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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Solitons in lattice field theories via tight-binding supersymmetry

Reflectionless potentials play an important role in constructing exact solutions to classical dynamical systems (such as the Korteweg-de Vries equation), non-perturbative solutions of various large-N field theories (such as the Gross-Neveu model), and closely related solitonic solutions to the Bogoliubov-de Gennes equations in the theory of superconductivity. These solutions rely on the inverse scattering method, which reduces these seemingly unrelated problems to identifying reflectionless potentials of an auxiliary one-dimensional quantum scattering problem. There are several ways of constructing these potentials, one of which is quantum mechanical supersymmetry (SUSY). In this paper, motivated by recent experimental platforms, we generalize this framework to develop a theory of lattice solitons. We first briefly review the classical inverse scattering method in the continuum limit, focusing on the Korteweg-de Vries (KdV) equation and SU(N) Gross-Neveu model in the large N limit. We then generalize this methodology to lattice versions of interacting field theories. Our analysis hinges on the use of trace identities, which are relations connecting the potential of an equation of motion to the scattering data. For a discrete Schrödinger operator, such trace identities had been known as far back as Toda; however, we derive a new set of identities for the discrete Dirac operator. We then use these identities in a lattice Gross-Neveu and chiral Gross-Neveu (Nambu-Jona-Lasinio) model to show that lattice solitons correspond to reflectionless potentials associated with the discrete scattering problem. These models are of significance as they are equivalent to a mean-field theory of a lattice superconductor. To explicitly construct these solitons, we generalize supersymmetric quantum mechanics to tight-binding models. We show that a matrix transformation exists that maps a tight-binding model to an isospectral one which shares the same structure and scattering properties. The corresponding soliton solutions have both modulated hopping and onsite potential, the former of which has no analogue in the continuum limit. We explicitly compute both topological and non-topological soliton solutions as well as bound state spectra in the aforementioned models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Noise-aware optimization in nominally identical manufacturing and measuring systems for high-throughput parallel workflows

Device-to-device variability in experimental noise critically impacts reproducibility, especially in automated, high-throughput systems like additive manufacturing farms. While manageable in small labs, such variability can escalate into serious risks at larger scales, such as architectural 3D printing, where noise may cause structural or economic failures. This contribution presents a noise-aware decision-making algorithm that quantifies and models device-specific noise profiles to manage variability adaptively. It uses distributional analysis and pairwise divergence metrics with clustering to choose between single-device and robust multi-device Bayesian optimization strategies. Unlike conventional methods that assume homogeneous devices or enforce generic robustness, the proposed framework explicitly determines whether shared optimization across devices is appropriate based on the degree of inter-device noise heterogeneity. This enables improved performance, reproducibility, and efficiency. An experimental case study involving three nominally identical 3D printers (same brand, model, and close serial numbers) demonstrates reduced redundancy, lower resource usage, and improved reliability, along with improved convergence stability and solution quality through the selection of the appropriate optimization strategy based on the degree of inter-device noise heterogeneity. Overall, this framework establishes a general approach for precision- and resource-aware optimization in scalable, automated experimental platforms, demonstrated here on a representative multi-device 3D printing case study.

Schenk, Christina↗
DOE OSTI2023

Impurity gas monitoring using ultrasonic sensing and neural networks: forward and inverse problems

Ultrasonic sensing is a non-invasive technique for monitoring impurity gas composition in various industrial applications where safety and regulatory compliance are crucial. In this study, ultrasonic sensing and neural networks were used to analyze impurity gases (i.e., air and argon) in helium. An experimental platform was established to acquire ultrasonic data. In the forward problem, an artificial neural network (ANN) model was used to forecast the response and time-of-flight (TOF) based on the excitation, and argon and air concentrations. The inverse problem was solved using a convolutional neural network (CNN) to predict the argon and air concentrations given the ultrasonic response and excitation. The results showed that the ANN accurately predicted the ultrasonic response and the change in TOF with concentration. As the air concentration was increased from 0 to 9.8%, the TOF sensitivity to detect argon decreased by 39.8% and 16.1% from ANN and sound speed theory, respectively. The CNN demonstrated high accuracy in predicting concentrations for inputs in the testing dataset. The application of the trained CNN indicated that it over-predicts air concentration while under-predicting the argon concentration. To improve accuracy, the predicted air and argon concentrations should be corrected by -0.992% and 1.027% bias, respectively.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Can protein expression be ‘solved’?

