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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Performance Evaluation of Different Parallel Programming Models in SCALE-Shift Sequences for Criticality and Shielding Applications [Abstract]

The SCALE code system has been widely used for nuclear criticality safety, reactor physics, radiation shielding, source term generation, and inventory analyses by researchers, industry, and regulatory bodies. Although limited support for shared- and distributed-memory parallel processing was introduced via C++ threading, OpenMP, and MPI, a hybrid parallel programming model with both distributed- and shared-memory parallelism has not been fully supported in the SCALE code system.

Nuclear Criticality Safety Program (NCSP)↗
DOE OSTI2025

A New NCSP Nuclear Criticality Safety Training and Pipeline Program

Nuclear criticality safety (NCS) training is vital and mandatory for NCS professionals to ensure the safe processing, handling, storage, and transportation of fissionable materials outside nuclear reactors. The requirement for this training is prescribed in several international and domestic guidance documents.

(NCS) Training↗
DOE OSTI2024

Data Efficiency Assessment of Generative Adversarial Networks for Critical Heat Flux Synthetic Data Generation

This study investigates the application of generative artificial intelligence techniques, particularly conditional generative adversarial networks (cGAN), in real-world engineering contexts, with a specific focus on synthetic data generation for critical heat flux (CHF). Utilizing a dataset comprising more than 20,000 real experimental CHF measurements, we conduct a series of experiments to examine cGAN’s behavior. These experiments encompass varying sizes of the training dataset, training cGAN on data from diverse experimental sources to generate new data on unseen experimental setups, and assessing the impact of excluding various input features on cGAN’s data generation accuracy. Our findings underscore the pronounced data dependency of cGAN for reliable performance, with decreased efficacy observed with smaller training dataset sizes. Notably, cGAN exhibits varying performance when trained on data from different experiments, with superior predictive capabilities observed for certain experiment sources compared to others. For instance, when cGAN was trained on data from Smolin et al.’s experiments or Zenkevich et al., it exhibited relatively good performance in generating the data from Becker et al., Kirillov et al., and Alekseev et al. experiments. In contrast, when trained with Alekseev et al.’s data and tasked with generating other experimental setups, cGAN showed notably poor performance. In both scenarios, cGAN’s performance was inferior compared to training on samples from all experiments concurrently. A feature importance analysis highlights the significant influence of parameters such as mass flux and heated length on accurate CHF generation, while other parameters like diameter and pressure have less impact. Inlet temperature is identified as a moderating factor by cGAN.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Initial Findings in Qualifying the Instrument Thimble 11 Position in the Advanced Test Reactor Critical

The Advanced Test Reactor (ATR) is a versatile nuclear research reactor located at the Idaho National Laboratory (INL) in Eastern Idaho, United States of America. It is one of the most powerful and flexible research reactors in the world and is primarily used for materials testing, isotope production and basic nuclear science research. The ATR is a light-water-cooled, beryllium-moderated reactor with a nominal thermal power capacity of 250 MW utilizing specially designed fuel, arranged in a serpentine pattern to create 9 flux traps. The special design of ATR allows for the neutron flux within each of the flux traps providing flexibility for experiments, programs and allowing experiments with different dose requirements to be irradiated simultaneously. The Advance Test Reactor Critical (ATRC) is a full-scale replica of the ATR core but is housed in a pool instead of a pressure vessel. ATRC is usually operated at less than 600 watts [1]. There are 12 dry instrument thimbles located around the outside of the core tank where a variety of measurement equipment is housed to facilitate reactor operations. Currently Instrument Thimble 11 (IT-11) is not utilized in ATR or ATRC. A range of measurements is ongoing to qualify IT-11 as a test platform for nuclear instrumentation research, development and further experimentation.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

