Search NASA⌕ Search

SEARCH · Search NASA

Results for “new generation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evolution of Dissipative Regimes in Atomically Thin Bi 2 Sr 2 CaCu 2 O 8 + x Superconductor

Thermoelectric transport is widely used to study Abrikosov vortex dynamics in unconventional superconductors. However, only a few thermoelectric studies have been conducted near the dimensional crossover that occurs when the vortex-vortex interaction length scale becomes comparable to the sample size. Here, the effects of finite size on the dissipation mechanisms of the Nernst effect in the optimally doped Bi 2 Sr 2 CaCu 2 O 8 + x high-temperature superconductor are reported, down to the atomic length limit. To access this regime, a new generation of thermoelectric chips based on silicon nitride microprinted circuit boards is developed. These chips ensure optimized signals while preventing sample deterioration. The results demonstrate that lateral confinement at the nanoscale can effectively reduce vortex dissipation. Investigating vortex dissipation at the micro- and nano-scale is essential for creating stable, miniaturized superconducting circuits.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Estimating the State of Charge in Lithium Primary Batteries: Recent Advances and Critical Insights

Lithium primary batteries (LPBs) remain essential in critical applications such as military, aerospace, medical and emergency devices, and portable electronics. Their superior energy density over lithium-ion batteries offers a significant advantage for long-duration use. Therefore, accurate estimation of the state of charge (SoC) is essential for ensuring the reliable and safe operation of these batteries. While extensive research has been conducted on SoC estimation techniques for lithium-ion secondary batteries, LPBs present unique challenges that complicate accurate SoC estimation. Moreover, research on nondestructive testing techniques for SoC estimation in LPBs is significantly lacking. In this review article, it is aimed to provide a comprehensive overview of recent advancements in SoC estimation for LPBs and generates new insights and directions for future research. Herein, existing methods are discussed and their effectiveness and mechanisms are identified, and areas for further optimization are outlined. More theoretical/experimental efforts to advance SoC detection in LPBs is recommended due to challenges identified with existing techniques.

25 ENERGY STORAGE↗
DOE OSTI2024

Rewritable Surface‐Grafted Polymer Brushes with Dynamic Covalent Linkages

Abstract Surface grafting of polymer brushes drastically modifies surface properties, including wettability, compatibility, responsiveness, etc. A broad variety of functionalities can be introduced to the surface via different types of polymers. Bringing together properties of two or more types of polymer brushes to one surface opens up even more possibilities in brush‐modified materials. However, while it is generally feasible to introduce several chemical compositions along the brushes via copolymerization, it is challenging to vary the types of polymer brushes along a surface. Although previous studies have demonstrated binary brushes via orthogonal polymerization techniques or partial deactivation/regrafting, they commonly limit the number of polymer types to two. Here, we propose a strategy to introduce dynamic covalent diketoenamine linkages at the root of polymer brushes. The grafting density could be precisely tuned during surface functionalization. The surface‐anchored polymer brushes were cleaved by the addition of small molecule amines. New polymer brushes can be regrafted from the surface following refunctionalization of exposed sites. The maneuverability allows tuning of the types and densities of the polymer brushes, pointing the way to the preparation of a new generation of well‐defined brush‐modified materials with mixed grafts, with potential applications in the design of smart materials and surfaces.

Cui, Feichen↗
DOE OSTI2024

Antiferromagnetic Ordering in A One‐Dimensional Organic Copper Chloride Hybrid Insulator

Abstract Low dimensional (LD) organic metal halide hybrids (OMHHs) have recently emerged as new generation functional materials with exceptional structural and property tunability. Despite the remarkable advances in the development of LD OMHHs, optical properties have been the major functionality extensively investigated for most of LD OMHHs developed to date, while other properties, such as magnetic and electronic properties, remain significantly under‐explored. Here, we report for the first time the characterization of the magnetic and electronic properties of a 1D OMHH, organic‐copper (II) chloride hybrid (C 8 H 22 N 2 )Cu 2 Cl 6 . Owing to the antiferromagnetic coupling between Cu atoms through chloride bridges in 1D [Cu 2 Cl 6 2− ] ∞ chains, (C 8 H 22 N 2 )Cu 2 Cl 6 is found to exhibit antiferromagnetic ordering with a Néel temperature of 24 K. The two‐terminal (2T) electrical measurement on a (C 8 H 22 N 2 )Cu 2 Cl 6 single crystal reveals its insulating nature. This work shows the potential of LD OMHHs as a highly tunable quantum material platform for spintronics.

