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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 145 records · Page 8

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DOE OSTI2022

Towards fast-charging high-energy lithium-ion batteries: From nano- to micro-structuring perspectives

Electric vehicles (EVs) have been playing an indispensable role in reducing greenhouse gas emissions for our modern society. However, current EVs are difficult to meet people’s diverse travel needs, especially in long endurance and fast-charging capacities. At the heart of this issue is the physicochemical limit of current lithium-ion batteries (LIBs), which are the core parts for powering the vehicles. Hence, LIBs with simultaneous high energy and power are critically required to further promote the development of EVs. Here, in this review, we first summarize the key electrochemical processes in electrochemical reactions which lead to the corresponding overpotentials in or between multiple battery components. Furthermore, numerical simulations are employed to quantitatively analyze the effects of versatile electrode parameters on electrochemical properties in high-energy NMC811//graphite systems. On the basis of the in-depth understandings from simulation, recent experimental efforts on designing electroactive materials and electrode architectures across multiple length scales are discussed. Among them, nano-structuring can promote local mass transport and stabilize the interfaces at the particle level, while micro-structuring can establish efficient pathways for charge carriers at the electrode level. Finally, we conclude that a tight feedback loop among structure engineering, characterization and simulation should be followed to speed up the understanding of the deficiencies existing in current electrode designs as well as point out the possible electrode optimization routes for next-generation fast-charging LIBs.

25 ENERGY STORAGE↗

DOE OSTI2024

Diversifying hierarchical ionic assembly by docking cations to anions as salt bridges

Here, we expand the diversity of building blocks available for ionic assembly by introducing tertiary (3°) ammonium cations into anion complexes. We use proton transfer between 3° amines and organo-phosphoric acids to generate H-bonding cations (R 3 NH + ) and anions (RHPO 4 – ) that co-assemble with cyanostar macrocycles into assemblies with 2:2:2 stoichiometry. At the heart is a supramolecular dimer where phosphate anions form salt bridges by H-bonding with cations. Unlike conventional 4° ammonium cations, 3,000 commercial amines provide diversity for high-throughput screening of 72 combinations (9 nitrogen bases and 8 acids), producing 13 privileged partners for quantitative assembly. Yields depend on the solvent and sterics of salt bridge formation. Ten more nitrogen bases connect to fluorophores (pyrene), photocatalysts (quinoline), drugs (Cipralex, Zytiga), and ionic liquids (imidazole). The synthesis and examination of 82 new salts exemplify how acid-base chemistry can open a pipeline to a diversity of building blocks for exploring hierarchical ionic assembly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Comparison of Machine Learning and Deep Learning for View Identification from Cardiac Magnetic Resonance Images

Background: Artificial intelligence is increasingly utilized to aid in the interpretation of cardiac magnetic resonance (CMR) studies. One of the first steps is the identification of the imaging plane depicted, which can be achieved by both deep learning (DL) and classical machine learning (ML) techniques without user input. We aimed to compare the accuracy of ML and DL for CMR view classification and to identify potential pitfalls during training and testing of the algorithms. Methods: To train our DL and ML algorithms, we first established datasets by retrospectively selecting 200 CMR cases. The models were trained using two different cohorts (passively and actively curated) and applied data augmentation to enhance training. Once trained, the models were validated on an external dataset, consisting of 20 cases acquired at another center. We then compared accuracy metrics and applied class activation mapping (CAM) to visualize DL model performance. Results: The DL and ML models trained with the passively-curated CMR cohort were 99.1% and 99.3% accurate on the validation set, respectively. However, when tested on the CMR cases with complex anatomy, both models performed poorly. After training and testing our models again on all 200 cases (active cohort), validation on the external dataset resulted in 95% and 90% accuracy, respectively. The CAM analysis depicted heat maps that demonstrated the importance of carefully curating the datasets to be used for training. Conclusions: Both DL and ML models can accurately classify CMR images, but DL outperformed ML when classifying images with complex heart anatomy.

