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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Integrating Electromagnetic Acoustic Transducers in a Modular Robotic Gripper for Inspecting Tubular Components

Tubular structures are critical components in infrastructure such as power plants. Throughout their life, they are subjected to extreme conditions or suffer from defects such as corrosion and cracks. Although regular inspection of these components is necessary, such inspection is limited by safety-related risks and limited access for human inspection. Robots can provide a solution for automatic inspection. The main challenge, however, lies in integrating sensors for nondestructive evaluation with robotic platforms. As part of developing a versatile lizard-inspired tube inspector robot, in this study the authors propose to integrate electromagnetic acoustic transducers into a modular robotic gripper for use in automated ultrasonic inspection. In particular, spiral coils with cylindrical magnets are integrated into a novel friction-based gripper to excite Lamb waves in thin cylindrical structures. To evaluate the performance of the integrated sensors, the gripper was attached to a robotic arm manipulator and tested on pipes of different outer diameters. Two sets of tests were carried out on both defect-free pipes and pipes with simulated defects, including surface partial cracking and corrosion. The inspection results indicated that transmitted and received signals could be acquired with an acceptable signal-to-noise ratio in the time domain. Moreover, the simulated defects could be successfully detected using the integrated robotic sensing system.

Materials Science↗
DOE OSTI2021

In Vivo Study of Osteochondral Defect Regeneration Using Innovative Composite Calcium Phosphate Biocement in a Sheep Model

This study aimed to clarify the therapeutic effect and regenerative potential of the novel, amino acids-enriched acellular biocement (CAL) based on calcium phosphate on osteochondral defects in sheep. Eighteen sheep were divided into three groups, the treated group (osteochondral defects filled with a CAL biomaterial), the treated group with a biocement without amino acids (C cement), and the untreated group (spontaneous healing). Cartilages of all three groups were compared with natural cartilage (negative control). After six months, sheep were evaluated by gross appearance, histological staining, immunohistochemical staining, histological scores, X-ray, micro-CT, and MRI. Treatment of osteochondral defects by CAL resulted in efficient articular cartilage regeneration, with a predominant structural and histological characteristic of hyaline cartilage, contrary to fibrocartilage, fibrous tissue or disordered mixed tissue on untreated defect (p < 0.001, modified O’Driscoll score). MRI results of treated defects showed well-integrated and regenerated cartilage with similar signal intensity, regularity of the articular surface, and cartilage thickness with respect to adjacent native cartilage. We have demonstrated that the use of new biocement represents an effective solution for the successful treatment of osteochondral defects in a sheep animal model, can induce an endogenous regeneration of cartilage in situ, and provides several benefits for the design of future therapies supporting osteochondral defect healing.

Kresakova, Lenka↗
DOE OSTI2025

Molecular aspect ratio effect on axial thermal transport in solution-spun carbon nanotube fibers

Neat, densely packed, and highly aligned carbon nanotube fibers (CNTFs) have appealing room-temperature axial thermal conductivity (⁠k⁠) and thermal diffusivity (⁠α⁠) for applications in lightweight heat spreading, flexible thermal connections, and thermoelectric active cooling. Although CNTFs are regularly produced from different input carbon nanotubes (CNTs), prior work has not quantified how the CNT molecular aspect ratio r (i.e., molecular length-to-diameter ratio) influences k and in well-aligned, packed CNTFs. Here, we perform self-heated steady-state and three-omega thermal measurements at room temperature on CNTF suspended in vacuum. Our results show that k increases from 150 to 380 W / mK for viscosity-averaged molecular aspect ratios increasing from r = 960 to 5600 and nanotube diameters of ~2 nm, which we attribute to the effects of thermal resistances between CNT bundles. CNTFs made with varying volume fraction Φ of constituent high-r and low-r CNT have properties that fall within or below the typical macroscopic rule-of-mixtures bounds. The thermal diffusivity α scales with k, leading to a sample-averaged volumetric heat capacity of 1.5 ± 0.3 MJ / m 3 K⁠. This work's findings that fibers made from longer CNT have larger k and α at room temperature motivate further investigation into thermal transport in solution-spun CNTF.

42 ENGINEERING↗
DOE OSTI2021

Extracting Material Property Measurement Data from Scientific Articles

Machine learning-based prediction of material properties is often hampered by the lack of sufficiently large training datasets. The majority of such measurement data is embedded in scientific literature and the ability to automatically extract these data is essential to support the development of reliable property prediction methods. In this work, we describe a methodology for an automatic property extraction framework using material solubility as the target property. We create an annotated dataset containing tags for solubility-related entities using a combination of regular expressions and manual tagging. We then compare five entity recognition models leveraging both token-level and span-level architectures on the task of classifying solute names, solubility values, and solubility units. Additionally, we explore a novel pretraining approach that leverages automated chemical name and quantity extraction tools to generate large datasets that do not rely on intensive manual effort. Finally, we perform an analysis to identify the causes of classification errors.

