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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Biogas Biocatalysis

Biogas derived from anaerobic digestion of waste streams such as biorefinery wastewater, animal, agricultural, and municipal solid waste, offers a versatile renewable energy source. Total domestic methane potential from landfill material, animal manure, wastewater, and organic waste, combined with biogas generated from AD of lignocellulosic biomass, is estimated to offer >4 quadrillion Btu potential energy. This energy could displace nearly half of current domestic natural gas consumption in the electric power sector and all consumption in the transportation sector. However, despite this promise of this feedstock, its gaseous state prevents facile integration with extant transportation and industrial infrastructure. Microbial conversion of biogas to liquid fuel and chemical intermediates offers valorization potential. However, biogas biocatalysis is currently limited by poor substrate gas-to-liquid mass transfer, low conversion efficiencies, and incomplete biogas utilization. To this end, the Biogas Biocatalysis AOP aims to develop a carbon- and energy-efficient biogas bioconversion process via techno-economic-informed strain and fermentation engineering strategies. Efforts here will improve both process economics and sustainability via process-intensified, carbon-efficient biogas bioconversion to value-added platform molecules, enabling bolt-on deployment for valorization of biogas derived from standalone AD infrastructure.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗
DOE OSTI2020

Robust Method to Identify Groundwater Affected By Redox Conditions at Los Alamos National Laboratory Legacy Cleanup Site - 20497

To facilitate the mission of the Department of Energy's (DoE's) Environmental Management Program at Los Alamos National Laboratory (LANL), a significant number of groundwater monitoring wells with depths ranging from 152-396 meter were completed for characterization and monitoring. Groundwater at Los Alamos tends to be oxygen saturated with very low concentrations of organic matter. Drilling fluids can introduce residual carbon causing an increase in microbial activity and local reducing conditions around the well, potentially impacting representativeness of groundwater data quality for redox sensitive constituents. We assert that the redox state of the wells can robustly be identified by aqueous solution concentrations of iron and manganese. An automated review process has been built into a computer-based data management system enabling an efficient screening process for identifying reducing conditions that are not caught using standard data-validation protocol, and ensures that important data quality issues are thoroughly identified and addressed in an efficient and timely manner. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Raman Spectroscopic In Situ Monitoring of Highly Turbid Media

The ability to run chemical processing more efficiently and cost effectively is a need that spans critical materials recovery and legacy nuclear waste cleanup. Sensors integrated to provide online monitoring are essential to addressing this need by providing near-real time feedback on process conditions, which can improve efficiency, aid in decision making, and reduce the need for grab sample measurements. Optical spectroscopy is well-suited for providing online chemical composition information and has been widely applied in varied chemical systems. However, applications in turbid matrices continue to represent substantial challenges to sensor performance, where absorption or scattering of excitation light can cause significant signal interference. Here, in this study, close-focus Raman probes are investigated for use in turbid media as a way to overcome the signal loss from the scattering of the Raman excitation source. This, paired with advanced data science techniques, allowed for the development of chemometric models for the accurate quantification of several analytes of interest (NO 3 – , NO 2 – , and PO 4 3– ) in highly turbid solutions with solids loadings of up to 20 wt %. This work focuses on offline sample measurement and characterization as an initial step toward the development of online monitoring capabilities. Chemical systems of interest were focused on nuclear waste at the Hanford Site, which represents highly complex matrices that could realize significant processing benefits through the integration of online monitoring.

