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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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Energy storage, which has revolutionized consumer electronics, is poised to change the way we drive our cars and the way we generate and use electricity. Leveraging four decades of numerous path-breaking innovations in energy storage, Argonne is leading the way in ushering in this change.
Particle accelerators have been essential tools of particle physics since initial development in the early twentieth century, with commercial applications soon following each successive advancement. Furthermore, particle accelerators today are found in diverse use, ranging from ion-implantation of consumer electronics to both imaging and treatment of cancers.
While consumer electronics and electric vehicles continue to push the market demanding for more energy in existing Li-ion batteries and lower costs, advanced battery designs could not meet the expectation to produce reliable and safe products at such a pace. There is a need to holistically re-think the design approach. INL's expertise in the current research of battery diagnostics and prognostics could fill this gap. In this presentation, the concept and approach will be discussed to explain why this is feasible and possible to change the paradigm of battery technology development from the conventional path.
The concept of the Ad-Mat approach is to leverage existing adjacent markets across a broad scope of technologies in order to reduce the manufacturing learning curve and ultimately accelerate redox flow battery (RFB) deployment at scale. Lithium-ion batteries (LIBs) are currently the dominant energy storage technology, and they came to technological maturity under unique market conditions when there was no meaningful competition in the consumer electronic and electric vehicle (EV) space. Today, alternative chemistries that may be technologically better-suited for long-duration storage applications are experiencing a high barrier to entry. This is in large part due to the substantial bias towards the scaled-up production and supply chain that now exists for LIBs. In the case of RFBs in particular, numerous analyses have suggested that RFBs should theoretically have a much lower system cost than LIBs - however, this relies on a mature and competitive manufacturing landscape, which has been extremely challenging to achieve for both flow batteries and other LIB competitors. At the moment, LIB alternatives tend to have isolated small-scale manufacturing pathways, which preclude the economies of scale that would be required to compete with the mature LIB industry. In the present state of the industry, niche manufacturing tools and approaches have evolved to support each alternative technology, such that there is substantial replication and duplication in effort. Continuing to pursue a strategy of isolated manufacturing processes/approaches for each LIB-alternative may never allow for at-scale deployment. In order for RFBs to meaningfully compete with LIBs in the realm of LDES, a new disruptive approach based on cross-industry learning and coordination is needed - and this is exactly what our Ad-Mat concept aims to tackle. In this re-envisioned manufacturing landscape, tools and processes from mature industries can be adapted and deployed across the range of alternative energy storage technologies. Adapting tools, equipment, processes, and industrial learning from mature industries to meet the technological requirements of RFBs would open new markets for existing OEMs in adjacent industries, would prevent unnecessary duplication and re-development, would improve efficiency across the manufacturing chain, and would ultimately support reduced costs and accelerated deployment of RFBs at scale.
The response of an oxide crystal to the atmosphere can be personified as breathing-a dynamic equilibrium between O 2 gas and O 2– anions in the solid. We characterize the analogous defect reaction in an iodide double-perovskite semiconductor, Cs 2 SnI 6 . Here, I 2 gas is released from the crystal at room temperature, forming iodine vacancies. The iodine vacancy defect is a shallow electron donor and is therefore ionized at room temperature; thus, the loss of I2 is accompanied by spontaneous n-type self-doping. Conversely, at high I 2 pressures, I 2 gas is resorbed by the perovskite, consuming excess electrons as I 2 is converted to 2I – . Halide mobility and irreversible halide loss or exchange reactions have been studied extensively in halide perovskites. However, the reversible exchange equilibrium between iodide and iodine [2I – (s) ↔ I 2(g) + 2e – ] described here has often been overlooked in prior studies, though it is likely general to halide perovskites and operative near room temperature, even in the dark. An analysis of the 2I – (s) /I 2(g) equilibrium thermodynamics and related transport kinetics in single crystals of Cs 2 SnI 6 therefore provides insight toward achieving stable composition and electronic properties in the large family of iodide perovskite semiconductors.
