Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Area of Review”

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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Scripting a new dialogue between diazotrophs and crops

Diazotrophs are bacteria and archaea that can reduce atmospheric dinitrogen (N 2 ) into ammonium. Plant–diazotroph interactions have been explored for over a century as a nitrogen (N) source for crops to improve agricultural productivity and sustainability. This scientific quest has generated much information about the molecular mechanisms underlying the function, assembly, and regulation of nitrogenase, ammonium assimilation, and plant–diazotroph interactions. This review presents various approaches to manipulating N fixation activity, ammonium release by diazotrophs, and plant–diazotroph interactions. Here, we discuss the research avenues explored in this area, propose potential future routes, emphasizing engineering at the metabolic level via biorthogonal signaling, and conclude by highlighting the importance of biocontrol measures and public acceptance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Ice‐Nucleating Particles That Impact Clouds and Climate: Observational and Modeling Research Needs

Abstract Atmospheric ice‐nucleating particles (INPs) play a critical role in cloud freezing processes, with important implications for precipitation formation and cloud radiative properties, and thus for weather and climate. Additionally, INP emissions respond to changes in the Earth System and climate, for example, desertification, agricultural practices, and fires, and therefore may introduce climate feedbacks that are still poorly understood. As knowledge of the nature and origins of INPs has advanced, regional and global weather, climate, and Earth system models have increasingly begun to link cloud ice processes to model‐simulated aerosol abundance and types. While these recent advances are exciting, coupling cloud processes to simulated aerosol also makes cloud physics simulations increasingly susceptible to uncertainties in simulation of INPs, which are still poorly constrained by observations. Advancing the predictability of INP abundance with reasonable spatiotemporal resolution will require an increased focus on research that bridges the measurement and modeling communities. This review summarizes the current state of knowledge and identifies critical knowledge gaps from both observational and modeling perspectives. In particular, we emphasize needs in two key areas: (a) observational closure between aerosol and INP quantities and (b) skillful simulation of INPs within existing weather and climate models. We discuss the state of knowledge on various INP particle types and briefly discuss the challenges faced in understanding the cloud impacts of INPs with present‐day models. Finally, we identify priority research directions for both observations and models to improve understanding of INPs and their interactions with the Earth System.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Recent Trends and Innovation in Additive Manufacturing of Soft Functional Materials

The growing demand for wearable devices, soft robotics, and tissue engineering in recent years has led to an increased effort in the field of soft materials. With the advent of personalized devices, the one-shape-fits-all manufacturing methods may soon no longer be the standard for the rapidly increasing market of soft devices. Recent findings have pushed technology and materials in the area of additive manufacturing (AM) as an alternative fabrication method for soft functional devices, taking geometrical designs and functionality to greater heights. For this reason, this review aims to highlights recent development and advances in AM processable soft materials with self-healing, shape memory, electronic, chromic or any combination of these functional properties. Furthermore, the influence of AM on the mechanical and physical properties on the functionality of these materials is expanded upon. Additionally, advances in soft devices in the fields of soft robotics, biomaterials, sensors, energy harvesters, and optoelectronics are discussed. Lastly, current challenges in AM for soft functional materials and future trends are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Review of multi-fidelity models

Multi-fidelity models provide a framework for integrating computational models of varying complexity, allowing for accurate predictions while optimizing computational resources. These models are especially beneficial when acquiring high-accuracy data is costly or computationally intensive. This review offers a comprehensive analysis of multi-fidelity models, focusing on their applications in scientific and engineering fields, particularly in optimization and uncertainty quantification. It classifies publications on multi-fidelity modeling according to several criteria, including application area, surrogate model selection, types of fidelity, combination methods and year of publication. The study investigates techniques for combining different fidelity levels, with an emphasis on multi-fidelity surrogate models. Here this work discusses reproducibility, open-sourcing methodologies and benchmarking procedures to promote transparency. The manuscript also includes educational toy problems to enhance understanding. Additionally, this paper outlines best practices for presenting multi-fidelity-related savings in a standardized, succinct and yet thorough manner. The review concludes by examining current trends in multi-fidelity modeling, including emerging techniques, recent advancements, and promising research directions.

