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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ferroelectricity in Atomic Layer Deposited Wurtzite Zinc Magnesium Oxide Zn 1– x Mg x O

Conformal deposition of wurtzite ferroelectrics, which is needed for their use in scaled nonvolatile memories, is challenging using current physical vapor deposition techniques. To overcome the conformality barrier, this work demonstrates ferroelectricity in wurtzite Zn 1− x Mg x O thin films prepared by plasma-enhanced atomic layer deposition, which is a non-line-of-sight deposition method. Films ranging in composition from x = 0.00 to x = 0.58 are predominantly wurtzite phase and exhibit a (0001)-texture. Increasing the magnesium content decreases the c/a ratio, increases the optical bandgap energy, increases the piezoelectric response, and enables polarization reversal. Clear polarization switching is demonstrated in 50 nm thick Zn 1− x Mg x O films by piezoresponse force microscopy in compositions containing x = 0.46 and x = 0.58.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Resilience Enhancements through Deep Learning Yields

This report documents the Resilience Enhancements through Deep Learning Yields (REDLY) project, a three-year effort to improve electrical grid resilience by developing scalable methods for system operators to protect the grid against threats leading to interrupted service or physical damage. The computational complexity and uncertain nature of current real-world contingency analysis presents significant barriers to automated, real-time monitoring. While there has been a significant push to explore the use of accurate, high-performance machine learning (ML) model surrogates to address this gap, their reliability is unclear when deployed in high-consequence applications such as power grid systems. Contemporary optimization techniques used to validate surrogate performance can exploit ML model prediction errors, which necessitates the verification of worst-case performance for the models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Rapid detection of rare events from in situ X-ray diffraction data using machine learning

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots of the evolving microstructure and attributes over time. However, the extreme data volumes and the high costs of traditional data acquisition and reduction approaches pose a barrier to quickly extracting actionable insights and improving the temporal resolution of these snapshots. This article presents a fully automated technique capable of rapidly detecting the onset of plasticity in high-energy X-ray microscopy data. The technique is computationally faster by at least 50 times than the traditional approaches and works for data sets that are up to nine times sparser than a full data set. This new technique leverages self-supervised image representation learning and clustering to transform massive data sets into compact, semantic-rich representations of visually salient characteristics ( e.g. peak shapes). These characteristics can rapidly indicate anomalous events, such as changes in diffraction peak shapes. It is anticipated that this technique will provide just-in-time actionable information to drive smarter experiments that effectively deploy multi-modal X-ray diffraction methods spanning many decades of length scales.

Zheng, Weijian↗
DOE OSTI2021

Electronic circuit for control or coupling of single charges or spins and methods therefor

A quantum dot structure having a split-gate geometry is provided. The quantum dot is configured for incorporation into a quantum dot array of a quantum processing unit. A gap between a reservoir accumulation gate and a quantum dot accumulation gate provides a tunnel barrier between an electric charge reservoir and a quantum dot well. An electrical potential applied to the gates defines a tunnel barrier height, width and charge tunneling rate between the well and the reservoir without relying on any barrier gate to control the charge tunneling rate.

Pioro-Ladriere, Michel↗
DOE OSTI2024

Exploring Li-Ion Transport Properties of Li 3 TiCl 6 : A Machine Learning Molecular Dynamics Study

We performed large-scale molecular dynamics simulations based on a machine-learning force field (MLFF) to investigate the Li-ion transport mechanism in cation-disordered Li 3 TiCl 6 cathode at six different temperatures, ranging from 25°C to 100°C. In this work, deep neural network method and data generated by ab − initio molecular dynamics (AIMD) simulations were deployed to build a high-fidelity MLFF. Radial distribution functions, Li-ion mean square displacements (MSD), diffusion coefficients, ionic conductivity, activation energy, and crystallographic direction-dependent migration barriers were calculated and compared with corresponding AIMD and experimental data to benchmark the accuracy of the MLFF. From MSD analysis, we captured both the self and distinct parts of Li-ion dynamics. The latter reveals that the Li-ions are involved in anti-correlation motion that was rarely reported for solid-state materials. Similarly, the self and distinct parts of Li-ion dynamics were used to determine Haven’s ratio to describe the Li-ion transport mechanism in Li 3 TiCl 6 . Obtained trajectory from molecular dynamics infers that the Li-ion transportation is mainly through interstitial hopping which was confirmed by intra- and inter-layer Li-ion displacement with respect to simulation time. Ionic conductivity (1.06 mS/cm) and activation energy (0.29eV) calculated by our simulation are highly comparable with that of experimental values. Overall, the combination of machine-learning methods and AIMD simulations explains the intricate electrochemical properties of the Li 3 TiCl 6 cathode with remarkably reduced computational time. Thus, our work strongly suggests that the deep neural network-based MLFF could be a promising method for large-scale complex materials.

