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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Electrophoretic Deposition of Platinum Nanoparticles using Ethanol-Water Mixtures Significantly Reduces Neural Electrode Impedance

We report platinum electrodes are critical components in many biomedical devices, an important example being implantable neural stimulation or recording electrodes. However, upon implantation, scar tissue forms around the electrode surface, causing unwanted deterioration of the electrical contact. We demonstrate that sub-monolayer coatings of platinum nanoparticles (PtNPs) applied to 3D neural electrodes by electrophoretic deposition (EPD) can enhance the electrode's active surface area and significantly lower its impedance. In this work we use ethanol-water mixtures as the EPD solvent, in contrast to our previous studies carried out in water. We show that EPD coating in 30 vol.% ethanol improves the device's electrochemical performance. Computational mesoscale multiparticle simulations were for the first time applied to PtNP-on-Pt EPD, revealing correlations between ethanol concentration, electrochemical properties, and coating homogeneity. Thereto, this optimum ethanol concentration (30 vol.%) balances two opposing trends: (i) the addition of ethanol reduces water splitting and gas bubble formation, which benefits surface coverage, and (ii) increased viscosity and reduced permittivity occur at high ethanol concentrations, which impair the coating quality and favoring clustering. A seven-fold increase in active surface area and significantly reduced in vitro impedance of the nano-modified neural stimulation electrode surfaces highlight the influence of ethanol-water mixtures in PtNP EPD.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Slow spin dynamics in the hyperhoneycomb lattice [ ( C 2 H 5 ) 3 NH ] 2 Cu 2 ( C 2 O 4 ) 3 revealed by H 1 NMR studies

We report the results of magnetic susceptibility χ and H 1 nuclear magnetic resonance (NMR) measurements on a three-dimensional hyperhoneycomb lattice compound [ ( C 2 H 5 ) 3 NH ] 2 Cu 2 ( C 2 O 4 ) 3 (CCCO). The average value of the antiferromagnetic (AFM) exchange coupling between the Cu 2 + ( S = 1 / 2 ) spins was determined to be J ~ 50 K from the χ measurements. No long-range magnetic ordering has been observed down to T = 50 mK, although NMR lines become slightly broader at low temperatures below 1 K. The broadening of the NMR spectrum observed below 1 K reveals that the Cu spin moments remain at this temperature, suggesting a non-spin-singlet ground state. The temperature and magnetic field dependence of 1 / T 1 at temperatures above 20 K is well explained by paramagnetic thermal spin fluctuations where the fluctuation frequency of Cu 2 + spins is higher than the NMR frequency of the order of megahertz. However, a clear signature of the slowing down of the Cu 2 + spin fluctuations was observed at low temperatures where 1 / T 1 shows a thermally activated behavior. The magnetic field dependence of the magnitude of the spin excitation gap suggests that the magnetic behaviors of CCCO are characterized as an AFM chain at low temperatures.

1-dimensional systems↗
DOE OSTI2022

Designing, synthesizing, and modeling active fluids

We review recent advances in the design, synthesis, and modeling of active fluids. Active fluids have been at the center of many technological innovations and theoretical advances over the past two decades. Research on this new class of fluids has been inspired by the fascinating and remarkably efficient strategies that biological systems employ, leading to the development of biomimetic nano- and micro-machines and swimmers. The review encompasses active fluids on both the nano- and micro-scale. We start with examples of biological active systems before we discuss how experimentalists leverage novel propulsion mechanisms to power nano- and micro-machines. Furthermore, we then examine how the study of these far-from-equilibrium systems has prompted the development of new simulation methods and theoretical models in nonequilibrium physics to account for their mechanical, thermodynamic, and emergent properties. Recent advances in the field have paved the way for the design, synthesis, and modeling of autonomous systems at the nano- and micro-scale and opened the door to the development of soft matter robotics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Soft-hard framework with exact four-momentum conservation for small systems