42 ENGINEERING↗
DOE OSTI2024

Electric Motor Thermal Management

The poster reports the accomplishments of EDT-Electric Motor Thermal Management consortium project for 2024 VTO Annual Merit Review (AMR). The overall aims of the project are to support research enabling compact, reliable, low-cost, and efficient electric machines aligned with roadmap research areas; to collaborate with ORNL, Ames, and SNL to provide motor thermal analysis support, reliability evaluation, and material measurements on related motor research at national laboratories; and collaborate with university partners including Georgia Institute of Technology and University of Wisconsin Madison to support university-led motor thermal management research efforts.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

LAI, EVI, NDVI, and kNDVI in 23 pantropical forests affected by 21 cyclones

Statement of purpose: Cyclones alter the function and composition of tropical forests, making effects of intensifying cyclones on carbon-rich forests a critical topic of study. Here, we quantified cyclone-induced damage and recovery of 21 cyclone disturbances affecting 23 pantropical forest sites between 1988-2017 utilizing leaf area index (LAI), enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and transformed NDVI (kNDVI) values from Google Earth Engine. Field observations collected in a meta-analysis (Bomfim et al., 2022, in review) were used to ground-truth and test effects of soil resource availability and disturbance factors on damage and recovery. This meta-analysis also served as the basis to begin vegetation index extraction, utilizing unique site and date combinations, from tropical forests effect by cyclone disturbances. We began collecting NDVI (5km resolution) from the NOAA Climate Data Record (CDR) of AVHRR Normalized Difference Vegetation Index (NDVI), Version 5 data product (Vermote, 2019) for all case studies included, 42. Next, we began extracting Landsat data from Landsat 4, 5, and 8, courtesy of the U.S. Geological Survey, in search of higher resolution data. We selected a 3 by 3 Landsat pixel area, leading to a 90m resolution data extraction. The specific imagery used includes Landsat 4 USGS Landsat 4 TM Collection 1 Tier 1 TOA (top of atmosphere) Reflectance, Landsat 5 USGS Landsat 5 TM (thematic mapper) Collection 1 Tier 1 TOA Reflectance, and Landsat 8 USGS Landsat 8 Collection 1 Tier 1 TOA Reflectance. Within Google Earth Engine, we selected the date and location (latitude and longitude), calculated NDVI, kNDVI, and EVI utilizing Landsat bands (see metadata_NGEE-tropics_cyclones), and extracted post- and pre-cyclone values for each case study to calculate cyclone-induced change in the vegetative index. Due to limited spatial resolution of Landsat remote sensing data, MODIS products were investigated next. First, the MOD13Q1.006 Terra Vegetation Indices 16-Day Global 250m product was used to extract 250m EVI and NDVI (Didan, 2015) and then the MCD15A3H.006 MODIS Leaf Area Index/FPAR 4-Day Global 500m product product was used to extract LAI 500m (Myneni et al., 2015). Pre- and post-cyclone values, change in the vegetative index, and standard deviation for all values are included in the main csv (see case_study_data.csv) for all vegetative indices collected, including LAI 500m, EVI 250m, NDVI 250m, NDVI 90m, kNDVI 90m, EVI 90m, and NDVI 5km. Lastly, recovery values were calculated utilizing a standardization method (see metadata_NGEE-tropics_cyclones) and recovery values for MODIS (see MODIS_recovery.csv) and Landsat (Landsat_recovery.csv) data are included.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Landmark Publications in Analytical Atomic Spectrometry: Fundamentals and Instrumentation Development

The almost-two-centuries history of spectrochemical analysis has generated a body of literature so vast that it has become nearly intractable for experts, much less for those wishing to enter the field. Authoritative, focused reviews help to address this problem but become so granular that the overall directions of the field are lost. This broader perspective can be provided partially by general overviews but then the thinking, experimental details, theoretical underpinnings, and instrumental innovations of the original work must be sacrificed. In the present compilation, this dilemma is overcome by assembling the most impactful publications in the area of analytical atomic spectrometry. Each entry was proposed by at least one current expert in the field and supported by a narrative that justifies its inclusion. The entries were then assembled into a coherent sequence and returned to contributors for a round-robin review. A total of 48 scientists participated in this endeavor, contributing a combined list of 1055 individual articles spanning 17 sub-disciplines of spectrochemical analysis into what the current community views as “key” publications. Of these cited articles, 60 received nominations from four or more scientists, establishing them as the most indispensable reading materials. The outcome of this collaborative effort is intended to serve as a valuable resource not only for current practitioners in atomic spectroscopy but also for present and future students who represent coming generations of analytical atomic spectroscopists.