Islam, Md Sazedul↗
DOE OSTI2025

Zwitterionic Photocurable Resin for High‐Resolution 3D Printing of Ultralow‐Fouling Microstructures

High‐resolution 3D printing technologies are enabling a new generation of microstructured materials for applications where biocompatibility is critical. However, most conventional 3D‐printable resins yield materials that exhibit trade‐offs between antifouling properties and mechanical robustness, limiting their applicability in living systems. In nature, zwitterionic surface groups form tightly bound hydration layers that act as effective barriers against protein and cell attachment. Inspired by this strategy, a zwitterionic acrylamide‐based photoresist—carboxybetaine di‐methacrylamide (CBDA)—is developed for projection‐based vat photopolymerization, enabling the fabrication of complex microarchitectures with exceptional antifouling properties. The bifunctional monomer allows the formation of dense, cross‐linked networks that resist swelling while maintaining a high density of zwitterionic groups. Printed structures exhibit strong resistance to protein and cell adhesion, as confirmed by porcine blood assays, alongside robust mechanical performance. As a demonstration, a tubular structure featuring a negative Poisson's ratio lattice is printed to showcase structural fidelity and versatility. This resin formulation offers a broadly applicable strategy for fabricating microscale devices and surfaces where antifouling performance and structural integrity are both essential—spanning biomedical interfaces, soft robotics, and beyond.

3D printing↗
DOE OSTI2024

From large to small $$ \mathcal{N} $$ = (4, 4) superconformal surface defects in holographic 6d SCFTs

Abstract Two-dimensional (2d)$$ \mathcal{N} $$ N = (4, 4) Lie superalgebras can be either “small” or “large”, meaning their R-symmetry is either$$ \mathfrak{so} $$ so (4) or$$ \mathfrak{so} $$ so (4) ⊕$$ \mathfrak{so} $$ so (4), respectively. Both cases admit a superconformal extension and fit into the one-parameter family$$ \mathfrak{d} $$ d (2,1;γ) ⊕$$ \mathfrak{d} $$ d (2,1;γ), with parameterγ∈ (−∞,∞). The large algebra corresponds to generic values ofγ, while the small case corresponds to a degeneration limit withγ→ −∞. In 11d supergravity, we study known solutions with superisometry algebra$$ \mathfrak{d} $$ d (2,1;γ) ⊕$$ \mathfrak{d} $$ d (2,1;γ) that are asymptotically locally AdS 7 ×𝕊 4 . These solutions are holographically dual to the 6d maximally superconformal field theory with 2d superconformal defects invariant under$$ \mathfrak{d} $$ d (2,1;γ) ⊕$$ \mathfrak{d} $$ d (2,1;γ). We show that a limit of these solutions, in whichγ→ −∞, reproduces another known class of solutions, holographically dual tosmall$$ \mathcal{N} $$ N = (4, 4) superconformal defects. We then use this limit to generate new small$$ \mathcal{N} $$ N = (4, 4) solutions with finite Ricci scalar, in contrast to the known small$$ \mathcal{N} $$ N = (4, 4) solutions. We then use holography to compute the entanglement entropy of a spherical region centered on these small$$ \mathcal{N} $$ N = (4, 4) defects, which provides a linear combination of defect Weyl anomaly coefficients that characterizes the number of defect-localized degrees of freedom. We also comment on the generalization of our results to include$$ \mathcal{N} $$ N = (0,4) surface defects through orbifolding.

