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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Sensitivity Studies, Gap Analysis, and Benchmark Experiment Optimization for Reactor Physics and Criticality Safety Applications

Many new reactor designs, such as advanced reactors and micro reactors, have materials that lack nuclear data validation. This is also true for many other applications in criticality safety and global security. Both differential and integral experiments are needed to validate cross-section data. Without this, a user cannot have confidence in the predicted results of a radiation-transport code. This work describes an approach called ARCHIMEDES (Application Relevant Critical/Subcritical HEU/Pu-based Integral Measurements for Enhancing Data and Evaluating Sensitivities) to design new criticality experiments that have similar k eff cross-section sensitivities to an application of interest. This process involves simulations to generate cross-section sensitivities to a parameter of interest (such as k eff ), a gap analysis to determine which existing benchmarks are most similar to the application, and an experiment optimization. Recently, there has been a great deal of interest in the reactor physics community on advanced reactors, micro reactors, and accelerator driven systems (ADS). This work will apply the described method to specific examples in this area. The focus of this work will be on the sensitivity study and gap analysis, while future work will include experiment design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Guided Resilience Self Assessment Application

Reliable electricity access is vital for everything from hospitals to national security. When grid disturbances occur, it is crucial to minimize the amount of time it takes to recover. Grid resiliency considers both the preparation for and recovery from high-impact low-frequency disturbances (HILF) such as weather events and cyber attacks. The Department of Energy (DOE) Wind Energy Technologies Office (WETO) funds the multi-laboratory Microgrids, Infrastructure Resilience, and Advanced Control Launchpad (MIRACL) project to investigate technologies to support and grow distributed wind. Researchers at Idaho National Laboratory (INL) contribute to resilience and cybersecurity efforts for the project, and have produced a resilience framework to evaluate system resilience based on individual system specifications. In order to make this framework easy for anyone to apply, I have coded a web application that allows users to input their power system qualities, goals, and perceived risks and then receive suggestions on how to improve their grid resiliency. The web application follows the seven steps in the planning stage of the framework process, allowing the user to input information about their grid and select from common goals, metrics, and hazards, as well as add their own. The application currently provides information about how to complete each step, requiring minimal prior knowledge of the framework. Future work for this application will include allowing the user to submit line drawings of their system and incorporate modeling tools so that the hazard simulations of applying the framework is completed for the user.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Composition-Dependent Photoluminescence Properties and Anti-Counterfeiting Applications of A 2 AgX 3 (A = Rb, Cs; X = Cl, Br, I)

Copper(I) halides are emerging as attractive alternatives to lead halide perovskites for optical and electronic applications. However, blue-emitting all-inorganic copper(I) halides suffer from poor stability and lack of tunability of their photoluminescence (PL) properties. In this work, the preparation of silver(I) halides A 2 AgX 3 (A = Rb, Cs; X = Cl, Br, I) through solid-state synthesis is reported. In contrast to the Cu(I) analogs, A 2 AgX 3 are broad-band emitters sensitive to A and X site substitutions. First-principle calculations show that defect-bound excitons are responsible for the observed main PL peaks in Rb 2 AgX 3 and that self-trapped excitons (STEs) contribute to a minor PL peak in Rb 2 AgBr 3 . This is in sharp contrast to Rb 2 CuX 3 , in which the PL is dominated by the emission by STEs. Moreover, the replacement of Cu(I) with Ag(I) in A 2 AgX 3 significantly improves photostability and stability in the air under ambient conditions, which enables their consideration for practical applications. Thus, luminescent inks based on A 2 AgX 3 are prepared and successfully used in anti-counterfeiting applications. The excellent light emission properties, significantly improved stability, simple preparation method, and tunable light emission properties demonstrated by A 2 AgX 3 suggest that silver(I) halides may be attractive alternatives to toxic lead halide perovskites and unstable copper(I) halides for optical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Graphitic Aza-Fused π-Conjugated Networks: Construction, Engineering, and Task-Specific Applications

