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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Low‐PGM and PGM‐Free Catalysts for Proton Exchange Membrane Fuel Cells: Stability Challenges and Material Solutions

Abstract Fuel cells as an attractive clean energy technology have recently regained popularity in academia, government, and industry. In a mainstream proton exchange membrane (PEM) fuel cell, platinum‐group‐metal (PGM)‐based catalysts account for ≈50% of the projected total cost for large‐scale production. To lower the cost, two materials‐based strategies have been pursued: 1) to decrease PGM catalyst usage (so‐called low‐PGM catalysts), and 2) to develop alternative PGM‐free catalysts. Grand stability challenges exist when PGM catalyst loading is decreased in a membrane electrode assembly (MEA)—the power generation unit of a PEM fuel cell—or when PGM‐free catalysts are integrated into an MEA. More importantly, there is a significant knowledge gap between materials innovation and device integration. For example, high‐performance electrocatalysts usually demonstrate undesired quick degradation in MEAs. This issue significantly limits the development of PEM fuel cells. Herein, recent progress in understanding the degradation of low‐PGM and PGM‐free catalysts in fuel cell MEAs and materials‐based solutions to address these issues are reviewed. The key factors that degrade the MEA performance are highlighted. Innovative, emerging material concepts and development of low‐PGM and PGM‐free catalysts are discussed.

Du, Lei↗
DOE OSTI2022

Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation

The ever-increasing demand for novel materials with superior properties inspires retrofitting traditional research paradigms in the era of artificial intelligence and automation. An autonomous experimental platform (AEP) has emerged as an exciting research frontier that achieves full autonomy via integrating data-driven algorithms such as machine learning (ML) with experimental automation in the material development loop from synthesis, characterization, and analysis, to decision making. In this review, we started with a primer to describe how to develop data-driven algorithms for solving material problems. Then, we systematically summarized recent progress on automated material synthesis, ML-enabled data analysis, and decision-making. Finally, we discussed the challenges and opportunities in an endeavor to develop the next-generation AEP for ultimately realizing an autonomous or self-driving laboratory. In conclusion, this review will provide insights for researchers aiming to learn the frontier of ML in materials science and deploy AEP in their labs for accelerating material development.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Water-Soluble Copper(I) Hydroxide Catalyst and Its Formation in Ligand-Free Suzuki–Miyaura Cross-Coupling Reactions

Copper has emerged as an alternative metal for metal-catalyzed cross-coupling reactions due to its low cost, readily availability, and low toxicity. Here this article reports a water-soluble active molecular catalyst and its formation in the ligand-free Suzuki–Miyaura (SM) cross-coupling reactions with copper iodide as the precatalyst in aqueous solutions. The SM coupling is homogeneous in nature, and the molecular catalyst is Cu(OH) in its singlet electronic state as identified by experimental and computational UV–vis absorption spectroscopy. The Cu(OH) catalyst is generated through the leaching of oval-shaped Cu 2 O nanoparticles, which are characterized with X-ray Auger electron spectroscopy, X-ray absorption spectroscopy, and transmission electron microscopy. The soluble Cu(OH) species is stable for at least 4 weeks under ambient conditions.

cross-coupling↗
DOE OSTI2021

Frequency and Temporal Analysis of Cicada Brood X Sounds

Cicadas are insects that belong to the order Hemiptera (i.e., true bugs). They feed on plant fluids above and below ground. Cicada species fall into two categories: periodical and annual. Seven species of periodical cicadas have been identified, emerging in 13-, 17-, and 21-year cycles [1]. The largest brood (i.e., periodical cicadas of the same cycle) of 17-year cicadas is Brood X, examples of which are shown in Fig. 1. Male cicadas produce the loudest sounds of the insect world. A single male can produce a clicking sound that exceeds 100 dB sound pressure level. This male cicada sound emanates from an organ called the tympanic membrane, which is located on both sides of the body near the base of the wing [2]. The vibrations from this organ generate the sound. Female cicadas make a similar— although less loud—clicking sound with their wings. Figure 2 shows the locations of active cicadas within the United States.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Quantifying microbial control of soil organic matter dynamics at macrosystem scales

