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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Effect of Viscosity of a Deep Eutectic Solvent on CO 2 Capture Performance in an Energy-Efficient Membrane Contactor-Based Process

Greenhouse gas contributions to climate change have driven intense interest in the separation of CO 2 from wet flue gas streams. Deep eutectic solvents (DESs) are an emerging class of highly selective CO 2 absorbents. A prototypical DES, reline, is a mixture of choline chloride and urea. Reline is a thermally stable, nontoxic, and biodegradable solvent with negligible volatility and is inexpensive. We demonstrate a scalable and energy-efficient hollow fiber membrane contactor (HFMC)-based process using a green solvent for CO 2 capture. This process uses reline in HFMC to provide close interfacial interactions and contact between DES and CO 2 . This approach overcomes the disadvantages associated with direct absorption in DES and could potentially be applied to a variety of solvent-based CO 2 capture methods. Commercial, low-cost polymer hollow fiber membranes were evaluated for the capture of CO 2 with reline. From a mixed gas containing N 2 and CO 2 , the DES-based HFMC separated CO 2 with a purity of 97 mol %. The effect of the viscosity of reline on the CO 2 capture performance was investigated by adding water to the reline. The addition of water to reline significantly reduced its viscosity, which led to a permeate flux of 170 mmol/(m 2 ·h) at 35 °C, 4 bar, and 60 wt % water in solvent, which was approximately 8 times higher than that of the pure reline in the membrane contactor system. In situ Fourier transform infrared spectroscopy and nuclear magnetic resonance (NMR) revealed that reline absorbs CO 2 by physical absorption without forming new chemical compounds and that CO 2 separation by reline occurs via the pressure swing mechanism. This research provides fundamental insights about green physical solvent-based separation processes and a pathway toward industrial deployment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Energy Efficient Large-Scale Storage of Liquid Hydrogen

World’s largest LH2storage tanks constructed in mid-1960s at NASA/KSC. These vacuum-perlite insulated tanks, still in service today, are 3,200 m3capacity (ea.). In 2018, construction began on an additional 4,700 m3LH2storage tank at LC-39B•NASA’s new Space Launch System (SLS) heavy lift rocket for Artemis program holds 2,033 m3of LH2in its 8.4-m diameter by 40-m height. Two new energy-efficient technologies are included: glass bubbles insulation system and an Integrated Refrigeration and Storage (IRAS) heat exchanger for passive + active thermal control:•Evacuated glass bubbles insulation system has been shown to reduce LH2boiloff by 46% versus perlite in field demonstrations. Controlled storage via IRAS, when fully implemented, will provide full control of ullage pressure, zero boiloff, and even production of densified LH22CEC-2021

cryogenics↗
DOE OSTI2013

Regency Centers Develops Leadership in Energy-Efficient Renovations

Regency Centers (Regency) partnered with the Department of Energy (DOE) to develop and implement solutions to retrofit existing buildings to reduce energy consumption by at least 30% versus requirements set by Standard 90.1-2004 of the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE), the American National Standards Institute (ANSI), and the Illuminating Engineering Society of North America (IESNA) as part of DOE’s Commercial Building Partnerships (CBP) Program.

EEMs↗
DOE OSTI2018

Evaluation of the Energy-Efficiency of an Aerated Slurry-Infiltrated Mesh Building System with Biomass-Based Insulation

Experimental investigations and numerical analyses were conducted on the thermal attributes of a building system made with locally available structural and insulation materials. The structural material, which also offers some insulation qualities, is referred to as aerated slurry-infiltrated mesh. The insulation materials used in this building are based on biomass; the alternatives considered here include ground wood, shredded straw, and cellulose. Thermal conductivity tests were performed on aerated slurries of different bulk densities, and on the biomass-based insulation materials, some of which were prepared with different bulk densities. The competitive merits of the biomass-based indigenous insulation materials were assessed. The correlations between bulk density and thermal conductivity were evaluated and rationalized based on the prevalent mechanisms of heat transfer in different materials. The effects of temperature on the thermal conductivity of different biomass-based indigenous insulation materials were investigated. For wall insulation, a cost analysis was conducted in order to select the optimum insulation level. As a result, the thermal mass of the aerated slurry-infiltrated mesh building system was found to favor its energy-efficiency when compared with a similar wood building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A Robust, Scalable Platform for the Electrochemical Conversion of CO 2 to Formate: Identifying Pathways to Higher Energy Efficiencies