Selvaraj, Selva Chandrasekaran (ORCID:000000029023↗
DOE OSTI2024

From anti-Arrhenius to Arrhenius behavior in a dislocation-obstacle bypass: Atomistic simulations and theoretical investigation

Dislocations are the primary carriers of plasticity in metallic materials. Understanding the basic mechanisms for dislocation movement is paramount to predicting the material mechanical response. Relying on atomistic simulations, we observe a transition from non-Arrhenius to Arrhenius behavior in the rate of an edge dislocation overcoming the long-range elastic interaction with a prismatic loop in tungsten. Close to the critical resolved shear stress, the process shows a non-Arrhenius behavior at low temperatures. However, as the temperature increases, the activation entropy starts to dominate, leading to a traditional Arrhenius-like behavior. Here, we have computed the activation entropy analytically along the minimum energy path following Schoeck’s method, which captures the cross-over between anti-Arrhenius and Arrhenius domains. Also, the Projected Average Force Integrator (PAFI), another simulation method to compute free energies along an initial transition path, exhibits considerable concurrence with Schoeck’s formalism. We conclude that entropic effects need to be considered to understand processes involving dislocations bypassing elastic barriers close to the critical resolved shear stress. More work needs to be performed to fully understand the discrepancies between Schoeck’s and PAFI compared to molecular dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Data Deposition Platform for Sharing Nuclear Magnetic Resonance Data

Nuclear magnetic resonance (NMR) data are rarely deposited in open databases, leading to loss of critical scientific knowledge. Existing data reporting methods (images, tables, lists of values) contain less information than raw data, and are poorly standardized. Together, these issues limit FAIR (findable, accessible, interoperable, reusable) access to these data, which in turn creates barriers for compound dereplication and the development of new data-driven discovery tools. Existing NMR databases are either not designed for natural products data, or employ complex deposition interfaces that disincentivize deposition. Journals, including the Journal of Natural Products (JNP), are now requiring data submission as part of the publication process, creating the need for a streamlined, user-friendly mechanism to deposit and distribute NMR data. Recently, our team reported the development of the Natural Products Magnetic Resonance Database (NP-MRD; www.np-mrd.org). Here in this paper we present a new data deposition platform for the NP-MRD project that is designed to enable users to deposit NMR data for published or submitted manuscripts in under five minutes. This platform includes a suite of automated data extraction and standardization tools, together with a simple-to-use web-based interface and detailed error reporting to simplify the data deposition process and is available at www.np-mrd.org/submissions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

Variance-aware weight quantization of multi-level resistive switching devices based on Pt/LaAlO3/SrTiO3 heterostructures

Abstract Resistive switching devices have been regarded as a promising candidate of multi-bit memristors for synaptic applications. The key functionality of the memristors is to realize multiple non-volatile conductance states with high precision. However, the variation of device conductance inevitably causes the state-overlap issue, limiting the number of available states. The insufficient number of states and the resultant inaccurate weight quantization are bottlenecks in developing practical memristors. Herein, we demonstrate a resistive switching device based on Pt/LaAlO 3 /SrTiO 3 (Pt/LAO/STO) heterostructures, which is suitable for multi-level memristive applications. By redistributing the surface oxygen vacancies, we precisely control the tunneling of two-dimensional electron gas (2DEG) through the ultrathin LAO barrier, achieving multiple and tunable conductance states (over 27) in a non-volatile way. To further improve the multi-level switching performance, we propose a variance-aware weight quantization (VAQ) method. Our simulation studies verify that the VAQ effectively reduces the state-overlap issue of the resistive switching device. We also find that the VAQ states can better represent the normal-like data distribution and, thus, significantly improve the computing accuracy of the device. Our results provide valuable insight into developing high-precision multi-bit memristors based on complex oxide heterostructures for neuromorphic applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A novel means to generate high pressure

