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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Learning from Crowds by Modeling Common Confusions

Crowdsourcing provides a practical way to obtain large amounts of labeled data at a low cost. However, the annotation quality of annotators varies considerably, which imposes new challenges in learning a high-quality model from the crowdsourced annotations. In this work, we provide a new perspective to decompose annotation noise into common noise and individual noise and differentiate the source of confusion based on instance difficulty and annotator expertise on a per-instance-annotator basis. We realize this new crowdsourcing model by an end-to-end learning solution with two types of noise adaptation layers: one is shared across annotators to capture their commonly shared confusions, and the other one is pertaining to each annotator to realize individual confusion. To recognize the source of noise in each annotation, we use an auxiliary network to choose from the two noise adaptation layers with respect to both instances and annotators. Extensive experiments on both synthesized and real-world benchmarks demonstrate the effectiveness of our proposed common noise adaptation solution.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Unsupervised Power System Event Detection and Classification Using Unlabeled PMU Data

This paper proposes a novel data-driven power system event detection and classification method based on 5TB of actual PMU measurements collected from the US western interconnect. Firstly, a set of comprehensive power quality rules are proposed to pre-filter the raw data and extract the regions of interest (ROI). Six distinct event categories are defined and corresponding patterns are chosen as references. Meanwhile, detailed characteristics of patterns are summarized to enhance our understanding of the actual events. Then, the time-independent feature vectors are generated by extracting the statistical, temporal, and spectral features from the raw time-series data. Furthermore, an ensemble model is proposed to cluster the events by combining multiple K-means clustering models using a voting strategy. Besides, both system-level and PMU-level clustering models are developed. The accuracy and robustness of the event detection method are further improved through interactive evaluation of the two-level clustering results. This paper summarizes the actual characteristics of each event category and provides a reliable basis for accurate label generation. The experiments demonstrate the effectiveness of the proposed event detection and classification method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Unsupervised Power System Event Detection and Classification Using Unlabeled PMU Data

This paper proposes a novel data-driven power system event detection and classification method based on 5TB of actual PMU measurements collected from the US western interconnect. Firstly, a set of comprehensive power quality rules are proposed to pre-filter the raw data and extract the regions of interest (ROI). Six distinct event categories are defined and corresponding patterns are chosen as references. Meanwhile, detailed characteristics of patterns are summarized to enhance our understanding of the actual events. Then, the time-independent feature vectors are generated by extracting the statistical, temporal, and spectral features from the raw time-series data. Furthermore, an ensemble model is proposed to cluster the events by combining multiple K-means clustering models using a voting strategy. Besides, both system-level and PMU-level clustering models are developed. The accuracy and robustness of the event detection method are further improved through interactive evaluation of the two-level clustering results. This paper summarizes the actual characteristics of each event category and provides a reliable basis for accurate label generation. The experiments demonstrate the effectiveness of the proposed event detection and classification method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Assessment of Demographic, Genetic, and Imaging Variables Associated With Brain Resilience and Cognitive Resilience to Pathological Tau in Patients With Alzheimer Disease