This work demonstrated a robust, scalable cell architecture for electroreduction of CO 2 (CO 2 R). An up to 90% faradaic efficiency for the conversion of CO 2 R to formate at 500 mA/cm 2 was realized at a 25 cm2 gas diffusion electrode (GDE) with a carbon-supported SnO 2 electrocatalyst. Furthermore, a 1.27 mm thick catholyte was used between the bipolar membrane and cathode GDE, which could be further reduced to tens of micrometers upon refinement. The deconvolution of the potential drop from each individual component/process guides the pathways to higher energy efficiencies of CO 2 R at this platform. Significant changes in the agglomerate size and aspect ratio on the electrode before and after an 11 h test were revealed by nano-CT, suggesting reduced CO 2 accessibility from electrode degradation. The versatility of this CO 2 R testing platform enables the ability to assess materials, components, and interactions at scales more in line with future devices.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2018

Ageless Aluminum-Cerium-Based Alloys in High-Volume Die Casting for Improved Energy Efficiency

Strong chemical reactions between Al and Ce lead to the formation of intermetallics with exceptional thermal stability. The rapid formation of intermetallics directly from the liquid phase during solidification of Al-Ce alloys leads to an ultrafine microconstituent structure that effectively strengthens as-cast alloys without further microstructural optimization via thermal processing. Die casting is a high-volume manufacturing technology that accounts for greater than 40% of all cast Al products, whereas Ce is highly overproduced as a waste product of other rare earth element (REE) mining. Reducing heat treatments would stimulate significant improvements in manufacturing energy efficiency, exceeding (megatonnes/year) per large-scale heat-treatment line. In this study, multiple compositions were evaluated with wedge mold castings to test the sensitivity of alloys to the variable solidification rate inherent in high-pressure die casting. Once a suitable composition was determined, it was successfully demonstrated at 800 lbs/h in a 600-ton die caster, after which the as-die cast parts performed similarly to ubiquitous A380 in the same geometry without requiring heat treatment. Furthermore, this work demonstrates the compatibility of Al REE alloys with high-volume die-casting applications with minimal heat treatments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Advances in Desiccant Wheels for Dehumidification, VOC Mitigation, and CO 2 Removal for Energy-Efficient IAQ Management

Humidity control is pivotal to maintain occupant thermal comfort and suppress mold growth in indoor environments. Furthermore, poor indoor air quality (IAQ) due to the presence of volatile organic compounds (VOCs) and high concentrations (>1,000 ppm) of CO 2 can cause health issues and negatively affect cognitive performance. Therefore, providing high-quality indoor air has gained significant attention over the past decade. Conventional cooling coil and filter-based HVAC systems have limited capability to meet the augmented demand for occupant thermal comfort and high indoor air quality. Moreover, modern buildings are increasingly airtight to save energy, and increasing ventilation to mitigate VOC and CO 2 concentration is discouraged. Separate sensible and latent cooling technology using a rotary desiccant wheel presents a promising solution in this respect. Because of the development of desiccant materials with high water vapor, VOC, and CO 2 uptake, desiccant wheels can be used as an integrated technology option for IAQ management. Here, to promote desiccant wheel use for energy-efficient management of IAQ in buildings, this article reviews recent advancements in using desiccant wheels for dehumidification, VOC mitigation, and CO 2 capture from outdoor air. Finally, the article presents the authors’ perspective by summarizing the key research gaps in the field and discussing the future direction of research to address these gaps from two different aspects, namely, suitable adsorbent material development and desiccant wheel design.