artificial intelligence↗

DOE OSTI2025

MetaHeart: Metasurface enabled biometrics camouflage

Privacy-invading biometrics monitoring is becoming a prominent security threat as modern sensing systems move to higher operating frequencies (mmWave, sub-THz), increasing sensing resolution and accuracy. As such, developing systems that can protect or obfuscate biometrics from adversarial intrusion becomes pivotal to preserving user privacy. In this work, we develop and implement MetaHeart, a real-time biometrics misinformation system based on reflective, programmable metasurfaces and dynamic phase-front manipulation of radar inferences. MetaHeart’s key goal is to prevent the leakage of a legitimate user’s heartbeat biometrics by spoofing fake heartbeat signals at a malicious, radar-equipped, heart rate sensing intruder. Furthermore, we experimentally demonstrate MetaHeart’s ability to fake Alice’s presence when she is not there and to fool Trudy’s inferences even when Alice is present, achieving an overall accuracy above 98%. Finally, we conduct a robustness analysis to determine MetaHeart’s required spatial placement within the intruder’s monitoring area that would allow for effective spoofing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2026

Lethality is Local, but Survival is Systemic: Temporal and Multi-Organ Responses to Chlorine Gas Exposure in a Murine Model

Chlorine gas (Cl2) is a highly toxic chemical associated with both localized lung injury and systemic health effects. While pulmonary damage has been well characterized, the systemic inflammatory and metabolic responses remain poorly understood. We aimed to define the temporal and multi-organ responses to Cl2 exposure in a murine model, with a focus on identifying spatiotemporal inflammation and its impact on survival and lethality. SKH1 mice were exposed for 10 min to varying concentrations of Cl2 (94.4–810 ppm, representative of non-lethal, LD10, and LD50 doses) and monitored for respiratory function, perfusion, and acidosis using organ-specific imaging. At multiple time points (40 min, 6 h, 24 h, and 7 d), we measured phosphoproteins, cytokines, chemokines, growth factors, and metabolic hormones in the lungs, heart, cortex, and plasma. Statistical modeling and logistic regression were used to identify biomarkers associated with lethality and survival. We found that lung injury was the primary cause of potential lethality, particularly via early phosphoprotein signaling disruptions. However, survival correlated with early systemic coordination of inflammatory and metabolic signals across organs. Perfusion and acidosis imaging were strongly associated with chemokine and hormone responses. Key survival-associated plasma biomarkers included decreased insulin, increased ghrelin, and decreased eotaxin. While potential lethality from Cl2 exposure is locally driven by pulmonary injury, survival depends on systemic, multi-organ responses that occur rapidly post-exposure. Within this model, our findings identify a potential therapeutic window to enhance survival and suggest candidate biomarkers that may be explored translationally for both triage and treatment of chlorine-related incidents.

chlorine gas↗

DOE OSTI2023

Developing and tuning a community scale energy model for a disadvantaged community

This work describes the development of a community-scale energy model for a mixed-use low-income community located in Huntington Beach, CA. An accurate community-scale energy model is useful for evaluating the use of limited capital resources used to invest in clean energy technologies. This work lays out the process of developing such a model while relying primarily on publicly available data and highlighting critical partnerships necessary for model development success. The primary contribution of this work is the demonstration of the process used to develop an accurate energy model for a disadvantaged community when minimal building and energy use data is available. The heart of the model is the physics-based community scale energy modeling platform URBANopt. Using a bottom-up load modeling approach, energy simulated energy use falls within 3% or less of aggregate annual utility data, and within 10% or less aggregate monthly utility data. The demonstrated model development and tuning process can be used by others to characterize other atypical communities, which may differ significantly from prototypical models.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

A review on nearly isothermal compression technology

Compressors can be described as the heart of a vapor compression refrigeration system, circulating the working fluid in the system. Significant benefits can be gained from improving its efficiency since energy consumption is responsible for almost the entire system's power input. An effort has been made to achieve isothermal compression through liquid refrigerant injection or inter-stage cooling in refrigeration systems. In recent years, much effort has been invested into isothermal compression technology for air compressors or compressed air energy storage systems with the rise of renewable energy. Here, this work has explored the advancements made in this area and categorized them to discuss the benefits, limitations, and tradeoffs. Evidently, increasing heat transfer area is a significant aid in improving heat transfer, resulting in better isothermal compression. However, liquid pistons open more avenues for this to be pursued, and therefore, are limited to air compression applications. In addition, water injection proved to be the most effective among the methods. Finally, there is a need for more experimental research on refrigeration applications and the field is still in its infancy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Intrinsic Bulk Quantum Oscillations in a Bulk Unconventional Insulator SmB 6