Physics↗
DOE OSTI2023

Additively manufactured Al-Ce-Ni-Mn alloy with improved elevated-temperature fatigue resistance

Here, the high cycle fatigue behavior of an additively manufactured (AM) Al-10.5Ce-3.1Ni-1.2Mn wt% alloy was evaluated at 350 °C. The measured fatigue strength of 50 MPa at this temperature is comparable to the most fatigue resistant wrought Al alloys (2618-T6 and 7079-T6) at 315 °C. Refinement of pore populations through advanced AM processing in the examined alloy led to oxide inclusions becoming dominant fatigue crack initiation sites. The distribution of microstructural features that determine crack initiation was measured by X-ray computed tomography and served as input to make fatigue strength model predictions with various methodologies. A Monte-Carlo based approach that was previously applied to predict the fatigue strength of cast aluminum alloys through pore size distributions yielded accurate predictions for the fatigue strength of this AM alloy. Given the tunability of defect distributions in AM alloys, the sensitivity of the Al-Ce-Ni-Mn alloy fatigue behavior to defect distributions and outstanding elevated-temperature fatigue resistance of this alloy; the results together suggest the possibility of a new generation of fatigue-resistant alloys produced by the additive manufacturing route.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking

The intermittency of carbon-free renewables and the demand changes associated with the widespread push for electrifying the transportation and building sectors provides an opportunity for buildings to go beyond energy efficiency and push towards providing demand flexibility to the electricity grid. The duality of energy efficiency and demand flexibility is necessary for success in a sustainable and reliable energy transition. Current building energy benchmarking models are limited in their ability to integrate concepts of demand flexibility and/or utilize granular smart meter data. Thus, current benchmarking methods are focused annual energy usage and fail to incorporate how the time of use of energy consumption impacts emissions in a quickly changing energy grid. Without a more comprehensive view of energy usage and associated real-time emissions, current benchmarking methods are unlikely to realize the full decarbonization potential of buildings. New emerging data streams provide an opportunity to develop a new generation of benchmarking energy models that embed dimensions of energy efficiency, grid interactivity, and demand flexibility into their analysis. In this paper, we propose a four-step method for embedding grid interactivity and demand flexibility into building benchmarking models that utilizes emerging building and time-series electricity data streams. We first engineer features to produce a mix-type dataset that encompasses many attributes of grid-interactive and efficient buildings, and then we apply K-medoids using Gower's Distance to produce peer-group clusters. We apply the method to a case study of 306 primary and secondary schools in southern California, USA. The results show that the method effectively clusters buildings by attributes of demand flexibility and energy efficiency. The clustering results reveal patterns in inefficient building operations and demand inflexibility at the building peer group level. In conclusion, the interpretation of clusters can serve as an integrated energy efficiency and demand flexibility benchmarking model and inform performance-specific policy targeting for buildings that go beyond traditional efficiency measures.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Unlocking the biofuel power of cover crop in Washington State: Enhancing potential through hydrothermal liquefaction

This study evaluates cover crops in Washington State (WA) as a renewable feedstock for hydrothermal liquefaction (HTL), supported by techno-economic (TEA) and life cycle (LCA) analysis. In the Pacific Northwest, fallow land is the common winter practice, generating no income for farmers. Over three years, field trials at two representative sites—Puyallup (cool, wet) and Othello (irrigated, no-till)tested triticale, hairy vetch, crimson clover, winter pea, and fava bean preceding cash crops. Biomass yields, composition, soil impacts, and net revenue were assessed across removal treatments. HTL conversion produced 32–37 wt% biocrude, lower than 48 wt% for sewage sludge, with modeled cradle-to-grave carbon intensities of 26–31 g CO 2 e/MJ and minimum fuel selling prices (MFSP) of $\$$6.75–$\$$7.18 per gallon gasoline equivalent (GGE), comparable to other lignocellulosic feedstocks. No significant changes were observed in soil carbon, nitrogen, or subsequent cash crop yields after cover crop removal. Farmer profitability was possible, particularly for triticale and hairy vetch at $\$$60 per dry ton. To address seasonal variability, blending with wastewater sludge was evaluated. All scenarios delivered >70 % carbon intensity reductions relative to fossil fuels, and with Renewable Identification Number (RIN) credits, MFSPs below $\$$2.5 GGE were achievable. These results demonstrate that cover crops can generate new revenue streams for farmers while serving as a flexible, low-carbon feedstock. Integrating cover crops with waste biomass offers a practical pathway to expand the bioeconomy and support year-round renewable fuel production.

