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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Restriction-In-Motion of Surface Ligands Enhances Photoluminescence of Quantum Dots - Experiment and Theory

Here the relationship between emission and ligand restriction of a series of ZnSe/ZnS quantum dots (QDs) encapsulated in nanoparticles is investigated systematically via experiments and quantum theory. The QDs have a ZnSe core and a ZnS shell, capped with hydrophobic ligands (triotylphosphine oxide/hexadecylamine), allowing them to be entrapped in a model biomembrane, bicelle, made of zwitterionic dipalmitoyl and dihexanoyl phosphatidylcholines and charged dipalmitoyl phosphatidylglycerol. Enhanced photoluminescence is observed upon encapsulation, depending on the QD-to-lipid ratio. Transmission electron microscopy and small-angle X-ray scattering confirm that QDs are preferably situated at the rim of bicellar discs. A simplified quantum dissipation heat-bath theory is proposed to correlate the enhancement with slower nonradiative processes caused by the restriction-in-motion (RIM) of the surface ligands. However, Fõrster resonance energy transfer due to QD aggregation counteracts the effect.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Direct Demonstration of Unified Brønsted-Evans-Polanyi Relationships for Proton-Coupled Electron Transfer Reactions on Transition Metal Surfaces

Brønsted-Evans-Polanyi (BEP) relationships, which relate elementary reaction barriers to reaction thermodynamics, have long been discussed in electrochemical science, but demonstration of their existence in heterogeneous electrocatalysis, across many different catalyst surfaces and voltages, is lacking. In this contribution, the BEP model is demonstrated to describe both multiple catalyst surfaces and variable voltages in electrochemical environments. For proton-coupled electron transfer (PCET) to surface nitrogen (N*) and nitric oxide (NO*), reaction energies and activation barriers are calculated using Density Functional Theory (DFT) on a parallel plate capacitor model at three different potentials and for nine different transition metal surfaces. Linear BEP relations that describe all potentials and catalyst surfaces are obtained for these elementary reactions, and the slopes of the correlations are shown to be directly related to the fractional coordinate of the transition states (FCTS) of the reactions. The results, which are explained in terms of Marcus Theory, prove a direct equivalence between unified BEP coefficients, describing both variable catalyst surfaces and voltages, and electrochemical symmetry factors and provide a straightforward means of estimating this quantify for PCET reactions on transition metal surfaces. The resulting relationships, in turn, could lead to predictions of electrocatalytic reactivity trends of enhanced accuracy and efficiency.

Electrochemistry↗
DOE OSTI2023

A numerical simulation of CCN impacts on weather modification efficiency

Aerosols affect development of clouds and precipitation by serving as cloud condensation nuclei (CCN) and ice nuclei (IN). Considering the dramatically changing ambient aerosol concentration, it is important to examine the potential “side effect” of aerosol pollution on precipitation enhancement by weather modification. In this study, the cloud seeding was performed on a precipitation event in Beijing in the summer of 2008, which is simulated by the NSSL two-moment cloud scheme of the Weather Research and Forecasting (WRF) model. Sensitivity tests were conducted by modifying the ambient aerosol concentration and the ice crystal seeding amount to investigate the cloud seeding efficacy in different CCN concentration scenarios. There was a slight difference in the precipitation distribution between the simulations with two ambient CCN concentrations: the northern precipitation center in polluted scenario was weaker and the southern center was stronger. Compared with normal CCN scenario, the cloud liquid water mass and ice crystal mass in the severe pollution scenario is larger, and the total contents of snow and graupel were not sensitive to the CCN concentration. With the same amount of man-made ice crystals seeding, the precipitation enhancement was quite different under different CCN conditions. The higher the CCN concentration usually leads to stronger precipitation suppression. As CCN concentration increase, the deposition growth of snow, auto-conversion and accretion of ice crystals to snow were weakened, as well as the conversion of melting snow and graupel into rainwater.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Observation of Seeded Mn K β Stimulated X-Ray Emission Using Two-Color X-Ray Free-Electron Laser Pulses