The finding of bulk quantum oscillations in the Kondo insulator SmB 6 proved a considerable surprise. Subsequent measurements of bulk quantum oscillations in other correlated insulators including YbB 12 lent support to our discovery of a class of bulk unconventional insulators that host bulk quantum oscillations. Here we perform a series of experiments to examine evidence for the intrinsic character of bulk quantum oscillations in floating zone-grown single crystals of SmB 6 that have been the subject of our quantum oscillation studies. We present results of thermodynamic, transport, and composition analysis experiments on pristine floating zone-grown single crystals of SmB 6 and compare quantum oscillations with metallic LaB 6 and elemental aluminum. These results establish the intrinsic origin of quantum oscillations from the insulating bulk of floating zone-grown SmB 6 . The similarity of the Fermi surface in insulating SmB 6 with the conduction-electron Fermi surface in metallic hexaborides is at the heart of a theoretical mystery.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Determining the impacts of venoarterial extracorporeal membrane oxygenation on cerebral oxygenation using a one-dimensional blood flow simulator

Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is a mechanical system that provides rapid and short-term support for patients with cardiac failure. In many patients, pulmonary function is also impaired, resulting in poorly-oxygenated cardiac outflow competing against well-oxygenated VA-ECMO outflow, a condition known as North-South syndrome. North-South syndrome is a primary concern because of its potential to cause cerebral hypoxia, which has a critical influence on neurological complications often seen in this patient population. In order to reduce ischemic neurological complications, it is important to understand how clinical decisions regarding VA-ECMO parameters influence blood oxygenation. In our work, we studied the impacts of flow rate and cannulation site on oxygenation using a one-dimensional (1D) model to simulate blood flow. Our model was initially tested by comparing blood flow results to those observed from experimental work in VA-ECMO patients. The 1D model was combined with a two-phase flow model to simulate oxygenation. Additionally, the influence of various other clinician-tunable parameters on oxygenation in the common carotid arteries (CCAs) were tested, including, blood viscosity, cannula position within the insertion artery, heart rate, and systemic vascular resistance (SVR), as well as geometrical changes such as arterial radius and length. Our results indicated that blood oxygenation to the brain strongly depended on the cannula insertion site and the VA-ECMO flow rate with a weaker but potentially significant dependence on arterial radius. During femoral cannulation, VA-ECMO flow rates greater than ~4.9 L/min were needed to perfuse the CCAs. However, axillary and central cannulation began to perfuse the CCAs at significantly lower flow (~1 L/min). These results may help explain the incidence of cerebral hypoxia in this patient population and the common need to change cannulation strategies during treatment to address this clinical problem. While this work describes patient-averaged results, determining these relationships between VA-ECMO parameters and cerebral hypoxia is an important step towards future work to develop patient-specific models that clinicians can use to improve outcomes.

1D blood flow↗

DOE OSTI2020

DFT and microkinetic comparison of Pt, Pd and Rh-catalyzed ammonia oxidation

Ammonia oxidation is the heart of the Ostwald process and is important in emissions control. Catalytic behaviors are a function of conditions and are observed to vary across the platinum group metals (PGMs) Pt, Pd, Rh. Here, we combine density functional theory computations and microkinetic modeling to rationalize these dependencies. We compute reactions over model (2 1 1) and (1 1 1) surfaces of PGMs. Binding energies are similar on Pd and Pt and generally greater on Rh, while activation energies vary across all metals. Rates on (2 1 1) surfaces are greater than (1 1 1) surfaces. Additionally, the stepped Pt is most active and stepped Rh most selective to N 2 at ammonia slip conditions, while at Ostwald process conditions, stepped Pd is most active and stepped Pt most selective to NO. Degree of rate and selectivity control analysis provides insights into the reactions limiting performance of PGMs. Both activation barriers and surface coverages influence rates and selectivities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

A sharp interface Lagrangian-Eulerian method for rigid-body fluid-structure interaction