Panapitiya, Gihan U.↗
DOE OSTI2024

A $C^1$-Conforming Arbitrary-Order Two-Dimensional Virtual Element Method for the Fourth-Order Phase-Field Equation

We present a two-dimensional conforming virtual element method for the fourth-order phase-field equation. Our proposed numerical approach to the solution of this high-order phase-field (HOPF) equation relies on the design of an arbitrary-order accurate, virtual element space with $C^1$ global regularity. Such regularity is guaranteed by taking the values of the virtual element functions and their full gradient at the mesh vertices as degrees of freedom. Attaining high-order accuracy requires also edge polynomial moments of the trace of the virtual element functions and their normal derivatives. In this work, we detail the scheme construction, and prove its convergence by deriving error estimates in different norms. A set of representative test cases allows us to assess the behavior of the method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Sampling frequency thresholds for the quantum advantage of the quantum approximate optimization algorithm

We compare the performance of the Quantum Approximate Optimization Algorithm (QAOA) with state-of-the-art classical solvers Gurobi and MQLib to solve the MaxCut problem on 3-regular graphs. We identify the minimum noiseless sampling frequency and depth p required for a quantum device to outperform classical algorithms. There is potential for quantum advantage on hundreds of qubits and moderate depth with a sampling frequency of 10 kHz. We observe, however, that classical heuristic solvers are capable of producing high-quality approximate solutions in linear time complexity. In order to match this quality for large graph sizes N, a quantum device must support depth p > 11. Additionally, multi-shot QAOA is not efficient on large graphs, indicating that QAOA p ≤ 11 does not scale with N. These results limit achieving quantum advantage for QAOA MaxCut on 3-regular graphs. Other problems, such as different graphs, weighted MaxCut, and 3-SAT, may be better suited for achieving quantum advantage on near-term quantum devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Space-Split Algorithm for Sensitivity Analysis of Discrete Chaotic Systems With Multidimensional Unstable Manifolds

Accurate approximations of the change of a system's output and its statistics with respect to the input are highly desired in computational dynamics. Ruelle's linear response theory provides breakthrough mathematical machinery for computing the linear response of chaotic dynamical systems. In this paper, we propose an algorithm for sensitivity analysis of discrete chaos with an arbitrary number of positive Lyapunov exponents. We combine the concept of perturbation space-splitting, which regularizes Ruelle's original expression, together with measure-based parameterization of the expanding subspace. We use these tools to rigorously derive trajectory-following recursive relations that converge exponentially fast, and construct a memory-efficient Monte Carlo scheme for derivatives of the output statistics. Thanks to the regularization and lack of simplifying assumptions on the system's behavior, our method is immune to the common problems of other popular methods such as the exploding tangent solutions and unphysical shadowing directions. Here, we provide a ready-to-use algorithm, analyze its complexity, and demonstrate several numerical examples of sensitivity computation using physically-inspired low-dimensional systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Toward quantum tunneling from excited states: Recovering imaginary-time instantons from a real-time analysis

We revisit the path integral description of quantum tunneling and its generalization to excited states. For clarity, we focus on the simple toy model of a point particle in a double-well potential, for which we perform all steps explicitly. Instead of performing the familiar Wick rotation from physical to imaginary time—which is inconsistent with the requisite boundary conditions when treating tunneling from excited states—we regularize the path integral by adding an infinitesimal complex contribution to the Hamiltonian, while keeping time strictly real. We find that this gives rise to a complex stationary-phase solution, in agreement with recent insights from Picard-Lefshetz theory. We then show that there exists a class of analytic solutions for the corresponding equations of motion, which can be made to match the appropriate boundary conditions in the physically relevant limits of a vanishing regulator and an infinite physical time. We provide a detailed discussion of this nontrivial limit. We find that, for systems without an explicit time-dependence, our approach reproduces the picture of an instantonlike solution defined on a finite Euclidean-time interval. Lastly, we discuss the generalization of our approach to broader classes of systems, for which it serves as a reliable framework for high-precision calculations. Published by the American Physical Society 2025