Instruments & Instrumentation↗
DOE OSTI2025

Optics for terawatt-scale photovoltaics: review and perspectives

Photovoltaics, a mature technology, is set to play a vital role in achieving a carbon-free energy system. This article examines the pivotal role of optics in advancing photovoltaics. We identify key scientific research areas where the optics community can make significant contributions. We are guided by the central question: How can optics facilitate the large-scale deployment of photovoltaics necessary for decarbonizing our societies?

Jäger, Klaus (ORCID:0000000260089559)↗
DOE OSTI2020

Guidelines to Achieving High Selectivity for the Hydrogenation of α,β-Unsaturated Aldehydes with Bimetallic and Dilute Alloy Catalysts: A Review

Selective hydrogenation of unsaturated aldehydes to unsaturated alcohols is a challenging class of reactions, yielding valuable intermediates for the production of pharmaceuticals, perfumes, and flavorings. On monometallic heterogeneous catalysts, the formation of the unsaturated alcohols is thermodynamically disfavored over the saturated aldehydes. Hence, new catalysts are required to achieve the desired selectivity. In this work, the literature of three major research areas in catalysis is integrated as a step toward establishing the guidelines for enhancing the selectivity: reactor studies of complex catalyst materials at operating temperature and pressure, surface science studies of crystalline surfaces in ultrahigh vacuum, and first-principles modeling using density functional theory calculations. Aggregate analysis shows that bimetallic and dilute alloy catalysts significantly enhance the selectivity to the unsaturated alcohols compared to monometallic catalysts. This comprehensive review focuses primarily on the role of different metal surfaces as well as the factors that promote the adsorption of the unsaturated aldehyde via its C=O bond, most notably by electronic modification of the surface and formation of the electrophilic sites. Furthermore, challenges, gaps, and opportunities are identified to advance the rational design of efficient catalysts for this class of reactions, including the need for systematic studies of catalytic processes, theoretical modeling of complex materials, and model studies under ambient pressure and temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Effects of structural defects on optical properties of In x Ga 1-x N layers and quantum wells

This review concentrates on the microstructure of In x Ga 1-x N layers and quantum wells (QWs) in relation to their optical properties. The microstructure of In x Ga 1-x N, with a constant In(x) concentration, shifts with layer thickness. Only layers below 100 nm for x = 0.1 are nearly defect-free. A photoluminescence peak is observed at 405 nm, in line with ~10% In, suggesting band-edge luminescence. Layers with greater thickness and In content present a corrugated surface with numerous structural defects, including V-defects, causing redshifts and multi-peaks in photoluminescence up to 490 nm. These defects, resembling those in GaN, lead to a corrugated sample surface. Atomic force microscopy shows a 3.7-fold larger corrugation in samples with 20 QWs compared to those with 5 QWs measured on 2 × 2 μm 2 areas. Like in GaN, dual growth on different crystallographic planes results in varied QW thicknesses, influencing optical traits of devices made from In x Ga 1-x N layers. The purpose of this review and the chosen subject is to highlight the significant contribution of Wladek Walukiewicz and his group to the current research on the properties of In x Ga 1-x N, which are crucial alloys in the field of optoelectronics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Model validation and selection in metabolic flux analysis and flux balance analysis

13C-Metabolic Flux Analysis (13C-MFA) and Flux Balance Analysis (FBA) are widely used to investigate the operation of biochemical networks in both biological and biotechnological research. Both methods use metabolic reaction network models of metabolism operating at steady state so that reaction rates (fluxes) and the levels of metabolic intermediates are constrained to be invariant. They provide estimated (MFA) or predicted (FBA) values of the fluxes through the network in vivo, which cannot be measured directly. These fluxes can shed light on basic biology and have been successfully used to inform metabolic engineering strategies. Several approaches have been taken to test the reliability of estimates and predictions from constraint-based methods and to compare alternative model architectures. Despite advances in other areas of the statistical evaluation of metabolic models, such as the quantification of flux estimate uncertainty, validation and model selection methods have been underappreciated and underexplored. We review the history and state-of-the-art in constraint-based metabolic model validation and model selection. Applications and limitations of the χ 2 -test of goodness-of-fit, the most widely used quantitative validation and selection approach in 13C-MFA, are discussed, and complementary and alternative forms of validation and selection are proposed. A combined model validation and selection framework for 13C-MFA incorporating metabolite pool size information that leverages new developments in the field is presented and advocated for. Finally, we discuss how adopting robust validation and selection procedures can enhance confidence in constraint-based modeling as a whole and ultimately facilitate more widespread use of FBA in biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Emergent Properties from Three-Dimensional Assemblies of (Nano)particles in Confined Spaces