A new framework, called x-scape, for the combined study of both hard and soft transverse momentum sectors in high-energy proton-proton (𝑝−𝑝) and proton-nucleus (𝑝−𝐴) collisions is set up. A dynamical initial state is set up using the 3d-Glauber model with transverse locations of hotspots within each incoming nucleon. A hard scattering that emanates from two colliding hotspots is carried out using the Pythia generator. Initial state radiation from the incoming hard partons is carried out in a new module called I-matter, which includes the longitudinal location of initial splits. The energy-momentum of both the initial hard partons and their associated beam remnants is removed from the hot spots, depleting the energy-momentum available for the formation of the bulk medium. Outgoing showers are simulated using the matter generator, and results are presented for both cases, allowing for and not allowing for energy loss. First comparisons between this hard-soft model and single inclusive hadron and jet data from 𝑝−𝑝 and minimum bias 𝑝−Pb collisions are presented. Single hadron spectra in 𝑝−𝑝 are used to carry out a limited (in number of parameters) Bayesian calibration of the model. Fair comparisons with data are indicative of the utility of this new framework. Theoretical studies of the correlation between jet 𝑝 𝑇 and event activity at mid and forward rapidity are carried out.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Unraveling the Dissolution-Mediated Reaction Mechanism of α-MnO 2 Cathodes for Aqueous Zn-Ion Batteries

Aqueous Zn/α-MnO 2 batteries have attracted immense interest owing to their high energy density, low cost, and safety, making them desirable for future large-scale energy application. Despite these merits, the comprehensive understanding of their reaction mechanism has been elusive due to the limitations of standard bulk characterization. Here, via transmission electron microscopy, the dissolution-mediated reaction mechanism of a Zn/α-MnO 2 system is discovered and explored in full scope to involve reversible formation of Zn 4 SO 4 (OH) 6 · x H 2 O and “birnessite-like” Zn-MnO x phase upon cycling. Overall, α-MnO 2 acts primarily as a source for cell activation through dissolution and thus is not directly involved in the Zn redox chemistry. Overall, this microscopic study offers a unique knowledge on the unconventional reaction chemistry of Zn/α-MnO 2 batteries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data

Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An Improved Representation of Aerosol Wet Removal by Deep Convection and Impacts on Simulated Aerosol Vertical Profiles

Here, we introduce a physics-based aerosol wet removal scheme with unified treatments of aerosol transport and removal by convective clouds into the Community Atmosphere Model version 6. Since several important physical processes are still neglected or poorly represented in this new physics-based scheme, we develop secondary improvements to the parameterizations of aerosol activation, resuspension, and cloud-borne aerosol detrainment in this new scheme. Changes in the aerosol wet removal scheme cause tropospheric aerosol concentrations to decrease to different extents: compared to the control run, the physics-based scheme significantly decreases aerosol burdens by up to 60% over the southern Pacific Ocean, whereas the secondary improvements mitigate the decreasing tendency. The burden changes also depend on aerosol chemical components: the sulfate mass decrease is compensated by secondary production, black carbon (BC) is effectively removed via increasing the hygroscopicity of particulate organic matter from 0 to 0.2, and dust shows the most spatially heterogeneous changes. Simulated aerosol profiles are evaluated against aircraft-based observations over the Pacific and Atlantic Oceans. The secondary-improved scheme reduces the overestimations of upper tropospheric BC and sea salt concentrations by a factor of 10 and 1,000, respectively, and reproduces the dependence of BC mass decrease rates on cloud types. Consideration of convective cloud-borne aerosol detrainment plays the most important role in enhancing the aerosol wet removal and decreasing the positive biases of tropospheric BC and sea salt concentrations. We also summarize unresolved issues related to convective cloud genesis and microphysics, cloud-borne aerosol evolution, and BC and dust emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Empowering 2D nanoelectronics via ferroelectricity

Introducing ferroelectricity to two-dimensional (2D) van der Waals (vdW) materials such as graphene, transition metal dichalcogenides, and black phosphorous presents a promising route for developing high-speed and low-power nanoelectronics. This Perspective reviews two actively pursued materials strategies, ferroelectric/vdW heterostructures and vdW ferroelectric materials. Finally, the topics discussed include their application potential and performance limitations as memory, logic, sensing, and optical devices, as well as the challenges and outlook of the field.

