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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Hong-Ou-Mandel interference of single-photon-level pulses stored in independent room-temperature quantum memories

Abstract Quantum repeater networks require independent absorptive quantum memories capable of storing and retrieving indistinguishable photons to perform high-repetition entanglement swapping operations. The ability to perform these coherent operations at room temperature is of prime importance for the realization of scalable quantum networks. We perform Hong-Ou-Mandel (HOM) interference between photonic polarization states and single-photon-level pulses stored and retrieved from two sets of independent room-temperature quantum memories. We show that the storage and retrieval of polarization states from quantum memories does not degrade the HOM visibility for few-photon-level polarization states in a dual-rail configuration. For single-photon-level pulses, we measure the HOM visibility with various levels of background in a single polarization, single-rail QM, and investigate its dependence on the signal-to-background ratio. We obtain an HOM visibility of 43%, compared to the 48% no-memory limit of our set-up. These results allow us to estimate a 33% visibility for polarization qubits under the same conditions. These demonstrations lay the groundwork for future applications using large-scale memory-assisted quantum networks.

Physics↗
DOE OSTI2021

Experimental evidence of plasmarons and effective fine structure constant in electron-doped graphene/h-BN heterostructure

Electron-electron interaction is fundamental in condensed matter physics and can lead to composite quasiparticles called plasmarons, which strongly renormalize the dispersion and carry information of electron-electron coupling strength as defined by the effective fine structure constant $α$ $^{*}_{ee}$. Although h-BN with unique dielectric properties has been widely used as an important substrate for graphene, so far there is no experimental report of plasmarons in graphene/h-BN yet. Here, we report direct experimental observation of plasmaron dispersion in graphene/h-BN heterostructures through angle-resolved photoemission spectroscopy (ARPES) measurements upon in situ electron doping. Characteristic diamond-shaped dispersion is observed near the Dirac cone in both 0° (aligned) and 13.5° (twisted) graphene/h-BN, and the electron-electron interaction strength $α$ $^{*}_{ee}$ is extracted to be $α$ $^{*}_{ee}$ ≈ 0.9 ± 0.1, highlighting the important role of electron-electron interaction. Our results suggest graphene/h-BN as an ideal platform for investigating strong electron-electron interaction with weak dielectric screening, and lays fundamental physics for gate-tunable nano-electronics and nano-plasmonics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Linking metabolic phenotypes to pathogenic traits among “ Candidatus Liberibacter asiaticus” and its hosts

Candidatus Liberibacter asiaticus (CLas) has been associated with Huanglongbing, a lethal vector-borne disease affecting citrus crops worldwide. While comparative genomics has provided preliminary insights into the metabolic capabilities of this uncultured microorganism, a comprehensive functional characterization is currently lacking. Here, we reconstructed and manually curated genome-scale metabolic models for the six CLas strains A4, FL17, gxpsy, Ishi-1, psy62, and YCPsy, in addition to a model of the closest related culturable microorganism, L. crescens BT-1. Predictions about nutrient requirements and changes in growth phenotypes of CLas were confirmed using in vitro hairy root-based assays, while the L. crescens BT-1 model was validated using cultivation assays. Host-dependent metabolic phenotypes were revealed using expression data obtained from CLas-infected citrus trees and from the CLas-harboring psyllid Diaphorina citri Kuwayama. These results identified conserved and unique metabolic traits, as well as strain-specific interactions between CLas and its hosts, laying the foundation for the development of model-driven Huanglongbing management strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Three-state nematicity in the triangular lattice antiferromagnet Fe 1/3 NbS 2

Nematic order is the breaking of rotational symmetry in the presence of translational invariance. While originally defined in the context of liquid crystals, the concept of nematic order has arisen in crystalline matter with discrete rotational symmetry, most prominently in the tetragonal Fe-based superconductors where the parent state is four-fold symmetric. In this case the nematic director takes on only two directions, and the order parameter in such 'Ising-nematic' systems is a simple scalar. In this study, using a spatially resolved optical polarimetry technique, we show that a qualitatively distinct nematic state arises in the triangular lattice antiferromagnet Fe 1/3 NbS 2 . The crucial difference is that the nematic order on the triangular lattice is a Z 3 or three-state Potts-nematic order parameter. As a consequence, the anisotropy axes of response functions such as the resistivity tensor can be continuously reoriented by external perturbations. This discovery lays the groundwork for devices that exploit analogies with nematic liquid crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Evidence for a monolayer excitonic insulator

