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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Development of electro-optical quantum transducers based on three-dimensional superconducting cavities

Quantum transducers enable the conversion of quantum information and signals between different physical platforms. Based on the pioneering works in three-dimensional superconducting cavity technology developed at Fermilab, we are advancing the development of three-dimensional microwave-optical transducers and exploring their applications in quantum information processing and sensing. We present our progress in the design, fabrication, and characterization of three-dimensional microwave cavities integrated with bulk lithium niobate resonators. The material characterization using three-dimensional cavities based on a resonant-type method allows for understanding of complex permittivity and loss mechanism of electro-optic materials at cryogenic temperatures. We also evaluate the potential of the high-efficiency quantum transducers in enhancing the performance of quantum sensors for applications such as dark matter detection, compared to conventional homodyne detection approaches. This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC0207CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics. This work is funded by the DOE's Early Career Research Program. This research used resources of the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Superconducting Quantum Materials and Systems Center (SQMS) under Contract No. DE-AC02-07CH11359.

Zorzetti, Silvia↗
DOE OSTI2026

Screening and qualification methodology for SiC end plug processing methods

Deployment of SiC-ceramic-based fuel cladding for light water reactors requires a hermetic end plug–to–cladding joint that can withstand neutron irradiation during normal operation and maintain integrity during design-basis accidents. Reactor experiments have shown that some SiC composite tubes with SiC end plugs can retain hermeticity after irradiation. However, achieving consistent joint performance under irradiation remains a key challenge. Resolving this issue is essential to enable integral irradiation testing and to demonstrate fuel integrity under commercial-reactor irradiation conditions. This report aims to: (1) provide guidance for designing radiation-tolerant end plug joints for SiC cladding; (2) demonstrate experimental methods to detect processing defects that are unstable under neutron irradiation at light-water-reactor-relevant temperatures and doses; and (3) outline a step-by-step approach for designing and conducting reactor experiments to screen joining methods. The resulting data will be used to improve joint processing and to define critical defect types and sizes that must be detected and eliminated through non-destructive evaluation for quality assurance. Based on prior irradiation experiments at the High Flux Isotope Reactor, differential swelling among the cladding, bonding layer, and end plug was identified as an underlying mechanism for irradiation-induced joint degradation. Accordingly, this effect must be considered in the design of radiation-tolerant joining techniques. In this work, miniature SiC end plug joint specimens irradiated during the previous project were analyzed using X-ray computed tomography to characterize the joint microstructure. Digital volume correlation of the tomography data quantified radiation-induced microstructural changes and enabled evaluation of defect-related risks. Finally, ongoing neutron irradiation efforts using larger specimen volumes are presented. These efforts aim to statistically assess joint performance and to build a microstructure–performance (e.g., leak-tightness) dataset to inform processing improvements and quality control.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Integrated photonic structures for photon-mediated entanglement of trapped ions

Trapped atomic ions are natural candidates for quantum information processing and have the potential to realize or improve quantum computing, sensing, and networking. These applications often require the collection of individual photons emitted from ions into guided optical modes, in some cases for the production of entanglement between separated ions. Proof-of-principle demonstrations of such photon collection from trapped ions have been performed using high-numerical-aperture lenses or cavities and single-mode fibers, but integrated photonic elements in ion-trap structures offer advantages in scalability and manufacturability over traditional optics. In this paper we analyze structures monolithically fabricated with an ion trap for collecting ion-emitted photons, coupling them into waveguides, and manipulating them via interference. We calculate geometric limitations on collection efficiency for this scheme, simulate a single-layer grating that shows performance comparable to demonstrated free-space optics, and discuss practical fabrication and fidelity considerations. Based on this analysis, we conclude that integrated photonics can support scalable systems of trapped ions that can distribute quantum information via photon-mediated entanglement.