2D materials↗
DOE OSTI2020

Basic Research Needs for Transformative Manufacturing (Brochure)

Manufacturing is central to the nation’s prosperity and security. Manufacturing currently represents about 12% of the gross domestic product, provides nearly 13 million jobs, and accounts for about 25% of energy use. The nation’s economy relies heavily on wide-ranging manufacturing sectors - all of which share common challenges including data issues, lack of physics and chemistry-based models across scales, and resource constraints in a global environment. Furthermore, there are many hurdles that must be overcome to move basic science innovations to market. Addressing broad-ranging challenges demands a basic-science strategy that underpins applied research activities. This strategy would accelerate innovation and transform manufacturing. A Basic Research Needs workshop for Transformative Manufacturing was held in March 2020. The focus of the workshop was to identify the basic science research priorities that could accelerate innovation to transform manufacturing in the future. This was the first workshop of its kind to examine how basic energy science can drive manufacturing forward and innovate new ways to manufacture goods. Five Priority Research Directions were identified that address these science challenges: (1) innovative synthetic approaches to enable scalable assembly of matter, (2) computational methods and theoretical models to transform how manufacturing processes are controlled, (3) new characterization tools that can handle the necessary complexity, scales, and processing speeds to meet manufacturing needs, (4) new science to address opportunities relevant to sustainable and energy-efficient manufacturing, and (5) foundational approaches to co-design of materials, process, and products.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Safety in Artificial Intelligence: Challenges and Opportunities for the U.S. National Labs and Beyond

This report discusses the importance of the critical and underexplored topic of artificial intelligence (AI) safety, as highlighted during the “Strategy Alignment on AI Safety” workshop convened at Lawrence Livermore National Laboratory (LLNL) in April 2024. Through a summary of keynote talks, panel discussions, and breakout sessions, world-leading AI safety experts from academic, industry, national labs, and government agencies clearly agree on the need for and importance of large-scale investments for research and capabilities in AI safety. With the field innovating at unprecedented rates, there is increasing urgency to develop novel evaluation methodologies that allow full considerations of risks/threats of AI technologies in different domains. Quantitative metrics and effective methodologies that can evaluate and audit the “safeness” of how a given AI technology is trained, deployed, or regulated are, at best, nascent for certain scenarios or, more commonly, nonexistent. This maturation gap presents the possibility of serious threats to national security, and further inaction may have serious consequences. Additionally, the gap between the public’s and research community’s perceptions of AI risks/rewards is significant. While numerous voices from the AI community have expressed concern that the risks could be so high that future AI systems could inflict extinction-level damage to humanity if deployed incorrectly, the public largely is aware only of risk in low-impact scenarios. This discrepancy highlights the crucial need for researchers to articulate to governmental bodies what, why, and when various AI risks matter as part of motivating funding requests. Thus, the call to action for this community is to pursue AI safety as a “Big Science” project on a scale comparable to the Manhattan Project. High risks and high payoffs are on the table, but safe AI is a fast-moving target, and large-scale investments are needed to guide development of this technology in a responsible way. We highlight the need for a multilayered solution combining the development of new methods and algorithmic approaches to mitigate threats with an active participation of the government(s) in setting high industry standards and regulations based on state-of-the-art technology. The U.S. Department of Energy (DOE) national laboratories have served as leading institutions for scientific innovation in the U.S. for more than 70 years. Drawing on their expertise in the AI community and their history of safeguarding critical and sensitive information, and as we look to the future, national labs are the best choice for evaluating and safeguarding AI technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Dynamically tunable second-harmonic generation using hybrid nanostructures incorporating phase-change chalcogenides

