Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “emergency generator”

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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Exploring altermagnetism in RuO 2 : from conflicting experiments to emerging consensus

Altermagnetism has recently emerged as a new class of magnetic order that combines the advantages of both ferromagnets and antiferromagnets. The compensated antiparallel spin structure, in combination with crystallographic rotational symmetry, gives rise to distinct magnetic properties, opening new opportunities for next-generation spintronic applications. In this review, we introduce a variety of experimental approaches—including electronic, optical, and particle-based spectroscopies—used to probe theoretically suggested altermagnetism. In particular, we review recent studies on the altermagnetic candidate RuO 2 , whose magnetic ground state remains under debate with conflicting experimental results, organizing the discussion according to the experimental techniques. Furthermore, we highlight recent findings on fully strained RuO 2 thin films that emphasize the critical role of strain in the emergence of altermagnetism. We believe that this review will provide not only practical guidelines for investigating altermagnetic systems but also valuable insights toward reaching consensus on the ongoing controversies surrounding RuO 2 ’s altermagnetism.

altermagnet↗
NASA NTRSDate not supplied

TPSAS-NF1676L-35370-DND

The above anvil cirrus plume (AACP) is a weather phenomenon that signifies an intense tropopause penetrating updraft which can inject cirrus clouds several kilometers into the stratosphere. Storms that have such intense updrafts are often supercells which generate severe weather such as tornadoes, high winds, and hail. In addition, AACPs moisten the stratosphere and influence the Earth's radiative balance. Though an AACP can be identified by the human eye, no automated AACP detection methods currently exist. Lack of detection inhibits understanding of where and how often AACPs occur, and how these storms influence stratospheric air composition. Previous work involved synthesis of multiple remote sensing and severe weather report/warning data sources to identify AACPs in Geostationary Operational Environmental Satellite system (GOES) satellite imagery and better understand their weather impacts (Bedka et al. (Wea. Forecasting, 2018)). This current study demonstrates an automated AACP identification method based on the application of a deep learning segmentation model known as a U-net. This study documents the development of a U-net model capable of identifying emergent AACPs using only satellite infrared (IR) and visible reflected sunlight imagery. The performance of a U-net is quantitatively benchmarked with human AACP identifications and qualitatively assessed through animations of detections generated from GOES-16 1-minute temporal resolution imagery.

Charles Liles↗
DOE OSTI2024

Technical Language Processing of Nuclear Power Plants Equipment Reliability Data

Operating nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) element data that contain information about the status of components, assets, and systems. Some of this information is in textual form where the occurrence of abnormal events or maintenance activities are described. Analyses of NPP textual data via natural language processing (NLP) methods have expanded in the last decade, and only recently the true potential of such analyses has emerged. So far, applications of NLP methods have been mostly limited to classification and prediction in order to identify the nature of the given textual element (e.g., safety or non-safety relevant). In this paper, we target a more complex problem: the automatic generation of knowledge based on a textual element in order to assist system engineers in assessing an asset’s historical health performance. The goal is to assist system engineers in the identification of anomalous behaviors, cause–effect relations between events, and their potential consequences, and to support decision-making such as the planning and scheduling of maintenance activities. “Knowledge extraction” is a very broad concept whose definition may vary depending on the application context. In our particular context, it refers to the process of examining an ER textual element to identify the systems or assets it mentions and the type of event it describes (e.g., component failure or maintenance activity). In addition, we wish to identify details such as measured quantities and temporal or cause–effect relations between events. This paper describes how ER textual data elements are first preprocessed to handle typos, acronyms, and abbreviations, then machine learning (ML) and rule-based algorithms are employed to identify physical entities (e.g., systems, assets, and components) and specific phenomena (e.g., failure or degradation). A few applications relevant from an NPP ER point of view are presented as well.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Understanding Formation of Irradiation-Induced Defects through 4D-STEM, Electron Tomography, and WBDF-STEM

A major challenge in advancing nuclear materials for next-generation fission and proposed fusion reactors is to comprehensively understand the formation of irradiation-induced defects. Here it is essential to correlate the evolution of irradiation-induced defects and the degradation of mechanical properties, as they collectively dictate the material's lifespan and ensure nuclear safety. Scanning transmission electron microscopy (STEM) based techniques have emerged as indispensable tools for irradiation-induced defect characterization, offering high spatial resolution imaging and chemical analysis, such as electron energy loss spectroscopy (EELS) and energy dispersive X-ray spectroscopy (EDXS). These techniques have been effectively used to obtain an atomic-scale view of the defect structure. Recent advances in electron microscopy, particularly in 4D-STEM, offer detailed insight into microstructural evolution by capturing full 2D diffraction patterns at every pixel position. Using high-speed direct electron detectors, this technology generates a four-dimensional dataset, overcoming the limitations of traditional STEM imaging.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Reverse order-disorder transition of Janus particles confined in two dimensions

