Search NASA⌕ Search

SEARCH · Search NASA

Results for “EMPOWERED”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Semiconductor to Topological Insulator Transition Induced by Stress Propagation in Metal Dichalcogenides Core-Shell Lateral Heterostructures

Polymorphic phase transition is an important route for engineering the properties of two-dimensional materials. Heterostructure construction, on the other hand, not only allows the integration of different functionalities for device applications, but also enables the exploration of new physics arising from proximity coupling. Yet, implementing a design that incorporates the advantages of both remains underexplored. Here in this paper, based on comprehensive experimental and theoretical studies of WSe 2 /SnSe 2 core-shell lateral heterostructure, we demonstrate an unexpected H to T' phase transition in transition metal dichalcogenides (TMDs), correlating to a change of materials properties from semiconductor to topological insulator (TI), and propose a novel shell-to-core stress propagation mechanism. This finding offers new insights into TMD phase transition empowered by the rational design of heterostructures. Owing to the superconducting properties of SnSe 2 at low temperatures, the unique TI/superconductor core-shell template is expected to add more arsenals to the ongoing search of Majorana fermions in condensed matter systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Expeditious synthesis of covalent organic frameworks: a review

Covalent organic frameworks (COFs), a burgeoning class of crystalline porous materials constructed by covalently connecting organic building blocks, have garnered tremendous attention. The predominant solvothermal synthesis of COFs usually requires high temperature and long reaction times (three days or longer), which creates substantial obstacles for their accelerated discovery and exploration in practical applications. Hence, the expeditious synthesis of COFs without compromising their inherent properties is exceedingly appealing from the viewpoint of cost, time, and energy footprint. To overcome the sluggishness of the synthesis, considerable efforts have been invested in the rapid synthesis of high-quality COFs through innovations in energy source, catalyst, solvent, monomer, nucleation, and workup activation, leading to a drastic reduction of reaction time from multiple days to a few hours, and even to seconds in some cases. In this contribution, we provide a comprehensive overview of the advances in expediting the synthesis science of COFs. Though a nascent effort, six prevalent strategies have been identified for the rapid synthesis of COFs, which have led to intriguing applications in a diverse range of areas including gas adsorption, separation, heterogeneous catalysis, environmental remediation, and photodynamic therapy. We also outline the major challenges and perspectives on the future directions empowered by expeditious COF synthesis.

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

Intelligence-assisted predesign for the sustainable recycling of lithium-ion batteries and beyond

The unprecedented consumption of lithium-ion batteries (LIBs) is occurring to meet the needs of modern transportation electrification. Recycling-friendly designs intrinsically facilitate the long-term sustainable utilization of natural resources, reducing the detrimental impacts of spent LIBs on the environment, and improving the economic viability of recycling. For this, we propose the incorporation of an intelligence-assisted predesign strategy into the battery-management system and battery chemistry, including ameliorating the traceability of battery structure and operation status, promoting cost-effective material sorting and separation, and adopting sustainable battery materials. The purposeful predesign of intelligent “Reuse–Refurbish–Recover” (3R) LIBs could be realized in an economically and environmentally sustainable (EES) manner. We report the intelligence-assisted predesign strategy will promote multi-disciplinary cooperation in a systematic and synergetic way; in addition, it will empower governments to establish and implement a series of regulations and standards for addressing the environmental pollution issues from spent batteries, thus avoiding the ever-increasing consumption of natural resources.

25 ENERGY STORAGE↗
DOE OSTI2022

Quantum machine learning for chemistry and physics

Machine learning (ML) has emerged as a formidable force for identifying hidden but pertinent patterns within a given data set with the objective of subsequent generation of automated predictive behavior. In recent years, it is safe to conclude that ML and its close cousin, deep learning (DL), have ushered in unprecedented developments in all areas of physical sciences, especially chemistry. Not only classical variants of ML, even those trainable on near-term quantum hardwares have been developed with promising outcomes. Such algorithms have revolutionized materials design and performance of photovoltaics, electronic structure calculations of ground and excited states of correlated matter, computation of force-fields and potential energy surfaces informing chemical reaction dynamics, reactivity inspired rational strategies of drug designing and even classification of phases of matter with accurate identification of emergent criticality. In this review we shall explicate a subset of such topics and delineate the contributions made by both classical and quantum computing enhanced machine learning algorithms over the past few years. We shall not only present a brief overview of the well-known techniques but also highlight their learning strategies using statistical physical insight. The objective of the review is not only to foster exposition of the aforesaid techniques but also to empower and promote cross-pollination among future research in all areas of chemistry which can benefit from ML and in turn can potentially accelerate the growth of such algorithms.