Nonlinear metasurfaces with high conversion efficiencies have been vastly investigated. However, strong dynamic tunability of such devices is limited in conventional passive plasmonic and dielectric material platforms. Germanium antimony telluride (GST) is a promising phase-change chalcogenide for the reconfiguration of metamaterials due to strong nonvolatile changes of the real and imaginary parts of the refraction index through amorphous-crystalline phase change. The orderly structured GST has an even higher potential in tunable second-harmonic generation (SHG) with a non-centrosymmetric crystal structure at the crystalline phase, while the amorphous phase of GST does not exhibit bulk second-order nonlinearity. Here, we experimentally demonstrate SHG switches by actively controlling the crystalline phase of GST for a GST-based hybrid metasurface featuring a gap-surface plasmon resonance, and a quarter-wave asymmetric Fabry–Perot (F–P) cavity incorporating GST. We obtain SHG switches with modulation depths as high as ~ 20 dB for the wavelengths at the on-state resonance. We also demonstrate the feasibility of multi-level SHG modulation by leveraging three controlled GST phases, i.e., amorphous, semi-crystalline, and crystalline, for the gap-surface plasmon hybrid device, which features stronger light–matter interaction and has higher resonant SHG efficiencies than the asymmetric F–P cavity device at respective GST phases. This research reveals that GST-based dynamic SHG switches can be potentially employed in practical applications, such as microscopy, optical communication, and photonic computing in the nonlinear regime.

42 ENGINEERING↗
DOE OSTI2023

Building a Computational and Experimental Rapid Response Pipeline to Counter the Coronavirus Disease 2019 Outbreak and Emerging Biothreats

The LDRD ER “Building a Computational and Experimental Rapid Response Pipeline to Counter the Coronavirus Disease 2019 Outbreak and Emerging Biothreats” was conceived to address a need for rapid, scalable, evaluation of computationally designed therapeutic or prophylactic antibodies and vaccine antigens, two important classes of protein medical countermeasure (MCM). This was done in complement to a computationally driven LDRD 20ERD032 “Active Learning for Rapid Design of Vaccines and Antibodies.” Natural antibodies and antigens are often insufficiently broad or robust across different pathogens and their variants. Leveraging a collaboration of simulation driven machine learning, structural expertise, and high-throughput characterization of candidate antibodies, we successfully re-targeted three different anti-SARS-CoV-1 antibodies to neutralize SARS-CoV-2 in vitro. Our antibody design work reached its most important stage in rapid response to the emergence of the Omicron variant of concern (VOC) in late 2021. In a matter of weeks, we computationally designed derivative antibodies of COV2-2130, one of two antibodies from Vanderbilt that form the basis of the AstraZeneca Evusheld prophylactic drug product. This drug product suffers a serious loss of efficacy against Omicron BA.1 and BA.1.1, the first Omicron strains. Our designs were successful, including a pair of designs which provide potent neutralization of not only Omicron BA.1 and BA.1.1, but also the earlier Delta variant, and subsequent Omicron strains including BA.2, BA.4, BA.5, and BA.2.75, demonstrating that our multi-target design process can, by its nature, produce robust antibody designs that strictly improve over the parental antibody. These results, recognized by a 2022 Director’s Science and Technology award, have enabled the follow-on GUIDE program, to commence in FY23.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Anisotropic optical properties of detwinned BaFe 2 As 2

The optical properties of a large, detwinned single crystal of BaFe 2 As 2 have been examined over a wide frequency range above and below the structural and magnetic transition at T N ≃138 K. Above T N the real part of the optical conductivity and the two infrared-active lattice modes are almost completely isotropic; the lattice modes show a weak polarization dependence just above T N . For T < T N , the optical conductivity due to the free-carrier response is anisotropic, being larger along the a axis than the b axis below ≃ 30 meV; above this energy the optical conductivity is dominated by the interband contributions, which appear to be isotropic. Furthermore, the splitting of the low-energy infrared-active mode below T N is clearly observed, and the polarization modulation of the new modes may be used to estimate that the crystal is ≃ 70% detwinned. The high-frequency mode,with a threefold increase in strength of the lower branch below T N and nearly silent upper branch,remains enigmatic.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Flat Bands and Chiral Optical Response of Moiré Insulators

Here, we present a low-energy model describing the reconstruction of the electronic spectrum in twisted bilayers of honeycomb crystals with broken sublattice symmetry. The resulting moiré patterns are classified into two families with different symmetry. In both cases, flat bands appear at relatively large angles without any magic-angle condition. Transitions between them give rise to sharp resonances in the optical absorption spectrum at frequencies well below the gap of the monolayer. Owing to their chiral symmetry, twisted bilayers display circular dichroism, that is, different absorption of left and right circularly polarized light. This optical activity is a nonlocal property determined by the stacking. In hexagonal boron nitride, sensitivity to the stacking leads to strikingly different circular dichroism in the two types of moirés. Our calculations exemplify how subtle properties of the electronic wave functions, encoded in current correlations between the layers, control physical observables of moiré materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Strain-Induced Atomic-Scale Building Blocks for Ferromagnetism in Epitaxial LaCoO 3