CO2 capture↗
DOE OSTI2020

Efficient Energy Funneling in Quasi‐2D Perovskites: From Light Emission to Lasing

Abstract Quasi‐2D Ruddlesden–Popper halide perovskites with a large exciton binding energy, self‐assembled quantum wells, and high quantum yield draw attention for optoelectronic device applications. Thin films of these quasi‐2D perovskites consist of a mixture of domains having different dimensionality, allowing energy funneling from lower‐dimensional nanosheets (high‐bandgap domains) to 3D nanocrystals (low‐bandgap domains). High‐quality quasi‐2D perovskite (PEA) 2 (FA) 3 Pb 4 Br 13 films are fabricated by solution engineering. Grazing‐incidence wide‐angle X‐ray scattering measurements are conducted to study the crystal orientation, and transient absorption spectroscopy measurements are conducted to study the charge‐carrier dynamics. These data show that highly oriented 2D crystal films have a faster energy transfer from the high‐bandgap domains to the low‐bandgap domains (<0.5 ps) compared to the randomly oriented films. High‐performance light‐emitting diodes can be realized with these highly oriented 2D films. Finally, amplified spontaneous emission with a low threshold 4.16 µJ cm −2 is achieved and distributed feedback lasers are also demonstrated. These results show that it is important to control the morphology of the quasi‐2D films to achieve efficient energy transfer, which is a critical requirement for light‐emitting devices.

Lei, Lei↗
DOE OSTI2020

Mutually Reinforced Polymer–Graphene Bilayer Membranes for Energy‐Efficient Acoustic Transduction

Abstract Graphene holds promise for thin, ultralightweight, and high‐performance nanoelectromechanical transducers. However, graphene‐only devices are limited in size due to fatigue and fracture of suspended graphene membranes. Here, a lightweight, flexible, transparent, and conductive bilayer composite of polyetherimide and single‐layer graphene is prepared and suspended on the centimeter scale with an unprecedentedly high aspect ratio of 10 5 . The coupling of the two components leads to mutual reinforcement and creates an ultrastrong membrane that supports 30 000 times its own weight. Upon electromechanical actuation, the membrane pushes a massive amount of air and generates high‐quality acoustic sound. The energy efficiency is ≈ 10–100 times better than state‐of‐the‐art electrodynamic speakers. The bilayer membrane's combined properties of electrical conductivity, mechanical strength, optical transparency, thermal stability, and chemical resistance will promote applications in electronics, mechanics, and optics.

Khan, Assad U.↗
DOE OSTI2022

Automated Mobility Platforms: A Framework for Versatile, Energy-Efficient Urban Transportation for the 21st Century: Preprint

This paper presents automated mobility platforms (AMPs) as a framework to deliver high-quality urban mobility. AMPs leverage advances in sensing technology developed from automated roadway vehicles to provide opportunities for efficient movement of people and goods in dense urban environments, campuses, and large facilities like airports. In this paper, we layout the concept of AMPs and how they can serve the mobility needs of the population by providing service at the intersection of micromobility (services such as electric scooters or bikes), personal rapid transit, and moving walkways. Several key attributes and justification for the AMPs concept are described, including improvements to accessibility (inherent in design) covering both socioeconomic and disability equity, safety, energy efficiency, cost-effectiveness, urban land and space management, and scalability. We summarize the results from an ongoing national laboratory-sponsored, faculty-supported, student-led investigation into AMPs that includes stakeholder engagement and technical feasibility assessment.