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

DNA-caged nanoparticles via electrostatic self-assembly

DNA-modified nanoparticles enable DNA sensing and therapeutics in nanomedicine and are also crucial for nanoparticle self-assembly with DNA-based materials. However, methods to conjugate DNA to nanoparticle surfaces are limited, inefficient, and lack control. Inspired by DNA tile nanotechnology, we demonstrate a new approach to nanoparticle modification based on electrostatic attraction between negatively charged DNA tiles and positively charged nanoparticles. This approach does not disrupt nanoparticle surfaces and leverages the programmability of DNA nanotechnology to control DNA presentation. We demonstrated this approach using a variety of nanoparticles, including polymeric micelles, polystyrene beads, gold nanoparticles, and superparamagnetic iron oxide nanoparticles with sizes ranging from 5–20 nm in diameter. DNA cage formation was confirmed through transmission electron microscopy (TEM), neutralization of zeta potential, and a series of fluorescence experiments. DNA cages present “handle” sequences that can be used for reversible target attachment or self-assembly. Handle functionality was verified in solution, at the solid–liquid interface, and inside fixed cells, corresponding to applications in biosensing, DNA microarrays, and erasable immunocytochemistry. Finally, these experiments demonstrate the versatility of the electrostatic DNA caging approach and provide a new pathway to nanoparticle modification with DNA that will empower further applications of these materials in medicine and materials science.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Counterpart identification and classification for eRASS1 and characterisation of the active galactic nuclei content

Context. Accurately accounting for the Active Galactic Nucleus (AGN) phase in galaxy evolution requires a large, clean AGN sample. This is now possible with SRG/eROSITA, which completed its first all-sky X-ray survey (eRASS1) on June 12, 2020. The public Data Release 1 (DR1, Jan 31, 2024) includes 930,203 sources from the western Galactic hemisphere. Aims. The data enable the selection of a large AGN sample and the discovery of rare sources. However, scientific return depends on accurate characterisation of the X-ray emitters, requiring high-quality multi-wavelength data. This paper presents the identification and classification of optical and infrared counterparts to eRASS1 sources. Methods. Counterparts to eRASS1 X-ray point sources were identified using Gaia DR3, CatWISE2020, and Legacy Survey DR10 (LS10) with the Bayesian NWAY algorithm and trained priors. Sources were classified as Galactic or extragalactic via a machine-learning model combining optical/IR and X-ray properties, trained on a reference sample. For extragalactic LS10 sources, photometric redshifts were computed using CIRCLEZ. Results. Within the LS10 footprint, all 656,614 eROSITA/DR1 sources have at least one possible optical counterpart; ∼570 000 are extragalactic and likely AGN. Half are new detections compared to AllWISE, Gaia, and Quaia AGN catalogues. Gaia and CatWISE2020 counterparts are less reliable, due to the survey’s shallowness and the limited amount of features available to assess the probability of being an X-ray emitter. In the Galactic plane, where the overdensity of stellar sources also increases the chance of associations, using conservative reliability cuts, we identified approximately 18 000 Gaia and 55 000 CatWISE2020 extragalactic sources. Conclusions. We have released three high-quality counterpart catalogues – plus the training and validation sets – as a benchmark for the field. These datasets have many applications, but in particular, they empower researchers to build AGN samples tailored for completeness and purity, accelerating the hunt for the Universe’s most energetic engines.

X-rays: general↗
DOE OSTI2022

Sensitivity Study of Type-I X-ray Bursts to Nuclear Reaction Rates

Type-I X-ray bursts are frequently occurring thermonuclear runaways on the surface of an accreting neutron star. The different nuclear reactions that empower the cataclysmic event play a key role in accurately comparing theoretical models and observations. We investigate the effect of the uncertainties in the nuclear reactions using a ONEZONE model for a set of different compositions and accretion rates that are within the range of the standard observed burst sources. A combination of a full-reaction network and a semi-analytic model is used to obtain the conditions at the time of X-ray burst ignition via simulating the settling process of the accreted material. We then evaluate the sensitivity of the X-ray burst model by varying the proton and alpha-induced reaction rates in JINA REACLIBV2.2 within representative nuclear physics uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

M-STAR: Magnetism second target advanced reflectometer at the Spallation Neutron Source