This paper reviews current progress on flexible and stretchable transistors and sensors for the next-generation multiplex electronics (commonly referred to as 'electronics skin' or 'e-skin') that is capable of simultaneous detection of multiple information from a variety of surfaces including human skin. Flexible chemical sensors for sweat analysis as well as physical sensors for detecting tactile force, bending, and temperature will be discussed, with emphasis on materials, detection mechanisms, and device demonstration to realize multiplex human-interactive devices. System integration enabling the real-time monitoring of health conditions is also demonstrated as a proof of concept. Finally, perspectives on e-skin for moving toward realizing practical wearable electronics in the market are discussed. This paper targets the translation of the nano- and flexible technologies from academic innovations to industrial practical applications with high-impact breakthroughs.
Abstract The challenge of sustainably producing goods and services for healthy living on a healthy planet requires simultaneous consideration of economic, societal, and environmental dimensions in manufacturing. Enabling technology for data driven manufacturing paradigms like Smart Manufacturing (a.k.a. Industry 4.0) serve as the technological backbone from which sustainable approaches to manufacturing can be implemented. Unfortunately, these technologies are typically associated with broader and deeper factory automation that is often too expensive and complex for the small and medium sized manufacturers (SMMs) that comprise the majority of manufacturing business in the USA and for whom their most valuable asset are the people whose jobs automation while replace. This paper describes an edge intelligent platform to integrate internet‐of‐things technologies with computing hardware, software, computational workflows for machine learning, and data ingestion, enabling SMMs to transition into smart manufacturing paradigms by leveraging the intelligence of their people. The platform leverages consumer grade electronics and sensors (affordable and portable), customized software with open source software packages (accessible), and existing communication network infrastructures (scalable). The software systems are implemented via Kubernetes orchestration of Docker containerization to ensure scalability and programmability. The platform is adaptive via computational workflow engines that produce information from data by processing with low‐cost edge computing devices while efficiently accessing resources of cloud servers as needed. The proposed edge platform connects workers to technological resources that provide computational intelligence (i.e., silicon‐based sensing and computation for data collection and contextualization) to enable decision making at the edge of advanced manufacturing.
The Oak Ridge National Laboratory (ORNL) has pioneered an approach where low-cost consumer-grade electronics can be used as the basis of a highly reliable data acquisition architecture. One twenty-channel system based on this approach has been operating almost 4 years at ORNL. The architecture allows a mix-and-match level of configurability so the designer can select devices that best match the desired performance trade-offs. The most important device to be selected is the analog-to-digital converter. This paper explores the performance of several candidate audio recording devices that can be used as high-speed analog-to-digital converters for such measurement systems. Various performance metrics are explored including frequency response, noise floor, and synchronous sampling. Sample rates as high as 192 KHz are supported with 16 and 24-bit resolution. While most of the devices are dual-channel, there are multi-channel devices now available that will allow modal type of synchronous sampling. One such device was tested and is discussed is this paper.
The persistent low temperature that characterize polar habitats combined with the requirement for light for all photoautotrophs creates a conundrum. The absorption of too much light at low temperature can cause an energy imbalance that decreases photosynthetic performance that has a negative impact on growth and can affect long-term survival. The goal of this review is to survey the mechanism(s) by which polar photoautotrophs maintain cellular energy balance, that is, photostasis to overcome the potential for cellular energy imbalance in their low temperature environments. Photopsychrophiles are photosynthetic organisms that are obligately adapted to low temperature (0⁰- 15 °C) but usually die at higher temperatures (≥20 °C). In contrast, photopsychrotolerant species can usually tolerate and survive a broad range of temperatures (5⁰- 40 °C). First, we summarize the basic concepts of excess excitation energy, energy balance, photoprotection and photostasis and their importance to survival in polar habitats. Second, we compare the photoprotective mechanisms that underlie photostasis and survival in aquatic cyanobacteria and green algae as well as terrestrial Antarctic and Arctic plants. We show that polar photopsychrophilic and photopsychrotolerant organisms attain energy balance at low temperature either through a regulated reduction in the efficiency of light absorption or through enhanced capacity to consume photosynthetic electrons by the induction of O 2 as an alternative electron acceptor. Finally, we compare the published genomes of three photopsychrophilic and one photopsychrotolerant alga with five mesophilic green algae including the model green alga, Chlamydomonas reinhardtii. We relate our genomic analyses to photoprotective mechanisms that contribute to the potential attainment of photostasis. Finally, we discuss how the observed genomic redundancy in photopsychrophilic genomes may confer energy balance, photoprotection and resilience to their harsh polar environment. Primary production in aquatic, Antarctic and Arctic environments is dependent on diverse algal and cyanobacterial communities. Although mosses and lichens dominate the Antarctic terrestrial landscape, only two extant angiosperms exist in the Antarctic. Furthermore, the identification of a single ‘molecular key’ to unravel adaptation of photopsychrophily and photopsychrotolerance remains elusive. Since these photoautotrophs represent excellent biomarkers to assess the impact of global warming on polar ecosystems, increased study of these polar photoautotrophs remains essential.