Importance: Better understanding is needed of the degree to which individuals tolerate Alzheimer disease (AD)-like pathological tau with respect to brain structure (brain resilience) and cognition (cognitive resilience). Objective: To examine the demographic (age, sex, and educational level), genetic (APOE-ε4 status), and neuroimaging (white matter hyperintensities and cortical thickness) factors associated with interindividual differences in brain and cognitive resilience to tau positron emission tomography (PET) load and to changes in global cognition over time. Design, setting, an participants: In this cross-sectional, longitudinal study, tau PET was performed from June 1, 2014, to November 30, 2017, and global cognition monitored for a mean [SD] interval of 2.0 [1.8] years at 3 dementia centers in South Korea, Sweden, and the United States. The study included amyloid-β-positive participants with mild cognitive impairment or AD dementia. Data analysis was performed from October 26, 2018, to December 11, 2019. Exposures: Standard dementia screening, cognitive testing, brain magnetic resonance imaging, amyloid-β PET and cerebrospinal fluid analysis, and flortaucipir (tau) labeled with fluor-18 (18F) PET. Main outcomes and measures: Separate linear regression models were performed between whole cortex [18F]flortaucipir uptake and cortical thickness, and standardized residuals were used to obtain a measure of brain resilience. The same procedure was performed for whole cortex [18F]flortaucipir uptake vs Mini-Mental State Examination (MMSE) as a measure of cognitive resilience. Bivariate and multivariable linear regression models were conducted with age, sex, educational level, APOE-ε4 status, white matter hyperintensity volumes, and cortical thickness as independent variables and brain and cognitive resilience measures as dependent variables. Linear mixed models were performed to examine whether changes in MMSE scores over time differed as a function of a combined brain and cognitive resilience variable. Results: A total of 260 participants (145 [55.8%] female; mean [SD] age, 69.2 [9.5] years; mean [SD] MMSE score, 21.9 [5.5]) were included in the study. In multivariable models, women (standardized β = -0.15, P = .02) and young patients (standardized β = -0.20, P = .006) had greater brain resilience to pathological tau. Higher educational level (standardized β = 0.23, P < .001) and global cortical thickness (standardized β = 0.23, P < .001) were associated with greater cognitive resilience to pathological tau. Linear mixed models indicated a significant interaction of brain resilience × cognitive resilience × time on MMSE (β [SE] = -0.235 [0.111], P = .03), with steepest slopes for individuals with both low brain and cognitive resilience. Conclusions and relevance: Results of this study suggest that women and young patients with AD have relative preservation of brain structure when exposed to neocortical pathological tau. Interindividual differences in resilience to pathological tau may be important to disease progression because participants with both low brain and cognitive resilience had the most rapid cognitive decline over time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Genetically Controlled Iron Oxide Biomineralization in Encapsulin Nanocompartments for Magnetic Manipulation of a Mammalian Cell Line

Magnetic nanoparticles have proven invaluable for biomechanical investigations due to their ability to exert localized forces. However, cellular delivery of exogenous magnetic agents often results in endosomal entrapment, thereby limiting their utility for manipulating subcellular structures. This study characterizes and exploits fully genetically controlled biomineralization of iron-oxide cores inside encapsulin nanocompartments to enable magnetic-activated cell sorting (MACS) and magnetic cell manipulation. The fraction of MACS-retained cells showed substantial overexpression of encapsulins and exhibited both para- and ferrimagnetic responses with magnetic moments of 10 -15 A m 2 per cell, comparable to standard exogenous labels for MACS. Electron microscopy revealed that MACS-retained cells contained densely packed agglomerates of ≈30 nm iron oxide cores consisting of ultrafine quasicrystalline ordered nuclei within an amorphous matrix of iron, oxygen, and phosphorus. Scanning transmission X-ray microscopy, X-ray absorption spectroscopy, and Raman microspectroscopy confirmed that the iron-oxide species are consistent with ferric oxide (Fe 2 O 3 ). In addition, the encapsulin-overexpressing MACS-retained cells can be manipulated by a magnetic needle and regrown in patterns determined by magnetic gradients. This study demonstrates that the formation of quasicrystalline iron oxide with mixed para/ferrimagnetic behavior in the cytosol of mammalian cells enables magnetic manipulation without the delivery of exogenous agents.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Single‐Domain Multiferroic Array‐Addressable Terfenol‐D (SMArT) Micromagnets for Programmable Single‐Cell Capture and Release