Felmy, Heather M. [Pacific Northwest National Labo↗
DOE OSTI2021

Efficient Active Learning for Gaussian Process Classification by Error Reduction

Active learning sequentially selects the best instance for labeling by optimizing an acquisition function to enhance data/label efficiency. The selection can be either from a discrete instance set (pool-based scenario) or a continuous instance space (query synthesis scenario). In this work, we study both active learning scenarios for Gaussian Process Classification (GPC). The existing active learning strategies that maximize the Estimated Error Reduction (EER) aim at reducing the classification error after training with the new acquired instance in a onestep-look-ahead manner. The computation of EER-based acquisition functions is typically prohibitive as it requires retraining the GPC with every new query. Moreover, as the EER is not smooth, it can not be combined with gradient-based optimization techniques to efficiently explore the continuous instance space for query synthesis. To overcome these critical limitations, we develop computationally efficient algorithms for EER-based active learning with GPC. Further, we derive the joint predictive distribution of label pairs as a one-dimensional integral, as a result of which the computation of the acquisition function avoids retraining the GPC for each query, remarkably reducing the computational overhead. We also derive the gradient chain rule to efficiently calculate the gradient of the acquisition function, which leads to the first query synthesis active learning algorithm implementing EER-based strategies. Our experiments clearly demonstrate the computational efficiency of the proposed algorithms. We also benchmark our algorithms on both synthetic and real-world datasets, which show superior performance in terms of sampling efficiency compared to the existing state-of-the-art algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Advanced Drying Process for Lower Manufacturing Cost of Electrodes

For this Vehicle Technologies Incubator/Energy Storage R&D topic, Lambda Technologies teamed with Navitas Systems and proposed a new advanced drying process that promised a 5X reduction in electrode drying time and significant reduction in the cost of large format lithium batteries used in PEV's. The operating principle of the proposed process was to use penetrating radiant energy source Variable Frequency Microwaves (VFM), that are selectively absorbed by the polar water or solvent molecules instantly in the entire volume of the electrode. The solvent molecules are thus driven out of the electrode thickness making the process more efficient and much faster than convective drying method. To evaluate the Advanced Drying Process (ADP) a hybrid prototype system utilizing VFM and hot air flow was designed and fabricated. While VFM drives the solvent out of the electrode thickness, the hot air flow exhausts the solvent vapors out of the chamber. The drying results from this prototype were very encouraging. For water based anodes there is a 5X drying advantage (time & length of oven) in using ADP over standard drying system and for the NMP based cathodes the reduction in drying time has 3X benefit. For energy savings the power consumption measurements were performed to ADP prototype and compared with the convection standard drying oven. The data collected demonstrated over 40% saving in power consumption with ADP as compared to the convection drying systems. The energy savings are one of the operational cost benefits possible with ADP. To further speed up the drying process, the ADP prototype was explored as a booster module before the convection oven and for the electrode material being evaluated it was possible to increase the drying speed by a factor of 4, which could not be accomplished with the standard dryer without surface defects and cracks. The instantaneous penetration of microwave in the entire slurry thickness showed a major advantage in rapid drying of the electrode materials. For the existing electrode materials, the material analysis and cell characterization data from ADP dried electrodes showed equivalent (or slightly better) performance. However, for high loading and thicker electrode materials (for high energy densities) the ADP advantages are more prominent. There was less binder migration, the resistance was lower hence the current capacities and retention of the battery cells were higher. The success of the project has enabled credible communications with commercial end users as well as battery coating line integrators. Goal is to scale ADP up for high volume manufacturing of Li-ion battery electrodes. The implementation of ADP in high volume manufacturing will reduce a high cost production step to bring the overall price of Li-ion batteries down. This will ultimately have a positive impact on the public by making electric and hybrid vehicles more affordable.

25 ENERGY STORAGE↗
DOE OSTI2012

Zone Refining for Low Loss Plutonium Purification

In an effort to enhance plutonium purification capabilities at Los Alamos National Laboratory, further develop of the currently existing zone refining capabilities is needed to create a functional low loss processing option in support of programmatic and materials science research activities. Currently, the most effective process for converting impure plutonium dioxide (~96% pure) to high-purity plutonium metal (>99.9%), consists of the following steps: (1) reducing the dioxide to an impure Plutonium metal with calcium metal in molten calcium chloride, (2) casting the impure metal into an anode and (3) electrorefining the impure metal to produce high-purity plutonium metal. The final step in this method is only 83% efficient as compared to the >95% efficiency of the other processing steps. Other more efficient processing methods are desirable to enhance current purification activities, thereby, reducing waste generation and conserving precious materials in need of purification. Although zone refining has been used extensively to purify many lanthanides and actinides, its usefulness in purifying plutonium has yet to be fully realized.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Characterization of chemical contaminants and their spectral properties from an atmospheric pressure ns-pulsed microdischarge in neon