The interplay between topology and correlations can generate a variety of quantum phases, many of which remain to be explored. Recent advances have identified monolayer WTe 2 as a promising material for doing so in a highly tunable fashion. The ground state of this two-dimensional crystal can be electrostatically tuned from a quantum spin Hall insulator to a superconductor. However, much remains unknown about the gap-opening mechanism of the insulating state. In this work, we report evidence that the quantum spin Hall insulator is also an excitonic insulator, arising from the spontaneous formation of electron–hole bound states, namely excitons. We reveal the presence of an intrinsic insulating state at the charge neutrality point in clean samples and confirm the correlated nature of this charge-neutral insulator by tunnelling spectroscopy. We provide evidence against alternative scenarios of a band insulator or a localized insulator and support the existence of an excitonic insulator phase in the clean limit. These observations lay the foundation for understanding a new class of correlated insulators with nontrivial topology and identify monolayer WTe 2 as a promising candidate for exploring quantum phases of ground-state excitons.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Graph states of atomic ensembles engineered by photon-mediated entanglement

Abstract Graph states are a broad family of entangled quantum states, each defined by a graph composed of edges representing the correlations between subsystems. Such states constitute versatile resources for quantum computation and quantum-enhanced measurement. Their generation and engineering require a high level of control over entanglement. Here we report on the generation of continuous-variable graph states of atomic spin ensembles, which form the nodes of the graph. We program the entanglement structure encoded in the graph edges by combining global photon-mediated interactions in an optical cavity with local spin rotations. By tuning the entanglement between two subsystems, we either localize correlations within each subsystem or enable Einstein–Podolsky–Rosen steering—a strong form of entanglement that enables the extraction of precise information from one subsystem through measurements on the other. We further engineer a four-mode square graph state, highlighting the flexibility of our approach. Our method is scalable to larger and more complex graphs, laying groundwork for measurement-based quantum computation and advanced protocols in quantum metrology.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Redefining fundamental concepts of transcription initiation in bacteria

Despite enormous progress in understanding the fundamentals of bacterial gene regulation, our knowledge remains limited when compared with the number of bacterial genomes and regulatory systems to be discovered. Derived from a small number of initial studies, classic definitions for concepts of gene regulation have evolved as the number of characterized promoters has increased. Together with discoveries made using new technologies, this knowledge has led to revised generalizations and principles. In this Expert Recommendation, we suggest precise, updated definitions that support a logical, consistent conceptual framework of bacterial gene regulation, focusing on transcription initiation. The resulting concepts can be formalized by ontologies for computational modelling, laying the foundation for improved bioinformatics tools, knowledge-based resources and scientific communication. Furthermore, this work will help researchers construct better predictive models, with different formalisms, that will be useful in engineering, synthetic biology, microbiology and genetics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Imaging two-dimensional generalized Wigner crystals

The Wigner crystal has fascinated condensed matter physicists for nearly 90 years. Signatures of two-dimensional (2D) Wigner crystals were first observed in 2D electron gases under high magnetic field, and recently reported in transition metal dichalcogenide moiré superlattices. Direct observation of the 2D Wigner crystal lattice in real space, however, has remained an outstanding challenge. Conventional scanning tunnelling microscopy (STM) has sufficient spatial resolution but induces perturbations that can potentially alter this fragile state. Here we demonstrate real-space imaging of 2D Wigner crystals in WSe 2 /WS 2 moiré heterostructures using a specially designed non-invasive STM spectroscopy technique. This employs a graphene sensing layer held close to the WSe 2 /WS 2 moiré superlattice. Local STM tunnel current into the graphene layer is modulated by the underlying Wigner crystal electron lattice in the WSe 2 /WS 2 heterostructure. Different Wigner crystal lattice configurations at fractional electron fillings of n = 1/3, 1/2 and 2/3, where n is the electron number per site, are directly visualized. The n = 1/3 and n = 2/3 Wigner crystals exhibit triangular and honeycomb lattices, respectively, to minimize nearest-neighbour occupations. The n = 1/2 state spontaneously breaks the original C3 symmetry and forms a stripe phase. Here our study lays a solid foundation for understanding Wigner crystal states in WSe 2 /WS 2 moiré heterostructures and provides an approach that is generally applicable for imaging novel correlated electron lattices in other systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

