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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Renormalized classical theory of quantum magnets

Here, we derive a renormalized classical spin (RCS) theory for 𝑆 >1/2 quantum magnets by constraining a generalized classical theory that includes all multipolar fluctuations to a reduced CP 1 phase space of dipolar SU(2) coherent states. When the spin Hamiltonian $\hat{ℋ}$(𝑆) is linear in the spin operators $\hat{𝑺}$ 𝑗 for each lattice site 𝑗, the RCS Hamiltonian $\tilde{ℋ}$ cl coincides with the usual classical model ℋ cl = lim 𝑆→∞⁡ $\hat{ℋ}$(𝑆). In the presence of nonlinear terms, however, the RCS theory is more accurate than ℋ cl . For the many materials modeled by spin Hamiltonians with (nonlinear) single-ion anisotropy terms, the use of the RCS theory is essential to accurately model phase diagrams and to extract the correct Hamiltonian parameters from neutron-scattering data.

magnetic anisotropy↗
DOE OSTI2023

Foundations of machine learning for low-temperature plasmas: methods and case studies

Abstract Machine learning (ML) and artificial intelligence have proven to be an invaluable tool in tackling a vast array of scientific, engineering, and societal problems. The main drivers behind the recent proliferation of ML in practically all aspects of science and technology can be attributed to: (a) improved data acquisition and inexpensive data storage; (b) exponential growth in computing power; and (c) availability of open-source software and resources that have made the use of state-of-the-art ML algorithms widely accessible. The impact of ML on the field of low-temperature plasmas (LTPs) could be particularly significant in the emerging applications that involve plasma treatment of complex interfaces in areas ranging from the manufacture of microelectronics and processing of quantum materials, to the LTP-driven electrification of the chemical industry, and to medicine and biotechnology. This is primarily due to the complex and poorly-understood nature of the plasma-surface interactions in these applications that pose unique challenges to the modeling, diagnostics, and predictive control of LTPs. As the use of ML is becoming more prevalent, it is increasingly paramount for the LTP community to be able to critically analyze and assess the concepts and techniques behind data-driven approaches. To this end, the goal of this paper is to provide a tutorial overview of some of the widely-used ML methods that can be useful, amongst others, for discovering and correlating patterns in the data that may be otherwise impractical to decipher by human intuition alone, for learning multivariable nonlinear data-driven prediction models that are capable of describing the complex behavior of plasma interacting with interfaces, and for guiding the design of experiments to explore the parameter space of plasma-assisted processes in a systematic and resource-efficient manner. We illustrate the utility of various supervised, unsupervised and active learning methods using LTP datasets consisting of commonly-available, information-rich measurements (e.g. optical emission spectra, current–voltage characteristics, scanning electron microscope images, infrared surface temperature measurements, Fourier transform infrared spectra). All the ML demonstrations presented in this paper are carried out using open-source software; the datasets and codes are made publicly available. The FAIR guiding principles for scientific data management and stewardship can accelerate the adoption and development of ML in the LTP community.

Physics↗
DOE OSTI2025

On measuring stimulated photon–photon scattering using multiple ultraintense lasers

Stimulated photon–photon scattering is a predicted consequence of quantum electrodynamics that has yet to be measured directly. Measuring the cross section for stimulated photon–photon scattering is the aim of a flagship experiment for NSF OPAL, a proposed laser user facility with two, 25-PW beamlines. We present optimized experimental designs for achieving this challenging and canonical measurement. A family of experimental geometries is identified that satisfies the momentum- and energy-matching conditions for two selected laser frequency options. Numerical models predict a maximum signal exceeding 1000 scattered photons per shot at the experimental conditions envisaged at NSF OPAL. Experimental requirements on collision geometry, polarization, cotiming and copointing, background suppression, and diagnostic technologies are investigated numerically. These results confirm that a beam cotiming shorter than the pulse duration and control of the copointing on a scale smaller than the shortest laser wavelength are needed to robustly scatter photons on a per-shot basis. Finally, we assess the bounds that a successful execution of this experiment may place on the mass scale of Born–Infeld nonlinear electrodynamics beyond the standard model of physics.