M-STAR is a next generation polarized neutron reflectometer with advanced capabilities. A new focusing guide concept is optimized for samples with dimensions down to a millimeter range. A proposed hybrid pulse-skipping chopper will enable experiments at constant geometry at one incident angle in a broad range of wavevector transfer Q up to 0.3 A –1 for specular, off-specular, and GISANS measurements. M-STAR will empower nanoscience and spintronics studies routinely on small samples (~2 × 2 mm 2 ) and of atomic-scale thickness using versatile experimental conditions of magnetic and/or electric fields, light, and temperature applied in situ to novel complex device-like nanosystems with multiple buried interfaces. M-STAR will enable improved grazing incidence diffraction measurements, as a surface-sensitive depth-resolved probe of, e.g., the out-of-plane component of atomic magnetic moments in ferromagnetic, antiferromagnetic, and more complex structures as well as in-plane atomic-scale structures inaccessible with contemporary diffractometry and reflectometry. New horizons will be opened by the development of an option to probe near-surface dynamics with inelastic grazing incidence scattering in the time-of-flight mode. These novel options in combination with ideally matched parameters of the second target station will place M-STAR in the world’s leading position for high resolution polarized reflectometry.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Designing workflows for materials characterization

Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis of new material is typically followed by a set of characterization steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, the sequence of synthesis and characterization methods and their interpretation, or research workflow, has traditionally been driven by human intuition and is highly domain specific. Here, we explore concepts of scientific workflows that emerge at the interface between theory, characterization, and imaging. In this study, we discuss the criteria by which these workflows can be constructed for special cases of multiresolution structural imaging and functional characterization, as a part of more general material synthesis workflows. Some considerations for theory–experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupts the classical progression from ideation, orchestration, and execution stages of workflow development. To accelerate this transition, we propose the framework for workflow design, including universal hyperlanguages describing laboratory operation, ontological domain matching, reward functions and their integration between domains, and policy development for workflow optimization. These tools will enable knowledge-based workflow optimization; enable lateral instrumental networks, sequential and parallel orchestration of characterization between dissimilar facilities; and empower distributed research.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-resolution multicontrast tomography with an X-ray microarray anode–structured target source

Multicontrast X-ray imaging with high resolution and sensitivity using Talbot–Lau interferometry (TLI) offers unique imaging capabilities that are important to a wide range of applications, including the study of morphological features with different physical properties in biological specimens. The conventional X-ray TLI approach relies on an absorption grating to create an array of micrometer-sized X-ray sources, posing numerous limitations, including technical challenges associated with grating fabrication for high-energy operations. We overcome these limitations by developing a TLI system with a microarray anode–structured target (MAAST) source. The MAAST features an array of precisely controlled microstructured metal inserts embedded in a diamond substrate. Using this TLI system, tomography of a Drum fish tooth with high resolution and tri-contrast (absorption, phase, and scattering) reveals useful complementary structural information that is inaccessible otherwise. The results highlight the exceptional capability of high-resolution multicontrast X-ray tomography empowered by the MAAST-based TLI method in biomedical applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Continuous measurements of volatile gases as detection of algae crop health

Wide adoption of algae cultivation to produce environmentally sustainable biofuels and fine chemicals is currently hampered by large losses (10 to 30%) incurred by grazer infections. We show the usage of real-time chemical ionization mass spectrometry to rapidly identify gaseous indicators of grazer infections in cyanobacteria cultures. Grazing was detected significantly faster (up to 3 d) using real-time mass spectrometry than the current methods of microscopy and qPCR. By employing this technology, cultivators may be empowered to treat grazer infestations sooner, thereby protecting the crop and enhancing profitability.

09 BIOMASS FUELS↗
DOE OSTI2022

Observation of Weyl exceptional rings in thermal diffusion

A non-Hermitian Weyl equation indispensably requires a three-dimensional (3D) real/synthetic space, and it is thereby perceived that a Weyl exceptional ring (WER) will not be present in thermal diffusion given its purely dissipative nature. Here, we report a recipe for establishing a 3D parameter space to imitate thermal spinor field. Two orthogonal pairs of spatiotemporally modulated advections are employed to serve as two synthetic parameter dimensions, in addition to the inherent dimension corresponding to heat exchanges. We first predict the existence of WER in our hybrid conduction–advection system and experimentally observe the WER thermal signatures verifying our theoretical prediction. When coupling two WERs of opposite topological charges, the system further exhibits surface-like and bulk topological states, manifested as stationary and continuously changing thermal processes, respectively, with good robustness. Our findings reveal the long-ignored topological nature in thermal diffusion and may empower distinct paradigms for general diffusion and dissipation controls.