Soil organic matter (SOM) stocks, decomposition and persistence are largely the product of controls that act locally. Yet the controls are shaped and interact at multiple spatiotemporal scales, from which macrosystem patterns in SOM emerge. Theory on SOM turnover recognizes the resulting spatial and temporal conditionality in the effect sizes of controls that play out across macrosystems, and couples them through evolutionary and community assembly processes. For example, climate history shapes plant functional traits, which in turn interact with contemporary climate to influence SOM dynamics. Selection and assembly also shape the functional traits of soil decomposer communities, but it is less clear how in turn these traits influence temporal macrosystem patterns in SOM turnover. Here, we review evidence that establishes the expectation that selection and assembly should generate decomposer communities across macrosystems that have distinct functional effects on SOM dynamics. Representation of this knowledge in soil biogeochemical models affects the magnitude and direction of projected SOM responses under global change. Yet there is high uncertainty and low confidence in these projections. To address these issues, we make the case that a coordinated set of empirical practices are required which necessitate (1) greater use of statistical approaches in biogeochemistry that are suited to causative inference; (2) long-term, macrosystem-scale, observational and experimental networks to reveal conditionality in effect sizes, and embedded correlation, in controls on SOM turnover; and (3) use of multiple measurement grains to capture local- and macroscale variation in controls and outcomes, to avoid obscuring causative understanding through data aggregation. Here, when employed together, along with process-based models to synthesize knowledge and guide further empirical work, we believe these practices will rapidly advance understanding of microbial controls on SOM and improve carbon cycle projections that guide policies on climate adaptation and mitigation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Plant glycosyltransferases for expanding bioactive glycoside diversity

Glycosylation is a successful strategy to alter the pharmacological properties of small molecules, and it has emerged as a unique approach to expand the chemical space of natural products that can be explored in drug discovery. Traditionally, most glycosylation events have been carried out chemically, often requiring many protection and deprotection steps to achieve a target molecule. Further, enzymatic glycosylation by glycosyltransferases could provide an alternative strategy for producing new glycosides. In particular, the glycosyltransferase family has greatly expanded in plants, representing a rich enzymatic resource to mine and expand the diversity of glycosides with novel bioactive properties. This article highlights previous and prospective uses for plant glycosyltransferases in generating bioactive glycosides and altering their pharmacological properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Comment on ‘Carbon Intensity of corn ethanol in the United States: state of the science’

Abstract In their recent contribution, Scully et al (2021 Environ. Res. Lett. 16 043001) review and revise past life cycle assessments of corn-grain ethanol’s carbon (C) intensity to suggest that a current ‘central best estimate’ is considerably less than all prior estimates. Their conclusion emerges from selection and recombination of sector-specific greenhouse gas emission predictions from disparate studies in a way that disproportionately favors small values and optimistic assumptions without rigorous justification nor empirical support. Their revisions most profoundly reduce predicted land use change (LUC) emissions, for which they propose a central estimate that is roughly half the smallest comparable value they review (figure 1). This LUC estimate represents the midpoint of (a) values retained after filtering the predictions of past studies based on a set of unfounded criteria; and (b) a new estimate they generate for domestic (i.e. U.S.) LUC emissions. The filter the authors apply endorses a singular means of LUC assessment which they assert as the ‘best practice’ despite a recent unacknowledged review (Malins et al 2020 J. Clean. Prod. 258 120716) that shows this method almost certainly underestimates LUC. Moreover, their domestic C intensity estimate surprisingly suggests that cropland expansion newly sequesters soil C, counter to ecological theory and empirical evidence. These issues, among others, prove to grossly underestimate the C intensity of corn-grain ethanol and mischaracterize the state of our science at the risk of perversely affecting policy outcomes.