Recombinant protein expression is central to biotechnology’s application in academic exploration as well as human health, climate applications and the bioeconomy in general. However, not all proteins can be expressed in all organisms, and the field lacks a predictive model of soluble protein overexpression that could replace laborious experimental trial-and-error. Here, we discuss the state of the field and identify the lack of large, high-fidelity datasets as the primary bottleneck to progress. We review possible assays that could be used for data collection to identify a path toward an extensible experimental platform for collecting soluble recombinant protein overexpression data across organisms. We suggest that the resulting dataset should be used to train increasingly generalizable predictive models of protein expression to answer the question: “How can predictive protein expression be solved?”.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

High repetition rate exploration of the Biermann battery effect in laser produced plasmas over large spatial regions

Abstract In this paper we present a high repetition rate experimental platform for examining the spatial structure and evolution of Biermann-generated magnetic fields in laser-produced plasmas. We have extended the work of prior experiments, which spanned over millimeter scales, by spatially measuring magnetic fields in multiple planes on centimeter scales over thousands of laser shots. Measurements with magnetic flux probes show azimuthally symmetric magnetic fields that range from 60 G at 0.7 cm from the target to 7 G at 4.2 cm from the target. The expansion rate of the magnetic fields and evolution of current density structures are also mapped and examined. Electron temperature and density of the laser-produced plasma are measured with optical Thomson scattering and used to directly calculate a magnetic Reynolds number of $1.4\times {10}^4$ , confirming that magnetic advection is dominant at $\ge 1.5$ cm from the target surface. The results are compared to FLASH simulations, which show qualitative agreement with the data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Spatially Mapping the CO 2 Alkaline Sorbent Diffuse Microenvironment Using Operando Raman Spectroscopy

When designing a chemical process, the local balance of transport and kinetics, collectively referred to as the diffuse microenvironment, plays a critical role in performance but is difficult to directly observe. This work demonstrates a method of two-dimensional spatial chemical mapping of the diffuse microenvironment in the context of alkali metal hydroxide direct air capture of carbon dioxide using a custom operando gas-absorption flow cell along with confocal Raman spectroscopy. Notably, we observe the concentration boundary layer near the gas–liquid interface and elucidate the interplay of carbonate and bicarbonate ions within it while inferring local hydroxide depletion through continuum modeling. These first of their kind observations provide a technique to compare the performance of direct air capture solvents based on diffuse microenvironment dynamics while also providing metrics important for air contactor design such as boundary layer thickness. Overall, this work showcases a new experimental platform to study interfacial diffuse microenvironments in and outside of the field of direct air capture of carbon dioxide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Multimodal In Situ Characterization Uncovers Unexpected Stability of a Cobalt Electrocatalyst for Acidic Sustainable Energy Technologies

An accelerated development of durable and affordable sustainable energy technologies is often hindered by a limited understanding of how non-precious materials within these systems degrade. In acidic proton exchange membrane fuel cells and water electrolyzers, metallic cobalt (Co) is considered an unstable component that is often combined with precious metals or other stabilizers. To understand the mechanisms behind Co instability, we employ an experimental platform that quantifies dissolution with on-line inductively coupled plasma mass spectrometry and product formation with electrochemical mass spectrometry during electrochemical testing, along with ex- situ characterization. Under varied conditions (electrocatalysis, time, gas-type saturation, and ion concentration), windows of Co stability are observed that are different than predicted with classical chemical thermodynamics, suggesting new stabilization and degradation mechanisms than previously understood. Notably, Co is active for the hydrogen evolution reaction (HER), with prolonged stability that is ~300 mV different than thermodynamically projected. Additionally, in an oxygenated environment, Co concurrently performs the HER and oxygen reduction reaction (ORR) yet undergoes different morphology changes and dissolution mechanisms. Interestingly, in the absence of electrocatalysis, there is a 22x decrease in dissolution in an oxygen-free environment, proposing a route to decrease Co losses during device shutdown protocols. Lastly, under more extreme operating conditions, Co becomes stable after a substantial amount of dissolution, suggesting that high concentrations of Co 2+ ions in the microenvironment induce the formation of a stable CoHO 2 surface. Altogether, these results can be leveraged to improve the design and development of more robust and cost-effective sustainable energy technologies, as well as promote strategic strategies for prolonged material utilization.