Knollmann, Felix W.↗
DOE OSTI2024

Crosstalk-robust quantum control in multimode bosonic systems

High-coherence superconducting cavities offer a hardware-efficient platform for quantum information processing. To achieve universal operations of these bosonic modes, the requisite nonlinearity is realized by coupling them to a transmon ancilla. However, this configuration is susceptible to crosstalk errors in the dispersive regime, where the ancilla frequency is Stark shifted by the state of each coupled bosonic mode. This leads to a frequency mismatch of the ancilla drive, lowering the gate fidelities. To mitigate such coherent errors, we employ quantum optimal control to engineer ancilla pulses that are robust to the frequency shifts. These optimized pulses are subsequently integrated into a recently developed echoed conditional displacement protocol for executing single- and two-mode operations. Through numerical simulations, we examine two representative scenarios: the preparation of single-mode Fock states in the presence of spectator modes and the generation of two-mode entangled Bell-cat states. Our approach markedly suppresses crosstalk errors, outperforming conventional ancilla control methods by orders of magnitude. These results provide guidance for experimentally achieving high-fidelity multimode operations and pave the way for developing high-performance bosonic quantum information processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Thin-film lithium niobate on diamond as a platform for efficient spin-phonon coupling

Negatively charged silicon vacancy (SiV − ) centers in diamond are leading candidates for solid-state quantum memory that can be controlled using electromagnetic or acoustic waves. The latter are particularly promising due to the strong strain response of SiV − , enabling large spin-phonon interaction strengths. Indeed, coherent spin control via surface acoustic waves (SAWs) has been demonstrated and is essential for developing on-chip phononic quantum networks. However, the absence of piezoelectricity in diamond requires an interface with a piezoelectric material for efficient transduction and delivery of acoustic waves to spins in diamonds. Here, we demonstrate a heterogeneously integrated phononic platform that combines thin-film lithium niobate with diamond to enable acoustic control of single SiV − spins. Additionally, leveraging large SAW-induced strain at the location of SiV − , we achieve coherent acoustic control of an electron spin with more than twofold improvement in Rabi frequency compared to state-of-the-art devices based on aluminum nitride on diamond. Furthermore, this work represents a crucial step towards realizing phonon-based quantum information processing systems.

Optically detected magnetic resonance↗
DOE OSTI2024

Controlling interactions between high-frequency phonons and single quantum systems using phononic crystals

The ability to control phonons in solids is key in many fields of quantum science, ranging from quantum information processing to sensing. Phonons often act as a source of noise and decoherence when solid-state quantum systems interact with the phonon bath of their host matrix. In this study, we demonstrate the ability to control the phononic local density of states of the host matrix using phononic crystals and measure its positive impact on single quantum systems. We design and fabricate diamond phononic crystals with features down to around 20 nm, resulting in a high-frequency complete phononic bandgap from 50 to 70 GHz. The engineered local density of states is probed using single silicon-vacancy colour centres embedded in the phononic crystals. We observe an 18-fold reduction in the phonon-induced orbital relaxation rate of the emitters compared to bulk, thereby demonstrating that the phononic crystal suppresses spontaneous single-phonon processes. Furthermore, we show that our approach can efficiently suppress single-phonon-emitter interactions up to 20 K, allowing the investigation of multi-phonon processes in the emitters. Our results represent an important step towards the realization of efficient phonon-emitter interfaces that can be used for quantum acoustodynamics and quantum phononic networks.

quantum information↗
DOE OSTI2024

Empowering a qudit-based quantum processor by traversing the dual bosonic ladder

Abstract High-dimensional quantum information processing has emerged as a promising avenue to transcend hardware limitations and advance the frontiers of quantum technologies. Harnessing the untapped potential of the so-called qudits necessitates the development of quantum protocols beyond the established qubit methodologies. Here, we present a robust, hardware-efficient, and scalable approach for operating multidimensional solid-state systems using Raman-assisted two-photon interactions. We then utilize them to construct extensible multi-qubit operations, realize highly entangled multidimensional states including atomic squeezed states and Schrödinger cat states, and implement programmable entanglement distribution along a qudit array. Our work illuminates the quantum electrodynamics of strongly driven multi-qudit systems and provides the experimental foundation for the future development of high-dimensional quantum applications such as quantum sensing and fault-tolerant quantum computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

