an extreme neutron-to-proton ratio of N/Z = 3, 8 He provides an ideal laboratory for the study of a variety of exotic phenomena, such as the emergence of a soft dipole mode that is dominated by transitions into the continuum. In this contribution, a covariant density-functional theory (DFT) framework is used to compute ground-state properties and the dipole response of 8 He. Although 8 He is admittedly too light for DFT to be applicable, the great merit of the approach is that the spurious contamination associated with the center-of-mass motion is guaranteed to decouple from the physical response. Given that a strong mixing between the isoscalar and isovector dipole modes is expected for a system with such a large neutron-proton asymmetry as 8 He, the narrow structures that emerged at low energies in the isovector dipole response are attributed to the shift of the spurious strength to zero (or near zero) excitation energy. Furthermore, the theoretical framework implemented here disfavors the emergence of a soft dipole mode in 8 He.

6 ≤ A ≤ 19↗

DOE OSTI2024

Effects of renormalon scheme and perturbative scale choices on determinations of the strong coupling from e + e − event shapes

We study the role of renormalon cancellation schemes and perturbative scale choices in extractions of the strong coupling constant α s ( m Z ) and the leading nonperturbative shift parameter Ω 1 from resummed predictions of the e + e − event shape thrust. We calculate the thrust distribution to N L 3 L ′ resummed accuracy in soft-collinear effective theory (SCET) matched to the fixed-order O ( α s 2 ) prediction, and perform a new high-statistics computation of the O ( α s 3 ) matching in , although we do not include the latter in our final α s fits due to some observed systematics that require further investigation. We are primarily interested in testing the phenomenological impact sourced from varying amongst three renormalon cancellation schemes and two sets of perturbative scale profile choices. We then perform a global fit to available data spanning center-of-mass energies between 35–207 GeV in each scenario. Relevant subsets of our results are consistent with prior SCET-based extractions of α s ( m Z ) , but we are also led to a number of novel observations. Notably, we find that the combined effect of altering the renormalon cancellation scheme and profile parameters can lead to few-percent-level impacts on the extracted values in the α s − Ω 1 plane, indicating a potentially important systematic theory uncertainty that should be accounted for. We also observe that fits performed over windows dominated by dijet events are typically of a higher quality than those that extend into the far tails of the distributions, possibly motivating future fits focused more heavily in this region. Finally, we discuss how different estimates of the three-loop soft matching coefficient c S ˜ 3 can also lead to measurable changes in the fitted { α s , Ω 1 } values. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