2D π-conjugated networks linked by aza-fused units represent a pivotal category of graphitic materials with stacked nanosheet architectures. Extensive efforts have been directed at their fabrication and application since the discovery of covalent triazine frameworks (CTFs). Besides the triazine cores, tricycloquinazoline and hexaazatriphenylene linkages are further introduced to tailor the structures and properties. Diverse related materials have been developed rapidly, and a thorough outlook is necessitated to unveil the structure–property–application relationships across multiple subcategories, which is pivotal to guide the design and fabrication toward enhanced task-specific performance. Herein, the structure types and development of related materials including CTFs, covalent quinazoline networks, and hexaazatriphenylene networks, are introduced. Advanced synthetic strategies coupled with characterization techniques provide powerful tools to engineer the properties and tune the associated behaviors in corresponding applications. Case studies in the areas of gas adsorption, membrane-based separation, thermo-/electro-/photocatalysis, and energy storage are then addressed, focusing on the correlation between structure/property engineering and optimization of the corresponding performance, particularly the preferred features and strategies in each specific field. In the last section, the underlying challenges and opportunities in construction and application of this emerging and promising material category are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Designer Metasurfaces for Antireflective Applications Enabled by Advanced Nanoparticle Technology

Optic processing advances have shifted system limitations, with current constraints consisting of antireflective (AR) coatings applied to optics and the inability to reduce size, weight, and price. Metasurfaces, and more broadly metaoptics, provide an avenue to overcome these limitations. The ability to generate substrate-engraved metasurfaces that can be tailored is demonstrated within a broad design space to satisfy large-area AR applications for bandpass or broadband needs, demonstrating an optically equivalent surface roughness standard deviation of only 5 Å. Using an advanced nanoparticle masking approach, two metasurfaces are fabricated: 1) vertical sidewall nanofeature metasurface (MS) for AR applications at 351 nm, and 2) sloped sidewall MS designed for broadband AR applications. For the 351 nm MS, the reflectance is measured to be 0.127%. In the case of the sloped sidewall MS, the reflectance is measured to be <0.25% over 400–700 nm and <1% over 400–1100 nm. To the best of the authors’ knowledge, this is the first demonstration of a broadband AR capable of this performance. The tunability of these structures, with a parameter space spanning even more remarkable designs such as broader bands and acceptance angles, coupled with high laser-induced damage durability and mechanical robustness, displays the strength of metasurfaces for AR applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Sulfurization Engineering of One–Step Low–Temperature MoS 2 and WS 2 Thin Films for Memristor Device Applications

2D materials have been of considerable interest as new materials for device applications. Non-volatile resistive switching applications of MoS 2 and WS 2 have been previously demonstrated; however, these applications are dramatically limited by high temperatures and extended times needed for the large-area synthesis of 2D materials on crystalline substrates. The experimental results demonstrate a one-step sulfurization method to synthesize MoS 2 and WS 2 at 550 °C in 15 min on sapphire wafers. Furthermore, a large area transfer of the synthesized thin films to SiO 2 /Si substrates is achieved. Following this, MoS 2 and WS 2 memristors are fabricated that exhibit stable non-volatile switching and a satisfactory large on/off current ratio (10 3 –10 5 ) with good uniformity. Tuning the sulfurization parameters (temperature and metal precursor thickness) is found to be a straightforward and effective strategy to improve the performance of the memristors. Furthermore, the demonstration of large-scale MoS 2 and WS 2 memristors with a one-step low-temperature sulfurization method with simple strategy to tuning can lead to potential applications such as flexible memory and neuromorphic computing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Recent Progress on Cerium Oxide‐Based Nanostructures for Energy and Environmental Applications

Cerium oxide (CeO 2 ) photo/electrocatalysts for energy storage and environmental applications have attracted considerable interest because of stable crystal structure, low toxicity/cost, superior chemical stability, stable redox (Ce 3+ /Ce 4+ ) pairs, abundant oxygen defects, and capablility for intense interaction with other materials. However, the wide bandgap and poor conductivity lower the CeO 2 photo/electrocatalytic and energy storage performances. To overcome these limitations, various modification strategies (tuning morphology, doping or loading of metal nanoparticles, and heterostructures) have been applied for the improvement of photocatalytic (removal of organic contaminants from water/wastewater and H 2 production and CO 2 reduction reactions) efficiency, electrocatalytic (hydrogen/oxygen evolution reactions and CO 2 reduction reactions), and energy storage performances (supercapacitor) of CeO 2 ‐based materials. Herein, the recent progress of CeO 2 ‐based materials for electro(photo)catalysis and energy storage applications has been discussed. The challenges and possible direction of CeO 2 ‐based materials for electro(photo)catalysis and energy storage applications have been emphasized. Furthermore, this comprehensive review is expected to advance the design of CeO 2 ‐based materials and their applications in electro(photo)catalysis and energy.