3D-printed micro ion trap technology for quantum information applications

Trapped-ion applications, such as in quantum information processing1, precision measurements, optical clocks and mass spectrometry, rely on specialized high-performance ion traps. The last three of these applications typically use traditional machining to customize macroscopic 3D Paul traps, whereas quantum information processing experiments usually rely on photolithographic techniques to miniaturize the traps and meet scalability requirements. Using photolithography, however, it is challenging to fabricate the complex 3D electrode structures required for optimal confinement. Here, in this work, we demonstrate a high-resolution 3D printing technology based on two-photon polymerization (2PP) that is capable of fabricating large arrays of high-performance miniaturized 3D traps. We show that 3D-printed ion traps combine the advantages, such as strong radial confinement, of traditionally machined 3D traps with on-chip miniaturization. We trap calcium ions in 3D-printed ion traps with radial trap frequencies ranging from 2 MHz to 24 MHz. The tight confinement eases ion cooling requirements and allows us to implement high-quality Rabi oscillations with Doppler cooling only. Also, we demonstrate a two-qubit gate with a Bell-state fidelity of 0.978 ± 0.012. With 3D printing technology, the design freedom is greatly expanded without sacrificing scalability and precision, so that ion trap geometries can be optimized for higher performance and better functionality.

quantum information↗
DOE OSTI2025

Ansatz-Free Hamiltonian Learning with Heisenberg-Limited Scaling

Learning the unknown interactions that govern a quantum system is crucial for quantum information processing, device benchmarking, and quantum sensing. The problem, known as Hamiltonian learning, is well understood under the assumption that interactions are local, but this assumption may not hold for arbitrary Hamiltonians. Previous methods all require high-order inverse polynomial dependency with precision, unable to surpass the standard quantum limit and reach the gold-standard Heisenberg-limited scaling. Whether Heisenberg-limited Hamiltonian learning is possible without prior assumptions about the interaction structures, a challenge we term ansatz-free Hamiltonian learning , remains an open question. In this work, we present a quantum algorithm to learn arbitrary sparse Hamiltonians without any structure constraints using only black-box queries of the system’s real-time evolution and minimal digital controls to attain Heisenberg-limited scaling in estimation error. Our method is also resilient to state-preparation-and-measurement errors, enhancing its practical feasibility. We numerically demonstrate our ansatz-free protocol for learning physical Hamiltonians and validating analog quantum simulations, benchmarking our performance against the state-of-the-art Heisenberg-limited learning approach. Moreover, we establish a fundamental trade-off between total evolution time and quantum control on learning arbitrary interactions, revealing the intrinsic interplay between controllability and total evolution-time complexity for any learning algorithm. These results pave the way for further exploration into Heisenberg-limited Hamiltonian learning in complex quantum systems under minimal assumptions, potentially enabling new benchmarking and verification protocols.

machine learning↗
DOE OSTI2025

Artificial Intelligence and Machine Learning Applications in Modern Power Systems

