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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Pairing around a single Dirac point: A unifying view of Kohn-Luttinger superconductivity in Chern bands, quarter metals, and topological surface states

Superconductivity of a single two-dimensional Dirac fermion offers a natural route to topological superconductivity. While usually considered extrinsic—arising from proximity to a conventional superconductor—we investigate when a doped Dirac cone can develop superconductivity from a short-range repulsive interaction 𝑈 via the Kohn–Luttinger mechanism. We show that an ideal, linear Dirac cone is immune to pairing at leading order in 𝑈 2 . Superconductivity instead emerges only through higher-order in 𝑘 corrections to the dispersion, which are unavoidable in any lattice realization and crucially dictate the pairing symmetry. The form of the pairing thus reflects how the well-known obstruction to realizing a single Dirac cone on a lattice is circumvented. When a Dirac cone arises from broken time-reversal symmetry—for instance, at a transition between Chern insulators or in a valley-polarized phase—we find a topological 𝑝−𝑖⁢𝑝 state whose chirality is opposite to that of the parent chiral metal above 𝑇 𝑐 . By contrast, for a surface Dirac cone of a 3D topological insulator, superconductivity is stabilized by anisotropies in the dispersion. For 𝐶 3⁢𝑣 -symmetric warping, as in , pairing is strongest when the Fermi surface becomes hexagonal, leading to order in the (𝑑±𝑖⁢𝑑)×(𝑝+𝑖⁢𝑝) channel with accidental near-nodes. In the highly anisotropic limit 𝑣 𝑥 ≫𝑣 𝑦 , relevant to side surfaces of layered materials, the Fermi surface splits into two branches, and nesting favors a pairing symmetry 𝛥∼s⁢g⁡n⁢(𝑘 𝑥 )⁢cos⁡(𝑘 𝑦 ) reminiscent of organic superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Strong-field physics in three-dimensional topological insulators

We investigate theoretically the strong-field regime of light-matter interactions in the topological-insulator class of quantum materials. In particular, we focus on the process of nonperturbative high-order harmonic generation from the paradigmatic three-dimensional topological insulator bismuth selenide (Bi 2 Se 3 ) subjected to intense midinfrared laser fields. We analyze the contributions from the spin-orbit-coupled bulk states and the topological surface bands separately and reveal a major difference in how their harmonic yields depend on the ellipticity of the laser field. Furthermore, bulk harmonics show a monotonic decrease in their yield as the ellipticity increases, in a manner reminiscent of high harmonic generation in gaseous media. However, the surface contribution exhibits a highly nontrivial dependence, culminating with a maximum for circularly polarized fields. We attribute the observed anomalous behavior to (i) the enhanced amplitude and the circular pattern of the interband dipole and the Berry connections in the vicinity of the Dirac point and (ii) the influence of the higher-order, hexagonal warping terms in the Hamiltonian, which are responsible for the hexagonal deformation of the energy surface at higher momenta. The latter are associated directly with spin-orbit-coupling parameters. Our results thus establish the sensitivity of strong-field-driven high harmonic emission to the topology of the band structure as well as to the manifestations of spin-orbit interaction.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Helical magnetic order and Fermi surface nesting in noncentrosymmetric ScFeGe

Here, an investigation of the structural, magnetic, thermodynamic, and charge transport properties of noncentrosymmetric hexagonal ScFeGe reveals it to be an anisotropic metal with a transition to a weak itinerant incommensurate helimagnetic state below T N =36 K. Neutron diffraction measurements discovered a temperature and field independent helical wave vector k = (0 0 0.193) with magnetic moments of 0.53 μ B per Fe confined to the ab-plane. Density functional theory calculations are consistent with these measurements and find several bands that cross the Fermi level along the c-axis with a nearly degenerate set of flat bands just above the Fermi energy. The anisotropy found in the electrical transport is reflected in the calculated Fermi surface, which consists of several warped flat sheets along the c-axis with two regions of significant nesting, one of which has a wave vector that closely matches that found in the neutron diffraction. The electronic structure calculations, along with a strong anomaly in the c-axis conductivity at TN, signal a Fermi surface driven magnetic transition, similar to that found in spin density wave materials. Magnetic fields applied in the ab-plane result in a metamagnetic transition with a threshold field of ≈ 6.7 T along with a sharp, strongly temperature dependent discontinuity and a change in sign of the magnetoresistance for in-plane currents. Thus, ScFeGe is an ideal system to investigate the effect of in-plane magnetic fields on a helimagnet with a c-axis propagation vector, where the relative strength of the magnetic interactions and anisotropies determine the topology and magnetic structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Enhanced anomalous Nernst effect in disordered Dirac and Weyl materials