Diamond anvil cells are the most popular means of generating pressures above 2 GPa. However, in many experiments, such as nuclear magnetic resonance and x-ray absorption, the metallic pressurizing gasket (which confines much of the sample) represents an occluding barrier that requires a low Z gasket material (e.g., Be), a split gasket, or other means to enable better coupling of the sample to electromagnetic radiation. In this paper, we demonstrate a novel method for generating high pressures that confines the sample just above the plane of the gasket by using a diamond with a laser hole drilled into the center of the tip. The sample is then confined by the hole, which is sealed by a flat gasket that fits over the hole. When load is applied to the diamonds, metal flows from the deformed gasket into the hole thereby pressurizing the sample similarly to how a piston pressurizes gas inside a cylinder. The pressurized sample is above the metallic gasket plane just inside the tip of the diamond, and thus easily accessible via x rays or visible light that skims just above the plane of the gasket providing an enhanced aperture of radiation collection. Furthermore, we have demonstrated the utility of this method by obtaining Raman spectra of SnC 2 O 4 and x-ray diffraction spectra of seleno-DL-cystine, all at high pressures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Factors that Impact the Redox Kinetics Associated with Sr1-xAxFeO3 (A = Ca, Ba) in Air Separations Technologies

Perovskite oxides, including SrFeO3-δ, have garnered significant interest for their impressive oxygen storage thermodynamics and kinetics. While traditional oxygen production is performed through cryogenic separation methods at the industrial scale, oxygen carrier-based separations have offered an attractive alternative at the modular scale. Perovskites are considered ideal oxygen carriers, with their structural flexibility minimizing both the thermodynamic barrier and the structural strain related to the oxygen uptake/release cycle. Our latest work has identified a few major factors that directly impact the oxygen release thermodynamics and kinetics for Sr1-xAxFeO3-δ (A = Ca, Ba) materials including elemental composition, crystallographic symmetry, surface area, and pretreatment conditions. This presentation will discuss these factors using Sr1¬-xCaxFeO3 and Ba1-xSrxFeO3 to illustrate their individual and collective impacts on the design of high-performance oxygen carriers when operating at 300-700 °C. Additionally, we will discuss how each of these factors can be leveraged for the numerous catalytic applications also dependent on the redox properties of mixed metal oxides.

Popczun, Eric↗
DOE OSTI2026

Final Technical Report for DE-SC0022206

This project developed foundational genetic, genomic, and epigenetic tools for anaerobic fungi (Neocallimastigomycota), a group of microorganisms with exceptional natural abilities to deconstruct lignocellulosic biomass. Efficient biomass deconstruction remains a major barrier to economical production of renewable fuels, chemicals, and materials from agricultural and forestry residues. The project sought to enable mechanistic studies and future engineering of anaerobic fungi by improving genomic resources, establishing methods for gene expression, and investigating epigenetic regulation of biomass-degrading pathways. Major accomplishments included generation of the first chromosome-scale genome assemblies for multiple anaerobic fungal species, providing publicly available genomic resources that support both engineering and fundamental biological research. The project established the first reproducible system for heterologous gene expression in anaerobic fungi and identified genomic features and mobile genetic elements that may support future development of stable transformation technologies. In parallel, the project demonstrated direct conversion of untreated lignocellulosic biomass into fuels and specialty chemicals through a fungal-yeast bioprocess and identified anaerobic fungal enzymes with utility for metabolic engineering. The research also revealed that epigenetic regulation plays an important role in controlling fungal gene expression and enzyme production, identifying potential strategies for enhancing biomass degradation. Collectively, this work established anaerobic fungi as a tractable emerging platform for bioenergy and biomanufacturing research, generated valuable public resources, trained the next generation of researchers, and advanced DOE-BER goals related to predictive biology, sustainable bioprocessing, and the circular bioeconomy.