In this study Janus particles with different patch sizes, confined to two dimensions, generate a series of patterns of interest to the field of nanoscience. Here we observe reverse melting, where for some densities the system melts under cooling. For a broad range of hydrophobic patch sizes ( 60° < θ 0 < 90°), a reentrant transition from solid to liquid and then to an ordered phase emerges as temperature (T) decreases due to the formation of rhombus chains at low T. This reentrant phase has pseudo long-range orientational order but short-range translational order, similar to a hexatic phase. Our work provides guidelines to study the melting and assembly of Janus particles in two dimensions, as well as mechanisms to generate phases with specific symmetry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Bundling measures for food systems transformation: a global, multimodel assessment

Background Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models. Methods In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT–Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously. Findings Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO 2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices). Interpretation This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.

Sundiang, Marina [Cornell Univ., Ithaca, NY (Unite↗
DOE OSTI2026

A robust alloy design (RAD) strategy for next-generation (IV) nuclear fission reactors

Next-generation nuclear reactors demand structural materials capable of withstanding extreme conditions, including high temperatures, intense neutron flux, and corrosive environments. Multi-Principal Element Alloys (MPEAs) have emerged as promising candidates due to their exceptional radiation tolerance, thermal stability, and compositional flexibility. This study introduces a versatile and customizable Robust Alloy Design (RAD) strategy for systematically designing MPEAs for GEN-IV reactor fuel cladding. The RAD framework integrates nuclear-relevant selection criteria, empirical parameter assessments, and high-throughput CALPHAD simulations to efficiently narrow compositional space and identify stable alloys. A unified RAD score developed for the first time, combines key performance metrics, including fuel-clad chemical interaction (FCCI), neutron absorption cross-section (NAC), valence electron configuration (VEC), and melting point factor (MPF), into a flexible ranking system adaptable to reactor-specific priorities. Among 724 candidates, V555(5Al–5Cr–5Fe–85V) emerged as the top alloy, validated experimentally with a homogeneous single-phase BCC microstructure and superior mechanical properties (nano-indentation: 3.389 ± 0.258 GPa; Vickers hardness: 240 ± 6.7 HV), significantly outperforming Zircaloy-4 and V-4Cr-4Ti. Importantly, the RAD strategy is not limited to nuclear applications; its customizable weighting system enables scalability to other extreme environments. This adaptability positions RAD strategy as a versatile tool for advanced materials design across multiple industries.

Alloy design↗
DOE OSTI2024

Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering

Enzymes can be engineered at the level of their amino acid sequences to optimize key properties such as expression, stability, substrate range, and catalytic efficiency or even to unlock new catalytic activities not found in nature. Because the search space of possible proteins is vast, enzyme engineering usually involves discovering an enzyme starting point that has some level of the desired activity followed by directed evolution to improve its “fitness” for a desired application. Recently, machine learning (ML) has emerged as a powerful tool to complement this empirical process. ML models can contribute to (1) starting point discovery by functional annotation of known protein sequences or generating novel protein sequences with desired functions and (2) navigating protein fitness landscapes for fitness optimization by learning mappings between protein sequences and their associated fitness values. In this Outlook, we explain how ML complements enzyme engineering and discuss its future potential to unlock improved engineering outcomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Switching speed limits in electrically driven VO 2 structural Mott–Peierls transition

Mott materials are archetypal quantum systems actively explored as next-generation electronic and photonic platforms, with potential applications spanning non-Von Neumann computing, robotics, energy storage, and microwave technologies. Among these, vanadium dioxide (VO 2 ) has emerged as one of the most intensively studied compounds, owing to its sharp, near-room-temperature insulator-to-metal phase transition. VO 2 also serves as a benchmark system for testing cutting-edge theories and experimental techniques. Here, we directly visualize the electrically driven transition dynamics in VO 2 using a microwave-driven, frequency-tunable pulsed transmission electron microscope that combines nanometer spatial and picosecond temporal resolution. Under high-frequency (MHz–GHz) excitation, we capture the ultrafast nucleation, propagation, and dissolution of metallic domains within an operating device over millions of reversible cycles. We observe the ultrafast formation of consistent metallic nuclei beneath the electrodes, followed by the propagation of a structural phase front at 4.54 nm/ns. Our experiments show that phonon-mediated structural recovery ultimately limits reversible switching of VO 2 at GHz frequencies, and that a tunable regime for reversible operation spans from kHz to GHz through device engineering. Beyond VO 2 , our approach provides a powerful framework for probing non-equilibrium structural transformations in correlated and functional materials under realistic electrical stimuli.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A metabolic modeling platform for the computation of microbial ecosystems in time and space (COMETS)