High-fidelity parallel entangling gates on a neutral-atom quantum computer

The ability to perform entangling quantum operations with low error rates in a scalable fashion is a central element of useful quantum information processing. Neutral-atom arrays have recently emerged as a promising quantum computing platform, featuring coherent control over hundreds of qubits and any-to-any gate connectivity in a flexible, dynamically reconfigurable architecture. The main outstanding challenge has been to reduce errors in entangling operations mediated through Rydberg interactions. Here we report the realization of two-qubit entangling gates with 99.5% fidelity on up to 60 atoms in parallel, surpassing the surface-code threshold for error correction. Our method uses fast, single-pulse gates based on optimal control, atomic dark states to reduce scattering and improvements to Rydberg excitation and atom cooling. We benchmark fidelity using several methods based on repeated gate applications, characterize the physical error sources and outline future improvements. Finally, we generalize our method to design entangling gates involving a higher number of qubits, which we demonstrate by realizing low-error three-qubit gates. By enabling high-fidelity operation in a scalable, highly connected system, these advances lay the groundwork for large-scale implementation of quantum algorithms, error-corrected circuits and digital simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Terrestrial photosynthesis inferred from plant carbonyl sulfide uptake

Terrestrial photosynthesis, or gross primary production (GPP), is the largest carbon flux in the biosphere, but its global magnitude and spatiotemporal dynamics remain uncertain. The global annual mean GPP is historically thought to be around 120 PgC yr −1 , which is about 30–50 PgC yr −1 lower than GPP inferred from the oxygen-18 ( 18 O) isotope and soil respiration. This disparity is a source of uncertainty in predicting climate–carbon cycle feedbacks. Here, in this study, we infer GPP from carbonyl sulfide, an innovative tracer for CO 2 diffusion from ambient air to leaf chloroplasts through stomata and mesophyll layers. We demonstrate that explicitly representing mesophyll diffusion is important for accurately quantifying the spatiotemporal dynamics of carbonyl sulfide uptake by plants. From the estimate of carbonyl sulfide uptake by plants, we infer a global contemporary GPP of 157 (±8.5) PgC yr −1 , which is consistent with estimates from 18 O (150–175 PgC yr −1 ) and soil respiration ($149^{+29}_{-23}$) PgC yr −1 ), but with an improved confidence level. Our global GPP is higher than satellite optical observation-driven estimates (120–140 PgC yr –1 ) that are used for Earth system model benchmarking. This difference predominantly occurs in the pan-tropical rainforests and is corroborated by ground measurements, suggesting a more productive tropics than satellite-based GPP products indicated. As GPP is a primary determinant of terrestrial carbon sinks and may shape climate trajectories, our findings lay a physiological foundation on which the understanding and prediction of carbon–climate feedbacks can be advanced.

Lai, Jiameng↗
DOE OSTI2025

A map of the rubisco biochemical landscape

Rubisco is the primary CO 2 -fixing enzyme of the biosphere, yet it has slow kinetics. The roles of evolution and chemical mechanism in constraining its biochemical function remain debated. Engineering efforts aimed at adjusting the biochemical parameters of rubisco have largely failed, although recent results indicate that the functional potential of rubisco has a wider scope than previously known. Here we developed a massively parallel assay, using an engineered Escherichia coli in which enzyme activity is coupled to growth, to systematically map the sequence–function landscape of rubisco. Composite assay of more than 99% of single-amino acid mutants versus CO 2 concentration enabled inference of enzyme velocity and apparent CO 2 affinity parameters for thousands of substitutions. This approach identified many highly conserved positions that tolerate mutation and rare mutations that improve CO 2 affinity. These data indicate that non-trivial biochemical changes are readily accessible and that the functional distance between rubiscos from diverse organisms can be traversed, laying the groundwork for further enzyme engineering efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A database of synthetic inelastic neutron scattering spectra from molecules and crystals

Abstract Inelastic neutron scattering (INS) is a powerful tool to study the vibrational dynamics in a material. The analysis and interpretation of the INS spectra, however, are often nontrivial. Unlike diffraction, for which one can quickly calculate the scattering pattern from the structure, the calculation of INS spectra from the structure involves multiple steps requiring significant experience and computational resources. To overcome this barrier, a database of INS spectra consisting of commonly seen materials will be a valuable reference, and it will also lay the foundation of advanced data-driven analysis and interpretation of INS spectra. Here we report such a database compiled for over 20,000 organic molecules and over 10,000 inorganic crystals. The INS spectra are obtained from a streamlined workflow, and the synthetic INS spectra are also verified by available experimental data. The database is expected to greatly facilitate INS data analysis, and it can also enable the utilization of advanced analytics such as data mining and machine learning. Notice: This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Material Fracturing and Failure Simulation Datasets