Beyond the Standard Model↗
DOE OSTI2024

Validation of a Tapered Impact Damper for Traffic Signal Structure Vibrations Using the Method of Harmonic Balance

Significant vibration amplitudes and cycles can be produced when traffic signal structures with low inherent damping are excited near one of their natural frequencies. For the mitigation of wind-induced vibrations, dynamic vibration absorbers coupled to the structure are often used. Here, this research investigates the performance of a tapered impact damper, consisting of a hanging spring-mass oscillator inside a housing capable of reducing vibration amplitude over a broader frequency range than the conventional tuned mass damper. A nonlinear, two degree-of-freedom model is developed with coordinates representing the traffic structure and the tapered impact damper. This research focuses on the application of the harmonic balance method to approximate the periodic solutions of the nonlinear equations to compute the nonlinear dynamics of the damped traffic signal structure. After designing and manufacturing a tapered impact damper, the traffic signal structure is tested with and without the damper using free vibration snapback tests. The experimental frequency and damping backbone curves are used to validate the analytical model, and the effectiveness of the damper is discussed.

42 ENGINEERING↗
DOE OSTI2022

High-order ( N = 4–6) multiphoton absorption and mid-infrared Kerr nonlinearity in GaP, ZnSe, GaSe, and ZGP crystals

We report a study of high-order multiphoton absorption, nonlinear refraction, and their anisotropy in four notable mid-infrared χ (2) crystals: GaP, ZnSe, GaSe, and ZGP using femtosecond pulses at 2.35 μm with peak intensity in excess of 200 GW/cm 2 . We found that the nonlinear absorption obeys a perturbation model with multiphoton absorption (MPA) orders from N = 4–6, in agreement with the bandgaps of the crystals. A study of the role of free carrier absorption, performed by changing the pulse duration from 30 to 70 fs while maintaining a constant peak intensity, showed that, at our intensity levels, free carriers generated during the MPA process absorb much more strongly than would be expected from their known linear absorption cross section. Possible mechanisms for this anomalous behavior are high-field effects, such as intravalley scattering in the conduction band and absorption to higher lying bands. Nonlinear refractive indices were measured using (i) closed aperture Z-scan and (ii) spectral broadening due to self-phase modulation, both methods agreeing with each other.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Nonlinear Interface Reduction for Time-Domain Analysis of Hurty/Craig-Bampton Superelements with Frictional Contact

Virtual prototyping in engineering design relies today on modern numerical models of contacting structures with accurate resolution of interface mechanics, which strongly affect the system-level stiffness and energy dissipation due to frictional losses. High-fidelity modeling within the localized interfaces is required to resolve local quantities of interest that may drive design decisions. The high-resolution finite element meshes necessary to resolve inter-component stresses tend to be computationally expensive, particularly when the analyst is interested in response time histories. The Hurty/Craig-Bampton (HCB) transformation is a widely used method in structural dynamics for reducing the interior portion of a finite element model while having the ability to retain all nonlinear contact degrees of freedom (DOF) in physical coordinates. These models may still require many DOF to adequately resolve the kinematics of the interface, leading to inadequate reduction and computational savings. This study proposes a novel interface reduction method to overcome these challenges by means of system-level characteristic constraint (SCC) modes and properly orthogonal interface modal derivatives (POIMDs) for transient dynamic analyses. Both SCC modes and POIMDs are computed using the reduced HCB mass and stiffness matrices, which can be directly computed from many commercial finite element analysis software. Comparison of time history responses to an impulse-type load in a mechanical beam assembly indicate that the interface-reduced model correlates well with the HCB truth model. Localized features like slip and contact area are well-represented in the time domain when the beam assembly is loaded with a broadband excitation. The proposed method also yields reduced-order models with greater critical timestep lengths for explicit integration schemes.