Kβ x-ray emission spectroscopy is a powerful probe for electronic structure analysis of 3d transition metal systems and their ultrafast dynamics. Selectively enhancing specific spectral regions would increase this sensitivity and provide fundamentally new insights. Recently we reported the observation and analysis of Kα amplified spontaneous x-ray emission from Mn solutions using an x-ray free-electron laser to create the 1s core-hole population inversion [Kroll et al., Phys. Rev. Lett. 120, 133203 (2018)]. To apply this new approach to the chemically more sensitive but much weaker Kβ x-ray emission lines requires a mechanism to outcompete the dominant amplification of the Kα emission. Here we report the observation of seeded amplified Kβ x-ray emission from a NaMnO 4 solution using two colors of x-ray free-electron laser pulses, one to create the 1s core-hole population inversion and the other to seed the amplified Kβ emission. Comparing the observed seeded amplified Kβ emission signal with that from conventional Kβ emission into the same solid angle, we obtain a signal enhancement of more than 10 5 . Finally, our findings are the first important step of enhancing and controlling the emission of selected final states of the Kβ spectrum with applications in chemical and materials science.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Challenges and Opportunities in Deep Reinforcement Learning With Graph Neural Networks: A Comprehensive Review of Algorithms and Applications

Deep reinforcement learning (DRL) has empowered a variety of artificial intelligence fields, including pattern recognition, robotics, recommendation-systems, and gaming. Similarly, graph neural networks (GNN) have also demonstrated their superior performance in supervised learning for graph-structured data. In recent times, the fusion of GNN with DRL for graph-structured environments has attracted a lot of attention. Here, this paper provides a comprehensive review of these hybrid works. These works can be classified into two categories: (1) algorithmic enhancement, where DRL and GNN complement each other for better utility; (2) application-specific enhancement, where DRL and GNN support each other. This fusion effectively addresses various complex problems in engineering and life sciences. Based on the review, we further analyze the applicability and benefits of fusing these two domains, especially in terms of increasing generalizability and reducing computational complexity. Finally, the key challenges in integrating DRL and GNN, and potential future research directions are highlighted, which will be of interest to the broader machine learning community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Capturing Travel Mode Adoption in Designing On-Demand Multimodal Transit Systems

This paper studies how to integrate rider mode preferences into the design of on-demand multimodal transit systems (ODMTSs). It is motivated by a common worry in transit agencies that an ODMTS may be poorly designed if the latent demand, that is, new riders adopting the system, is not captured. This paper proposes a bilevel optimization model to address this challenge, in which the leader problem determines the ODMTS design, and the follower problems identify the most cost efficient and convenient route for riders under the chosen design. The leader model contains a choice model for every potential rider that determines whether the rider adopts the ODMTS given her proposed route. To solve the bilevel optimization model, the paper proposes an exact decomposition method that includes Benders optimal cuts and no-good cuts to ensure the consistency of the rider choices in the leader and follower problems. Moreover, to improve computational efficiency, the paper proposes upper and lower bounds on trip durations for the follower problems, valid inequalities that strengthen the no-good cuts, and approaches to reduce the problem size with problem-specific preprocessing techniques. The proposed method is validated using an extensive computational study on a real data set from the Ann Arbor Area Transportation Authority, the transit agency for the broader Ann Arbor and Ypsilanti region in Michigan. The study considers the impact of a number of factors, including the price of on-demand shuttles, the number of hubs, and access to transit systems criteria. The designed ODMTSs feature high adoption rates and significantly shorter trip durations compared with the existing transit system and highlight the benefits of ensuring access for low-income riders. Finally, the computational study demonstrates the efficiency of the decomposition method for the case study and the benefits of computational enhancements that improve the baseline method by several orders of magnitude. Funding: This research was partly supported by National Science Foundation [Leap HI Proposal NSF-1854684] and the Department of Energy [Research Award 7F-30154].

Operations Research & Management Science↗
DOE OSTI2023

Sorption-enhanced steam reforming of toluene using multifunctional perovskite phase transition sorbents in a chemical looping scheme

Abstract Sorption-enhanced steam reforming (SESR) of toluene (SESRT) using catalytic CO 2 sorbents is a promising route to convert the aromatic tar byproducts formed in lignocellulosic biomass gasification into hydrogen (H 2 ) or H 2 -rich syngas. Commonly used sorbents such as CaO are effective in capturing CO 2 initially but are prone to lose their sorption capacity over repeated cycles due to sintering at high temperatures. Herein, we present a demonstration of SESRT using A- and B-site doped Sr 1− x A’ x Fe 1− y B’ y O 3− δ (A’ = Ba, Ca; B’ = Co) perovskites in a chemical looping scheme. We found that surface impregnation of 5–10 mol% Ni on the perovskite was effective in improving toluene conversion. However, upon cycling, the impregnated Ni tends to migrate into the bulk and lose activity. This prompted the adoption of a dual bed configuration using a pre-bed of NiO/ γ –Al 2 O 3 catalyst upstream of the sorbent. A comparison is made between isothermal operation and a more traditional temperature-swing mode, where for the latter, an average sorption capacity of ∼38% was witnessed over five SESR cycles with H 2 -rich product syngas evidenced by a ratio of H 2 : CO x > 4.0. XRD analysis of fresh and cycled samples of Sr 0.25 Ba 0.75 Fe 0.375 Co 0.625 O 3- δ reveal that this material is an effective phase transition sorbent—capable of cyclically capturing and releasing CO 2 without irreversible phase changes occurring.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Retrospective on decadal progress of the NOAA/NPS ocean noise reference station network