42 ENGINEERING↗
DOE OSTI2025

Reuniting crystallography with real space: Ab initio structure elucidation with 4D-STEM

Structure elucidation via single-crystal methods has historically lacked experimental access to real-space information, instead relying exclusively on diffraction-space measurements of Bragg reflections. Here we exploit the dual-space imaging power of 4D scanning transmission electron microscopy to meaningfully integrate real-space information into the crystallographic workflow. We show that virtual apertures assembled by segmentation of high-angle annular dark-field images enable i) pixel-by-pixel separation of coherent Bragg signal from clusters of closely spaced nanocrystals and ii) selective extraction of integrated intensities from thinner subregions of individual specimens, facilitating retroactive tuning of multiple scattering artifacts. This strategy empowers us to simply pick and choose whichever nanoscale regions of interest generate the highest-quality diffraction patterns, allowing us to solve several independent structures of the metal-organic framework UiO-66 from specimens whose agglomerated morphology proved intractable for conventional microcrystal electron diffraction. Our method is compatible with both rotational and serial approaches to data processing, ultimately divulging the first scanning nanobeam electron diffraction structures determined by direct methods at subangstrom resolution.

Saha, Ambarneil↗
DOE OSTI2023

Reducing microgrid availability to reduce costs for coastal Puerto Rican communities

Renewable microgrids are sustainable, resilient solutions to mitigate and adapt to climate change. Making electric loads nearly 100% available (i.e., power remains on) during outages increases cost. Near 100% availability is required when human life or high-cost assets are involved, but availability can be reduced for less consequential loads leading to lower costs. This study analyses costs for photo-voltaic and lithium-ion battery microgrids with availability ranging from 0–99%. We develop a methodology to analyse three Puerto Rican coastal communities. Here, we consider power outage effects for hurricanes, earthquakes, and everyday outages. The results show cost versus availability from 0–99%. There is 27–31% cost reduction at 80% availability in comparison to 99% availability. A regression model of microgrid availability versus three ratios: 1) the annual generation to demand ratio, 2) storage to interruption energy ratio, and 3) peak storage to load ratio produced a coefficient of determination of 0.99949 with 70% of the data used for training and 30% for testing. The results can therefore be extended to other coastal Puerto Rican communities of varying sizes that have ratios within the ranges analysed in this study. This can empower decision makers to rapidly analyse designs that have availabilities well below 100%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Tracking atomic structure evolution during directed electron beam induced Si-atom motion in graphene via deep machine learning

Using electron beam manipulation, we enable deterministic motion of individual Si atoms in graphene along predefined trajectories. Structural evolution during the dopant motion was explored, providing information on changes of the Si atom neighborhood during atomic motion and providing statistical information of possible defect configurations. The combination of a Gaussian mixture model and principal component analysis applied to the deep learning-processed experimental data allowed disentangling of the atomic distortions for two different graphene sublattices. This approach demonstrates the potential of e-beam manipulation to create defect libraries of multiple realizations of the same defect and explore the potential of symmetry breaking physics. The rapid image analytics enabled via a deep learning network further empowers instrumentation for e-beam controlled atom-by-atom fabrication. Here, the analysis described in the paper can be reproduced via an interactive Jupyter notebook at https://git.io/JJ3Bx.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

On-demand fabrication of piezoelectric sensors for in-space structural health monitoring

Abstract Inflatable structures, promising for future deep space exploration missions, are vulnerable to damage from micrometeoroid and orbital debris impacts. Polyvinylidene fluoride-trifluoroethylene (PVDF-trFE) is a flexible, biocompatible, and chemical-resistant material capable of detecting impact forces due to its piezoelectric properties. This study used a state-of-the-art material extrusion system that has been validated for in-space manufacturing, to facilitate fast-prototyping of consistent and uniform PVDF-trFE films. By systematically investigating ink synthesis, printer settings, and post-processing conditions, this research established a comprehensive understanding of the process-structure-property relationship of printed PVDF-trFE. Consequently, this study consistently achieved the printing of PVDF-trFE films with a thickness of around 40 µ m, accompanied by an impressive piezoelectric coefficient of up to 25 pC N −1 . Additionally, an all-printed dynamic force sensor, featuring a sensitivity of 1.18 V N −1 , was produced by mix printing commercial electrically-conductive silver inks with the customized PVDF-trFE inks. This pioneering on-demand fabrication technique for PVDF-trFE films empowers future astronauts to design and manufacture piezoelectric sensors while in space, thereby significantly enhancing the affordability and sustainability of deep space exploration missions.

Instruments & Instrumentation↗