42 ENGINEERING↗
DOE OSTI2025

A DATA EFFICIENT SPARSE MODELING FRAMEWORK FOR POWER ESTIMATION IN WATER TREATMENT SENSING OPERATIONS

With increasing freshwater scarcity, advanced process design mechanisms such as Closed-Circuit Reverse Osmosis (CCRO) and Digital/Physical Twin systems are gaining traction in water treatment and reuse operations. While digital and physical twin models enable improved system insight and control, their development is often expensive and computationally intensive, requiring large volumes of synthetic or experimental data to characterize underlying process dynamics. This work introduces a sparse surrogate modeling framework to estimate power consumption from measured flow and pressure variables, along with their nonlinear polynomial and interaction expansions. To ensure model reliability and reduce overfitting, a two-stage pipeline is proposed. First, a dynamic data filtering algorithm is employed to remove uninformative observations and transient operational states. Second, a sparse penalized regression technique is applied to select a minimal set of parsimonious features. The proposed model achieves high sparsity, retaining only 7 out of 34 candidate features (≈79.41% sparsity) while delivering a root mean square error (RMSE) of 0.072 on the test dataset.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2023

The Aemulus Project. V. Cosmological Constraint from Small-scale Clustering of BOSS Galaxies

We analyze clustering measurements of BOSS galaxies using a simulation-based emulator of two-point statistics. We focus on the monopole and quadrupole of the redshift-space correlation function, and the projected correlation function, at scales of 0.1 ~ 60 h -1 Mpc. Although our simulations are based on wCDM with general relativity (GR), we include a scaling parameter of the halo velocity field, γ f , defined as the amplitude of the halo velocity field relative to the GR prediction. We divide the BOSS data into three redshift bins. After marginalizing over other cosmological parameters, galaxy bias parameters, and the velocity scaling parameter, we find fσ 8 (z = 0.25) = 0.413 ± 0.031, fσ 8 (z = 0.4) = 0.470 ± 0.026, and fσ 8 (z = 0.55) = 0.396 ± 0.022. Compared with Planck observations using a flat Lambda cold dark matter model, our results are lower by 1.9σ, 0.3σ, and 3.4σ, respectively. These results are consistent with other recent simulation-based results at nonlinear scales, including weak lensing measurements of BOSS LOWZ galaxies, two-point clustering of eBOSS LRGs, and an independent clustering analysis of BOSS LOWZ. All these results are generally consistent with a combination of ${\gamma }_{f}^{1/2}{\sigma }_{8}\approx 0.75$. We note, however, that the BOSS data is well fit assuming GR, i.e., γf = 1. We cannot rule out an unknown systematic error in the galaxy bias model at nonlinear scales, but near-future data and modeling will enhance our understanding of the galaxy–halo connection, and provide a strong test of new physics beyond the standard model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Probing drift velocity dispersion in MAPbI 3 photovoltaic cells with nonlinear photocurrent spectroscopy

Conventional time-of-flight (TOF) measurements yield charge carrier mobilities in photovoltaic cells with time resolution limited by the RC time constant of the device, which is on the order of 0.1–1 µs for the systems targeted in the present work. We have recently developed an alternate TOF method, termed nonlinear photocurrent spectroscopy (NLPC), in which carrier drift velocities are determined with picosecond time resolution by applying a pair of laser pulses to a device with an experimentally controlled delay time. In this technique, carriers photoexcited by the first laser pulse are “probed” by way of recombination processes involving carriers associated with the second laser pulse. Here, we report NLPC measurements conducted with a simplified experimental apparatus in which synchronized 40 ps diode lasers enable delay times up to 100 µs at 5 kHz repetition rates. Carrier mobilities of ∼0.025 cm 2 /V/s are determined for MAPbI 3 photovoltaic cells with active layer thicknesses of 240 and 460 nm using this instrument. Here, our experiments and model calculations suggest that the nonlinear response of the photocurrent weakens as the carrier densities photoexcited by the first laser pulse trap and broaden while traversing the active layer of a device. Based on this aspect of the signal generation mechanism, experiments conducted with co-propagating and counter-propagating laser beam geometries are leveraged to determine a 60 nm length scale of drift velocity dispersion in MAPbI 3 films. Contributions from localized states induced by thermal fluctuations are consistent with drift velocity dispersion on this length scale.