Herein this paper introduces a sharp interface method to simulate fluid-structure interaction (FSI) involving rigid bodies immersed in viscous incompressible fluids. The capabilities of this methodology are benchmarked using a range of test cases and demonstrated using large-scale models of biomedical FSI. The numerical approach developed herein, which we refer to as an immersed Lagrangian-Eulerian (ILE) method, integrates aspects of partitioned and immersed FSI formulations by solving separate momentum equations for the fluid and solid subdomains, as in a partitioned formulation, while also using non-conforming discretizations of the dynamic fluid and structure regions, as in an immersed formulation. A simple Dirichlet-Neumann coupling scheme is used, in which the motion of the immersed solid is driven by fluid traction forces evaluated along the fluid-structure interface, and the motion of the fluid along that interface is constrained to match the solid velocity and thereby satisfy the no-slip condition. To develop a practical numerical method, we adopt a penalty approach that approximately imposes the no-slip condition along the fluid-structure interface. In the coupling strategy, a separate discretization of the fluid-structure interface is tethered to the volumetric solid mesh via stiff spring-like penalty forces. Our fluid-structure coupling scheme relies on an immersed interface method (IIM) for discrete geometries, which enables the accurate determination of both velocities and stresses along complex internal interfaces. Numerical methods for FSI can suffer from instabilities related to the added mass effect, but computational tests indicate that the methodology introduced here remains stable for selected test cases across a broad range of solid-fluid mass density ratios, including extremely small, nearly equal, equal, and large density ratios. Biomedical FSI demonstration cases include results obtained using this method to simulate the dynamics of a bileaflet mechanical heart valve in a pulse duplicator, and to model transport of blood clots in a patient-averaged anatomical model of the inferior vena cava.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

A review on advances in oxidative coupling of methane (OCM) for industrial use and prospects of CO 2 –H 2 O splitting integration

The discovery of shale gas reserves has encouraged the development of direct methods for methane conversion into valuable chemicals, offering an alternative to indirect approaches that involve an energy-intensive and intermittent syngas production step, leading to high CO 2 emissions. Amongst the direct methods, the oxidative coupling of methane (OCM) is a potential pathway to reduce CO 2 emissions and can produce commodity chemicals such as ethylene, a chemical regarded as central to the petrochemical industry. Even though OCM has been studied for over four decades, the technology still has not found commercial application. Amongst the challenges regarding industrial deployment of OCM, the most significant one is the requirement of a high ethylene yield of 30 % which is currently reported to be around 20 %. Moreover, the highly exothermic nature of the process and controlling the carbon selectivity over oxides of carbon (COx) is the heart of the problem. Numerous researchers have presented promising results in terms of catalysts, reactor designs and feeding strategies for OCM. However, due to lack of inclusiveness in the results, none of the combination of catalysts, reactors and system optimizations has been able to bring about its industrial viability. The current paper presents an extensive review of the noteworthy attempts to achieve industrial targets for OCM. Moreover, a comprehensive criteria is presented which highlights the desired end state for the industrial deployment of OCM technology. Furthermore, the criteria is based on literature survey and a comparison with industrially deployed ethylene production plants i.e., naphtha or ethane steam cracker plants. Finally, a novel integration technology is presented which includes a combination of OCM and CO 2 -H 2 O splitting in a chemical looping reactor design to enable efficient energy utilization and minimal heat losses to the environment.

CO2 Splitting↗

DOE OSTI2022

Snowmass2021 theory frontier white paper: Astrophysical and cosmological probes of dark matter

While astrophysical and cosmological probes provide a remarkably precise and consistent picture of the quantity and general properties of dark matter, its fundamental nature remains one of the most significant open questions in physics. Obtaining a more comprehensive understanding of dark matter within the next decade will require overcoming a number of theoretical challenges: the groundwork for these strides is being laid now, yet much remains to be done. Chief among the upcoming challenges is establishing the theoretical foundation needed to harness the full potential of new observables in the astrophysical and cosmological domains, spanning the early Universe to the inner portions of galaxies and the stars therein. Identifying the nature of dark matter will also entail repurposing and implementing a wide range of theoretical techniques from outside the typical toolkit of astrophysics, ranging from effective field theory to the dramatically evolving world of machine learning and artificial-intelligence-based statistical inference. Through this work, the theory frontier will be at the heart of dark matter discoveries in the upcoming decade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Exploring thermal state in mixed immersive virtual environments

Combining immersive virtual environment (IVE) with a controlled environment is a potential solution for analyzing human thermal experience during building design. Existing studies in this field have not adequately analyzed scenarios involving stabilized comfortable and uncomfortable temperature conditions using both thermal state votes and physiological responses, or the influence of the seasons. By combining IVE with a climate chamber, called mixed IVE (MIVE) in this study, experiments were conducted to test the hypothesis that participants' virtual experience did not significantly alter their thermal experience compared to their in-situ experience. Response variables were the control temperature distribution, the thermal state vote (at temperature steps 18.3 °C, 23.8 °C, and 29.4 °C), and physiological responses (heart rate and skin temperature). The results show that the first two response variables were not significantly different between the MIVE and in-situ settings (except for one case). Due to the heat development of the head mounted display device, the mean forehead skin temperature in the MIVE experiments was significantly higher than that in the in-situ experiments in most cases. Furthermore, such difference in skin temperature did not seem to affect general thermal state votes. In addition, significant skin temperature differences at some locations were also observed between the MIVE and in-situ settings.