Spawn-Lee, Seth A. (ORCID:0000000188215345)↗
DOE OSTI2022

ATHENA: Analytical Tool for Heterogeneous Neuromorphic Architectures

The ASC program seeks to use machine learning to improve efficiencies in its stockpile stewardship mission. Moreover, there is a growing market for technologies dedicated to accelerating AI workloads. Many of these emerging architectures promise to provide savings in energy efficiency, area, and latency when compared to traditional CPUs for these types of applications — neuromorphic analog and digital technologies provide both low-power and configurable acceleration of challenging artificial intelligence (AI) algorithms. If designed into a heterogeneous system with other accelerators and conventional compute nodes, these technologies have the potential to augment the capabilities of traditional High Performance Computing (HPC) platforms [5]. This expanded computation space requires not only a new approach to physics simulation, but the ability to evaluate and analyze next-generation architectures specialized for AI/ML workloads in both traditional HPC and embedded ND applications. Developing this capability will enable ASC to understand how this hardware performs in both HPC and ND environments, improve our ability to port our applications, guide the development of computing hardware, and inform vendor interactions, leading them toward solutions that address ASC’s unique requirements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Specialized Plant Growth Chamber Designs to Study Complex Rhizosphere Interactions

The rhizosphere is a dynamic ecosystem shaped by complex interactions between plant roots, soil, microbial communities and other micro- and macro-fauna. Although studied for decades, critical gaps exist in the study of plant roots, the rhizosphere microbiome and the soil system surrounding roots, partly due to the challenges associated with measuring and parsing these spatiotemporal interactions in complex heterogeneous systems such as soil. To overcome the challenges associated with in situ study of rhizosphere interactions, specialized plant growth chamber systems have been developed that mimic the natural growth environment. This review discusses the currently available lab-based systems ranging from widely known rhizotrons to other emerging devices designed to allow continuous monitoring and non-destructive sampling of the rhizosphere ecosystems in real-time throughout the developmental stages of a plant. We categorize them based on the major rhizosphere processes it addresses and identify their unique challenges as well as advantages. We find that while some design elements are shared among different systems (e.g., size exclusion membranes), most of the systems are bespoke and speaks to the intricacies and specialization involved in unraveling the details of rhizosphere processes. We also discuss what we describe as the next generation of growth chamber employing the latest technology as well as the current barriers they face. We conclude with a perspective on the current knowledge gaps in the rhizosphere which can be filled by innovative chamber designs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Atmospheric Modeling to Enable Prediction of Golden Eagle Interactions with Wind Power Plants

This panel will explore the use of technologies and methods that enhance our understanding of eagle behavior in and near wind energy facilities. The decreasing costs of tracking technologies and substantial computational capabilities are allowing for finer resolution and confidence of eagle observations and the modeling of such datasets increase our understanding of their movements and use of airspace and underlying landscapes. Behavior ecologists' intrinsic knowledge of eagle behavior can augment and further enhance inferences from technology-derived information alone, e.g., GPS, camera, radar, etc. The panel will discuss the state of science and, given the cost-effective tools available, what research objectives are emerging to better assess and reduce wind-eagle risk. The discussion will focus on the following areas: Integrating Behavioral and Quantitative Ecologist perspectives of bald eagle and golden eagle behavior and wind energy risk; Regional-scale vs. facility-scale investigations of bald eagle and golden eagle use of airspace. For example, avoidance behavior to assess risk at facility-scale, and eagle use of landscapes, e.g., territories, nesting, and life-cycle behavior; Bald eagle and golden eagle use of airspace and nexus with atmospheric flow dynamics of wind energy generation; GPS, biomonitoring, tracking camera, radar, and other tools/techniques for deepening the knowledge of eagle behavior in and around wind farms.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2021

Performance of black silicon photodiodes for VUV detection in noble liquids

Black silicon (b-Si) photodiodes are an emerging technology that employs silicon nanostructures to enhance the efficiency of photon detection. Recently, we demonstrated nearly 100% quantum efficiency at <200 nm vacuum ultraviolet (VUV) wavelengths at ambient and in noble liquids, making such devices particularly useful for direct detection of scintillation light in noble liquid detectors. This is important in nuclear science experiments like DarkSide, LUX, XENON, and nEXO, where detection of weak VUV scintillation photons in noble liquids are used to identify rare physics radiation events. Here, we measured the response of b-Si photodiode to the scintillation light generated by alpha particles, all immersed in a LAr and LXe test cell. We established a guideline for future development of b-Si photodetectors with internal gain to reach single-photon sensitivity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Covalent Organic Frameworks for Water Treatment