Dissolution↗
DOE OSTI2023

Evaluating Ion Accumulation and Storage in Traveling Wave Based Structures for Lossless Ion Manipulations

Structures for lossless ion manipulations (SLIM) technology has demonstrated high resolving power ion mobility separation and flexibility to integrate complex ion manipulations into a single experimental platform. To enable IMS separations, trapping/accumulating ions inside SLIM (or in-SLIM) prior to injection of a packet for separations provides ease of operation and reduces the need for dedicated ion traps external to SLIM. To fully characterize the ion accumulation process, we have evaluated the effect of TW amplitudes, ion collection times, and storage times on the “in-SLIM” accumulation process. The study utilized a SLIM module comprising 5 distinct tracks, each with a specific ion accumulation configuration. The effect of the TW conditions on the accumulation process was investigated for a 3-peptide mixture: kemptide, angiotensin II, and neurotensin at a TW speed of 106 m/s. The effect of ion accumulation time/collection time and storage time was investigated, in addition to TW amplitude. Overall, the signal of the analyte ions increased when the ion collection time increased from 49 to 163 ms but decreased when the ion collection time increased further to 652 ms due to the space charge effects. Ion losses were observed at high TW amplitudes (e.g., 15 V p–p and 20 V p–p ). In addition, under space charge conditions (e.g., collection times of 163 and 652 ms), the signal of the analyte ions decreased with an increase in storage times for all TW amplitudes applied to the trapping region. For ion accumulation, the data indicate that gentler TW conditions must be utilized to minimize ion losses and fragments to benefit from the “in-SLIM” accumulation process. Finally, wider SLIM tracks provided better performance than those with narrower tracks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Experimental Whole-Ecosystem Warming Enables Novel Estimation of Snow Cover and Depth Sensitivities to Temperature, and Quantification of the Snow-Albedo Feedback Effect

Climate change is reducing the amount, duration, and extent of snow across high-latitude ecosystems. But, in landscapes where persistent winter snow cover develops, experimental platforms to specifically investigate interactions between warming and changes in snowpack, and impacts on ecosystem processes, have been lacking. We leveraged a whole-ecosystem warming experiment in a boreal peatland forest to quantify how snow duration, depth, and fractional cover vary with warming of up to +9°C. We found that every snow-related quantity we examined declined precipitously as the amount of warming increased. The importance of deep, continuous snow cover for moderating shallow soil temperature is highlighted by an increase in soil temperature variance and the frequency of short-duration freeze-thaw cycles in the warmer plots. We used a paired-plot approach to estimate the magnitude of the snow-albedo feedback effect, and demonstrate that albedo-driven warming linked to reduced snow cover varies between December (+0.4°C increase in maximum air temperature) and March (+1.2°C increase) because of differences in insolation. Overall, results show that even modest future warming will have profound impacts on northern winters and cold-season ecosystem processes. Plot-level data from this warming experiment, and emergent relationships between warming and quantities related to snow cover and duration, could be of enormous value for testing and improving the representation of snow processes in simulation models, especially under future climate scenarios that are outside of the range of historically observed variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Autonomous quantum error correction and fault-tolerant quantum computation with squeezed cat qubits