Genome-scale stoichiometric modeling of metabolism has become a standard systems biology tool for modeling cellular physiology and growth. Extensions of this approach are emerging as a valuable avenue for predicting, understanding and designing microbial communities. Computation of microbial ecosystems in time and space (COMETS) extends dynamic flux balance analysis to generate simulations of multiple microbial species in molecularly complex and spatially structured environments. Here we describe how to best use and apply the most recent version of COMETS, which incorporates a more accurate biophysical model of microbial biomass expansion upon growth, evolutionary dynamics and extracellular enzyme activity modules. In addition to a command-line option, COMETS includes user-friendly Python and MATLAB interfaces compatible with the well-established COBRA models and methods, as well as comprehensive documentation and tutorials. Overall, this protocol provides a detailed guideline for installing, testing and applying COMETS to different scenarios, generating simulations that take from a few minutes to several days to run, with broad applicability to microbial communities across biomes and scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Multimodal characterization of Te inclusions in Cd 1−x Zn x Te and Cd 1−x Zn x Te 1−y Se y for gamma and X-ray detectors

While CdZnTe (CZT) and CdZnTeSe (CZTS) semiconductors have emerged as compounds for room-temperature gamma and X-ray detection materials, they continue to be constrained by the formation of Te-inclusion defects generated during the growth and post-growth phases of the material, which adversely affect the detector performance. We demonstrate the utility of multimodal microscopic imaging and analysis for the characterization of the optical and electronic properties of Te inclusions in CZT and CZTS crystals at both micron and nanometer length scales. Having first identified regions with micron-scale Te inclusions using confocal Raman microscopy techniques, optically coupled infrared scattering near-field optical microscopic mapping was performed to map the distribution of these inclusions with nanometer spatial resolution and correlate the presence of Te inclusions in the matrix with other properties. Kelvin probe force microscopy was then utilized to characterize the variations of the work function associated with the presence of Te inclusions. Here, we observe an increase of ~ 240 mV in the work function associated with Te inclusions compared to the bulk CZT/CZTS crystals. Additionally, we observe that individual bulk grains in CZT can exhibit slight potential variations. Our findings develop a portrait of the charge trapping mechanisms in CZT and CZTS that act to degrade detector performance, while the demonstration of these combined microscopy techniques provides a new analytical tool that can be utilized for further optimization of the detector performance for these semiconducting compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Visualization and quantum control of light-accelerated condensates by terahertz multi-dimensional coherent spectroscopy

Abstract Characterizing and controlling high-order correlation of quantum systems is key for developing quantum devices and switching technologies. Although conventional static and ultrafast spectroscopy gives access to collective excitations characterizing quantum states, more exotic correlations cannot be easily separated from other contributions. Here we develop density matrix simulations to show that seventh-order-wave-mixing peaks with distinct temperature and field dependences in two-dimensional terahertz nonlinear spectra reveal light-induced correlations in non-equilibrium superconducting states. Above critical terahertz driving, these emerging peaks split from conventional peaks along the second axis introduced by pump-probe relative phase in two-dimensional frequency space. They are photo-generated by correlations between two-photon fluctuations and interacting quasi-particle and quasi-particle/Higgs superconductor excitations. By photo-inducing persistent symmetry breaking via light-wave propagation, we also demonstrate seventh-order-wave-mixing sensing of Higgs collective modes. Our theory suggests to use multi-dimensional spectroscopy for quantum sensing of light-driven superconductivity and paves a path for quantum operations by few-cycle-THz-periodic photocurrent modulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Electronic glasses from a broken gauge symmetry in disorder-free systems

Glass phases can be stabilized by quenched disorders, as in most spin-glass materials, or self-generated through kinetic freezing in disorder-free systems. A canonical example of the latter is structural glasses, which have been extensively studied for many decades. Yet, how the rugged energy landscape of a glass phase is spontaneously generated in disorder-free systems remains one of the key questions in glass physics. Here, in this work, we present a general electronic mechanism for the emergence of glassy phase using the example of itinerant electrons coupled to XY spins on a lattice. This model can also be viewed as the mean-field theory of a superconducting system with attractive density-density interactions. Intriguingly, the electron gauge symmetry in the strong pairing limit gives rise to a macroscopic degeneracy of XY spins. In the presence of electron hopping that breaks the gauge symmetry, the lifting of the extensive degeneracy leads to a glass phase with disordered pairings. Our findings highlight a scenario in which a glassy state originates from the breaking of quantum gauge symmetry without quenched disorders.