Here, we analyze the thermoelectric response of Dirac and Weyl semimetals using the semiclassical approach, focusing on the extrinsic contributions due to skew-scattering and side jump. Our results apply to the linear response Nernst effect in ferromagnetic Dirac materials such as Fe 3 Sn 2 and Weyl semimetals like Co 3 Sn 2 S 2 . In the case of Fe 3 Sn 2 we obtain a very good agreement with known experimental anomalous Hall effect measurements, and based on that we predict a large Nernst effect in this material.We also extend the investigation to second-order response, focusing on monolayer graphene on hBN with trigonal warping as an example. Our analysis indicates that the extrinsic contributions can be a significant component of anomalous Nernst response and may be used to explain an enhanced thermoelectric response.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multiband Fermi surface in $1T–$$\mathrm{VSe_2}$ and its implication for the charge density wave phase

Angle-resolved photoemission spectroscopy experiments reveal a surprisingly richer surface electronic structure in $1T–$$\mathrm{VSe_2}$ than previously predicted or probed. Earlier claims supporting a charge density wave phase in this material are reexamined in terms of these findings and are found to be untenable. Here, the Fermi surface is found to be gapless, while band warping effects, currently attributed to three-dimensional lattice distortion, result from the simultaneous dispersion of the closely lying multiple bands. Based on these findings, a charge density wave scenario in $1T–$$\mathrm{VSe_2}$ is unlikely. On the other side, the presence of multiple states crossing the Fermi level should constitute relevant constraints for any viable microscopic model of the structural phase transition of $\mathrm{VSe_2}$.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Gravity Probe Spin: Prospects for measuring general-relativistic precession of intrinsic spin using a ferromagnetic gyroscope

An experimental test at the intersection of quantum physics and general relativity is proposed: measurement of relativistic frame dragging and geodetic precession using intrinsic spin of electrons. Furthermore, the behavior of intrinsic spin in spacetime dragged and warped by a massive rotating body is an experimentally open question, hence the results of such a measurement could have important theoretical consequences. Such a measurement is possible by using mm-scale ferromagnetic gyroscopes in orbit around the Earth. Under conditions where the rotational angular momentum of a ferromagnet is sufficiently small, a ferromagnet’s angular momentum is dominated by atomic electron spins and is predicted to exhibit macroscopic gyroscopic behavior. If such a ferromagnetic gyroscope is sufficiently isolated from the environment, rapid averaging of quantum uncertainty via the spin-lattice interaction enables readout of the ferromagnetic gyroscope dynamics with sufficient sensitivity to measure both the Lense-Thirring (frame dragging) and de Sitter (geodetic precession) effects due to the Earth.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Cosmological dynamics of string theory axion strings

The quantum chromodynamics (QCD) axion may solve the strong CP problem and explain the dark matter (DM) abundance of our Universe. The axion was originally proposed to arise as the pseudo-Nambu-Goldstone boson of global U⁢(1) PQ Peccei-Quinn (PQ) symmetry breaking, but axions also arise generically in string theory as zero modes of higher-dimensional gauge fields. In this work we show that string theory axions behave fundamentally differently from field theory axions in the early Universe. Field theory axions may form axion strings if the PQ phase transition takes place after inflation. In contrast, we show that string theory axions do not generically form axion strings. In special inflationary paradigms, such as D-brane inflation, string theory axion strings may form; however, their tension is parametrically larger than that of field theory axion strings. We then show that such QCD axion strings overproduce the DM abundance for all allowed QCD axion masses and are thus ruled out, except in scenarios with large warping. A loop-hole to this conclusion arises in the axiverse, where an axion string could be composed of multiple different axion mass eigenstates; a heavier eigenstate could collapse the network earlier, allowing for the QCD axion to produce the correct DM abundance and also generating observable gravitational wave signals.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Securing Smart Manufacturing: Detection of Cyber-Physical Attacks in CNC-Based Systems

As Industry 4.0 advances, the integration of computer numerical control (CNC) machines and advanced manufacturing technologies is transforming production into smart manufacturing systems that blend physical and digital processes as cyber-physical systems. However, this increased cyber-physical connectivity exposes manufacturing systems to cyber threats that can cause severe operational and financial disruptions. This paper presents a comparative study on cyber attacks and anomaly detection techniques in manufacturing, focusing on network traffic from CNC machines. The data extracted from network packets includes machine commands and control signals exchanged between the machine's interface and control system, crucial for maintaining operational integrity. We explore two types of cyber attacks, design modification and command injection, which pose substantial risks to CNC machine productivity and system integrity. Our investigation involves experiments on a real CNC system, highlighting the urgent need for effective detection mechanisms. To address these threats, we evaluate three anomaly detection methods: dynamic time warping (DTW), rolling average, and a deep learning, long short-term memory (LSTM) time-series-based autoencoder. Each is assessed for its effectiveness in identifying anomalous behaviors caused by the attacks. Our findings demonstrate the unique strengths and limitations of each detection technique, providing a deeper understanding of their applicability in realworld manufacturing environments. The comparative analysis indicates that while certain methods are highly effective against specific attack types, others offer broader applicability across different attacks. This study contributes to the accurate detection of anomalies in CNC machining processes, thereby enhancing the reliability and security of smart manufacturing systems against diverse cyber threats.