Fracturing is a fundamental physics phenomena with broad relevance across multiple domains, ranging from infrastructure integrity, aerospace durability, reservoir production, and seismic events. We present a diverse dataset of simulated fracture evolution and material failure generated from two numerical solvers: the phase-field method and the combined finite-discrete element method (FDEM). These solvers differ in formulation, physical fidelity, and computational efficiency. The dataset includes five materials: PBX, anisotropic shale, tungsten, aluminum, and steel. For each, phase-field simulations span 400,000 cases: 200,000 under uniaxial tension and 200,000 under biaxial tension. The computationally expensive FDEM simulations include 90,000 split evenly among PBX, shale, and tungsten under uniaxial loading. All simulations begin with randomized initial fracture patterns. Each entry includes temporal data capturing fracture propagation dynamics. This comprehensive dataset is designed to support the development of foundational or surrogate machine learning approaches for predicting material failure. While no such models are introduced here, the dataset lays a robust foundation for advancing future research and innovation in these areas.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Thermal perturbation of NMR properties in small polar and non-polar molecules

Water is an important constituent in an abundant number of chemical systems; however, its presence complicates the analysis of in situ 1 H MAS NMR investigations due to water’s ease of solidification and vaporization, the large changes in mobility, affinity for hydrogen bonding interactions, etc., that are reflected by dramatic changes in temperature-dependent chemical shielding. To understand the signatures of water and other small molecules in complex environments, in particular how water interacts with the other molecules, in this work the thermally-perturbed NMR properties of water are investigated in detail by in situ MAS NMR. Our results substantially extend the previously published temperature-dependent 1 H and 17 O chemical shifts, linewidths, and spin-lattice relaxation times over a much wider range of temperatures and with significantly enhanced thermal resolution. The following major results are obtained: Hydrogen bonding is clearly shown to weaken at elevated temperatures in both 1 H and 17 O spectra, showing an increase in chemical shielding. At low temperatures, tetrahedral domains of H-bonding networks are evidenced and the observation of solid ice is made under in situ MAS conditions. The 1 H chemical shift properties in other small polar and non-polar molecules have also been described over a range of temperatures, showing the dramatic effect hydrogen bonding perturbation. Gas phase species are described where chemical exchange between gas and liquid phases plays an important role on the observed NMR shifts. The results disclosed herein lay the foundation for a clearer interpretation of complex systems during the increasingly popular in situ NMR characterization at elevated temperatures and pressures for studying chemical systems containing water molecules.

17O NMR↗
DOE OSTI2020

Metabolic Profiling of Volatile Organic Compounds (VOCs) Emitted by the Pathogens Francisella tularensis and Bacillus anthracis in Liquid Culture

We conducted comprehensive (untargeted) metabolic profiling of volatile organic compounds (VOCs) emitted in culture by bacterial taxa Francisella tularensis (F. tularensis) subspecies novicida and Bacillus anthracis (B. anthracis) Sterne, surrogates for potential bacterial bioterrorism agents, as well as selective measurements of VOCs from their fully virulent counterparts, F. tularensis subspecies tularensis strain SCHU S4 and B. anthracis Ames. F. tularensis and B. anthracis were grown in liquid broth for time periods that covered logarithmic growth, stationary, and decline phases. VOCs emitted over the course of the growth phases were collected from the headspace above the cultures using solid phase microextraction (SPME) and were analyzed using gas chromatography-mass spectrometry (GC-MS). We developed criteria for distinguishing VOCs originating from bacteria versus background VOCs (originating from growth media only controls or sampling devices). Analyses of collected VOCs revealed methyl ketones, alcohols, esters, carboxylic acids, and nitrogen- and sulfur-containing compounds that were present in the bacterial cultures and absent (or present at only low abundance) in control samples indicating that these compounds originated from the bacteria. Distinct VOC profiles where observed for F. tularensis when compared with B. anthracis while the observed profiles of each of the two F. tularensis and B. anthracis strains exhibited some similarities. Furthermore, the relative abundance of VOCs was influenced by bacterial growth phase. These data illustrate the potential for VOC profiles to distinguish pathogens at the genus and species-level and to discriminate bacterial growth phases. The determination of VOC profiles lays the groundwork for non-invasive probes of bacterial metabolism and offers prospects for detection of microbe-specific VOC biomarkers from two potential biowarfare agents.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A novel hardmask-to-substrate pattern transfer method for creating 3D, multi-level, hierarchical, high aspect-ratio structures for applications in microfluidics and cooling technologies