Covalent organic frameworks (COFs) are an emerging type of porous crystalline material with highly ordered aperture size and tunable structures with designer properties. COFs have been proposed as promising materials for water treatment because of their notable intrinsic properties like excellent chemostability, high surface area, abundant functional sites, and uniform adjustable aperture size. This review focuses on fundamental COF design principles for water treatment (stability, aperture size, and surface functionalization) and the state-of-the-art application of COFs in desalination, organic contaminant sorption, and ion capture. Additional potential promising applications of COFs for water treatment, including solar steam generation, photocatalysis for degradation of organic contaminants, and capacitive deionization are also presented along with an outlook toward future opportunities in the field.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Untapped Benefits of Porous Liquids for Gas Capture: Low-Energy Regeneration

Current liquid-phase gas capture materials incur high operational costs due to energy-intensive regeneration processes, creating an industrial need for alternative materials that retain engineering benefits while reducing energy requirements. Porous liquids (PLs), liquid-phase materials with permanent internal porosity, have emerged as promising replacements with excellent gas absorption capacity and selectivity. Despite these benefits, evaluation of regeneration in PLs remains rare. In this Perspective, we evaluate the effects of solvent interactions, mass transport, and binding site formation that control PL regeneration. While conventional regeneration methods exist in PLs, the diversity of PL compositions allows for novel regeneration processes including light irradiation via use of photosensitive azobenzene-based cages, isostatic compression to collapse internal pore structures, and localized heating via sonication for gas desorption. In conclusion, the wide variability in porous host materials that generate the internal porosity in PLs facilitates innovative low-energy regeneration pathways, positioning them as a transformative solution in separation technologies.

gas capture↗
DOE OSTI2021

Ion Pairing Mediates Molecular Organization Across Liquid/Liquid Interfaces

Liquid/liquid interfaces play a central role in scientific fields ranging from nanomaterial synthesis and soft matter electronics to nuclear waste remediation and chemical separations. This diversity of functions arises from an interface’s ability to respond to changing conditions in its neighboring bulk phases. Understanding what drives this interfacial flexibility can provide novel avenues for designing new functional interfaces. However, limiting this progress is an inadequate understanding of the subtle intermolecular and interphase interactions taking place at the molecular level. Here, we use surface-specific vibrational sum frequency generation spectroscopy combined with atomistic molecular dynamics simulations to investigate the self-assembly and structure of model ionic oligomers consisting of an oligodimethylsiloxane (ODMS) tail covalently attached to a positively charged methyl imidazolium (MIM + ) head group at buried oil/aqueous interfaces. We show how the presence of seemingly innocuous salts can impart dramatic changes to the ODMS tail conformations in the oil phase via specific ion effects and ion-pairing interactions taking place in the aqueous phase. These specific ion interactions are shown to drive enhanced amphiphile adsorption, induce morphological changes, and disrupt emergent hydrogen-bonding structures at the interface. Tuning these interactions allows for independent control over the oligomer structure in the oil phase versus interfacial population changes and represents key mechanistic insight that is needed to control chemical reactions at liquid/liquid interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Individual and Collective Strategies to Limit the Impacts of Large Power Outages of Long Duration

As modern society becomes ever more dependent on the availability of electric power, the costs that could arise from individual and social vulnerability to large outages of long duration (LLD-outages) increases. During such an outage, even a small amount of power would be very valuable. Here, this article compares individual and collective strategies for providing limited amounts of electric power to residential customers in a hypothetical New England community during a large electric power outage of long duration. We develop estimates of the emergency load required for survival and assess the cost of strategies to address outages that last 5, 10, and 20 days in either winter or summer. We find that the cost of collective solutions could be as much as 10 to 40 times less than individual solutions (less than $2 per month per home). However, collective solutions would require community-wide coordination, and if local distribution system lines are destroyed, only individual back-up systems could provide contingency power until those lines are repaired. Costs might be reduced if more robust distributed generation were employed that could be operated continuously with the ability to sell power back to the grid. Our cost-effectiveness analysis only assesses what could be done, developing estimates of preparedness cost. A decision about what should be done would require additional input from a range of stakeholders as well as some form of analytical deliberative process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Protein Factory on a Chip for Rapid Therapeutics