Machine learning (ML) and artificial intelligence (AI) algorithms offer valuable tools for the analysis and interpretation of large datasets. These tools have the capability to uncover insights that may not be readily apparent within these datasets. In recent years, the integration of ML and AI has become increasingly prevalent in various applications within the power system domain. One of the earliest instances of machine learning in power systems can be traced back to demand forecasting, where artificial neural networks were employed for short-term load forecasting. In contemporary power systems, an abundance of high-resolution geospatial and temporal data is generated at various time intervals, ranging from sub-seconds (Phasor Measurement Units or PMUs) to seconds (Supervisory Control and Data Acquisition or SCADA), minutes (Process Information or PI), and extending to days, months, and years. These datasets contain valuable information concerning system reliability and performance. This information holds the potential to offer critical insights into system operations, as well as solutions for predicting and mitigating contingencies to prevent cascading outages. Despite the immense power of machine learning tools, system operators, planners, and utilities often exhibit hesitancy in fully embracing AI-enabled system operations and planning. This cautious approach persists, even as numerous diverse applications of machine learning continue to emerge in the realm of power systems. In this chapter, our focus will delve deep into ML and AI applications tailored for power systems. These applications aim to furnish system operators with enhanced situational awareness and augment their decision-making capabilities, especially during challenging operating conditions. Specific areas of interest encompass root cause analyses of electricity market datasets and the strategic selection of representative samples from vast power system databases for training ML/AI models. Finally, the chapter will conclude with a short discussion on the future of ML/AI in power systems and possible directions that the industry is moving towards.

power system applications, machine learning (ML), ↗
DOE OSTI2025

Mechanical Resonant Sensing of Spin Texture Dynamics in a 2D Antiferromagnet

Abstract The coupling between the spin degrees of freedom and macroscopic mechanical motions, including striction, shearing, and rotation, has attracted wide interest with applications in actuation, transduction, and information processing. Experiments so far have established the mechanical responses to the long‐range ordered or isolated single spin states. However, it remains elusive whether mechanical motions can couple to a different type of magnetic structure, the non‐collinear spin textures, which exhibit nanoscale spatial variations of spin (domain walls, skyrmions,etc.) and are promising candidates to realize high‐speed computing devices. Here, collective spin texture dynamics is detected with nanoelectromechanical resonators fabricated from 2D antiferromagnetic (AFM) MnPS 3 with 10 −9 strain sensitivity. By examining radio frequency mechanical oscillations under magnetic fields, new magnetic transitions are identified with sharp dips in resonant frequency. They are attributed to collective AFM domain wall motions as supported by the analytical modeling of magnetostriction and large‐scale spin‐dynamics simulations. Additionally, an abnormally large modulation in the mechanical nonlinearity at the transition field infers a fluid‐like response due to ultrafast domain motion. The work establishes a strong coupling between spin texture and mechanical dynamics, laying the foundation for electromechanical manipulation of spin texture and developing quantum hybrid devices.

Chemistry↗
DOE OSTI2025

Interface‐Induced Stability of Nontrivial Topological Spin Textures: Unveiling Room‐Temperature Hopfions and Skyrmions

Topological spin configurations, such as soliton-like spin texture and Dirac electron assemblies, have recently emerged in fundamental science and technology. Achieving stable topological spin textures at room temperature is crucial for their use as long-range information carriers. However, their creation and manipulation are hindered by multi-step field training and competing interactions. Thus, a spontaneous ground state for multidimensional topological spin textures is desirable, with skyrmions forming swirling, hedgehog-like spin structures in two dimensions and hopfions as their twisted 3D counterparts. Here, the first observation of robust and reproducible topological spin textures of hopfions and skyrmions observed at room temperature and in zero magnetic field is reported, which are stabilized by geometric confinement and protected by interfacial magnetism in a ferromagnet/topological insulator/ferromagnet trilayer heterostructure. These skyrmion-hopfion configurations are directly observed at room temperature with Lorenz transmission electron microscopy. Using micromagnetic modeling, the experimental observations of hopfion-skyrmion assemblies are reproduced. This model reveals a complete picture of how spontaneously organized skyrmion lattices encircled by hopfion rings are controlled by surface electrons, uniaxial anisotropy, and Dzyaloshinskii-Moriya interaction. This study provides evidence that topological chiral spin textures can facilitate the development of magnetic topological carriers, paving the way for ultralow-power and high-density information processing.