Biofuels↗
DOE OSTI2024

Anion-derived contact ion pairing as a unifying principle for electrolyte design

Enabling new electrochemical technologies requires systems that can operate under ever-more demanding conditions, and progress in energy storage applications reveals tantalizing opportunities to reimagine electrolyte design for performance at extreme potentials. Here, a common thread among these innovations is the formation of significant populations of contact ion pairs (CIPs) in the electrolyte, regardless of the specific cation chemistry or solvent system. The examples summarized in this review suggest that a set of general electrolyte design rules likely exists, where the purposeful selection of anion chemistry can yield CIP structures with tunable control over reaction thermodynamics, kinetics, and interphase chemistry. Identifying the relevant descriptors for high-performance, anion-derived CIP structures can be achieved utilizing a combined experimental and computational approach, aided by machine learning and artificial intelligence, to more rapidly survey the vast combinatorial space available and to enable a new generation of electrolytes for decarbonized electrochemical processes at scale.

electrochemistry↗
DOE OSTI2022

Defects and anomalies in powder bed fusion metal additive manufacturing

Metal additive manufacturing is a disruptive technology that is revolutionizing the manufacturing industry. Despite its unrivaled capability for directly fabricating metal parts with complex geometries, the wide realization of the technology is currently limited by microstructural defects and anomalies, which could significantly degrade the structural integrity and service performance of the product. Accurate detection, characterization, and prediction of these defects and anomalies have an important and immediate impact in manufacturing fully-dense and defect-free builds. As such, this review seeks to elucidate common defects/anomalies and their formation mechanisms in powder bed fusion additive manufacturing processes. They could arise from raw materials, processing conditions, and post-processing. While defects/anomalies in laser welding have been studied extensively, their formation and evolution remain unclear. Additionally, the existence of powder in powder bed fusion techniques may generate new types of defects, e.g., porosity transferring from powder to builds. Practical strategies to mitigate defects are also addressed through fundamental understanding of their formation. Such explorations enable the validation and calibration of models and ease the process qualification without costly trial-and-error experimentation.

42 ENGINEERING↗
DOE OSTI2026

Comparison of structurally diverse simulation models for prediction of epidemic outcomes caused by a long-distance dispersed pathogen

Long-distance dispersal (LDD) pathogens pose substantial challenges for epidemic control due to their ability to generate new infection foci at great distances. While various modeling approaches have been developed to understand and manage such outbreaks, little work has compared how models of different structures behave under shared conditions. Here, in this study, we compare four structurally distinct epidemiological models — EPIMUL, GEMF, PoPS, and Warwick — each adapted to simulate the spread of wheat stripe rust (WSR), a wind-dispersed LDD pathogen, under identical epidemiological parameters and dispersal kernel. Using data from a controlled field experiment, we evaluate the ability of each model to replicate disease prevalence under nine intervention scenarios that vary in timing and culling area. While the models differ substantially in design — ranging from spatial grid-based to network-based and raster-based frameworks — the shared dispersal kernel allowed for close alignment in their predictions. All models accurately captured general epidemic trends, particularly the strong effect of early intervention on disease suppression. We qualitatively compared their behavioral responses across scenarios and also evaluated an ensemble prediction by averaging across model outputs. Our findings highlight how integrating shared epidemiological components into distinct modeling frameworks can improve consistency and accuracy, while reinforcing the importance of early culling in managing LDD pathogen outbreaks.