Williams, Bethanie [Tennessee Technological Univer↗
DOE OSTI2020

sMF-BO-2CoGP: A sequential multi-fidelity constrained Bayesian optimization framework for design applications

Bayesian optimization (BO) is an effective surrogate-based method that has been widely used to optimize simulation-based applications. While the traditional Bayesian optimization approach only applies to single-fidelity models, many realistic applications provide multiple levels of fidelity with various levels of computational complexity and predictive capability. In this work, we propose a multi-fidelity Bayesian optimization method for design applications with both known and unknown constraints. The proposed framework, called sMF-BO-2CoGP, is built on a multi-level CoKriging method to predict the objective function. An external binary classifier, which we approximate using a separate CoKriging model, is used to distinguish between feasible and infeasible regions. Finally, the sMF-BO-2CoGP method is demonstrated using a series of analytical examples and a flip-chip application for design optimization to minimize the deformation due to warping under thermal loading conditions.

42 ENGINEERING↗
DOE OSTI2022

Training data selection for event classification in a highly variable environment

A problem of interest for nuclear nonproliferation is monitoring activities at nuclear facilities, where proliferation events may only take place a few times and often under variable conditions. Machine learning has revolutionized data analytics by enabling the use of measurable signatures to generate predictive models of facility operations. However, traditional methods for training these models require large, reliable data sets with labeled observations, a challenge for nonproliferation. Highly variable conditions further complicate this as events from training data may have occurred in conditions quite different from the event of interest. Our hypothesis is that when events occur in a highly variable environment, careful training data selection for each test event could outperform the standard approach of using all available training data. We developed a method to optimize training data selection for the given test event and applied it to predicting the power level of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory. In this study, the reactor startup exhibits variability between occurrences due to natural variability in environmental conditions and operational procedures. Using a combination of analysis techniques, a similitude assessment was performed on data collected from HFIR to isolate clusters that were optimal for training a predictive model. Concepts such as dynamic time warping and Jaccard similarity were used in conjunction with clustering analysis. In order to validate this approach, the model was trained on every combination of unique training events and the predictive performance was compared to the performance using a subset of the training data selected by isolated clusters found through the similitude assessment.

Iyer, A↗
DOE OSTI2025

Elastic Bayesian Model Calibration

Functional data are ubiquitous in scientific modeling. For instance, quantities of interest are modeled as functions of time, space, energy, density, etc. Uncertainty quantification methods for computer models with functional response have resulted in tools for emulation, sensitivity analysis, and calibration that are widely used. However, many of these tools do not perform well when the computer model’s parameters control both the amplitude variation of the functional output and its alignment (or phase variation). This paper introduces a framework for Bayesian model calibration when the model responses are misaligned functional data. The approach generates two types of data out of the misaligned functional responses: (1) aligned functions so that the amplitude variation is isolated and (2) warping functions that isolate the phase variation. These two types of data are created for the computer simulation data (both of which may be emulated) and the experimental data. The calibration approach uses both types so that it seeks to match both the amplitude and phase of the experimental data. The framework is careful to respect constraints that arise, especially when modeling phase variation, and is framed in a way that it can be done with readily available calibration software. In conclusion, we demonstrate the techniques on two simulated data examples and on two dynamic material science problems: a strength model calibration using flyer plate experiments and an equation of state model calibration using experiments performed on the Sandia National Laboratories’ Z-machine.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Search for heavy diboson resonances in semileptonic final states in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

This paper reports on a search for heavy resonances decaying into WW , ZZ or WZ using proton–proton collision data at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV. The data, corresponding to an integrated luminosity of 139 fb -1 , were recorded with the ATLAS detector from 2015 to 2018 at the Large Hadron Collider. The search is performed for final states in which one W or Z boson decays leptonically, and the other W boson or Z boson decays hadronically. The data are found to be described well by expected backgrounds. Upper bounds on the production cross sections of heavy scalar, vector or tensor resonances are derived in the mass range 300–5000 GeV within the context of Standard Model extensions with warped extra dimensions or including a heavy vector triplet. Production through gluon–gluon fusion, Drell–Yan or vector-boson fusion are considered, depending on the assumed model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Gaussian null coordinates, near-horizon geometry and conserved charges on the horizon of extremal nondilatonic black p-branes

In this paper, we examine the emergence of conserved charges on the horizon of a particular class of extremal nondilatonic black [Formula: see text]-branes (which reduce to extremal dilatonic black holes in [Formula: see text] dimensions upon toroidal compactification) in the presence of a probe massless scalar field in the bulk. This result is achieved by writing the black [Formula: see text]-brane geometry in a Gaussian null coordinate system which allows us to get a nonsingular near-horizon geometry description. We find that the near-horizon geometry is [Formula: see text] and that the [Formula: see text] section has an internal structure which can be seen as a warped product of [Formula: see text] in Gaussian null coordinates. We show that the bulk scalar field satisfying the field equations is expanded in terms of nonnormalizable and normalizable modes, which for certain suitable quantization conditions are well-behaved at the boundary of [Formula: see text] space. Furthermore, we show that picking the normalizable modes results in the existence of conserved quantities on the horizon. We discuss the impact of these conserved quantities in the late-time regime.