hopfions↗
DOE OSTI2025

High Mobility and Electrostatics in GeSn Quantum Wells With SiGeSn Barriers

GeSn is an emerging material with potential applications in next‐generation integrated optoelectronics and quantum information processing. While GeSn/SiGeSn quantum wells exhibit promising optical properties, their electrical transport characteristics and governing electrostatics in gated structures remain unexplored. Heterostructure field‐effect transistors are fabricated using GeSn/SiGeSn quantum wells and electronic transport properties of 2D holes are characterized. At 2 K, heterostructure field‐effect transistors with well/barrier compositions of Ge 0.945 Sn 0.055 /Si 0.03 Ge 0.93 Sn 0.04 and Ge 0.9 Sn 0.1 /Si 0.017 Ge 0.927 Sn 0.056 , show peak mobilities of 9000 and 19 000 cm 2 /Vs, respectively, the latter setting a record for the highest mobility reported for GeSn quantum wells with a Sn concentration around 6 % or greater. Remarkably, at low carrier densities, devices with a SiGeSn barrier exhibit mobilities several times higher than previously reported for GeSn quantum wells with a Ge barrier. This higher mobility contrasts with the expectation that alloy scattering from the barrier would reduce carrier mobility. Two mechanisms based on atom probe tomography data analyses are proposed: i) unintentionally improved SiGeSn/GeSn interface and/or ii) reduced alloy scattering from short‐range order. Significant current–voltage hysteresis is observed, with the effective threshold gate voltage shifting by more than 5 V, attributed to non‐equilibrium trapped charge at various interfaces within the SiGeSn heterostructure.

GeSn↗
DOE OSTI2026

Longitudinal Multi-omics Reveal Phase-Dependent Viral Adaptive Strategies and Functional Potential During Formation of Algal-bacterial Granular Sludge

Virus-host interactions within microbial aggregates critically influence microbiome function and stability, yet how physicochemical stresses shape the interactive dynamics remains largely unexplored. Here, we investigated virus–host dynamics during the transition of algal-bacterial granular sludge (ABGS) from activated sludge under continuous hydraulic shear using integrated metagenomics and metatranscriptomics. Hydraulic stress initially reduced host a-diversity, which coincided with a marked increase in viral lysogenicity. During this host diversity bottleneck, viral microdiversity increased, and genes related to virion structure and DNA packaging were under positive selection (pN/pS >1). As host diversity recovered, viral microdiversity declined, while viral anti-defense systems (ADS) significantly increased in abundance. Lagged correlation analysis revealed a significant positive correlation between viral ADS and host defense systems (DS), suggesting an evolutionary arms race. Furthermore, active lysogenic infections were accompanied by enrichment of DS and auxiliary viral genes (AVGs) involved in genetic information processing and amino acid metabolism, potentially enhancing host fitness. Overall, our study unveils a phase-dependent co-evolutionary interplay between viruses and hosts during ABGS formation, providing insights into the development and maintenance of microbial structural and functional resilience in engineered ecosystems.

Qi, Huiyuan↗
DOE OSTI2025

Unveiling the nature of Ga-based chalcogenides for electrical switching selectors

Three-dimensional phase-change memory with stackable crossbar architecture is a promising technology to meet the urgent demands for high-density storage and rapid information processing in the era of explosive data growth. The performance depends strongly on the properties of ovonic threshold switching (OTS) selectors, which control the on/off states of memory units. Amorphous GaS serves as an outstanding OTS material, distinguished by its sizable mobility gap and high crystallization temperature, while the underlying mechanism continues to be inadequately comprehended. Here, in this work, we systematically studied the structural and electronic properties of amorphous Ga-X (X = S/Se/Te) using first-principles calculations. The results show that Ga atoms adopt tetrahedral motifs, while S/Se/Te atoms predominantly exhibit the structure of a distorted triangular pyramid. This structural arrangement is ascribed to the substantial dative bonds formed by the lone-pair electrons of the anions and the vacant sp3 orbitals around Ga atoms. Large mobility gaps (e.g., GaS: 2.43 eV, GaSe: 1.76 eV, GaTe: 1.26 eV) and distinct mid-gap states (e.g., ∼0.66 eV above valence band tail) ensure that these three chalcogenide glasses can be switched on under an external electric field while effectively suppressing leakage current without a bias, and the defect electronic states originate from short, robust Ga-Ga bonds due to the formation of distorted chain-like local structures. Our research elucidates the mechanisms of amorphous Ga-X as OTS materials, enriching the spectrum of electrical switching selectors by incorporating III-VI chalcogenides. This inclusion offers novel opportunities for the refinement and optimization of high-density integrated memory systems.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Regional specialization in prefrontal cortex manifests in the reliability of task progression codes