Aided Active Learning (AAL) for Enhanced Critical Heat Flux Prediction

Accurate prediction of critical heat flux (CHF) is crucial for the safe and efficient operation of nuclear reactors. Traditional CHF modeling methods often require extensive experimental data, which are hard to obtain. This study introduces the Aided Active Learning (AAL) framework, which strategically minimizes data requirements without sacrificing model accuracy. Unlike conventional Active Learning (AL), AAL introduces an additional step of randomly selecting a subset from the sample pool before applying the query strategy. To evaluate the performance of AAL, two query strategies—uncertainty-based sampling and error-reduction sampling—were evaluated across the following models: random forest (RF), feedforward neural network (FNN), and variational feedforward neural network (vFNN). The proposed framework demonstrated that AAL effectively reduces the number of training samples needed to achieve comparable predictive accuracy. For the RF model, AL required only 710 samples to achieve an R2 score of 0.98, as compared to the 4,785 samples needed by random sampling. Similarly, the FNN model achieved the same R2 score with just 355 samples when using AL, a significant improvement over the 825 samples required by random sampling. In case of uncertainty-based sampling strategy, vFNN attained an R2 of 0.98 with 3,420 samples, reducing the sample requirement by 47% relative to the 6,440 samples needed for random sampling. Its performance suggests that larger training data are required to fully leverage its uncertainty quantification capabilities.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Critical Roles of Chalcogenide Anion on Strengthening Stability of Ni 2 Mo 6 Te 8 for Almost Exclusive Electrocatalysts Nitrate to Ammonia Conversion

Electrochemical hydrogenation of nitrate to ammonia using renewable electricity is a promising route for sustainability but lacks catalysts that can deliver balanced selectivity, activity, and durability. For this work, a new family of noble metal-free and high-performing Chevrel phase Ni 2 Mo 6 T 8 (T = S, Se, and Te) catalysts that have similar structural and textural properties and differ presumably only in chalcogenide anion is systematically studied. The side-by-side comparisons allow the uncovering of the critical roles of chalcogenide anions in impacting kinetic activities and long-term durability. The incorporation of anions with larger size and smaller electronegativity from sulfide to selenide and telluride invokes stronger inhibition of the otherwise competing hydrogen evolution reaction (HER) and steers the hydrogenation toward the selective formation of ammonia, thus improving both Faradic selectivity and the turnover frequency to high levels of 99.4% and 21.5 s –1 , respectively, on the Ni 2 Mo 6 Te 8 catalyst. More significantly, the bulkier anion in the Ni 2 Mo 6 T 8 catalyst kinetically inhibited the intercalation of electrolyte cations, a major degradation mechanism in the catalyst family examined here and delivered several times improved durability. Therefore, this study introduces novel active motifs for selective nitrate reduction and provides insights into the catalyst degradation mechanism and practical ways to improve durability.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Critical Review of Machine Learning of Energy Materials

Abstract Machine learning (ML) is rapidly revolutionizing many fields and is starting to change landscapes for physics and chemistry. With its ability to solve complex tasks autonomously, ML is being exploited as a radically new way to help find material correlations, understand materials chemistry, and accelerate the discovery of materials. Here, an in‐depth review of the application of ML to energy materials, including rechargeable alkali‐ion batteries, photovoltaics, catalysts, thermoelectrics, piezoelectrics, and superconductors, is presented. A conceptual framework is first provided for ML in materials science, with a broad overview of different ML techniques as well as best practices. This is followed by a critical discussion of how ML is applied in energy materials. This review is concluded with the perspectives on major challenges and opportunities in this exciting field.

Chen, Chi↗
DOE OSTI2024

Mechanical Milling – Induced Microstructure Changes in Argyrodite LPSCl Solid-State Electrolyte Critically Affect Electrochemical Stability

Microstructure of argyrodite solid-state electrolyte (SSE) critically affects lithium metal electrodeposition/dissolution. While the stability of unmodified SSE is mediocre, once optimized state-of-the-art electrochemical performance is achieved (symmetric cells, full cells with NMC811) without secondary interlayers or functionalized current collectors. Planetary mechanical milling in wet media (m-xylene) is employed to alter commercial Li 6 PS 5 Cl (LPSCl) powder. Quantitative stereology demonstrates how milling progressively refines grain and pore size/distribution in the SSE compact, increases its density, and geometrically smoothens the SSE-Li interface. Mechanical indentation demonstrates that these changes lead to reduced site-to-site variation in the compact's hardness. Milled microstructures promote uniform early-stage electrodeposition on foil collectors and stabilize solid electrolyte interphase (SEI) reactivity. Analysis of half-cells with bilayer electrolytes demonstrates the importance of microstructure directly contacting current collector, with interface roughness due to pore and grain size distribution being key. For the first time, short-circuiting Li metal dendrite is directly identified, employing 1.5 mm diameter “mini” symmetrical cell and cryogenic focused ion beam (cryo-FIB) electron microscopy. The branching sheet-like dendrite traverses intergranularly, filling the interparticle voids and forming an SEI around it. Importantly, mesoscale modeling reveals the relationship between Li-SSE interface morphology and the onset of electrochemical instability, based on underlying reaction current distribution.