The potential for new, re-emerging, or engineered pandemic threats could challenge our nation's biosecurity, requiring rapid and flexible countermeasure development platforms. In healthcare, one of the main hindrances to the timely development of protein-based therapeutics for cancer, infectious disease, and other diseases has been a slow and expensive quality-controlled production stage. We present a protein-based technology that has the potential to address these crucial problems in biosecurity and healthcare by maximizing protein production and system portability, while minimizing production latency and cost. Specifically, we have developed a reusable, portable first-generation platform that leverages the advantages of cell-free protein synthesis (CFPS) and flow cells to create practical amounts of clinically relevant therapeutics. We have demonstrated that this technology is reusable and programmable, enabling a single platform that can synthesize multiple dosages of various therapeutics and vaccine in the field. Implementing this technology could mitigate pandemic threats by providing a rapidly-deployable (just-in-time), versatile (precision medicine) production of biologic therapeutics to the infected patient’s locale (point-of-care). In drug development, once promising drug variations are identified, the platform can be scaled to quickly produce practical amounts of protein for patient testing in the matter of days (vs. months) at a fraction of the cost of existing technology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Automated AI-driven Molecular Design for Therapeutic Discovery

In recent years, artificial intelligence and machine learning (AI/ML) approaches have revolutionized the process of designing new therapeutics, enabling scientists to rapidly respond to emerging threats from various pathogens. A prime example is the SARS-CoV-2 main protease, a key target for the development of antiviral inhibitors. In this study, we employed a novel, integrated approach that combines AI-driven iterative design of inhibitor candidates, screening based on physio-chemical properties and toxicity, physics-based computational modeling of protein-inhibitor interactions, and AI-assisted analysis of Native MS biophysical assay and characterization of designed candidates. Our deep learning 3D-scaffold model, which uses an input scaffold as a starting point, generated tens of thousands of compounds while preserving the key scaffold. To optimize these candidates, we calculated a comprehensive set of 136 descriptors, including both 2D and 3D molecular features, for compounds targeting the SARS-CoV-2 Main protease (Mpro) and a neurodegenerative disease-associated protein, cyclophilin (Cyp). The generated compounds were initially filtered based on their properties and then ranked according to their predicted binding affinity using our automated modeling and ML methods. Experimental validation of the Mpro candidates showing inhibitory activity demonstrates that our workflow can expedite the therapeutic discovery.

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

The Surface Chemistry and Structure of Colloidal Lead Halide Perovskite Nanocrystals

Since the initial discovery of colloidal lead halide perovskite nanocrystals, there has been significant interest placed on these semiconductors because of their remarkable optoelectronic properties, including very high photoluminescence quantum yields, narrow size- and composition-tunable emission over a wide color gamut, defect tolerance, and suppressed blinking. These material attributes have made them attractive components for next-generation solar cells, light emitting diodes, low-threshold lasers, single photon emitters, and X-ray scintillators. While a great deal of research has gone into the various applications of colloidal lead halide perovskite nanocrystals, comparatively little work has focused on the fundamental surface chemistry of these materials. While the surface chemistry of colloidal semiconductor nanocrystals is generally affected by their particle morphology, surface stoichiometry, and organic ligands that contribute to the first coordination sphere of their surface atoms, these attributes are markedly different in lead halide perovskite nanocrystals because of their ionicity. Herein, emerging work on the surface chemistry of lead halide perovskite nanocrystals is highlighted, with a particular focus placed on the most-studied composition of CsPbBr 3 . We begin with an in-depth exploration of the native surface chemistry of as-prepared, 0-D cuboidal CsPbBr 3 nanocrystals, including an atomistic description of their surface termini, vacancies, and ionic bonding with ligands. We then proceed to discuss various post-synthetic surface treatments that have been developed to increase the photoluminescence quantum yields and stability of CsPbBr 3 nanocrystals, including the use of tetraalkylammonium bromides, metal bromides, zwitterions, and phosphonic acids, and how these various ligands are known to bind to the nanocrystal surface. To underscore the effect of post-synthetic surface treatments on the application of these materials, we focus on lead halide perovskite nanocrystal-based light emitting diodes, and the positive effect of various surface treatments on external quantum efficiencies. We also discuss the current state-of-the-art in the surface chemistry of 1-D nanowires and 2-D nanoplatelets of CsPbBr 3 , which are more quantum confined than the corresponding cuboidal nanocrystals but also generally possess a higher defect density because of their increased surface area-to-volume ratios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