The brain has the remarkable ability to guide the performance of complex tasks. Distinct prefrontal cortical areas make specific contributions to this ability, with the orbitofrontal cortex (OFC) critical for processing information related to trial outcomes and the dorsomedial prefrontal cortex (dmPFC) critical for sustained effort and selecting the right action at the right time. Yet, in both areas, neural activity represents both outcome- and action-related quantities. How similar neural representations support different functions remains unclear. Here, we compared OFC and dmPFC activity in rats performing a spatial alternation task. We show that, in contrast to other task-related variables, task progression is represented in both areas, but with distinct patterns of across-trial reliability that match each area’s previously documented functional specialization. Our results indicate that the engagement of reliable, task-phase-specific activity patterns differs across prefrontal regions in a manner well suited to engage different computations at different times.

Biological and medical sciences↗
DOE OSTI2025

Curvature Memory in Electrically Stimulated Lipid Membranes

Here, we demonstrate, using non-equilibrium molecular dynamics simulations, that lipid membrane capacitance varies with surface charge accumulation linked to membrane shape and curvature changes. Specifically, we show that lipid membranes exhibit a hysteretic response when exposed to oscillatory electric fields. The electromechanical coupling in these membranes leads to hysteretic buckling, in which the membrane can spontaneously buckle in one of two distinct directions along the electric field, even for the same ionic charge accumulation at the water–membrane interface. In this regard, these binary buckled membrane states suggest potential applications in neuromorphic computing. Their bistable nature, characterized by two distinct and stable configurations, could serve as a foundation for implementing memory storage systems and logic operations. Furthermore, we introduce a circuit model that captures these dynamic effects, offering insights into emergent memory effects in electrically stimulated lipid membranes. Finally, this work presents lipid bilayers as dynamic, adaptable elements and suggests a new platform for exploring energy storage, information processing, and memory encoding at the lipid membrane level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Macroscopic Monochalcogenide van der Waals Ferroics: Growth, Domain Structures, and Curie Temperature

Two-dimensional and layered van der Waals materials promise to overcome the limitations of conventional ferroelectrics in terms of miniaturization and material integration, but synthesis has produced only small (up to few micrometer-sized) ferroic crystals. Here, we report the realization of in-plane ferroelectric few-layer crystals of the monochalcogenides tin(II) sulfide and selenide (SnS, SnSe) whose linear dimensions exceed the current state of the art by up to 1 order of magnitude. Such large crystals allow the investigation of ferroic domain patterns that are unaffected by edges and finite-size effects. Analysis of the abundant stripe domains by electron microscopy and nanobeam electron diffraction shows two distinct domain types: twin domains separated by positively charged walls with alternating head-to-head and tail-to-tail polarization as well as not previously observed purely rotational domains connected by neutral domain walls with head-to-tail dipoles. Access to large crystals allowed the determination of the Curie temperature of few-layer SnSe van der Waals ferroelectrics, and it enables the investigation of this class of ferroelectrics by widely available methods such as polarized optical microscopy. Furthermore, the combination with layer transfer protocols promises uniform materials for exploring fundamentals and for implementing devices for information processing and energy conversion.

36 MATERIALS SCIENCE↗