Portable applications of microdischarges will mandate operation in the presence of contaminant species. This paper examines the temporal evolution of microdischarge optical and ultraviolet emissions during pulsed operation by experimental methods. By varying the pulse length of a microdischarge initiated in a 4-­hole silicon microcavity array operating in a 655 Torr ambient primarily composed of Ne, we were able to measure the emission growth rates for different contaminant species native to the discharge environment as a function of pulse length. It was found that emission from hydrogen and oxygen impurities demonstrated similar rates of change, while emissions from molecular and atomic nitrogen, measured at 337.1 and 120 nm’s respectively, exhibited the lowest rate of change. We conclude that it is likely that O 2 undergoes the same resonant energy transfer process between rare gas excimers that has been shown for H 2 . Further, efficient resonant processes were found to be favored during ignition and extinction phases of the pulse, while emission at the 337.1 nm line from N 2 was favored during the intermediate stage of the plasma. In addition to experimental results, a zero-­dimensional analysis is also presented to further understand the nature of the microdischarge.

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

CEFAS Poster for Advanced Manufacturing Workshop 3/26/24

Electric-field assisted sintering (EFAS) is an advanced manufacturing method for the consolidation and processing of ceramic and metal materials. It is a particularly excellent candidate for efficient materials processing as it has greater than 90% energy cost savings and improved CO2 emissions compared to traditional sintering in a furnace. This is due to direct rapid heating of the materials and molds leveraging an electrification phenomenon called Joule heating where electrical current is passed through the sample/mold assemblies causing direct heating. The technique does have limitations though as it is traditionally a batch-process and suffers from scale up difficulties. To overcome this, researchers at Idaho National Laboratory changed the form factor of traditional EFAS instruments to develop and construct a continuous rolling electric-field assisted sintering (CEFAS) device.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Distinct Assembly Processes and Microbial Communities Constrain Soil Organic Carbon Formation

Soil stores more carbon (C) than all vegetation and the atmosphere combined. Soil C stocks are broadly shaped by temperature, moisture, soil physical characteristics, vegetation, and microbial-mediated metabolic processes. The efficiency with which microorganisms use soil C regulates the balance between C storage in soil and the atmosphere. In this review, we discuss how microbial physiology and community assembly processes determine microbial growth rate and efficiency and, in turn, soil organic C cycling through the lens of community ecology. We introduce a conceptual framework cataloging life history (i.e., growth rate, resource acquisition, and stress tolerance) and assembly traits (i.e., competition, facilitation, and dispersal) that correspond with different growth efficiencies. We also compare how dominant mycorrhizal fungal type affects growth efficiency. We propose that further development and inclusion of specific community parameters in microbial-explicit Earth system models are needed for accurately predicting soil organic C responses to global change.

carbon sequestration↗
DOE OSTI2018

Efficient accesses of data structures using processing near memory

Systems, apparatuses, and methods for implementing efficient queues and other data structures. A queue may be shared among multiple processors and/or threads without using explicit software atomic instructions to coordinate access to the queue. System software may allocate an atomic queue and corresponding queue metadata in system memory and return, to the requesting thread, a handle referencing the queue metadata. Any number of threads may utilize the handle for accessing the atomic queue. The logic for ensuring the atomicity of accesses to the atomic queue may reside in a management unit in the memory controller coupled to the memory where the atomic queue is allocated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