ADVANCED PROPULSION SYSTEMS↗
NASA NTRSDate not supplied

Energy Efficient Large-Scale Storage of Liquid Hydrogen

The world’s largest liquid hydrogen storage tanks were constructed in the mid-1960sat the NASA Kennedy Space Center. These two vacuum-jacketed, perlite powder insulated tanks, still in service today, have 3,200 m3 of useable capacity. In 2018, construction began on an additional storage tank at Launch Complex 39B. This new tank will give an additional storage capacity of 4,700 m3 for a total on-site storage capacity of roughly 8,000 m3. NASA’s new Space Launch System (SLS) heavy lift rocket for the Artemis program includes an LH2tank that makes up the bulk of the vehicle, holding 2,033 m3 of LH2 in its 8.4-m diameter by40-m height. The new storage tank includes two new energy-efficient technologies: a glass bubbles insulation system in lieu of perlite, and an Integrated Refrigeration and Storage (IRAS)heat exchanger for controlled storage capability. The evacuated glass bubbles insulation system is based on the prior two decades of research to prove the thermal performance benefits as well as the mechanical and vacuum integrity; and has been shown to reduce LH2 boiloff by 46%versus perlite in field demonstrations. The IRAS capability is centered on a heat exchanger system that is built within the inner vessel to reject heat from the bulk liquid through the future implementation of an external helium refrigerator. Controlled storage via IRAS, when fully implemented, will provide full control of the ullage pressure, zero boiloff, and even production of densified LH2 pending its adoption on future launch vehicles. The design basics are described along with main construction and testing processes involved. The key features of the new technology items and implications on simplified operations and long-term energy savings are addressed

cryogenics↗
DOE OSTI2022

Neuromorphic scaling advantages for energy-efficient random walk computations

Neuromorphic computing, which aims to replicate the computational structure and architecture of the brain in synthetic hardware, has typically focused on artificial intelligence applications. What is less explored is whether such brain-inspired hardware can provide value beyond cognitive tasks. Here we show that the high degree of parallelism and configurability of spiking neuromorphic architectures makes them well suited to implement random walks via discrete-time Markov chains. Overall, these random walks are useful in Monte Carlo methods, which represent a fundamental computational tool for solving a wide range of numerical computing tasks. Using IBM’s TrueNorth and Intel’s Loihi neuromorphic computing platforms, we show that our neuromorphic computing algorithm for generating random walk approximations of diffusion offers advantages in energy-efficient computation compared with conventional approaches. We also show that our neuromorphic computing algorithm can be extended to more sophisticated jump-diffusion processes that are useful in a range of applications, including financial economics, particle physics and machine learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Hardware and Software Co-design Framework for Energy Efficient Neuromorphic Systems

Neuromorphic systems can be realized by a variety of algorithms and architectures. A common understanding is that spiking neuromorphic designs, which encode information into spatio-temporal spiking events, are both a biologically-accurate and efficient way of processing information. However, representing the information through timing relationships induces sophisticated circuit designs in traditional CMOS-based implementations. In recent years, high-capacity resistive memory (RRAM, aka, memristor) has demonstrated great potential in mimicking synaptic behaviors. Several RRAM-based spiking neuromorphic designs exist, most of which focus on rate coding schemes. These designs simplify circuit implementations of neuron models and explore challenges such as unsatisfactory speed, resolution, and performance. As an alternative, we will explore temporal coding spiking neuromorphic systems that encode information as the relative timing of neuron activations (spikes), which have been proven to be more adaptive and energy-efficient. Developing a neuromorphic system for spiking neural network (SNN) inference and online training, however, faces some major technical challenges: (1) It lacks circuit implementation support for temporal-coding SNN to achieve satisfying power efficiency and accuracy; (2) Although existing research works have investigated memristive synapse and neuron designs for spike-timing-dependent plasticity, the non-ideal conditions in implementation, such as device variations and signal degradation, degrade online learning accuracy of large scale systems; and (3) Non-optimized, inter-layer data traffic in SNNs, leads to unnecessary data communication costs. In this project, we plan to address these challenges by a hardware and software co-design framework that incorporates solutions at the circuit, architecture, and algorithm levels. At the circuit-level, we will elaborate on the in-situ SNN processing element designs for supporting both inference and online training modes. Variation-aware schemes will be studied to improve reliability. At the architecture level, we propose a pipelined, asynchronous architecture to retain the timing resolution of spikes. At the algorithm level, we will investigate an innovative SNN training algorithm for enabling activation sparsification and reducing unnecessary data communication costs. This neuromorphic system will provide an effective solution to real-life energy-constrained applications and significantly contribute to the exploration of next-generation high-performance computing systems under the DOE context.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Li 3 PO 4 Matrix Enables a Long Cycle Life and High Energy Efficiency Bismuth-Based Battery