Astronomy & Astrophysics↗
DOE OSTI2022

Performance portability study of epistasis detection using SYCL on NVIDIA GPU

We describe the experience of converting a CUDA implementation of a high-order epistasis detection algorithm to SYCL. The goals are for our work to be useful to application and compiler developers with a detailed description of migration paths between CUDA and SYCL. Evaluating the CUDA and SYCL applications on an NVIDIA V100 GPU, we find that the optimization of loop unrolling needs to be applied manually to the SYCL kernel for obtaining comparable performance. The performance of the SYCL group reduce function, an alternative to the CUDA warp-based reduction, depends on the problem and work group sizes. The 64-bit popcount operation implemented with tree of adders is slightly faster than the built-in popcount operation. When the number of OpenMP threads is four, the highest performance of the SYCL and CUDA applications are comparable.

Jin, Zheming↗
DOE OSTI2025

SPADES (Scalable Parallel Discrete Events Simulation) [SWR-24-99]

SPADES (Solver for PArallel Discrete Event Simulation) is an open-source parallel discrete event simulation (PDES) package built on the AMReX library. Targeted at solving discrete event systems in parallel, this software package aims to be performance portable and scalable on heterogeneous computing architectures, e.g., graphic processing units (GPU). SPADES implements optimistic synchronization with rollback through an implementation of the Time Warp algorithm. An alternative conservative synchronization approach is also implemented using the Lower Bound on Incoming Time Stamp. In our implementation, logical processes are represented as cells in a grid and event messages are represented as particles. SPADES supports various parallel decomposition strategies, including the use of the Message Passing Interface (MPI) and OpenMP threading. All major GPU architectures (e.g., Intel, AMD, NVIDIA) are supported through the use of performance portability functionalities implemented in AMReX. The SPADES software is released in NREL Software Record SWR-24-99 “SPADES (Scalable Parallel Discrete Events Simulation)”.

Henry de Frahan, Marc [National Renewable Energy L↗
DOE OSTI2025

extapi-acsys

Provides public APIs to the Fermilab control system. This service exposes several GraphQL endpoints for various, logical APIs that clients may use to retrieve control system data and, in some cases, make changes to the control system. This service is currently running on acsys-proxy.fnal.gov on port 8000 with the development instance on port 8001. The middle layer of the control system uses gRPCs for communications. The GraphQL resolvers of this service use various gRPC services to obtain the information that is returned. This uses the async-graphql and warp crates to provide GraphQL over http support. The resolvers use the tonic crate for gRPC client support.

Neswold, Rich [Fermi National Accelerator Laborato↗
DOE OSTI2023

SmallTAL: Real-Time Egocentric Online Temporal Action Localization for the Data-Impoverished

Abstract We propose a real-time, online temporal action localization system that requires a small amount of annotated data. The main challenges we address are high intra-class variability and a large and diverse background class. We address these using a flexible frame descriptor, dynamic time warping, and a novel approach to database construction. Our solution receives egocentric RGB-D streams as input and makes predictions at regular temporal intervals. We validate our approach by localizing actions in a digital twin of an electrical substation, in which certain objects have been replaced by functional virtual replicas.

Computer Science↗
DOE OSTI2023

Fabrication of engineered dopant profiles in Er/Lu:YAG transparent laser ceramics via additive manufacturing

Transparent ceramic Er:YAG laser rods were fabricated via the direct ink write (DIW) method with engineered doping profiles featuring an Er-doped core with endcaps and core-clad structures. Laser rods up to 11 cm in length were produced which required development of a scalable process. To achieve this, multiple improvements were implemented, including printing the rods horizontally on a substrate, rather than vertically, eliminating the need for an external support structure and using a sacrificial drying layer to mitigate warping and defects. Highly transparent rods were achieved with optical scatter levels as low as 0.5%/cm (at 543 nm). A small refractive index difference of 5.7 ppm was measured at the interface between the Er-doped core and the Lu-doped endcaps and cladding. These results demonstrate DIW as a straightforward method for making good optical quality laser rods with engineered doping profiles to improve laser performance.

36 MATERIALS SCIENCE↗