Ray, Schindra Kumar [Department of Chemistry North↗
DOE OSTI2020

Calcium–Based Metal–Organic Frameworks and Their Potential Applications

Metal–organic frameworks (MOFs) built on calcium metal (Ca-MOFs) represent a unique subclass of MOFs featuring high stability, low toxicity, and relatively low density. Ca-MOFs show considerable potential for molecular separations, electronic, magnetic, and biomedical applications, although they are not investigated as extensively as transition metal-based MOFs. Compared to MOFs made of other groups of metals, Ca-MOFs may be particularly advantageous for certain applications such as adsorption and storage of light molecules because of their gravimetric benefit, and drug delivery due to their high biocompatibility. This review intends to provide an overview on the recent development of Ca-MOFs, including their synthesis, crystal structures, important properties, and related applications. Here, various synthetic methods and techniques, types of building blocks, structure and porosity features, selected physical properties, and potential uses will be discussed and summarized. Representative examples will be illustrated for each type of important applications with a focus on their structure–property relations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Silica–Derived Nanostructured Electrode Materials for ORR, OER, HER, CO 2 RR Electrocatalysis, and Energy Storage Applications: A Review**

Silica-derived nanostructured catalysts (SDNCs) are a class of materials synthesized using nanocasting and templating techniques, which involve the sacrificial removal of a silica template to generate highly porous nanostructured materials. The surface of these nanostructures is functionalized with a variety of electrocatalytically active metal and non-metal atoms. SDNCs have attracted considerable attention due to their unique physicochemical properties, tunable electronic configuration, and microstructure. These properties make them highly efficient catalysts and promising electrode materials for next generation electrocatalysis, energy conversion, and energy storage technologies. The continued development of SDNCs is likely to lead to new and improved electrocatalysts and electrode materials. This review article provides a comprehensive overview of the recent advances in the development of SDNCs for electrocatalysis and energy storage applications. It analyzes 337,061 research articles published in the Web of Science (WoS) database up to December 2022 using the keywords “silica”, “electrocatalysts”, “ORR”, “OER”, “HER”, “HOR”, “CO 2 RR”, “batteries”, and “supercapacitors”. The review discusses the application of SDNCs for oxygen reduction reaction (ORR), oxygen evolution reaction (OER), hydrogen evolution reaction (HER), carbon dioxide reduction reaction (CO 2 RR), supercapacitors, lithium-ion batteries, and thermal energy storage applications. It concludes by discussing the advantages and limitations of SDNCs for energy applications.

25 ENERGY STORAGE↗
DOE OSTI2023

Ready for the Frontier: Preparing Applications for the World’s First Exascale System

Frontier, a supercomputer at the Oak Ridge Leadership Computing Facility (OLCF), debuted atop the Top500 list of the world’s most powerful supercomputers in June 2022 as the very first computer to produce exascale performance. Making sure scientific applications are optimized on this architecture is the critical link necessary to translate the newly available computational power into scientific insight and solutions. To that goal, the OLCF developed the Center for Accelerated Application Readiness (CAAR) program to ensure that a suite of highly optimized applications is ready for scientific runs at the onset of production operations for Frontier. This paper describes our experience in porting and optimizing such suite of applications in the OLCF’s CAAR program.

Budiardja, Reuben↗
DOE OSTI2025

Small scale electron linear accelerators for industrial applications

Linear accelerators (linacs), producing electron or X-ray radiation in the MeV range, are critical tools for industrial irradiation, medical device sterilization, food pasteurization, non-destructive testing, security, medical, and many other applications. Many of these applications require compact and flexible radiation sources. In this paper, we present new technologies for small-scale electron linear accelerators and examples of their practical implementations. Furthermore, these developments include low energy accelerators with self-shielding options and form factors, ranging from cabinet-size to hand-portable generators; medium-energy accelerators for novel radiotherapy and security applications; and high-energy 10 MeV linacs capable of reaching 20–35 kW beam power for emerging industrial and phytosanitary applications