The reactivity of molecular oxygen is crucial to clean energy technologies and green chemical synthesis, but kinetic barriers complicate both applications. In synthesis, dioxygen should be able to undergo oxygen atom transfer to two organic molecules with perfect atom economy, but such reactivity is rare. Monooxygenase enzymes commonly reductively activate dioxygen by sacrificing one of the oxygen atoms to generate a more reactive oxidant. Here, we used a manganese-tetraphenylporphyrin catalyst to pair electrochemical oxygen reduction and water oxidation, generating a reactive manganese-oxo at both electrodes. This process supports dioxygen atom transfer to two thioether substrate molecules, generating two equivalents of sulfoxide with a single equivalent of dioxygen. This net dioxygenase reactivity consumes no electrons but uses electrochemical energy to overcome kinetic barriers.
Digital networks are the foundation of the information services, and play an expanding and indispensable role in our lives, via the Internet, email, mobile phones, etc. However, these networks consume energy, both through the direct energy use of the network interfaces and equipment that comprise the network, and in the effect they have on the operating patterns of devices connected to the network. The purpose of this research was to investigate a variety of technology and policy issues related to the energy use caused by digital networks, and to further develop several energy-efficiency technologies targeted at networks.
PFCs Extent of Problem: Widely used in aerospace, automotive, building and construction, electronics, and consumer products; found in tap water of over 15 M Americans; detectable levels in blood of 96% of those tested; and linked to public health issues like cancer; EPA health advisory of 70 parts per trillion.
With the rapid concurrent advance of artificial intelligence (AI) and Internet of Things (IoT) technology, manufacturing environments are being upgraded or equipped with a smart and connected infrastructure that empowers workers and supervisors to optimize manufacturing workflow and processes for improved energy efficiency, equipment reliability, quality, safety, and productivity. This challenges capital cost and complexity for many small and medium-sized manufacturers (SMMs) who heavily rely on people to supervise manufacturing processes and facilities. This research aims to create an affordable, scalable, accessible, and portable (ASAP) solution to automate the supervision of manufacturing processes. The proposed approach seeks to reduce the cost and complexity of smart manufacturing deployment for SMMs through the deployment of consumer-grade electronics and a novel AI development methodology. The proposed system, AI-assisted Machine Supervision (AIMS), provides SMMs with two major subsystems: direct machine monitoring (DMM) and human-machine interaction monitoring (HIM). The AIMS system was evaluated and validated with a case study in 3D printing through the affordable AI accelerator solution of the vision processing unit (VPU).