Steingasser, Thomas (ORCID:0000000217262117)↗
DOE OSTI2025

Detector Materials Scoping Study: Research and Development Recommendations

Radiation detection materials have a unique role in many nuclear security missions. The variety of different applications requires the use of different materials whose characteristics are determined by the specific application requirements. While baseline capabilities have been established to use radiation detection in these applications, the potential to greatly advance those capabilities still exists through the development of superior radiation detection materials and/or the development of new materials that enable new technologies to be implemented more effectively. In 2024 the Defense Nuclear Nonproliferation Research and Development (DNN R&D) Near Field Detection Portfolio charged a detector materials scoping study, composed of a group of radiation-detection materials subject matter experts, to produce a community-wide consensus view of the current state of radiation materials research and to set recommendations for expanded investment over a ten-year time frame. This scoping study sought to understand and document the landscape of how radiation detection materials are used, what characteristics drive the selection of various materials, and what developments are needed to drive the state of the art. To respond to this charge, the scoping study created three working groups, each focusing on a different topical area in radiation detection materials research - Semiconductor Materials, Inorganic Scintillators and Organic Scintillators - with the task to identify the current state of the art in materials research and to provide mission-relevant research and development recommendations. Each working group was chaired by two members of the project team with widely recognized expertise in the field. Solicitations were sent out to experts at the DOE national laboratories, industry, academia and federal government agencies to participate in these working groups. The working groups met at regular intervals throughout 2024 and early 2025, each delivering a technical roadmap designed to enable the pursuit of R&D more intensely on high-impact materials challenges and detector solutions that are deemed as the greatest strategic value to DNN R&D and its stakeholders. The roadmap is also intended to help communicate recommended programmatic priorities within DNN R&D and across the nonproliferation and research communities.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A physics-informed and hierarchically regularized data-driven model for predicting fluid flow through porous media

This paper presents a new deep learning data-driven model for predicting structure dependent pore-fluid velocity fields in rock. The model is based on a Convolutional Auto-Encoder (CAE) artificial neural network capable of learning from image data generated by direct numerical simulations of fluid flow through pore-structures, such as by Lattice Boltzmann or molecular dynamics methods. The main novelty of the model in comparison to previous CAE-based data-driven approaches consists of three parts. The first is a methodology for decomposing the full-domain of the porous media into sub-regions, or “sub-domains”, in order to reduce the overall size of the CAE, batch process the sub-domains in parallel, and enable the CAE to learn local and generalizable nonlinear mappings of pore-fluid velocities. The second consists of embedding the finite difference solutions of the incompressible Navier-Stokes and continuity equations into convolutional layers prior to the CAE in order to provide the CAE with knowledge of fluid dynamics physics (PhyFlow). The third main novelty is that the training of the CAE is regularized with a hierarchical loss function that encourages the learning of fluid flow patterns (in a way similar to ranked modes in principal component analysis), ranking from most to least important. This is shown to increase the stability in learning, reduce over-fitting, and promote interpretability of the CAE neural network layers (HierCAE). The comprehensive new data-driven model, which we call the PhyFlow-HierCAE model, is shown to exhibit improved accuracy and generalizability of flow field predictions over conventional CAE models, attributable to the embedded physical knowledge and the hierarchical regularization, as well as realize orders of magnitude speed-ups in computation times as a surrogate for the direct numerical simulations. Examples of training and forward predictions on unseen pore-structures are provided and evaluated for data from Lattice Boltzmann and molecular dynamics simulations of pore-fluid flow. The model is shown to be a fast and accurate emulator (or “surrogate”) for predicting effective permeability of unseen pore-structures based on learning from relatively small direct numerical simulation datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Polarity-Tolerant Chloride Binding in Foldamer Capsules by Programmed Solvent-Exclusion

Persistent anion binding in a wide range of solution environments is a key challenge that continues to motivate and demand new strategies in synthetic receptor design. Though strong binding in low-polarity solvents has become routine, our ability to maintain high affinities in high-polarity solvents has not yet reached the standard set by nature. Anions are bound and transported regularly in aqueous environments by proteins that use secondary and tertiary structure to isolate anion binding sites from water. Inspired by this principle of solvent exclusion, we created a sequence-defined foldameric capsule whose global minimum conformation displays a helical folded state and is preorganized for 1:1 anion complexation. The high stability of the folded geometry and its ability to exclude solvent were supported by solid-state and solution phase studies. This capsule then withstood a 4-fold increase in solvent dielectric constant (εr) from dichloromethane (9) to acetonitrile (36) while maintaining a high and solvent-independent affinity of 10 5 M –1 ; ΔG ~ 28 kJ mol –1 . This behavior is unusual. More typical of solvent-dependent behavior, Cl – affinities were seen to plummet in control compounds, such as aryl-triazole macrocycles and pentads, with their solvent-exposed binding cavities susceptible to dielectric screening. Finally, dimethyl sulfoxide denatures the foldamer by putative solvent binding, which then lowers the foldamer’s Cl – affinity to normal levels. Furthermore, the design of this capsule demonstrates a new prototype for the development of potent receptors that can operate in polar solvents and has the potential to help manage hydrophilic anions present in the hydrosphere and biosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Hyperheavy spherical and toroidal nuclei: The role of shell structure