The National Oceanic and Atmospheric Administration (NOAA), in partnership with the U.S. National Park Service (NPS), established the Ocean Noise Reference Station Network (NRS) in 2014 as a foundational component of NOAA’s Ocean Noise Strategy. This long-term effort aims to characterize baseline ocean ambient sound conditions across diverse marine environments and to inform management of noise impacts on protected species and habitats within U.S. waters. The NRS is now composed of 13 autonomous passive acoustic monitoring stations strategically positioned across the U.S. Exclusive Economic Zone (EEZ), extending from Arctic regions to tropical waters in depths ranging from 33 to 4,790 m. These locations include several National Marine Sanctuaries and National Parks, such as the recently designated Chumash Heritage National Marine Sanctuary off the coast of California. Each station is equipped to continuously sample low-frequency underwater sound at five kHz, enabling the detection of anthropogenic, geophysical, and biological acoustic signals. To date the network has sampled over 72 years of calibrated acoustic data. The spatial breadth and consistent methodology of the NRS allow for comparative acoustic assessments across diverse marine ecosystems. In addition to applied research functions, the NRS has served as a platform for education and training, offering opportunities for students to develop skills for marine science and data analysis. Looking forward, the NRS project team is focused on network expansion, improved data delivery, and broader integration with collaborative scientific initiatives. NRS recordings are being archived in partnership with NOAA’s National Centers for Environmental Information to enhance accessibility and long-term utility. Efforts are underway to develop standardized metadata and summary products to accompany raw audio files, making the data more usable for a wide range of stakeholders in the ocean science community. The NRS is evolving into a fully integrated national framework for ocean sound monitoring that supports scientific inquiry, management decision-making, national security interests, and public engagement with ocean acoustic environments.

Long-term monitoring↗
DOE OSTI2020

Baking and plasma pretreatment of sapphire surfaces as a way to facilitate the epitaxial plasma-enhanced atomic layer deposition of GaN thin films

The growth of high-quality epitaxial gallium nitride (GaN) thin films is achieved by using a baking and plasma pretreatment of the substrate prior to the GaN plasma-enhanced atomic layer deposition (PE-ALD). In this work, it is found that such pretreatment makes the GaN films grow coherently on sapphire substrates, following a layer-by-layer growth mechanism. The deposited GaN film shows high crystalline quality, a sharp GaN/sapphire interface, and a flat surface. The possibility of growing high-quality GaN epilayers in this way broadens the range of applications for PE-ALD in GaN-based devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Performance analysis of photodetectors based on 2D materials and heterostructures

The unprecedented demand for sophisticated, self-powered, compact, ultrafast, cost-effective, and broadband light sensors for a myriad of applications has spurred a lot of research, precipitating in a slew of studies over the last decade. Apart from the photosensing ability of an active element in the light sensor, the device architecture is crucial in terms of photoinduced charge carrier generation and separation. Since the inception of graphene and the subsequent research growth in the atomically thin 2D materials, researchers have developed and adapted different families of 2D materials and device architectures, including single element 2D, 0D/2D, 2D/2D, 1D/2D stacked structures, and so on. Here this review discusses the recent reports on the light-sensing properties of various 2D materials, their heterostructures, and characteristics applicable to the ultraviolet-near infrared (UV-NIR), short-wave IR (SWIR), mid-wave IR (MWIR), long-wave IR (LWIR), and terahertz (THz) spectral ranges. It highlights the novelty of the burgeoning field, the heightened activity at the boundaries of engineering and materials science, particularly in the generation of charge carriers, their separation, and extraction, and the increased understanding of the underpinning science through modern experimental approaches. Devices based on the simultaneous effects of the pyro-phototronic effect (PPE) and the localized surface plasmon resonance (LSPR) effect, the photothermoelectric effect (PTE)-assisted photodetectors (PDs), waveguide-integrated silicon-2D PDs, metal-2D-metal PDs, and organic material PDs are examined rigorously. Theoretical treatment utilizing various computational approaches to investigate 2D materials and heterostructures for photodetection applications is also briefly discussed. At the end, current challenges and solutions to enhance the figures of merit of photodetectors are proposed.