14 SOLAR ENERGY↗
DOE OSTI2022

Geometric learning for computational mechanics Part II: Graph embedding for interpretable multiscale plasticity

The history-dependent behaviors of classical plasticity models are often driven by internal variables evolved according to phenomenological laws. The difficulty to interpret how these internal variables represent a history of deformation, the lack of direct measurement of these internal variables for calibration and validation, and the weak physical underpinning of those phenomenological laws have long been criticized as barriers to creating realistic models. In this work, geometric machine learning on graph data (e.g. finite element solutions) is used as a means to establish a connection between nonlinear dimensional reduction techniques and plasticity models. Geometric learning-based encoding on graphs allows the embedding of rich time-history data onto a low-dimensional Euclidean space such that the evolution of plastic deformation can be predicted in the embedded feature space. Finally, a corresponding decoder can then convert these low-dimensional internal variables back into a weighted graph such that the dominating topological features of plastic deformation can be observed and analyzed.

42 ENGINEERING↗
DOE OSTI2021

Structural dynamics modeling of spent nuclear fuel during hypothetical package drop events

The response of spent nuclear fuel (SNF) to hypothetical package drop events is of particular interest in the scope of spent fuel storage and transportation because of the mechanical shock encountered in such scenarios. Previous testing and modeling by the U.S. Department of Energy has demonstrated that the shock and vibration environment of normal shipping and handling conditions (excluding package drop events) is relatively benign and does not challenge the integrity of spent nuclear fuel. Cask drop events are worth considering because SNF packages are required to withstand free drops onto unyielding surfaces as part of their licensing basis. The acceleration experienced during drop events can be orders of magnitude higher, and thus more advanced models are needed to encompass potential nonlinear behavior of the fuel, such as spacer grid buckling and rod-to-rod impact. This work describes a number of finite element models developed to calculate the response of spent nuclear fuel to various hypothetical drop events that have been validated by package and fuel assembly drop tests conducted in the last decade. Sensitivity of the model response to factors such as package drop orientation, secondary impacts, and irradiated material properties as well as their potential impacts to fuel cladding integrity, was also investigated. Cask drops are not expected as a regular occurrence during SNF transportation, but this work helps raise the understanding of SNF mechanical loads to the point of consistency with the package design requirements.

Kadooka, Kevin↗
DOE OSTI2021

Assessment the leaching characteristics and long-term leaching behavior of some radionuclides from synthesized zeolite cement matrix

Highlights: • Synthesis and characterization of zeolite cement synthesized from fly ash • Leaching tests were used to assess the release rate of {sup 85}Sr and {sup 60}Co radionuclides. • Simple mathematical models were used to detect leaching mechanisms. • Long-term leaching behavior of {sup 85}Sr and {sup 60}Co from cementitious matrix was assessed. The development of cementitious materials remains a vital goal to produce valuable products with good mechanical, physical and chemical properties suitable for the safe disposal of concentrated radionuclides resulted from the treatment of contaminated solutions. In this paper, zeolite cement with good properties was laboratory synthesized from industrial by-products fly ash and characterized using various characterization techniques. The leaching characteristics of strontium and cobalt radionuclides from the synthesized zeolite cement were scrutinized conforming with the standard leaching methodology of International Atomic Energy Authority (IAEA). A mechanical strength assessment was executed to characterize the extent of immobilization process of the solidified matrices. The cumulative leaching fraction (φ) of the two studied radionuclides was found to be less than 5% in all examined conditions, which implies the applicability of the IAEA-recommended methodology for estimating the diffusion coefficient. The experimental leaching data were regressed nonlinearly to various mathematical kinetic models to assess the controlling leaching mechanism and to determine the leaching parameters. The regression results indicated that strontium ({sup 85}Sr) and cobalt ({sup 60}Co) leaching resulted from two succeeding mechanisms: as first order kinetic reaction, and then diffusion. The calculated values of leachability indices signify that the performance of each of the studied matrices is within an acceptable range. A simplified mathematical model, rooted in the first order reaction and diffusion mechanisms, was simulated to predict the radionuclides leaching rates from zeolite cement matrices. By comparing the synthesized zeolite cement with other cementitious materials, it can be concluded that the synthesized material can be classified as an efficient material suitable to immobilize {sup 85}Sr and {sup 60}Co from radioactive wastes. The acquired findings demonstrated that the studied immobilized waste matrices have acceptable mechanical effectiveness.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Enantioselective Intramolecular Allylic Substitution via Synergistic Palladium/Chiral Phosphoric Acid Catalysis: Insight into Stereoinduction through Statistical Modeling