The assembly of (nano)particles into compact hierarchical structures yields emergent properties not found in the individual constituents. The formation of these structures relies on a profound knowledge of the nanoscale interactions between (nano)particles, which are often designed by researchers aided by computational studies. These interactions have an effect when the (nano)particles are brought into close proximity, yet relying only on diffusion to reach these closer distances may be inefficient. Recently, physical confinement has emerged as an efficient methodology to increase the volume fraction of (nano)particles, rapidly accelerating the time scale of assembly. Specifically, the high surface area of droplets of one immiscible fluid into another facilitates the controlled removal of the dispersed phase, resulting in spherical, often ordered, (nano)particle assemblies. In this review, we discuss the design strategies, computational approaches, and assembly methods for (nano)particles in confined spaces and the emergent properties therein, such as trigger-directed assembly, lasing behavior, and structural photonic color. Finally, we provide a brief outlook on the current challenges, both experimental and computational, and farther afield application possibilities.

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

Quantum Plasmonic Sensors

The extraordinary sensitivity of plasmonic sensors is well-known in the optics and photonics community. These sensors exploit simultaneously the enhancement and the localization of electromagnetic fields close to the interface between a metal and a dielectric. This enables, for example, the design of integrated biochemical sensors at scales far below the diffraction limit. Despite their practical realization and successful commercialization, the sensitivity and associated precision of plasmonic sensors are starting to reach their fundamental classical limit given by quantum fluctuations of light—known as the shot-noise limit. To improve the sensing performance of these sensors beyond the classical limit, quantum resources are increasingly being employed. This area of research has become known as “quantum plasmonic sensing”, and it has experienced substantial activity in recent years for applications in chemical and biological sensing. This review aims to cover both plasmonic and quantum techniques for sensing, and it shows how they have been merged to enhance the performance of plasmonic sensors beyond traditional methods. We discuss the general framework developed for quantum plasmonic sensing in recent years, covering the basic theory behind the advancements made, and describe the important works that made these advancements. We also describe several key works in detail, highlighting their motivation, the working principles behind them, and their future impact. The intention of the review is to set a foundation for a burgeoning field of research that is currently being explored out of intellectual curiosity and for a wide range of practical applications in biochemistry, medicine, and pharmaceutical research.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Recent advances and applications of deep learning methods in materials science

Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identification of features. The recent development of large materials databases has fueled the application of DL methods in atomistic prediction in particular. In contrast, advances in image and spectral data have largely leveraged synthetic data enabled by high-quality forward models as well as by generative unsupervised DL methods. In this article, we present a high-level overview of deep learning methods followed by a detailed discussion of recent developments of deep learning in atomistic simulation, materials imaging, spectral analysis, and natural language processing. For each modality we discuss applications involving both theoretical and experimental data, typical modeling approaches with their strengths and limitations, and relevant publicly available software and datasets. We conclude the review with a discussion of recent cross-cutting work related to uncertainty quantification in this field and a brief perspective on limitations, challenges, and potential growth areas for DL methods in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Carbon dioxide and nitrogen reduction reactions using 2D transition metal dichalcogenide (TMDC) and carbide/nitride (MXene) catalysts