2D transition metal chalcogenides↗
DOE OSTI2021

Fundamental Studies of Tritium Diffusivity in Pure and Defective Zircaloy-4 Getters (Tritium Science Program FY2020 Report)

Zirconium (Zr) alloys are extensively used as tritium (T) getters in nuclear reactors due to their low absorption cross section to thermal neutron, good mechanical properties at high temperature and resistant to corrosion in different environmental conditions. Zr alloys have better thermal properties than many other refractory alloys including stainless steel. The nuclear characteristic is simulated, and T is produced in tritium-producing burnable absorber rods (TPBAR) by the irradiation of neutron flux in pressurized water reactor (PWR). T thus produced diffuses through the pellets and is captured by the getter where it chemically reacts with Zr to form metal hydride (ZrTx). These hydrides are brittle and affect adversely the mechanical properties of alloys. In addition to that, mismatch in the lattice structures after hydride formation creates a stress which needs to be considered in component design and their life evaluation. Therefore, understanding the behavior of T and its species becomes significant as fuel burnup is increased, which leads to increase in hydrogen pickup and oxide formation. The transport of T and its species in pure Zr alloys, and in alloys with certain alloying elements and defects are important to understand in order to enhance the performance of the materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Enhancing Discoverability and Management of Atmospheric Data at Scale: Solutions from the ARM Data Center

The Atmospheric Radiation Measurement (ARM) is a multi-laboratory and multi-institutional U.S. Department of Energy (DOE) Office of Science National User Facility. The ARM Data Center (ADC), located at Oak Ridge National Laboratory, collects, archives, and shares vast atmospheric data crucial for climate research. The ADC manages over 7 PB of data from 460 instruments worldwide, processing it into more than 11,000 diverse data products using the Network Common Data Form (NetCDF) for machine-independent accessibility. The primary challenge addressed in this paper is the efficient management and distribution of vast and diverse datasets essential for the climate research community, enhancing accessibility through advanced tools like Data Discovery. The ADC has developed advanced infrastructure and software architecture to handle the continuous influx of heterogeneous data to enhance data discoverability, resulting in increased scientific collaboration. In 2023, users from over 34 countries downloaded and utilized ARM data, resulting in 1,455 publications. The ADC’s efforts have significantly improved the discoverability and usability of atmospheric data, fostering extensive scientific research and collaboration. This paper details the solutions implemented by the ADC team for efficient data discovery and distribution, and it demonstrates ARM’s capability of staging processed data for scientific analysis.

Shah, Chirag [ORNL] (ORCID:0000000203145737)↗
DOE OSTI2023

Development of a Portable In Situ Phosphorous Sensor

While phosphorus is a critical nutrient for all forms of life, runoff leads to phosphorus accumulation in surface water where it can cause a variety of health, environmental, and economic problems. The Department of Energy is interested in conducting long-term field experiments to monitor the impact of phosphorus in terrestrial and aquatic environments, and to better understand a cost vs. benefit analysis of reducing phosphorus pollution. Performing such long-term experiments requires affordable sensors capable of monitoring low-level phosphorus concentrations under challenging environmental conditions. However, such sensors are currently not available. The goal of this proposed project is to develop and demonstrate a low-cost portable phosphorus sensor suitable for in situ measurements. We will determine the technical requirements for a Raman-based sensor system, design and build a signal amplifier, integrate it with a Raman-based sensor, and demonstrate a proof-of-concept level sensor system. The expected accomplishments for Phase I include the identification of the technical requirements of a combined Raman laser/spectrometer and cavity enhancement system, building a proof-of-concept level sensor system capable of detecting orthophosphate compounds at the desired level of 0.25 mg P/L and organic P compounds, and verification of the sensor performance under laboratory and field conditions. In addition, we will identify initial hardening requirements that will need to be implemented during Phase II. While we plan to develop an integrated sensor system for monitoring phosphorus, the cavity-based enhancement system can also be used in combination with other (non-phosphorus) Raman sensors that we plan to develop or that are already commercially available. A recent market report highlights the increasing demand for such environmental monitoring applications, with the market for chemical detection anticipated to grow at a compound annual growth rate of 6.5% (2020-2025). Wide-spread monitoring of phosphorus could reduce the damage from eutrophication in freshwater, which is estimated to be $2.2 billion annually, thereby increasing biodiversity, reducing costs required for drinking water treatment, and decreasing economic losses related to recreation and angling and lake property values.

54 ENVIRONMENTAL SCIENCES↗