The mode of asymmetric induction in an enantioselective intramolecular allylic substitution reaction catalyzed by a combination of palladium and a chiral phosphoric acid was investigated by a combined experimental and statistical modeling approach. Experiments to probe nonlinear effects, the reactivity of deuterium-labeled substrates, and control experiments revealed that nucleophilic attack to the π-allylpalladium intermediate is the enantio-determining step, in which the chiral phosphate anion is involved in stereoinduction. Here, using multivariable linear regression analysis, we determined that multiple noncovalent interactions with the chiral environment of the phosphate anion are integral to enantiocontrol in the transition state. The synthetic protocol to form chiral pyrrolidines was further applied to the asymmetric construction of C-O bonds at fully substituted carbon centers in the synthesis of chiral 2,2-disubstituted benzomorpholines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Mid-Infrared Nonlinear Frequency Conversion Using Monolithic Barium Titanate on Silicon-on-Insulator

In this work, efficient nonlinear frequency conversion in the mid-infrared (mid-IR) region was demonstrated by a barium titanate (BTO) on a silicon-on-insulator (SOI) substrate. The BTO thin film was epitaxially grown by pulsed-laser deposition (PLD). The tensorial second order optical nonlinearity and the ferroelectric domain property of the BTO were characterized by the polarimetric mid-IR second harmonic generation (SHG) measurements. Azimuthal-dependent polarized SHG was modeled at different combinations of the nonlinear coefficient $d_{ij}$ and the domain fraction factor $ΔD^Y/ΔD^X$. Strong SHG intensity was experimentally observed over a broad spectrum at λ = 3.1 μm - 3.7 μm. A characteristic linear dependence between the SHG signal and the square of the pumping laser intensity was observed. The monolithic integration between the epitaxial BTO and the Si provides a compact platform for efficient on-chip light generation and quantum photonic technologies.

25 ENERGY STORAGE↗
DOE OSTI2025

Experimental observation of nonlinear relation between pressure and water flux is consistent with the solution-diffusion model

In several recent studies, it has been proposed that the fundamental understanding of penetrant transport in dense polymer membranes occurring via the solution-diffusion model, which has been the generally accepted theoretical framework for describing penetrant transport in such materials for the past several decades, is flawed. An alternate mechanistic framework based on the idea of two-phase flow in a porous medium (i.e., pore-flow) has been broadly advanced instead, with proponents of this approach claiming that the pore-flow theoretical framework provides the necessary mechanistic insight to design novel polymeric membrane materials for emerging applications. In this study, we show experimental results for hydraulic permeation of water that are entirely consistent with the solution-diffusion theory, without modification, for three dense polymeric membranes: crosslinked poly(ethylene glycol diacrylate) (XLPEGDA), Nafion 117 ionomer in the sodium counterion form (Nafion 117-Na), and cellulose acetate (CA). By measuring water flux at transmembrane pressures up to 240 bar, we observe a nonlinear relationship between the transmembrane pressure (TMP) and water flux, J w , for XLPEGDA and Nafion 117-Na, while this relationship is linear for CA. We demonstrate that the behavior of these three materials is described via the solution-diffusion model. According to the solution-diffusion model, flux is, to a good approximation, proportional to the transmembrane concentration difference induced by the pressure difference across the membrane, rather than to TMP itself. Water sorption isotherms are reported for all three materials. They further justify the nonlinear relationship between TMP and J w observed in XLPEGDA and Nafion 117-Na, emphasizing that the nonlinearity in the flux/TMP relationship stems from nonlinearities in the sorption isotherm with pressure. Additionally, the relationship between water flux and TMP can be predicted, a priori, with no adjustable parameters when a predictive model for the diffusion coefficient of water is employed in conjunction with the experimental water sorption isotherms in the solution-diffusion model. Furthermore, our results demonstrate the validity of the solution-diffusion model to describe transport of penetrants in dense polymer membranes, while highlighting the sensitivity of the solution-diffusion model to the many physical and mathematical simplifications commonly applied to the theory in literature.