The origin of strain-induced ferromagnetism, which is robust regardless of the type and degree of strain in LaCoO 3 (LCO) thin films, is enigmatic despite intensive research efforts over the past decade. Here, by combining scanning transmission electron microscopy with ab initio density functional theory plus U calculations, we report that the ferromagnetism does not emerge directly from the strain itself but rather from the creation of compressed structural units within ferroelastically formed twin-wall domains. Here, the compressed structural units are magnetically active with the rocksalt-type high-spin/low-spin order. Our study highlights that the ferroelastic nature of ferromagnetic structural units is important for understanding the intriguing ferromagnetic properties in LCO thin films.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Axon-like active signal transmission

Any electrical signal propagating in a metallic conductor loses amplitude due to the natural resistance of the metal. Compensating for such losses presently requires repeatedly breaking the conductor and interposing amplifiers that consume and regenerate the signal. This century-old primitive severely constrains the design and performance of modern interconnect-dense chips. Here we present a fundamentally different primitive based on semi-stable edge of chaos (EOC), a long-theorized but experimentally elusive regime that underlies active (self-amplifying) transmission in biological axons. By electrically accessing the spin crossover in LaCoO 3 , we isolate semi-stable EOC, characterized by small-signal negative resistance and amplification of perturbations. In a metallic line atop a medium biased at EOC, a signal input at one end exits the other end amplified, without passing through a separate amplifying component. While superficially resembling superconductivity, active transmission offers controllably amplified time-varying small-signal propagation at normal temperature and pressure, but requires an electrically energized EOC medium. Operando thermal mapping reveals the mechanism of amplification—bias energy of the EOC medium, instead of fully dissipating as heat, is partly used to amplify signals in the metallic line, thereby enabling spatially continuous active transmission, which could transform the design and performance of complex electronic chips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Operando 3D imaging of defects dynamics of twinned-nanocrystal during catalysis

Using operando Bragg coherent x-ray diffraction imaging, we visualised three-dimensionally a single twinned-gold nanocrystal during the CO oxidation reaction. We describe the defect dynamics process occurring under operating conditions and indicate the correlation between the nucleation of highly strained regions at the surface of the nanocrystal and its catalytic activity. Understanding the twinning deformation mechanism sheds light on the creation of active sites, and could well contribute to the understanding of the catalytic behaviour of other catalysts. Furthermore, with the start-up of 4th generation synchrotron sources, we anticipate that coherent hard x-ray diffraction imaging techniques will play a major role in imaging in situ chemical processes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Mechanism of dielectric barrier discharge plasma technology to improve the quantity of short-chain fatty acids in anaerobic fermentation of waste active sludge

The mechanism of improving the anaerobic fermentation performance of waste active sludge by using dielectric barrier discharge (DBD) plasma pretreatment technology was investigated. The maximum accumulation of short-chain fatty acids (SCFAs) was observed on the 7th day of anaerobic fermentation when the DBD power was 76.50 W, which was 1726.70 mg COD/L, 1.50 times of the control group. The ratio of acetic acid in DBD group was 9.30% higher than that in the control. Further mechanism research indicated that DBD pretreatment can destroy the structure of extracellular polymer substances and release organic substances such as protein and polysaccharide. The dissolved organic matter analysis indicated that the DBD technique could increase the release of biodegradable organics (eg., tyrosine proteins, soluble microbial by-products), thus accelerate the biotransformation of organic substance. Bacterial community structure analysis showed that the increase in the abundance of Firmicutes and Bacteroidetes and the decrease in the abundance of Proteobacteria in DBD group were beneficial to the accumulation of SCFAs. Besides, further archaeal analysis indicated that the decrease of Methanosaeta sp. and Methanosarcina sp . abundance in the DBD group facilitate acetic acid accumulation. This study demonstrated that the DBD technique can be used as an effective and potential pretreatment method to improve sludge anaerobic fermentation performance.

Wang, Jie↗