On the optimal sizing of power take-off systems for wave energy converters

The power take-off (PTO) system in a wave energy converter (WEC) is the means by which the energy in an ocean wave is converted into useful energy. There has been a general lack of technology convergence in the wave energy industry and PTO design has been largely device-specific with the design process determined by the WEC developer. An optimized PTO design can significantly affect the efficiency, reliability, performance, and overall cost and viability of a device. There remains a need in the marine energy industry for best practices and efficient design processes to be identified as it could greatly benefit developers and researchers in designing an optimal WEC PTO. This research utilizes the open-source Matlab-Simulink based software, WEC-Sim, which was developed by the National Renewable Energy Laboratory, and the Eagle, a high-performance computing system, to model and optimize two WECs of different archetypes and then investigates if any trends exist that can be exploited for greater efficiency in optimal PTO design. The results from this research indicate that there may be an optimal sizing for WEC PTOs for both power and PTO force rating and that substantial reductions can be made in the cost of a device without significant loss in the energy produced. Furthermore this optimal sizing may be independent of WEC type and deployment location. With an optimal, or near optimal, approach to WEC PTO sizing demonstrated, a methodology is proposed to address the challenge of nameplate ratings in the wave energy industry.

13 HYDRO ENERGY↗
DOE OSTI2011

Energy Saving Melting and Revert Reduction Technology (E-SMARRT): Design Support for Tooling Optimization

High pressure die casting is an intrinsically efficient net shape process and improvements in energy efficiency are strongly dependent on design and process improvements that reduce scrap rates so that more of the total consumed energy goes into acceptable, usable castings. Computer simulation has become widely used within the industry but use is not universal. Further, many key design decisions must be made before the simulation can be run and expense in terms of money and time often limits the number of decision iterations that can be explored. This work continues several years of work creating simple, very fast, design tools that can assist with the early stage design decisions so that the benefits of simulation can be maximized and, more importantly, so that the chances of first shot success are maximized. First shot success and better running processes contributes to less scrap and significantly better energy utilization by the process. This new technology was predicted to result in an average energy savings of 1.83 trillion BTUs/year over a 10 year period. Current (2011) annual energy saving estimates over a ten year period, based on commercial introduction in 2012, a market penetration of 30% by 2015 is 1.89 trillion BTUs/year by 2022. Along with these energy savings, reduction of scrap and improvement in yield will result in a reduction of the environmental emissions associated with the melting and pouring of the metal which will be saved as a result of this technology. The average annual estimate of CO2 reduction per year through 2022 is 0.037 Million Metric Tons of Carbon Equivalent (MM TCE).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Knowledge gaps for neuromorphic ionic computing