XY model↗
DOE OSTI2021

Phase-engineered bosonic quantum codes

Continuous-variable systems protected by bosonic quantum codes have emerged as a promising platform for quantum information. To date, the design of code words has centered on optimizing the state occupation in the relevant basis to generate the distance needed for error correction. Here, we show tuning the phase degree of freedom in the design of code words can affect, and potentially enhance, the protection against Markovian errors that involve excitation exchange with the environment. As illustrations, we first consider phase engineering bosonic codes with uniform spacing in the Fock basis that correct excitation loss with a Kerr unitary and show that these modified codes feature destructive interference between error code words and, with an adapted “two-level” recovery, the error protection is significantly enhanced. We then study protection against energy decay with the presence of mode nonlinearities and analyze the role of phase for optimal code designs. As a result, we extend the principle of phase engineering to bosonic codes defined in other bases and multiqubit codes, demonstrating its broad applicability in quantum error correction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Direct experimental evidence of tunable charge transfer at the LaNiO 3 / CaMnO 3 ferromagnetic interface

Interfacial charge transfer in oxide heterostructures gives rise to a rich variety of electronic and magnetic phenomena. Designing heterostructures where one of the thin-film components exhibits a metal-insulator transition opens a promising avenue for controlling such phenomena both statically and dynamically. In this work, we utilize a combination of depth-resolved soft x-ray standing-wave and hard x-ray photoelectron spectroscopies in conjunction with polarization-dependent x-ray absorption spectroscopy to investigate the effects of the metal-insulator transition in LaNiO 3 on the electronic and magnetic states at the LaNiO 3 /CaMnO 3 interface. Here, we report a direct observation of the reduced effective valence state of the interfacial Mn cations in the metallic superlattice with an above-critical LaNiO 3 thickness (6 unit cells, u.c.) facilitated by the charge transfer of itinerant Ni 3d e g electrons into the interfacial CaMnO 3 layer. Conversely, in an insulating superlattice with a below-critical LaNiO 3 thickness of 2 u.c., a homogeneous effective valence state of Mn is observed throughout the CaMnO 3 layers due to the blockage of charge transfer across the interface. The ability to switch and tune interfacial charge transfer enables precise control of the emergent ferromagnetic state at the LaNiO 3 /CaMnO 3 interface and, thus, has far-reaching consequences on the future strategies for the design of next-generation spintronic devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Four-Spin Terms and the Origin of the Chiral Spin Liquid in Mott Insulators on the Triangular Lattice

At strong repulsion, the triangular-lattice Hubbard model is described by s=1/2 spins with nearest-neighbor antiferromagnetic Heisenberg interactions and exhibits conventional 120° order. Using the infinite density matrix renormalization group and exact diagonalization, we study the effect of the additional four-spin interactions naturally generated from the underlying Mott-insulator physics of electrons as the repulsion decreases. Although these interactions have historically been connected with a gapless ground state with emergent spinon Fermi surface, we find that, at physically relevant parameters, they stabilize a chiral spin liquid (CSL) of Kalmeyer-Laughlin (KL) type, clarifying observations in recent studies of the Hubbard model. Finally, we present a self-consistent solution based on a mean-field rewriting of the interaction to obtain a Hamiltonian with similarities to the parent Hamiltonian of the KL state, providing a physical understanding for the origin of the CSL.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Investigating Scientific Data Change with User Research Methods

Scientific datasets are continually expanding and changing due to fluctuations with instruments, quality assessment and quality control processes, and modifications to software pipelines. Datasets include minimal information about these changes or their effects requiring scientists manually assess modifications through a number of labor intensive and ad-hoc steps. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists systematically identify and make decisions around data changes. Currently, there is a lack of understanding, and common practices, for identifying and evaluating changes in datasets since systematically measuring and managing data change is under explored in scientific work. We are conducting user research to address this need by exploring scientist's conceptualizations, behaviors, needs, and motivations when dealing with changing datasets. Our user research utilizes multiple methods to produce foundational, generative insights and evaluate research products produced by our team. In this paper, we detail our user research process and outline our findings about data change that emerge from our studies. Our work illustrates how scientific software teams can push beyond just usability testing user interfaces or tools to better probe the underlying ideas they are developing solutions to address.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1982

Multiprism collimator

A special purpose optical collimator system which generates multiple collimated light beams with precisely related angular separation of the beams, is comprised of a stack of relatively flat plate-like refracted prisms in the form of wedges. Each prism has a specified angular deviation, mounted on top of one another in a fixture which holds the wedges so that they are adapted to operate at minimum angular deviation and thus are relatively insensitive to rotational and angular charges. A collimated sources of monochromatic light, generated for example by a helium-neon laser and a collimated beam expander, provides a common incident beam to the wedges whereupon a number equally spaced emergent beams are provided.

Minott, P. O.↗