The properties of toroidal hyperheavy even-even nuclei and the role of toroidal shell structure are extensively studied within covariant density functional theory. The general trends in the evolution of toroidal shapes in the Z ≈ 130–180 region of the nuclear chart are established for the first time. These nuclei are stable with respect to breathing deformations. The most compact fat toroidal nuclei are located in the Z ≈ 136, N ≈ 206 region of the nuclear chart, but thin toroidal nuclei become dominant with increasing proton number and toward proton and neutron drip lines. The roles of toroidal shell structure, its regularity, supershell structure, and shell gaps as well as the role of different groups of the pairs of the orbitals in its formation are investigated in detail. The lowest in energy solutions at axial symmetry are characterized either by large shell gaps or low density of the single-particle states in the vicinity of the Fermi level in at least one of the subsystems (proton or neutron). Related quantum shell effects are expected to act against the instabilities in breathing and sausage deformations for these subsystems. The investigation with a large set of covariant energy density functionals reveals that substantial proton Z = 154 and 186 and neutron N = 228, 308, and 406 spherical shell gaps exist in all functionals. The nuclei in the vicinity of the combination of these particle numbers form the islands of stability of spherical hyperheavy nuclei. Furthermore, the study suggests that the N = 210 toroidal shell gap plays a substantial role in the stabilization of fat toroidal nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

An implementation of a high-order generalized finite difference method for solving the time-harmonic cold plasma wave equation in toroidal geometry

A high-order physics-informed meshless finite difference numerical technique is introduced for solving the time-harmonic cold plasma wave equation in toroidal geometries, presenting a novel application of the generalized finite difference (GFD) method to plasma wave simulations. The algorithm employs an irregular distribution of computational points, with local point density informed by the shortest wavelength derived from the cold plasma dispersion relation. Numerical stability and robustness are addressed using regularization techniques. The algorithm, implemented for two spatial dimensions, solves for the wave electric field and is demonstrated to achieve convergence rates of $\mathcal{O}$($\mathcal{h}$ $\mathcal{P}$ )⁠. Verification tests reproduce plane wave solutions, and example simulations of ion cyclotron resonance heating and electron cyclotron resonance heating demonstrate its capability, approaching realistic tokamak plasma scenarios. This work contributes to laying a foundation for the GFD method to be used in more sophisticated, optimized, and physically realistic full-wave simulations in time-harmonic plasma wave research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Improved Guarantees for Optimal Nash Equilibrium Seeking and Bilevel Variational Inequalities

We consider a class of hierarchical variational inequality (VI) problems that subsumes VI-constrained optimization and several other problem classes, including the optimal solution selection problem and the optimal Nash equilibrium (NE) seeking problem. Our main contribution is threefold. (i) We consider bilevel VIs with monotone and Lipschitz continuous mappings and devise a single-timescale iteratively regularized extragradient method, named IR-EG 𝚖,𝚖 . We improve the existing iteration complexity results for addressing both bilevel VI and VI-constrained convex optimization problems. (ii) Under the strong monotonicity of the outer-level mapping, we develop a method named IR-EG 𝚜,𝚖 and derive faster guarantees than those in (i). We also study the iteration complexity of this method under a constant regularization parameter. These results appear to be new for both bilevel VIs and VI-constrained optimization. (iii) To our knowledge, complexity guarantees for computing the optimal NE in nonconvex settings do not exist. Motivated by this lacuna, we consider VI-constrained nonconvex optimization problems and devise an inexactly projected gradient method, named IPR-EG, where the projection onto the unknown set of equilibria is performed using IR-EG 𝚜,𝚖 with a prescribed termination criterion and an adaptive regularization parameter. We obtain new complexity guarantees in terms of a residual map and an infeasibility metric for computing a stationary point. Here, we validate the theoretical findings using preliminary numerical experiments for computing the best and the worst NEs.

bilevel optimization↗
DOE OSTI2021

Electrolyte Takeover Strategy for Performance Recovery in Polysulfide-Permanganate Flow Batteries