Solomon, Kevin [University of Delaware] (ORCID:000↗
DOE OSTI2021

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers: Preprint

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network--that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest--in the sense of electrical distance--from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for real-time operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Electrostatic Barriers to Nanoparticle Accessibility of a Porous Matrix

Translocation from one cavity to another through a narrow constriction (i.e., a “hole”) represents the fundamental elementary process underlying hindered mass transport of nanoparticles and macromolecules within many natural and synthetic porous materials, including intracellular environments. This process is complex and may be influenced by long-range (e.g., electrostatic) particle–wall interactions, transient adsorption/desorption, surface diffusion, and hydrodynamic effects. In this study, we used a three-dimensional (3D) tracking method to explicitly visualize the process of nanoparticle diffusion within periodic porous nanostructures, where electrostatic interactions were mediated via ionic strength. The effects of electrostatic interactions on nanoparticle transport were surprisingly large. For example, an increase in the Debye length of only a few nanometers (in a material with a hole diameter of ~100 nm) increased the mean cavity escape time 3-fold. A combination of computational and experimental analyses indicated that this hindered cavity escape was due to an electrostatic energy barrier in the region of the hole, which was quantitatively explained using DLVO theory. These findings explicitly demonstrate that the cavity escape process was barrier-limited and dominated by electrostatic effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Role of isospin composition in low-energy nuclear fusion

We employ a microscopic approach that examines the impact of isospin dynamics on the process of low- energy nuclear fusion along an isotope chain and dependence on deformation. Our method utilizes the density constrained time-dependent Hartree-Fock theory (DC-TDHF), where isoscalar and isovector characteristics of the energy density functional (EDF) are examined in turn. This approach is applied to a series of fusion interactions of 176 Yb with increasingly neutron rich isotopes of calcium. By evaluating the contributions from the isoscalar and isovector components of the EDF, we look to quantify the influence of isospin composition on the conditions under which fusion is most likely to take place. Furthermore, our findings reveal that, in nonsymmetric systems, the isovector dynamics plays a significant role. Its typical effect is a reduction in the potential barrier, which turns into enhancement for neutron-rich systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Probing Mg Intercalation in the Tetragonal Tungsten Bronze Framework V 4 Nb 18 O 55

While commercial Li-ion batteries offer the highest energy densities of current rechargeable battery technologies, their energy storage limit has almost been achieved. Therefore, there is considerable interest in Mg batteries, which could offer increased energy densities in comparison to Li-ion batteries if a high-voltage electrode material, such as a transition-metal oxide, can be developed. However, there are currently very few oxide materials which have demonstrated reversible and efficient Mg 2+ insertion and extraction at high voltages; this is thought to be due to poor Mg 2+ diffusion kinetics within the oxide structural framework. Here, in this paper, the authors provide conclusive evidence of electrochemical insertion of Mg 2+ into the tetragonal tungsten bronze V 4 Nb 18 O 55 , with a maximum reversible electrochemical capacity of 75 mA h g –1 , which corresponds to a magnesiated composition of Mg 4 V 4 Nb 18 O 55 . Experimental electrochemical magnesiation/demagnesiation revealed a large voltage hysteresis with charge/discharge (1.12 V vs Mg/Mg 2+ ); when magnesiation is limited to a composition of Mg 2 V 4 Nb 18 O 55 , this hysteresis can be reduced to only 0.5 V. Hybrid-exchange density functional theory (DFT) calculations suggest that a limited number of Mg sites are accessible via low-energy diffusion pathways, but that larger kinetic barriers need to be overcome to access the entire structure. The reversible Mg 2+ intercalation involved concurrent V and Nb redox activity and changes in crystal structure, as confirmed by an array of complementary methods, including powder X-ray diffraction, X-ray absorption spectroscopy, and energy-dispersive X-ray spectroscopy. Consequently, it can be concluded that the tetragonal tungsten bronzes show promise as intercalation electrode materials for Mg batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Roll-to-Roll, Dual-Layer Slot Die Coating of Chitin and Cellulose Oxygen Barrier Films for Renewable Packaging

Cellulose and chitin are the two most abundant naturally produced biopolymers and are being extensively studied as candidates for renewable oxygen barrier films used in packaging. It has been shown that bilayers formed from cellulose nanocrystals (CNCs) and chitin nanofibers (ChNFs) exhibit oxygen barrier properties similar to polyethylene terephthalate (PET). However, this prior work explored only coating each layer individually in sequence through techniques such as spray coating. Here, we demonstrate the viability of dual-layer slot die coating of CNC/ChNF bilayers onto cellulose acetate (CA) substrates. The dual-layer slot die method enables significantly lower oxygen permeability versus spray coating while using a roll-to-roll system that applies the bilayer in a single pass. This work discusses suspension properties, wetting, and drying conditions required to achieve well-controlled ChNF/CNC bilayers. Spray-coated bilayer films were on average 25% thinner than the dual-layer bilayer film; however, the thickness-normalized oxygen permeability (OP) of the dual-layer-coated ChNF/CNC bilayer film on CA was 20 times better than that of the spray-coated bilayers. Additionally, it has been shown that ChNF contributes to the wetting and barrier properties. Values of OP for the slot die-coated bilayers under optimized drying conditions were as low as 1.2 cm 3 ∙μm∙m -2 ∙d -1 ∙kPa -1 , corresponding to a normalized oxygen transmission rate of 0.32 cm 3 ∙m -2 ∙d -1 at 23 °C and 50% relative humidity. It is also noted that the adhesive properties of the dual-layer coating are also improved when films are air-dried and that ChNF contributes to the wetting and barrier properties.