materials↗
DOE OSTI2022

JET EROSION OF PARTICLE BEDS: PROJECTING CRITICAL SUSPENSION VELOCITIES FROM EFFECTIVE CLEARING / CLEANING RADII

Here we explore the relationship between effective cleaning/clearing radii, ECR, and critical suspension velocities, Ucs. Although one set of physics controls both the radial extent of erosion (i.e., the ECR) and the velocity needed to erode from the center of jet impingement to any given location (i.e., Ucs, typically defined from nozzle center to the vessel center), the relationship between these two remains unexplored quantitatively. Here we advance the model of Kuhn, et al., (PNNL-22816, 2013) as described by Pease, et al. (FEDSM2017-69444, 2017) to evaluate the relationship between the effective clearing/cleaning radius and the nozzle velocity on flat surfaces including flat bottomed vessels. Two governing dimensionless groups are identified. We present both a closed form analytical but transcendental solution and a non-iterative approximation modeled after the Serghides approximation of Colebrook’s nonlinear equation for both ECR versus nozzle velocity and Ucs. Comparison of the model to data from flume testing on a flat surface finds reasonable agreement.

jet, erosion, critical suspension velocity, effect↗
DOE OSTI2023

A Novel Deep Reinforcement Learning Approach to Traffic Signal Control with Connected Vehicles

The advent of connected vehicle (CV) technology offers new possibilities for a revolution in future transportation systems. With the availability of real-time traffic data from CVs, it is possible to more effectively optimize traffic signals to reduce congestion, increase fuel efficiency, and enhance road safety. The success of CV-based signal control depends on an accurate and computationally efficient model that accounts for the stochastic and nonlinear nature of the traffic flow. Without the necessity of prior knowledge of the traffic system’s model architecture, reinforcement learning (RL) is a promising tool to acquire the control policy through observing the transition of the traffic states. In this paper, we propose a novel data-driven traffic signal control method that leverages the latest in deep learning and reinforcement learning techniques. By incorporating a compressed representation of the traffic states, the proposed method overcomes the limitations of the existing methods in defining the action space to include more practical and flexible signal phases. The simulation results demonstrate the convergence and robust performance of the proposed method against several existing benchmark methods in terms of average vehicle speeds, queue length, wait time, and traffic density.

42 ENGINEERING↗
DOE OSTI2020

Nanostructured Tube Wakefield Accelerator

Unprecedented $\rm TeVm^{-1}$ acceleration gradients are modeled to be realizable using a nonlinear surface crunch-in mode in nanostructured tubes. This mode is realizable using advances in nanofabrication and solid energy density attosecond bunch compression. Three dimensional computational and analytical modeling demonstrates GeV energy gain in sub-millimeter long tubes with effective wall densities $n_{\rm t}\sim10^{22-24}\rm cm^{-3}$ and hundreds of nanometer core radius when driven by submicron near solid electron beams, $n_{\rm b}\sim0.05n_{\rm t}$. Besides the many $\rm TVm^{-1}$ average gradients, strong self-focusing and nanomodulation of the beam which increases its peak density and the wakefield strength also opens up controlled high-energy photon production.

43 PARTICLE ACCELERATORS↗