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

A Review of Medium-Mn, Low-Density Steels for Transportation Applications

Low-density steels constitute a broad and complex alloy space (Fe–Mn–Al–C) suitable for a variety of applications. In particular, there has been growing interest in duplex (ferrite + austenite) or multiphase (+ martensite, carbides) low-density steels as a lightweight, advanced high-strength steel (AHSS) for vehicle applications, spurred by extensive decarbonization efforts. Medium-Mn (med-Mn) (3 to 12 wt pct) steels with 3.5 to 10 wt pct Al additions have decreased densities, presenting an interesting opportunity for high-specific strength, intrusion-resistant, and energy-absorbing sheet components with reduced alloying contents compared to high-Mn grades like austenitic Fe–Mn–Al–C or twinning-induced plasticity steels. Compared to leaner med-Mn steels, the physical metallurgy of med-Mn, low-density steels (MMLS) is complex and distinguished by increased δ-ferrite fractions and austenite stacking fault energies, decreased martensite start temperatures, and modified phase transformation windows. Mechanical properties of MMLS are comparable to 3rd generation AHSS, attributable to the unique, multiphase microstructures, and the array of strengthening mechanisms that can be accessed. Despite this, challenges and unknowns remain with respect to their industrial implementation, and new processing routes may need to be developed. Here, this review aims to highlight the composition effects, processing methods, microstructural evolution, deformation behavior, and application properties geared toward manufacturing and performance, altogether assessing the potential of MMLS for transportation applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Review of Machine Learning Classification Using Quantum Annealing for Real-World Applications

Optimizing the training of a machine learning pipeline helps in reducing training costs and improving model performance. One such optimizing strategy is quantum annealing, which is an emerging computing paradigm that has shown potential in optimizing the training of a machine learning model. The implementation of a physical quantum annealer has been realized by D-wave systems and is available to the research community for experiments. Recent experimental results on a variety of machine learning applications using quantum annealing have shown interesting results where the performance of classical machine learning techniques is limited by limited training data and high dimensional features. This article explores the application of D-wave’s quantum annealer for optimizing machine learning pipelines for real-world classification problems. Finally, we review the application domains on which a physical quantum annealer has been used to train machine learning classifiers. We discuss and analyze the experiments performed on the D-Wave quantum annealer for applications such as image recognition, remote sensing imagery, computational biology, and particle physics. We discuss the possible advantages and the problems for which quantum annealing is likely to be advantageous over classical computation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A semantics-driven framework to enable demand flexibility control applications in real buildings

Decarbonising and digitalising the energy sector requires scalable and interoperable Demand Flexibility (DF) applications. Semantic models are promising technologies for achieving these goals, but existing studies focused on DF applications exhibit limitations. These include dependence on bespoke ontologies, lack of computational methods to generate semantic models, ineffective temporal data management and absence of platforms that use these models to easily develop, configure and deploy controls in real buildings. This paper introduces a semantics-driven framework to enable DF control applications in real buildings. The framework supports the generation of semantic models that adhere to Brick and SAREF while using metadata from Building Information Models (BIM) and Building Automation Systems (BAS). The work also introduces a web platform that leverages these models and an actor and microservices architecture to streamline the development, configuration and deployment of DF controls. The paper demonstrates the framework through a case study, illustrating its ability to integrate diverse data sources, execute DF actuation in a real building, and promote modularity for easy reuse, extension, and customisation of applications. The paper also discusses the alignment between Brick and SAREF, the value of leveraging BIM data sources, and the framework's benefits over existing approaches, demonstrating a 75% reduction in effort for developing, configuring, and deploying building controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Cold spray technology in nuclear energy applications: A review of recent advances

Cold spray technology is a promising solid-state, powder-based deposition methods for fabrication of coatings, near-net-shape manufacturing, and component repair. In recent years, this technology has been investigated for many applications in the nuclear energy sector. For example, it has been explored for the deposition of coatings of corrosion and oxidation materials on zirconium-alloys fuel claddings in light water reactors (LWR) for achieving more accident-tolerant fuel (ATF) cladding. Other examples of its use for nuclear energy applications include coatings for enhancements in wear resistance and heat transfer, near-net shape manufacturing of next-generation fuel claddings of oxide dispersion-strengthened (ODS) steels, and for mitigation and repair of potential chloride induced stress corrosion cracking in used fuel storage canister systems. This work reviews published literature on the application of cold spray process for nuclear energy applications, while pointing to gaps that have yet to be addressed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Application of machine learning to evaluating and remediating models for energy and environmental engineering