Dispersal kernel↗
DOE OSTI2020

Resilience framework and metrics for energy master planning of communities

Changes in the nature, intensity, and frequency of climate-related extreme events have imposed a higher risk of failure on energy systems, especially those at the community level. Furthermore, the evolving energy demand patterns and transition towards renewable and localised energy supply can affect energy system resilience. How can an energy system be planned and reconfigured to address these challenges without compromising the system's resilience against chronic stresses and extreme events? Unlike energy system reliability, resilience is neither a common nor an explicit consideration in energy master planning at the community level. In addition, there is no universally agreed-upon method or metrics for measuring or estimating resilience and defining mitigation strategies. This paper introduces a multi-layered energy resilience framework and set of metrics for energy master planning of communities, including the new generation of district energy systems. The potential system disturbances and their short and long-term impacts on various components of the energy system are discussed for commonly expected and extreme events. Three layers of energy resilience are discussed: engineering-designed resilience, operational resilience, and community-societal resilience. A starting set of energy resilience metrics to support engineering design and energy master planning for communities is identified. Implications for future research and practice are noted.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Radiological analysis and transmutation calculation of representative castable nanostructured alloys

In this work, radiological analysis regarding the waste management was performed on two current reduced-activation ferritic-martensitic (RAFM) steels Eurofer 97 and F82H and two castable nanostructured alloys (CNAs) CNA1 and CNA3 using the European DEMO first wall spectrum. CNA1 and CNA3 are a new generation of RAFM steels, which have increased amounts of nanoscale carbonitrides and carbides precipitates, respectively, via small composition modifications. Furthermore, the increased nitrogen in CNA1 leads to higher activity at ≥50 years, and thus to the disposal concern under the current NRC regulation. However, the calculation using Fetter’s evaluation leads to reduced waste disposal rating (WDR) of down to 0.25 depending on the damage dose from ~0.05 wt percent nitrogen in CNA1, and thus less concern on the waste disposal. Contact dose rate after 10 years from the first wall replacement primarily depends on the initial Co and Nb impurity levels. Other added elements, such as V and Si in CNA1 and Ti and Mn in CNA3, do not have significant effect on the specific activity, contact dose rate, or decay heat. Composition limits of CNAs are given based on the shallow burial disposal and materials recycling. In addition, composition evolution of typical precipitates in the CNAs was calculated using the DEMO first wall and the HFIR spectra. Larger transmutation-induced composition evolution occurs in the V/Ta-rich carbonitrides in CNA1 than that in the Ti-rich carbides in CNA3.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Design and engineering challenges of a multi-energy hard x-ray camera for long-pulse profile measurements at WEST tokamak

The WEST tokamak has recently been prepared for long pulse operation with a water-cooled full first wall. Heating is provided by radiofrequency systems, including Lower Hybrid Current Drive (LHCD). The Princeton Plasma Physics Laboratory has developed a multi-energy hard x-ray camera for profile measurements at WEST. The camera is based on a new generation of 2D pixel array detectors that allow the energy threshold to be independently set for each pixel. The diagnostic will provide spatial, temporal and energy resolved measurements of the hard x-ray emission from the full plasma cross-section, investigating several physical quantities such as the electron temperature from continuum emission, the fast electron tail density produced by radiofrequency current drive and runaway electrons, as well as characteristic tungsten x-rays due to beam-target emission at the edge. Overall, this work describes the engineering challenges that the WEST long pulse scenario poses for this diagnostic and how the design addresses and solves them. Vacuum, thermal stress and heat transfer calculations are presented and discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Influence of fine-scale B2 precipitation on dynamic compression and wear properties in hypo-eutectic Al0.5CoCrFeNi high-entropy alloy

The near equiatomic high-entropy alloys based on Al, Co, Cr, Fe, Ni have provided a novel microstructural template for alloy design. The face-centered cubic (FCC) matrix strengthened by body-centered cubic (BCC) based ordered B2 precipitates can be used to develop a new generation of precipitation strengthened alloys. The present study focuses on an Al0.5CoCrFeNi hypo-eutectic alloy consisting of an as-solidified FCC+B2 microstructure. Guided by solution thermodynamic modeling, this alloy has been isothermally aged for solid-state precipitation of a high fraction of fine-scale intragranular B2 particles. The dynamic compressive strength, hardness, and sliding wear response of the alloy as a function of B2 phase fraction is examined. The flow stress at 0.02% true strain increased from ~ 670 MPa to ~1350 (102%) MPa, the ultimate compressive strength increased from ~1160 MPa to 1500 MPa (20%), and the wear resistance increased more than 5 times with progressively increasing phase fraction of B2 precipitates.

Gwalani, Bharat↗