BACKGROUND Neuromorphic computing, inspired by the human brain’s ability to process information efficiently, represents a transformative approach to computation. In this Review, we explore the emerging field of neuromorphic ionic computing, which leverages ionic conduction and coupling to mimic neural processes, and identify critical knowledge gaps that must be addressed to realize its full potential. A central theme of the discussion is energy efficiency, a challenge that is both a limitation and an opportunity for this technology. Although complementary metal-oxide semiconductor (CMOS)–based neuromorphic technologies have made strides in scaling to billions of neurons and are increasingly applied in artificial intelligence and numerical computing, they remain orders of magnitude behind the human brain in terms of connectivity and energy efficiency. Neuromorphic ionic computing promises to overcome these limitations by leveraging the distinct architectural and operational principles of the brain. Our brains achieve this energy efficiency by combining several key features: using the same network elements to store and process information; using an incredibly complex and massively interconnected three-dimensional (3D) network of locally active elements that enables sparsity, robustness in the presence of noise, adaptation, and life-long learning; computing at comparatively low voltage and frequency; and last, taking advantage of a plethora of ions and small molecules as information carriers. Here, we propose that ionic computing systems can take advantage of similar features to achieve substantial gains in energy efficiency. ADVANCES Since the first reports of neuromorphic ionic behavior in nanofluidic channels, we have witnessed an explosion of reports that used ionic devices to produce synaptomimetic behaviors. However, achieving the goals of ionic computing requires not only implementation of much more sophisticated device functionality but also overcoming fundamental barriers in materials science, device architecture, and system integration. Current ionic devices, even those incorporating state-of-the-art materials, still suffer from limited functionality and stability, which restrict their performance and increase energy demands. Developing new materials with enhanced ionic properties is essential to overcome these limitations. Similarly, the design of neuromorphic devices must evolve to leverage the particular advantages of ionic processes. Existing architectures often follow a single-information-carrier logic of conventional electronics or are constructed of mesoscale fluidics, failing to capitalize on the energy-efficient mechanisms inherent to ionic systems or implement the multiple-information-carrier paradigm. Current neuromorphic chips focus on large-scale networks of analog memory elements based on mechanisms such as charge trap (flash), filamentary, phase change, or spin, which are built on top of a network of artificial CMOS neurons. Although such prototype networks have achieved impressive performance, it is difficult to envision how they can implement the key features such as massive connectivity, sophisticated plasticity, adaptability, sparsity, and “multichromatic” computing. Although small-scale devices have demonstrated promising results, integrating them, maintaining energy efficiency, and implementing temperature control as systems grow in complexity and size to computationally relevant scale remain major hurdles. Furthermore, interfacing neuromorphic ionic devices with existing computing technologies presents technical and conceptual challenges that will require innovative approaches that combine insights from neuroscience, materials science, and engineering. OUTLOOK Despite these challenges, the potential impact of neuromorphic ionic computing is profound with potential applications ranging from artificial intelligence to robotics and beyond. We also argue that neuromorphic ionic computing systems should not, at least in the beginning, compete with CMOS technologies but rather should focus on applications that require extreme energy efficiency with chemical and/or biological compatibility, such as biomedical applications (for example, brain-computer interfaces), environmental monitoring, and agricultural and food applications. Ultimately, this Review highlights the crucial role of interdisciplinary collaboration in advancing the field. Neuromorphic ionic computing is not merely a technological innovation; it represents a substantial step toward sustainable computation, aligning with the growing demand for energy-conscious solutions in a world that is increasingly reliant on data and computation.

Neuromorphic↗
DOE OSTI2023

Correlative montage parallel array cryo-tomography for in situ structural cell biology

Abstract Imaging large fields of view while preserving high-resolution structural information remains a challenge in low-dose cryo-electron tomography. Here we present robust tools for montage parallel array cryo-tomography (MPACT) tailored for vitrified specimens. The combination of correlative cryo-fluorescence microscopy, focused-ion-beam milling, substrate micropatterning, and MPACT supports studies that contextually define the three-dimensional architecture of cells. To further extend the flexibility of MPACT, tilt series may be processed in their entirety or as individual tiles suitable for sub-tomogram averaging, enabling efficient data processing and analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Development and Testing of an Integrated Acid Mine Drainage (AMD) Treatment and Rare Earth/Critical Mineral Plant

The overall objective of this project was to design, construct, and test a pilot-scale continuous process for efficiently treating acid mine drainage (AMD) while producing rare earth element/critical mineral (REE/CM) concentrates. The process technology evaluated in this project included two distinct operations: 1. an upstream pre-concentration unit that treats raw AMD to environmentally compliant discharge standards while capturing an REE/CM preconcentrate, and 2. a downstream REE purification process that further enriches the pre-concentrate while producing mixed or partially separated rare earth oxides (REOs). The project team members successfully completed all of the proposed goals of the project and advanced the technology readiness levels (TRL) of the constituent operations to TRL 7 for the upstream concentration unit (full-scale system demonstration) and TRL 6 for the downstream purification process (pilot-scale demonstration).