Aluminum is increasingly used in consumer products and in lightweighting applications for airplanes, passenger cars and other vehicles. However, smelting primary aluminum is an energy-intensive process, and advanced low-energy smelting technologies have not yet been successfully scaled up to commercial production. Another way to reduce energy consumption associated with aluminum use is to increase the amount of secondary aluminum (recovered from manufacturing scrap and from recycled products) used as a raw material, thereby increasing the circularity of aluminum flows. This too has proven difficult due to the relatively low rates of recycling for most aluminum-containing products in the U.S., and the inevitable alloy mixing that occurs when end-of-life products are broken down during recycling. We previously investigated strategies for increasing secondary aluminum use, within limitations imposed by the presence of alloying elements and alloy requirements for new products. In this work, we provide context and assess the feasibility of those strategies by investigating established patterns and attitudes around recycling, remanufacturing, and other methods that promote circular material flows. Our objective is to identify technological, logistical, economic, and other barriers that exist to implementing such methods in aluminum-intensive sectors. A secondary objective is to construct a hypothetical blue-sky scenario in which aluminum use in the U.S. approaches a fully circular material flow. The blue-sky scenario allows us to identify future barriers to increasing material flow circularity and to gauge the scenario's attainability relative to current industrial practice. Our focus goes beyond recycling, in which an end-of-life product is disassembled, processed, and then separated into its component materials which serve as inputs for new products. While common in the U.S. and globally, this type of recycling involves non-trivial energy expenditures in the scrapping and processing stages and leads to impure streams of mixed secondary materials that may not be feasible or economical to use. We also consider consumer and manufacturer practices including refurbishing, remanufacturing, repair and reuse. None of these practices require that products are broken down into separate material streams before reconstitution into new products; the energy requirements are therefore lower, and the secondary components potentially easier and more economical to use. We evaluate each of these methods in terms of their economic viability for the consumer, the (re-)manufacturing firm and the scrapping and recycling firm. We also investigate barriers to and drivers of these circular practices, with particular attention paid to consumer attitudes. Initial research indicates that for consumer recycling, convenience of the recycling system is of paramount importance, with pre-existing attitudes towards recycling on a personal and community level almost as important. On the manufacturer side, a variety of logistical and economic barriers exist to instituting widespread product take-back and refurbishment programs. To better understand these barriers and how they can be overcome, we investigate several U.S. manufacturers that currently operate take-back, refurbishment and repair programs for their products, and conduct a review of similar programs in European countries where such programs are mandated by law rather than being conducted voluntarily.
A considerable amount of energy is consumed to cool electronic equipment in data centers. A method for substantially reducing the energy needed for this cooling was demonstrated. The method involves immersing electronic equipment in a non-conductive liquid that changes phase from a liquid to a gas. The liquid used was 3M Novec 649. Two-phase immersion cooling using this liquid is not viable at this time. The primary obstacles are IT equipment failures and costs. However, the demonstrated technology met the performance objectives for energy efficiency and greenhouse gas reduction. Before commercialization of this technology can occur, a root cause analysis of the failures should be completed, and the design changes proven.
Proton mirror modes are large amplitude nonpropagating structures frequently observed in the magnetosheath. It has been suggested that electron temperature anisotropy can enhance the proton mirror instability growth rate while leaving the proton cyclotron instability largely unaffected, therefore causing the proton mirror instability to dominate the proton cyclotron instability in Earth's magnetosheath. In this paper we use particle-in-cell simulations to investigate the electron temperature anisotropy effects on proton mirror instability evolution. Contrary to the hypothesis, electron temperature anisotropy leads to excitement of the electron whistler instability. Finally, our results show that the electron whistler instability grows much faster than the proton mirror instability and quickly consumes the electron-free energy so that there is no electron temperature anisotropy left to significantly impact the evolution of the proton mirror instability.
Here, a computational framework for assisting in the development of novel textiles is presented. Electronic textiles are key in the rapidly growing field of wearable electronics for both consumer and military uses. There are two main challenges to the modeling of electronic textiles: the discretization of the textile microstructure and the interaction between electromagnetic and mechanical fields. A director-based beam formulation with an assumed electrical current is used to discretize the fabric at the level of individual fibrils. The open-source package FEniCS was used to implement the finite element model. Contact integrals were added into the FEniCS framework so that multiphysics contact laws can be incorporated in the same framework, leveraging the code generation and automated differentiation capabilities of FEniCS to produce the tangents needed by the implicit solution method. The computational model is used to construct and determine the mechanical, thermal, and electrical properties of a representative volume elements of a plain woven textile. Dynamic relaxation to solve the mechanical fields and the electrical and thermal fields is solved statically for a given mechanical state. The simulated electrical responses are fit to a simplified Kirchhoff network model to determine effective resistances of the textile.
Energy efficient control of a cooling system cooling an electronic system is provided based, in part, on projected conditions. The control includes automatically determining an adjusted control setting(s) for an adjustable cooling component(s) of the cooling system. The automatically determining is based, at least in part, on projected power consumed by the electronic system at a future time and projected temperature at the future time of a heat sink to which heat extracted is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the cooling system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on an experimentally obtained model(s) relating the targeted temperature and power consumption of the adjustable cooling component(s) of the cooling system.