Machine learning (ML) algorithms have been increasingly successful in their applications to solve energy and environmental engineering problems. ML algorithms have the advantage of being able to solve highly nonlinear issues effectively. Furthermore, considering the limited sample size of data collected in energy and environmental engineering, obtaining a ML model with reasonable accuracy is simple. Unfortunately, the vast majority of the current applications of ML algorithms lack effective screening of dominant factors and comprehensive model validation, which weakens the predictive ability of the models. The present study takes the minimum miscible pressure (MMP) of CO 2 - oil systems as an example. It establishes a systematic and robust predictive model to address this issue. Based on 147 sets of slim tube tests, the predictive models of the MMPs are investigated by application of eight ML algorithms. The paper concludes that most of the published ML models in the field of energy and environmental engineering prediction are not reliable. Furthermore, it addresses the main reasons for the poor performance of some predictive models built by ML and provides guidelines on how to make such models robust. Further, to the best of our knowledge, this is the first study to point out the defects of current ML modeling methods and propose countermeasures for their application in energy and environmental engineering problems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Robotics for HVAC applications: A critical review and future perspectives

Recent advances in artificial intelligence (AI), enhanced computational capabilities, and innovations in sensors and hardware have driven the increasing development and application of robots in heating, ventilation, and air conditioning (HVAC) systems. We selected and reviewed 101 studies published between 2005 and 2025, sourced from IEEE Xplore, Scopus, Web of Science, and the ACM Digital Library. To analyze these works, we developed a five-dimensional analytical framework (morphology, sensing, navigation, task execution, and system integration), inspired by the Springer Handbook of Robotics and tailored specifically for robotic applications in HVAC. Based on the reviewed studies, six distinct tasks spanning the entire HVAC lifecycle have been identified. Among the six tasks, inspection and maintenance dominate (59 %), followed by indoor monitoring and auditing (21 %), whereas leakage detection, comfort support, and installation/retrofit remain less explored. To address the identified gaps, this review proposes future research directions including investigating robot-aware HVAC design principles, developing multimodal HVAC sensing and data fusion techniques, enhancing robot training and hardware capabilities, and expanding robotic applications beyond Maintenance and Operations (M&O). The findings from this review inform future robotics research for HVAC applications and ultimately enhance system affordability, energy efficiency, resilience or reliability, and occupant environmental comfort. Moreover, it seeks to inspire researchers to explore the intersections of robotics, computer science, building science, and HVAC engineering fostering advancements in this multidisciplinary field.

AI↗
DOE OSTI2022

HIDRA-MAT liquid metal droplet injector for liquid metal applications in HIDRA

A liquid metal droplet injector was explicitly designed for the Hybrid Illinois Device for Research and Applications Material Analysis Test-stand (HIDRA-MAT) at the University of Illinois Urbana-Champaign to prepare liquid metal plasma-facing components (PFCs) for plasma exposure. The design goals were to create a compact, reliable, and robust design that could apply liquid metal droplets in-vacuo to a variety of samples. The injector was designed for liquid metal use, and results discussed pertain to lithium. The injector can produce lithium droplets of consistent size by utilizing programmable piston movement. Here, droplet formation data is presented for four different piston step sizes (0.125 mm, 0.25 mm, 0.5 mm, and 1 mm) at three different nozzle temperatures (185 °C, 230 °C, and 270 °C). Droplets are formed on the injector nozzle tip and a linear shift mechanism vertically translates the droplet to the substrate for application. This design prevents the droplet from inadvertently detaching off the nozzle and falling to the sample. Application of the liquid metal droplet ensures placement consistency on the substrate and helps avoid damage to components in HIDRA-MAT that should not interact with liquid metals. A description of the liquid lithium droplet creation and application results is given and provides additional insight into the cooling and oxidation of lithium droplets under vacuum conditions. A second nozzle was fabricated and demonstrated repeatability in droplet diameter creation having a variance of ±0.14 mm for droplets created from the same number of piston steps. The end-use for the injector on HIDRA-MAT is to apply liquid metals to PFCs and expose them to HIDRA's plasma with subsequent intershot in-vacuo surface analysis in HIDRA-MAT for plasma-material interaction studies.

42 ENGINEERING↗