The abundance of active material precursors for a polysulfide-permanganate flow battery makes it a compelling chemistry for large-scale, and potentially long-duration (>10 h), grid electricity storage. Precipitation, arising from either reactant crossover or electrolyte side reactions, decrease cell efficiencies during charge/discharge cycling. Regardless of the abundance and low cost of active materials, a system without high cyclability cannot meet grid electricity storage economic targets for applications that cycle regularly. Precipitated species can be removed, and reactor efficiency performance restored, by using an electrolyte takeover process, or ETP. Two ETP methods are investigated. One ETP uses the negative electrolyte, an alkaline polysulfide (pS) solution, as takeover solution, and another uses dilute acidic peroxide (DAP) as the takeover solution. Both ETPs maintain functional cell operation within an acceptable performance range over >1000 h and >200 cycles, a duration over which cells that do not undergo ETPs clog and fail. The DAP ETP proves especially effective and limits irrecoverable voltage efficiency fade below 0.02%/cycle. These ETPs, either individually, or in combination, can enable the requisite cyclability for practical polysulfide-permanganate flow battery systems.

25 ENERGY STORAGE↗
DOE OSTI2021

Scalable Techniques for Stochastic Power Flow Problems (Final Report)

The proposed research focuses on developing scalable algorithms for two-stage security-constrained OPF problems with AC power flow constraints, a class of problems complicated by (i) scale arising from a scenario representation; and (ii) the presence of nonlinearity, nonconvexity, and possibly second-stage discreteness or complementarity. Unfortunately, most existing solvers cannot contend with both challenges simultaneously; accordingly, the proposed research focuses on developing solution techniques that can both scale with the number of scenarios and contend with nonconvexity and second-stage complementarity. We consider three avenues for addressing such problems: (i) Variable sample-size SQP (VS-SQP) methods that combine sparse Quasi-Newton updates with a scalable variance-reduced stochastic gradient scheme for stochastic QP subproblems, allowing for contending with second-stage complementarity via regularization; (ii) Variable sample-size stochastic Interior-point (VS-sIP) schemes that propose a sampling-based regularized (to allow for contending with complementarity) interior-point schemes in which a Schur-complement technique is employed for decomposing the Newton direction computation step; (iii) Variable sample-size tractable ADMM (VS-tADMM) schemes combine variable sample-sizes with carefully designed techniques for resolving each of the nonconvex updates (by leveraging the QCQP structures). We intend to compare the three schemes using performance profiles in terms of solution quality, scalability, etc. and then select one scheme which will then be developed and further refined in Python for purposes of the GO competition.

42 ENGINEERING↗
DOE OSTI2021

A general solution for accelerating screw dislocations in arbitrary slip systems with reflection symmetry

Solutions to the differential equations of linear elasticity in the continuum limit in arbitrary crystal symmetry are known only for steady-state dislocations of arbitrary character, i.e. line defects moving at constant velocity. Troubled by singularities at certain ‘critical’ velocities (typically close to certain sound speeds), these dislocation fields are thought to be too idealized, and divergences are usually attributed to neglecting the finite size of the core and to the restriction to constant velocity. In the isotropic limit, accelerating pure screw and edge dislocations were studied some time ago. A generalization to anisotropic crystals has been attempted for pure screw and edge dislocations only for some special cases. This work aims to fill the gap of deriving a general anisotropic solution for pure screw dislocations applicable to slip systems featuring a reflection symmetry, a prerequisite to studying pure screw dislocations without mixing with edge dislocations. Finally, further generalizations to arbitrary mixed dislocations as well as regularizations of the dislocation core are beyond the scope of this paper and are left for future work.

42 ENGINEERING↗
DOE OSTI2023

Exploring regular and turbulent flow states in active nematic channel flow via Exact Coherent Structures and their invariant manifolds

This work is a unified study of stable and unstable steady states of 2D active nematic channel flow using the framework of Exact Coherent Structures (ECS). ECS are stationary, periodic, quasiperiodic, or traveling wave solutions of the governing equations that, together with their invariant manifolds, organize the dynamics of nonlinear continuum systems. We extend our earlier work on ECS in the preturbulent regime by performing a comprehensive study of stable and unstable ECS for a wide range of activity values spanning the preturbulent and turbulent regimes. In the weakly turbulent regime, we compute more than 200 unstable ECS that co-exist at a single set of parameters, and uncover the role of symmetries in organizing the phase space geometry. We provide conclusive numerical evidence that in the preturbulent regime, generic trajectories shadow a series of unstable ECS before settling onto an attractor. Lastly, our studies hint at shadowing of quasiperiodic type ECS in the turbulent regime.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