We propose an autonomous quantum error correction scheme using squeezed cat (SC) code against excitation loss in continuous-variable systems. Through reservoir engineering, we show that a structured dissipation can stabilize a two-component SC while autonomously correcting the errors. The implementation of such dissipation only requires low-order nonlinear couplings among three bosonic modes or between a bosonic mode and a qutrit. While our proposed scheme is device independent, it is readily implementable with current experimental platforms such as superconducting circuits and trapped-ion systems. Compared to the stabilized cat, the stabilized SC has a much lower dominant error rate and a significantly enhanced noise bias. Furthermore, the bias-preserving operations for the SC have much lower error rates. In combination, the stabilized SC leads to substantially better logical performance when concatenating with an outer discrete-variable code. The surface-SC scheme achieves more than one order of magnitude increase in the threshold ratio between the loss rate κ 1 and the engineered dissipation rate κ 2 . Under a practical noise ratio κ 1 /κ 2 = 10 -3 , the repetition-SC scheme can reach a 10 -15 logical error rate even with a small mean excitation number of 4, which already suffices for practically useful quantum algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Heisenberg-limited Hamiltonian learning for interacting bosons

We develop a protocol for learning a class of interacting bosonic Hamiltonians from dynamics with Heisenberg-limited scaling. For Hamiltonians with an underlying bounded-degree graph structure, we can learn all parameters with root mean square error ϵ using ${\mathcal{O}}(1/\epsilon )$ total evolution time, which is independent of the system size, in a way that is robust against state-preparation and measurement error. In the protocol, we only use bosonic coherent states, beam splitters, phase shifters, and homodyne measurements, which are easy to implement on many experimental platforms. A key technique we develop is to apply random unitaries to enforce symmetry in the effective Hamiltonian, which may be of independent interest.

computer science↗
DOE OSTI2023

Tunable spin and valley excitations of correlated insulators in Γ-valley moiré bands

Moiré superlattices formed from transition metal dichalcogenides (TMDs) have been shown to support a variety of quantum electronic phases that are highly tunable using applied electromagnetic fields. While the valley character of the low-energy states dramatically affects optoelectronic properties in the constituent TMDs, this degree of freedom has yet to be fully explored in moiré systems. Here, we establish twisted double bilayer WSe 2 as an experimental platform to study electronic correlations within Γ-valley moiré bands. Through a combination of local and global electronic compressibility measurements, we identify charge-ordered phases at multiple integer and fractional moiré band fillings ν. By measuring the magnetic field dependence of their energy gaps and the chemical potential upon doping, we reveal spin-polarized ground states with novel spin polaron quasiparticle excitations. In addition, an applied displacement field allows us to realize a new mechanism of metal-insulator transition at ν=–1 driven by tuning between Γ- and K-valley moiré bands. Together, our results demonstrate control over both the spin and valley character of the correlated ground and excited states in this system.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Electrically writing a magnetic heliknoton in a chiral magnet

A magnetic heliknoton is the three-dimensional counterpart to the two-dimensional magnetic skyrmion, and serves as a pivotal topological soliton for extending topological magnetism into three dimensions. However, its experimental realization remains elusive. Here we report the controlled nucleation of a magnetic heliknoton in the chiral magnet FeGe at zero magnetic field, achieved through nanoscale current-pulse excitation. By combining angle-dependent quantitative electron holography with micromagnetic simulations, we resolve the three-dimensional spin texture of the heliknoton. In particular, the heliknoton exhibits current-driven collinear motion without the Hall effect. Furthermore, our findings establish a readily accessible experimental platform for further exploration of three-dimensional topological solitons and highlight their potential for practical applications.

Magnetic properties and materials↗
DOE OSTI2023

Probing many-body dynamics in a two-dimensional dipolar spin ensemble

Abstract The most direct approach for characterizing the quantum dynamics of a strongly interacting system is to measure the time evolution of its full many-body state. Despite the conceptual simplicity of this approach, it quickly becomes intractable as the system size grows. An alternate approach is to think of the many-body dynamics as generating noise, which can be measured by the decoherence of a probe qubit. Here we investigate what the decoherence dynamics of such a probe tells us about the many-body system. In particular, we utilize optically addressable probe spins to experimentally characterize both static and dynamical properties of strongly interacting magnetic dipoles. Our experimental platform consists of two types of spin defects in nitrogen delta-doped diamond: nitrogen-vacancy colour centres, which we use as probe spins, and a many-body ensemble of substitutional nitrogen impurities. We demonstrate that the many-body system’s dimensionality, dynamics and disorder are naturally encoded in the probe spins’ decoherence profile. Furthermore, we obtain direct control over the spectral properties of the many-body system, with potential applications in quantum sensing and simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Thermal transport in warm dense matter revealed by refraction-enhanced x-ray radiography with a deep-neural-network analysis