Improving the carbon dioxide and nitrogen reduction reactions (CO 2 RR and NRR) can reduce anthropogenic greenhouse gas emissions while selectively producing chemicals needed for the fuel, plastic, and chemical industries. Efficient CO 2 RR can be used to replace fossil fuels as well as repurpose captured CO 2 , while new NRR pathways can be used to supplement or replace the energy intensive Haber–Bosch process for NH 3 generation with no CO 2 emissions. Therefore, this review article focuses on (photo)electrocatalytic and photocatalytic conversion of CO 2 and N 2 molecules into useful products, such as carbon monoxide, methanol, formic acid, and ammonia, using 2D transition metal dichalcogenides (TMDCs) and metal carbides/nitrides (MXenes). Additionally, these highly tunable 2D catalysts will be evaluated for their ability to selectively and efficiently undergo CO 2 RR and NRR by controlling defects, phases, edge sites, interfaces, and functional groups. We first address the CO 2 RR and NRR challenges, with a particular focus on theoretical mechanisms and minimum energy pathways. We follow this discussion with a detailed review of state-of-the-art 2D TMDC and MXene experimental catalysts for CO 2 RR and NRR (photo)electrocatalytic and photocatalytic reactions, and then address areas of opportunity for these catalytic reactions.

14 SOLAR ENERGY↗
DOE OSTI2023

Reducing nighttime light exposure in the urban environment to benefit human health and society

Nocturnal light pollution can have profound effects on humans and other organisms. Recent research indicates that nighttime outdoor lighting is increasing rapidly. Evidence from controlled laboratory studies demonstrates that nocturnal light exposure can strain the visual system, disrupt circadian physiology, suppress melatonin secretion, and impair sleep. There is a growing body of work pointing to adverse effects of outdoor lighting on human health, including the risk of chronic diseases, but this knowledge is in a more nascent stage. In this Review, we synthesize recent research on the context-specific factors and physiology relevant to nocturnal light exposure in relation to human health and society, identify critical areas for future research, and highlight recent policy steps and recommendations for mitigating light pollution in the urban environment.

Science & Technology - Other Topics↗
DOE OSTI2021

Update of Erosion Conditions and Assessment of Mitigation Options for the L-Bar Site

The L-Bar former uranium milling site was remediated and closed per regulations and is now under the long-term stewardship of the U.S. Department of Energy, Office of Legacy Management (DOE/LM). Since assuming stewardship in 2004, DOE/LM has observed erosion and sedimentation processes at the L-Bar Site that will challenge meeting the design closure criteria in the long term, and therefore erosion control structures were installed in several areas. Portions of these structures were subsequently damaged by summer convective storm events and they are being redesigned. At the request of DOE/LM, Desert Research Institute (DRI) reviewed the proposed redesign plans of the erosion control structures. The purpose of this review is to support DOE/LM decisions regarding mitigation of ongoing erosion processes, including assessing possible repair of the existing erosion control structures, as well as plan for effective long-term site management. This design review is performed in reference to the Uranium Mill Tailings Radiation Control Act (UMTRCA) standards contained in 40 CFR 192.02 that require containment of residual radioactive material be effective for up to 1,000 years (if achievable, but certainly for 200 years), limit radon release, protect groundwater, and minimize future maintenance. The erosion control structures under review are not subject to the UMTRCA standard directly, but they contribute to the performance of the overall containment system by virtue of their relationship with the large diversion channels bounding the disposal cell. The 11 design drawings included in “Erosion Control Alternatives Analysis, L-Bar, New Mexico, Disposal Site, LTS-111-0043-08-002,” dated January 11, 2019, and listed in Appendix A, and supporting calculations in Weston (2019) are the focus of the review. Additionally, DOE/LM provided supporting data such as a 2018 photogrammetry-based digital elevation model of the site, precipitation records collected from an on-site weather station, and sedimentation records collected at an on-site basin. This assessment includes review of the proposed design to mitigate current site conditions but also addresses site changes between the initial erosion assessment report (Miller et al., 2012) and current conditions. The analysis is at a predesign engineering level and does not include development of hydraulic or sediment transport models. Site precipitation data are included in Miller et al. (2012). The natural conditions of the site, the design of site diversion systems, observed erosion at the site, and predesign engineering analysis are used to develop a holistic view of the challenges to L-Bar Site stability and possible responsive actions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

CAR-T Cell Therapy: Mechanism, Management, and Mitigation of Inflammatory Toxicities

Engineered T cell therapies such as chimeric antigen receptor (CAR) expressing T cells (CAR-T cells) have great potential to treat many human diseases; however, inflammatory toxicities associated with these therapies present safety risks and can greatly limit its widespread use. This article briefly reviews our current understanding of mechanisms for inflammatory toxicities during CAR T-cell therapy, current strategies for management and mitigation of these risks and highlights key areas of knowledge gap for future research..

59 BASIC BIOLOGICAL SCIENCES↗