42 ENGINEERING↗

DOE OSTI2024

A variance deconvolution estimator for efficient uncertainty quantification in Monte Carlo radiation transport applications

Monte Carlo simulations are at the heart of many high-fidelity simulations and analyses for radiation transport systems. As is the case with any complex computational model, it is important to propagate sources of input uncertainty and characterize how they affect model output. Unfortunately, uncertainty quantification (UQ) is made difficult by the stochastic variability that Monte Carlo transport solvers introduce. The standard method to avoid corrupting the UQ statistics with the transport solver noise is to increase the number of particle histories, resulting in very high computational costs. In this contribution, we propose and analyze a sampling estimator based on the law of total variance to compute UQ variance even in the presence of residual noise from Monte Carlo transport calculations. Here, we rigorously derive the statistical properties of the new variance estimator, compare its performance to that of the standard method, and demonstrate its use on neutral particle transport model problems involving both attenuation and scattering physics. We illustrate, both analytically and numerically, the estimator’s statistical performance as a function of available computational budget and the distribution of that budget between UQ samples and particle histories. We show analytically and corroborate numerically that the new estimator is unbiased, unlike the standard approach, and is more accurate and precise than the standard estimator for the same computational budget.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Ion-gated carbon molecular sieve gas separation membranes

Membrane technology lies at the heart of many industrial gas separation processes and applications. Molecular sieving membranes that break the Robeson limit are desirable for energy-efficient gas separation. In this paper, we report a facile strategy of directly integrating ionic liquids (ILs) into porous membranes. Particularly, the ILs form an ultra-thin layer on the carbon molecular sieve (CMS) membranes rather than penetrating into the pores, acting as a smart gate for gas entry to boost the selectivity. The hybrid membrane exhibits CO 2 permeability >600 barrer and enhanced CO 2 /N 2 selectivity >50, which surpasses the Robeson limit and shows potential in CO 2 /N 2 separation process. Molecular dynamics simulations confirm the gating effect of the IL layer of molecular thickness. In conclusion, this work demonstrates a universal strategy to improve CMS membrane performance by creating an IL-membrane interface and tuning the ion-pore interaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

A review of quantum imaging methods and enabling technologies

The field of quantum imaging has recently seen an explosion of new methods and techniques. At the heart of most quantum imaging approaches are three enabling technologies: the source of the quantum light, the detectors that turn sensing into imaging, and the method by which the quantum nature of light is leveraged to improve the desired measurement. This review addresses the dominant and emerging technologies in each of these components as well as details concerning the implementations of various quantum imaging methods.

36 MATERIALS SCIENCE↗

DOE OSTI2023

All-polymer nanocomposites having superior strength, toughness and ultralow energy dissipation

Toughening polymers has attracted significant interest. Traditionally, polymer toughness is enhanced by constructing polymer networks or introducing sacrificial bonds into the chains between crosslink points. These strategies, though, introduce pronounced energy dissipation and associated heat, both of which are undesirable under long-term cyclic loading, for example at the interface of implants in the human body. By incorporating single-chain nanoparticles (SCNPs) into linear polymer chains to generate all-polymer nanocomposites (APNCs), we have been able to achieve high strength, high toughness with low energy dissipation. Using a combination of simulation and experimental results, we are advancing a “SCNPs effect” where tightly cross-linked SCNPs produce a modulus contrast to achieve strengthening and toughening. Benefitting from the soft interface, the penetrable and deformable SCNPs cause the surrounding polymer chains to move in concert, significantly reducing the interfacial friction to achieve low energy dissipation. The intramolecular cross-linking of the SCNPs and adhesion between the SCNPs and polymer matrix are critical for realizing such high-performance systems. Based on a Gaussian regression model and back propagation (BP) neural network, the mechanical strength can be predicted and is supported by simulations. Finally, the APNC concept described can be applied to elastomers and gels, broadening its utilization in high-cycle and low-dissipation applications, like soft robots, flexible sensors and cartilage replacements, and artificial heart valves.

36 MATERIALS SCIENCE↗