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2018

Transforming the Chemical Industry

There are huge reservoirs of oil in the deep waters of the Gulf of Mexico. A major oil company is now retrieving that oil safely, despite huge challenges—oil leaves the seabed at boiling hot temperatures, through 7,000 feet of steel pipe exposed to corrosive saltwater at temperatures near freezing. An extra margin of safety comes from a specialized plastic coating on the pipe that both insulates and protects the pipe: it can cope with oil as hot as 390º. The special plastic is made from chains of carbon-based molecules (called polymers) that do not occur in nature. Rather they are the result of a powerful chemical process developed over decades of research by two university scientists—research supported by the Basic Energy Sciences (BES) office of DOE and other federal agencies—for which they were both awarded a Nobel Prize. That process expanded the chemical industry’s toolset, enabling many new products as well as more efficient production processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Development of Ultrafiltration Membrane-Separation Technology for Energy-Efficient Water Treatment and Desalination Process

The growing scarcity of fresh water is a major political and economic challenge in the 21st century. Compared to thermal-based distillation technique of water production, pressure driven membrane-based water purification process, such as ultrafiltration (UF), nanofiltration (NF) and reverse osmosis (RO), can offer more energy-efficient and environmentally friendly solution to clean water production. Potential applications also include removal of hazardous chemicals (i.e., arsenic, pesticides, organics) from water. Although those membrane-separation technologies have been used to produce drinking water from seawater (desalination) and non-traditional water (i.e., municipal wastewater and brackish groundwater) over the last decades, they still have problems in order to be applied in large-scale operations. Currently, a major huddle of membrane-based water purification technology for large-scale commercialization is membrane fouling and its resulting increases in pressure and energy cost of filtration process. Membrane cleaning methods, which can restore the membrane properties to some degree, usually cause irreversible damage to the membranes. Considering that electricity for creating of pressure constitutes a majority of cost (~50%) in membrane-based water purification process, the development of new nano-porous membranes that are more resistant to degradation and less subject to fouling is highly desired. Styrene-ethylene/butylene-styrene (SEBS) block copolymer is one of the best known block copolymers that induces well defined morphologies. Due to the polarity difference of aromatic styrene unit and saturated ethylene/butylene unit, these two polymer chains self-assemble each other and form different phase-separated morphologies depending on the ratios of two polymer chain lengths. Because the surface of SEBS is hydrophobic which easily causes fouling of membrane, incorporation of ionic group (e,g, sulfonate) to the polymer is necessary to reduces fouling. Recently, sulfonated SEBS became commercially available and has been extensively explored for membrane-mediated water purification technology. The sulfonated block copolymer creates a well developed nano-sale phase-separated morphologies composed of hydrophilic domains (sulfonated polystyrene) and hydrophobic domains (polyethylene/polybutylene). The hydrophilic domains determines transport properties (water transport, salt and/or ion rejection, etc) and the hydrophobic domains provides mechanical stability of the membrane. Unfortunately, a high degree of sulfonation of SEBS induces excessive swelling and deterioration of mechanical stability of the membrane. In an effort to develop robust polymeric membrane materials for water purification technology, phosphonic acid-functionalized SEBS membranes are investigated during this report period. In compare to sulfonated polymers, the corresponding phosphonated polymers are known to swell less because of the formation of extensive hydrogen bonding networks between phosphonates. In addition to the expected better mechanical stability, phosphonated polymers has another advantage over sulfonated polymers for the use water purification membrane; each phosphonate can accommodate two ions while each sulfonate accommodates only one ion. Membrane properties (ion type, ionic density, etc) of new membranes will be studied and their separation performance will be evaluated in water purification and desalination process. Through systematic study of the relationship of chemical structure–surface property–membrane performance, we aim to better understand the nature of membrane fouling and develop more fouling-resistant water purification membranes. The basic understanding of this relationship will lead to the development of advanced membrane materials which can offer a solution to environmentally sustainable production of fresh water.

36 MATERIALS SCIENCE↗