Bismuth is a lithium-ion battery anode material that can operate at an equilibrium potential higher than graphite and provide a capacity twice as high as that of Li 4 Ti 5 O 12 , making it intrinsically free from lithium plating that may cause catastrophic battery failure. However, the potential of bismuth is hampered by its inferior cyclability (limited to tens of cycles). Here, we propose an “ion conductive solid-state matrix” approach to address this issue. By homogeneously confining bismuth nanoparticles in a solid-state γ-Li 3 PO 4 matrix that is electrochemically formed in situ, the resulting composite anode exhibits a reversible capacity of 280 mA hours per gram (mA h/g) at a rate of 100 mA/g and a record cyclability among bismuth-based anodes up to 500 cycles with a capacity decay rate of merely 0.071% per cycle. We further show that full-cell batteries fabricated from this composite anode and commercial LiFePO 4 cathode deliver a stable cell voltage of ~2.5 V and remarkable energy efficiency up to 86.3%, on par with practical batteries (80–90%). This work paves a way for harnessing bismuth-based battery chemistry for the design of high capacity, safer lithium-ion batteries to meet demanding applications such as electric vehicles.

25 ENERGY STORAGE↗
DOE OSTI2020

Energy-efficient generation of skyrmion phases in Co/Ni/Pt-based multilayers using Joule heating

We have studied the effects of electrical current pulses on skyrmion formation in a series of Co/Ni/Pt-based multilayers. Transmission x-ray microscopy reveals that by applying electrical current pulses of duration and current density on the order of 50 μs and 1.7 × 10 10 A/m 2 , respectively, in an applied magnetic field of 50 mT, stripe-to-skyrmion transformations are attained. The skyrmions formed by such pulses remain stable across a wide range of magnetic fields, including zero field. We attribute the transformation primarily to current-induced Joule heating on the order of ~128 K. Reducing the magnetic moment and perpendicular anisotropy using thin rare-earth spacers reduces the pulse duration, current density, and magnetic field necessary to 25 µs, 2.4 × 10 9 A/m 2 , and 27 mT, respectively. Finally, these findings show that energetic inputs allow for the formation of skyrmion phases in a broad class of materials, and that material properties can be tuned to yield more energy-efficient access to skyrmion phases.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An Accurate, Error-Tolerant, and Energy-Efficient Neural Network Inference Engine Based on SONOS Analog Memory

In this work, we demonstrate SONOS (silicon-oxide-nitrideoxide- silicon) analog memory arrays that are optimized for neural network inference. The devices are fabricated in a 40nm process and operated in the subthreshold regime for in-memory matrix multiplication. Subthreshold operation enables low conductances to be implemented with low error, which matches the typical weight distribution of neural networks, which is heavily skewed toward near-zero values. This leads to high accuracy in the presence of programming errors and process variations. We simulate the end-to-end neural network inference accuracy, accounting for the measured programming error, read noise, and retention loss in a fabricated SONOS array. Evaluated on the ImageNet dataset using ResNet50, the accuracy using a SONOS system is within 2.16% of floating-point accuracy without any retraining. The unique error properties and high On/Off ratio of the SONOS device allow scaling to large arrays without bit slicing, and enable an inference architecture that achieves 20 TOPS/W on ResNet50, a >10× gain in energy efficiency over state-of-the-art digital and analog inference accelerators.

97 MATHEMATICS AND COMPUTING↗