Abstract Programming magnetic fields with microscale control can enable automation at the scale of single cells ≈10 µm. Most magnetic materials provide a consistent magnetic field over time but the direction or field strength at the microscale is not easily modulated. However, magnetostrictive materials, when coupled with ferroelectric material (i.e., strain‐mediated multiferroics), can undergo magnetization reorientation due to voltage‐induced strain, promising refined control of magnetization at the micrometer‐scale. This work demonstrates the largest single‐domain microstructures (20 µm) of Terfenol‐D (Tb 0.3 Dy 0.7 Fe 1.92 ), a material that has the highest magnetostrictive strain of any known soft magnetoelastic material. These Terfenol‐D microstructures enable controlled localization of magnetic beads with sub‐micrometer precision. Magnetically labeled cells are captured by the field gradients generated from the single‐domain microstructures without an external magnetic field. The magnetic state on these microstructures is switched through voltage‐induced strain, as a result of the strain‐mediated converse magnetoelectric effect, to release individual cells using a multiferroic approach. These electronically addressable micromagnets pave the way for parallelized multiferroics‐based single‐cell sorting under digital control for biotechnology applications.

Khojah, Reem↗
DOE OSTI2025

Electrically Reconfigurable Liquid Metal Nanophotonic Platform for Color Display and Imaging

Dynamically tunable optical materials and device architectures are essential for future photonic technologies, yet conventional solid metals lack the intrinsic tunability required for advanced functionalities. Gallium-based liquid metals (LMs) present an appealing alternative thanks to their distinctive mechanical and optical properties; however, their practical integration in tunable photonic elements remains largely unexplored. Here, in this study, an electrochemically controlled nanophotonic platform is demonstrated that integrates a dynamically reconfigurable LM ground plane with gold nanoantenna arrays within a microfluidic system, enabling precise and reversible modulation of optical resonances across the visible to mid-infrared spectral ranges. By employing moderate operational voltages (1.5–3.0 V), real-time tuning of high-resolution structural color patterns is achieved through nanoscale control of the interfacial gap between the LM and Au nanoantennas. This innovative platform facilitates electrically programmable, high-contrast color patterns suitable for dynamic optical displays, secure anti-counterfeiting labels, and imaging applications. Additionally, this platform enables tunable mid-infrared spectral responses, which may be utilized for chemical and biological sensing applications. This versatile integrated LM-based nanophotonic platform opens new paths toward multifunctional, actively tunable/reconfigurable photonic device and system technologies.

Imaging↗
DOE OSTI2022

Liquid Crystal‐Based Detection of Antigens with ELISA Sensitivity

Abstract A highly sensitive label‐free liquid crystal (LC)‐based technique is presented for detecting Immunoglobulin G (IgG) antigens used to uncover viral infections. The effectiveness, sensitivity, and selectivity of this detection method is demonstrated with goat IgG antigen at concentrations as low as 100 pg ml −1 , which is comparable to the sensitivity of the current enzyme‐linked immunosorbent assay (ELISA). The sensor is fabricated by decorating a transmission electron microscopy grid immobilized glass surfaces with antibodies; the target antigen is detected by a liquid crystal suspended onto the grid. This is different from previous methods where the antigen is detected either at the LC‐aqueous interface or in an LC sandwich cell with an antibody/antigen‐decorated substrate. This new approach has advantages such as easy sample preparation, higher sensitivity, and better storage capabilities. Binding the target antigen to the antibody results in a reorientation of the LC director that is detected optically. In addition to demonstrating the sensitivity, the physical principle of the detection is also discussed. This technique may apply to detect virtually any antigen of interest.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Harnessing Particle Size‐Control and DNA‐Oligo Functionalization in ZIF‐76 for Biological Applications