Abstract This letter solves a major hurdle that mars photolithography-based fabrication of micro-mesoscale structures in silicon. Conventional photolithography is usually performed on smooth, flat wafer surfaces to lay a 2D design and subsequently etch it to create single-level features. It is, however, unable to process non-flat surfaces or already etched wafers and create more than one level in the structure. In this study, we have described a novel cleanroom-based process flow that allows for easy creation of such multi-level, hierarchical 3D structures in a substrate. This is achieved by introducing an ultra-thin sacrificial silicon dioxide hardmask layer on the substrate which is first 3D patterned via multiple rounds of lithography. This 3D pattern is then scaled vertically by a factor of 200–300 and transferred to the substrate underneath via a single shot deep etching step. The proposed method is also easily characterizable—using features of different topographies and dimensions, the etch rates and selectivities were quantified; this characterization information was later used while fabricating specific target structures. Furthermore, this study comprehensively compares the novel pattern transfer technique to already existing methods of creating multi-level structures, like grayscale lithography and chip stacking. The proposed process was found to be cheaper, faster, and easier to standardize compared to other methods—this made the overall process more reliable and repeatable. We hope it will encourage more research into hybrid structures that hold the key to dramatic performance improvements in several micro-mesoscale devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Deep compressed seismic learning for fast location and moment tensor inferences with natural and induced seismicity

Fast detection and characterization of seismic sources is crucial for decision-making and warning systems that monitor natural and induced seismicity. However, besides the laying out of ever denser monitoring networks of seismic instruments, the incorporation of new sensor technologies such as Distributed Acoustic Sensing (DAS) further challenges our processing capabilities to deliver short turnaround answers from seismic monitoring. In response, this work describes a methodology for the learning of the seismological parameters: location and moment tensor from compressed seismic records. In this method, data dimensionality is reduced by applying a general encoding protocol derived from the principles of compressive sensing. The data in compressed form is then fed directly to a convolutional neural network that outputs fast predictions of the seismic source parameters. Thus, the proposed methodology can not only expedite data transmission from the field to the processing center, but also remove the decompression overhead that would be required for the application of traditional processing methods. An autoencoder is also explored as an equivalent alternative to perform the same job. We observe that the CS-based compression requires only a fraction of the computing power, time, data and expertise required to design and train an autoencoder to perform the same task. Implementation of the CS-method with a continuous flow of data together with generalization of the principles to other applications such as classification are also discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Insights into coordination and ligand trends of lanthanide complexes from the Cambridge Structural Database

Abstract Understanding lanthanide coordination chemistry can help develop new ligands for more efficient separation of lanthanides for critical materials needs. The Cambridge Structural Database (CSD) contains tens of thousands of single crystal structures of lanthanide complexes that can serve as a training ground for both fundamental chemical insights and future machine learning and generative artificial intelligence models. This work aims to understand the currently available structures of lanthanide complexes in CSD by analyzing the coordination shell, donor types, and ligand types, from the perspective of rare-earth element (REE) separations. We obtain four sets of lanthanide complexes from CSD: Subset 1, all Ln-containing complexes (49472 structures); Subset 2, mononuclear Ln complexes (27858 structures); Subset 3, mononuclear Ln complexes without cyclopentadienyl ligands (Cp) (26156 structures); Subset 4, Ln complexes with at least one 1,10-phenanthroline (phen) or its derivative as a coordinating ligand (2226 structures). The subsequent analysis of lanthanide complexes in these subsets examines the trends in coordination numbers and first shell distances as well as identifies and characterizes the ligands and donor groups. In addition, examples of Ln-complexes with commercially available complexants and phen-based ligands are interrogated in detail. This systematic investigation lays the groundwork for future data-driven ligand designs for REE separations based on the structural insights into the lanthanide coordination chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