09 BIOMASS FUELS↗
DOE OSTI2022

Multifamily Air Leakage Evaluation: A Modular Case Study

The purpose of this case study is to compare the air leakage rates of modular and site-built multifamily dwelling units. The methods, materials, and equipment were observed to be very similar in the modular and site-constructed units in this case study. The installation quality of building envelope measures such as insulation and air barrier appeared to be better for modular construction, because they were installed in a controlled, factory setting. Through field observations, we identified cosmetic damage to the envelope of modular units following transport to the building site, but with no resulting significant air leakage pathways. However, we did see air leakage pathways resulting from field modifications to the envelope of modular units to accommodate structural and mechanical connections. We found that the extensive use of through-wall HVAC systems, combined with the transport, placement, and rework of modular units may compromise the high-quality envelope installation and airtightness observed in the factory without careful planning and/or design. Opportunities for improvement identified from the tested modular dwelling units include minimizing and optimally locating penetrations, pre-cutting and detailing penetrations at the factory where possible, properly sealing field modifications, and using split HVAC systems in place of through-wall packaged systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Advancing Solar Innovation for Low and Moderate-Income Households (Final Technical Report)

The overarching goal of this project was to deepen the understanding of the social and economic aspects of solar adoption, with a specific eye towards any pathways or barriers that could be identified that directly impact low and moderate-income households. Specific objectives included (1) identifying and assessing significant non-economic barriers that complicate the ability of LMI households to adopt and benefit from solar, even under scenarios with low economic barriers; (2) assessing the differential ability of groups to benefit from solar adoption based on their ability to invest in different solar innovations; (3) explaining why some LMI communities nonetheless experience significantly higher rates of solar adoption and benefit than others; (4) developing a methodological model for generating data addressing key issues to the project; and (5) designing and developing an interactive web portal that aggregates existing datasets, provides researchers trend analysis capabilities, standardizes project protocols for other states and communities; provides the opportunities for researchers using the same protocol in other communities to upload their results; and engages with the general public by providing them the ability to upload their own perspectives and stories of solar technology adoption. Through a common framework for conducting semi-structured field interviews. In partnership with cooperative extension services, in conjunction with survey research and the aggregation of existing solar adoption datasets, this study has identified that currently ,there is a strong values alignment and knowledge access challenge that continues to affect solar adoption. Participants in this study – many of whom are either low or moderate-income and/or live in underserved rural communities do not believe solar is an option where they live or believe solar is appropriate for their lifestyle. This perception challenge is further exacerbated by the absolute dearth of adopters in most communities and a total lack of local marketing for solar energy. What marketing that does exist is geared towards audiences other than those in the participant's community, reinforcing a perception that 22% of survey respondents (n = 1,551) have: that solar energy is not meant for them and their community. Overcoming these serious human challenges pertaining to knowledge and marketing are critical to reducing the customer acquisition costs incurred amongst LMI communities and especially those in rural America where the opportunities solar provides to increase local energy resilience, security, all while engaging in personal stewardship of the planet could align with local values. Community-Based Social Marketing, built in partnership with community leaders and geared towards meeting local visions of ideal life, is a near term opportunity to bridge the gap between local priorities and national market and policy imperatives for solar while moving towards the administration's goals for renewable energy as part of a just and equitable decarbonization program. The tools and methods developed for this study can serve as a template for identifying other specific local challenges for solar adoption in other state, and provide the opportunity for a common data framework for understanding system-wide trends and barriers to achieving uptake of residential solar in communities that may, ultimately, benefit the most from the technology.

14 SOLAR ENERGY↗