Abstract Advanced therapeutics require novel nanocarriers to ensure their functionality is preserved during transit. Zeolitic imidazolate frameworks (ZIFs) have emerged as promising materials in this field owing to their combined biocompatibility, high porosity, and tunable chemistry. While a diverse family of ZIFs has been reported, few have been explored beyond the prototypical ZIF‐8. Herein, the size‐controlled synthesis of three distinct ZIF‐76 analogs is demonstrated, overcoming the unique synthetic challenges intrinsic to the lta topology and complex crystallization kinetics associated with the mixed linker approach. This assesses the materials’ platform effectiveness for intracellular delivery first by exploring the structural and colloidal stability in biologically relevant media. To circumvent particle aggregation, fluorescently labeled DNA oligonucleotides are post‐synthetically attached to the ZIF surface. This modification significantly improves the colloidal stability in media and facilitates particle internalization tracking. Finally, the particle‐cell interactions are assessed, revealing rapid cell membrane association with macrophages, but not lung epithelial cells, and ZIF accumulation within macrophages which increased over time. Importantly, this study outlines a generalized approach toward expanding the available library of ZIFs for biological applications, enabling the potential for targeted therapeutic delivery for intracellular infections treatment.

Deneff, Jacob I.↗
DOE OSTI2023

Dispersion-Engineered Deep Sub-Wavelength Plasmonic Metasurfaces for Broadband Seira Applications

Surface enhanced infrared absorption (SEIRA) spectroscopy is a powerful tool in which plasmonically enhanced electromagnetic fields provide high-sensitivity molecular detection. Most SEIRA platforms operate at a single resonant frequency, which must be tuned to match that of the target molecule, and commonly rely on time-consuming lithographic techniques. This study presents a high-throughput and cost-effective plasmonic metasurface for broadband, tunable, and strong infrared signal enhancement. The platform is built upon the principle of dispersion-engineered plasmonic Fabry–Pérot (FP) nanocavity arrays. It offers 1) tight squeezing of infrared (IR) photons into deep sub-wavelength nano-volumes and 2) spectrally tunable near-field enhancements of up to ≈10 6 , two to three orders of magnitude higher than most optical metasurface systems. By coupling multilayer nano-thin film deposition and nanoskiving fabrication techniques, the dispersive FP metasurfaces can be rapidly and reproducibly constructed in a scalable and lithography-free manner. Using IR spectroscopy, the selective and sensitive label-free detection of a molecular monolayer is achieved at a range of frequencies. An enhancement factor of nearly 10 5 is measured at the carbonyl (C = O) vibrational marker band of the molecule. The confluence of high field enhancement, broadband plasmonic response, and facile fabrication makes this metasurface a promising platform for SEIRA spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Extending Imaging Volume in Soft X‐Ray Tomography

Soft X‐ray tomography offers rapid imaging of whole, single cells with a few tens of nanometers spatial resolution without fixation or labeling. Herein, this technique is limited to specimens about 10 μm thick, such that applications of soft X‐ray tomography of large human cells or multicellular specimens are not possible. A theoretical and experimental framework for soft X‐ray tomography that enables extension of imaging volumes to 18 μm‐thick specimens is developed. This approach, based on long depth of field and half‐acquisition tomography, is easily applicable to microscopes equipped with a full‐rotation specimen stage. This opens opportunities for imaging large human cells, such as those commonly seen in cancer research, as well as cell‐to‐cell interactions, where two or more cells occupy the same imaging volume.

Ekman, Axel↗
DOE OSTI2023

Cellulose Nanocrystals are a Renewable and Biocompatible Nanocarrier of Agrochemicals Directly to Plant Cells

More sustainable agricultural practices are critical to meeting humanity's food needs while minimizing adverse environmental impacts. Engineered nanomaterials used as nanocarriers promise to reduce the volume of agrochemicals required for crop production but concerns about nanocontamination of agricultural products necessitate the discovery of naturally occurring alternatives. Here, in this study, plant‐derived cellulose nanocrystals (CNC) as a “green” alternative to man‐made nanomaterials for the economical delivery of agrochemicals to plants are suggested. Using confocal microscopy and fluorescently labeled CNC, it is demonstrated that CNC can successfully penetrate the plant cell wall and enter cells without causing any negative effects on the overall plant phenotype, genome, and metabolome. The efficiency of CNC to deliver chemicals is demonstrated through in vitro tests involving CNC covalently conjugated with 2,4‐dichlorophenoxyacetic acid (2,4‐D). Plant cell culture experiments confirmed that CNC can be used as a 2,4‐D nanocarrier and reduces the volume of plant growth regulators needed to cultivate plant cells. This work creates a new platform for cyclical agricultural practices where CNC extracted from agricultural waste can be used for the direct delivery of agrochemicals to crops, thereby reducing the environmental burden created by both agricultural waste and excess herbicides.