Abstract Transport properties of high energy density matter affect the evolution of many systems, ranging from the geodynamo in the Earth’s core, to hydrodynamic instability growth in inertial confinement fusion capsules. Large uncertainties of these properties are present in the warm dense matter regime where both plasma models and condensed matter models become invalid. To overcome this limit, we devise an experimental platform based on x-ray differential heating and time-resolved refraction-enhanced radiography coupled to a deep neural network. We retrieve the first measurement of thermal conductivity of CH and Be in the warm dense matter regime and compare our measurement with the most commonly adopted models. The discrepancies observed are related to the estimation of a correction term from electron-electron collisions. The results necessitate improvement of transport models in the warm dense matter regime and could impact the understanding of the implosion performance for inertial confinement fusion.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Light-activated microtubule-based two-dimensional active nematic

We assess the ability of two light responsive kinesin motor clusters to drive dynamics of microtubule-based active nematics: opto-K401, a processive motor, and opto-K365, a non-processive motor. Measurements reveal an order of magnitude improvement in the contrast of nematic flow speeds between maximally- and minimally-illuminated states for opto-K365 motors when compared to opto-K401 construct. For opto-K365 nematics, we characterize both the steady-state flow and defect density as a function of applied light. We also examine the transient behavior as the system switches between steady-states upon changes in light intensities. Although nematic flows reach a steady state within tens of seconds, the defect density exhibits transient behavior for up to 10 minutes, showing a separation between small-scale active flows and system-scale structural states. Furthermore, our work establishes an experimental platform that can exploit spatiotemporally-heterogeneous patterns of activity to generate targeted dynamical states.

42 ENGINEERING↗
DOE OSTI2022

Inferring the temperature profile of the radiative shock in the COAX experiment with shock radiography, Dante, and spectral temperature diagnostics

Predicting and modeling the behavior of experiments with radiation waves propagating through low-density foams require a detailed quantification of the numerous uncertainties present. In regimes where a prominent radiative shock is produced, key dynamical features include the shock position, temperature, and curvature and the spatial distribution and temperature of the corresponding supersonic radiation wave. The COAX experimental platform is designed to constrain numerical models of such a radiative shock propagating through a low-density foam by employing radiography for spatial and shock information, Dante for characterizing the x-ray flux from the indirectly driven target, and a novel spectral diagnostic designed to probe the temperature profile of the wave. In this work, we model COAX with parameterized 2D simulations and a Hohlraum-laser modeling package to study uncertainties in diagnosing the experiment. The inferred temperature profile of the COAX radiation transport experiments has been shown to differ from simulations more than expected from drive uncertainties that have been constrained by simultaneous soft x-ray flux and radiography measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Simultaneous imaging and diffraction in the dynamic diamond anvil cell

The ability to visualize a sample undergoing a pressure-induced phase transition allows for the determination of kinetic parameters, such as the nucleation and growth rates of the high-pressure phase. For samples that are opaque to visible light (such as metallic systems), it is necessary to rely on x-ray imaging methods for sample visualization. Here, we present an experimental platform developed at beamline P02.2 at the PETRA III synchrotron radiation source, which is capable of performing simultaneous x-ray imaging and diffraction of samples that are dynamically compressed in piezo-driven diamond anvil cells. This setup utilizes a partially coherent monochromatic x-ray beam to perform lensless phase contrast imaging, which can be carried out using either a parallel- or focused-beam configuration. The capabilities of this platform are illustrated by experiments on dynamically compressed Ga and Ar. Melting and solidification were identified based on the observation of solid/liquid phase boundaries in the x-ray images and corresponding changes in the x-ray diffraction patterns collected during the transition, with significant edge enhancement observed in the x-ray images collected using the focused-beam. These results highlight the suitability of this technique for a variety of purposes, including melt curve determination.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