Cellulose nanocrystals↗
DOE OSTI2023

Artificial Intelligence Guided Studies of van der Waals Magnets

A materials informatics framework to explore a large number of candidate van der Waals (vdW) materials is developed. In particular, in this study a large space of monolayer transition metal halides is investigated by combining high-throughput density functional theory calculations and artificial intelligence (AI) to accelerate the discovery of stable materials and the prediction of their magnetic properties. Here, the formation energy is used as a proxy for chemical stability. Semi-supervised learning is harnessed to mitigate the challenges of sparsely labeled materials data in order to improve the performance of AI models. This approach creates avenues for the rapid discovery of chemically stable vdW magnets by leveraging the ability of AI to recognize patterns in data, to learn mathematical representations of materials from data and to predict materials properties. Using this approach, previously unexplored vdW magnetic materials with potential applications in data storage and spintronics are identified.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Visualization of a Limonene Synthesis Metabolon Inside Living Bacteria by Hyperspectral SRS Microscopy

Abstract Monitoring biosynthesis activity at single‐cell level is key to metabolic engineering but is still difficult to achieve in a label‐free manner. Using hyperspectral stimulated Raman scattering imaging in the 670–900 cm −1 region, localized limonene synthesis are visualized inside engineered Escherichia coli . The colocalization of limonene and GFP‐fused limonene synthase is confirmed by co‐registered stimulated Raman scattering and two‐photon fluorescence images. The finding suggests a limonene synthesis metabolon with a polar distribution inside the cells. This finding expands the knowledge of de novo limonene biosynthesis in engineered bacteria and highlights the potential of SRS chemical imaging in metabolic engineering research.

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

Magnesium‐Mediated Electrochemical Synthesis of Ammonia

Metal-mediated electrochemical synthesis of ammonia (NH3) is a promising method to activate N2 at room temperature. While a Li-mediated approach has been optimized to produce NH3 at high current density and selectivity, Li's scarcity and its highly negative plating potential limit scalability and energy efficiency. Alternative mediators have been proposed, but only Ca has shown some promise, achieving ≈50% Faradaic efficiency (FE), though requiring voltages beyond -3 V. Here, we report a Mg-mediated nitrogen reduction reaction (Mg-NRR), where N2 is activated on Mg to form Mg3N2, followed by protolysis to release NH3 and regenerate Mg. A notable NH3 FE of 25.28 ± 3.80% is achieved at a current density of -45 mA cm-2, corresponding to an NH3 partial current density of -11.30 ± 1.77 mA cm-2 under 6 bar N2. Isotope-labeled experiments confirm that NH3 originates from N2, with similar FE (25.15 ± 1.01%). Importantly, NH3 production is demonstrated at a total cell potential as low as -3 V. This Li-free Mg-NRR system offers key advantages, including lower energy input and use of earth-abundant materials, making it a scalable route for sustainable NH3 synthesis.

Goyal, Ishita↗
DOE OSTI2025

Structural and Electronic Complexities of a Sulfur‐Bridged Di‐Iron Complex Composed of Mono‐ and Di‐Nitrosyl Units

The delocalized, thermodynamically stable cation, [(N 2 S 2 )Fe(NO)•Fe(NO) 2 ] + , an adduct of mono-nitrosyl and dinitrosyl iron units, is analyzed to address the unusual stability of the sulfur-bridged diiron complex in its three overall redox levels, +, 0, and −. X-ray diffraction and myriad spectroscopic techniques probe products of sequential electron uptake in the corresponding neutral and anionic species. Conundrums include unified blueshifts of the overall 3-band, ν(NO), pattern with added electrons. One-electron reduction changes the anti-ferromagnetically coupled, S = 0, cationic diiron species to the neutral analog, S = ½, with unpaired spin mainly localized on the MNIU, which decreases its ∠Fe–N–O angle by 10 degrees in response to the extra electron density. Subsequent reduction to the anionic species, S = 1, involves a major geometric change at the MNIU, which moves the Fe in {Fe(NO)} 8 out of the N 2 S 2 plane. Site-specific 15 N labeling of nitrosyl in the MNIU confirms the IR analysis and shows rapid NO exchange between the MNIU/DNIU (mono-nitrosyl iron unit/dinitrosyl iron unit) pairs during its synthesis at RT. Mössbauer spectroscopy, S K-edge XAS, and molecular orbital calculations confirm the ability of NO and the versatility of sulfur bridges to buffer and distribute electrons, a key to their major importance in metalloenzymes.

DNIC↗
DOE OSTI2025

Selective Electrochemical Reduction of CO 2 to Metal Oxalates in Nonaqueous Solutions Using Trace Metal Pb on Carbon Supports Enhanced by a Tailored Microenvironment

In this work, the electroreduction of carbon dioxide (CO 2 ) to oxalate is enabled by incorporating trace metallic lead (Pb) on carbon‐based supports (CBS) with polymer overlayers. These composite materials serve as an efficient electrocatalytic system for the facile conversion and storage of CO 2 , a pernicious atmospheric pollutant. Results from controlled potential electrolysis experiments indicate that 1) trace metallic Pb on the ppb scale is active toward the reductive coupling of CO 2 to oxalate at comparable Faradaic efficiencies to bulk metallic Pb and 2) polymer encapsulation of this trace metallic Pb leads to promotion of CO 2 reduction (CO 2 R) selectively to metal oxalates over other products such as CO. Importantly, metal oxalates are important alternative cementitious materials and precursors for other materials’ synthesis applications. The solid products undergo rigorous spectroscopic characterization, including 13 CO 2 labeling experiments, to ensure the metal oxalates are in fact produced from CO 2 R. These findings serve as a model for leveraging microenvironment effects to enhance activity and selectivity for CO 2 R using trace‐metal catalysts for carbon utilization and storage technologies.

alternative cementitious materials↗
DOE OSTI2026

Toward Intelligent Multimodal Holography for Real-Time Chemical Imaging of Dynamic Ion Separation

Molecular-level visualization of ion transport and separation dynamics in complex environments is crucial for advancing energy systems, water purification, and critical materials recovery. Achieving this requires imaging platforms that combine structural sensitivity, chemical specificity, and real-time operation. Digital off-axis holography (DOAH) provides high-throughput, label-free quantitative phase imaging but inherently lacks chemical selectivity. Integrating DOAH with complementary spectroscopic channels such as fluorescence or hyperspectral imaging introduces the needed molecular specificity, while also creating challenges in multimodal data fusion, synchronization, and computational throughput. Artificial intelligence offers a powerful route to address these limitations by uniting physics-based reconstruction with data-driven interpretation. In this Perspective, we outline a framework for intelligent multimodal holography and demonstrate its potential using a preliminary AI-driven test case. Raw DOAH holograms of lanthanide solutions subjected to magnetic field gradients were analyzed using multi-agent AI workflows that autonomously selected reconstruction tools, extracted NMF components, and generated scientific claims consistent with true paramagnetic and diamagnetic behavior. This demonstration shows how AI-enabled reasoning can deliver real-time chemical–structural interpretation directly from raw holograms. Together, these advances define a path toward adaptive, intelligent holography platforms capable of supporting in situ chemical separations, dynamic ion transport analysis, and next-generation interfacial science.

Ricchiuti, Giovanna↗