25 ENERGY STORAGE↗
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 OSTI2020

A Boosted Critical Temperature of 166 K in Superconducting D 3 S Synthesized from Elemental Sulfur and Hydrogen

The discovery of superconductivity in H 3 S at 203 K marked an advance towards room-temperature superconductivity and demonstrated the potential of H-dominated compounds to possess a high critical temperature (T c ). There have been numerous reports of the H-S system over the last five years, but important questions remain unanswered. It is crucial to verify whether the Tc was determined correctly for samples prepared from compressed H 2 S, since they are inevitably contaminated with H-depleted byproducts. Here, we prepare stoichiometric H 3 S by direct in situ synthesis from elemental S and excess H 2 . The Im$_\bar{3}$ m phase of D 3 S samples exhibits a T c significantly higher than previously reported values (ca. 150 K), reaching a maximum T c of 166 K at 157 GPa. Furthermore, we confirm that the sharp decrease in T c below 150 GPa is accompanied by continuous rhombohedral structural distortions and demonstrate that the Cccm phase is nonmetallic, with molecular H 2 units in the crystal structure.

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

Dissecting Critical Factors for Electrochemical CO 2 Reduction on Atomically Precise Au Nanoclusters

Here, this work investigates the critical factors impacting electrochemical CO 2 reduction reaction (CO 2 RR) using atomically precise Au nanoclusters (NCs) as electrocatalysts. First, the influence of size on CO 2 RR is studied by precisely controlling NC size in the 1–2.5 nm regime. We find that the electrocatalytic CO partial current density increases for smaller NCs, but the CO Faradaic efficiency (FE) is not directly associated with the NC size. This indicates that the surface-to-volume ratio, i.e. the population of active sites, is the dominant factor for determining the catalytic activity, but the selectivity is not directly impacted by size. Second, we compare the CO 2 RR performance of Au 38 isomers (Au 38 Q and Au 38 T) to reveal that structural rearrangement of identical size NCs can lead to significant changes in both CO 2 RR activity and selectivity. Au 38 Q shows higher activity and selectivity towards CO than Au 38 T, and density functional theory (DFT) calculations reveal that the average formation energy of the key *COOH intermediate on the proposed active sites is significantly lower on Au 38 Q than Au 38 T. These results demonstrate how the structural isomerism can impact stabilization of reaction intermediates as well as the overall CO 2 RR performance of identical size Au NCs. Overall, this work provides important structure–property relationships for tailoring the NCs for CO 2 RR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Systems Theory Principles and Complex Systems Engineering Concepts for Protection and Resilience in Critical Infrastructure: Lessons from the Nuclear Sector

Part of the Presidential Policy Directive 21 (PPD-21) (PPD 2013) mandate includes evaluating safety, security, and safeguards (or nonproliferation) mechanisms traditionally implemented within the nuclear reactors, materials, and waste sector of critical infrastructure—including a complex, dynamic set of risks and threats within an all-hazards approach. In response, research out of Sandia National Laboratories (Sandia) explores the ability of systems theory principles (hierarchy and emergence) and complex systems engineering concepts (multidomain interdependence) to better understand and address these risks and threats. Herein, this Sandia research explores the safety, safeguards, and security risks of three different nuclear sector-related activities—spent nuclear fuel transportation, small modular reactors, and portable nuclear power reactors—to investigate the complex and dynamic risk related to the PPD-21-mandated all-hazards approach. This research showed that a systems-theoretic approach can better identify inter-dependencies, conflicts, gaps, and leverage points across traditional safety, security, and safeguards hazard mitigation strategies in the nuclear reactors, materials, and waste sector. Resulting from this, mitigation strategies from applying systems theoretic principles and complex systems engineering concepts can be (1) designed to better capture interdependencies, (2) implemented to better align with real-world operational uncertainties, and (3) evaluated as a systems-level whole to better identify, characterize, and manage PPD-21's all hazards strategies.

42 ENGINEERING↗
DOE OSTI2026

Critical Review of Brazil Disk Techniques for Tensile Strength Characterization With an Emphasis on High Explosive Materials

Mechanical properties are a critical performance metric for many high explosive (HE) materials and tensile strength properties are particularly important. Direct tensile measurements using dogbone shaped samples are the gold standard but they have the disadvantage that they are fairly large and require samples machined from billets. Diametral compression, more commonly known as Brazil disk (BD) testing, is an indirect method for measuring tensile strength on smaller and more easily fabricated samples. A review of the BD literature is presented with an emphasis on tensile strength measurements in high explosive materials. BD literature is reviewed in three primary areas: (i) rocks and concrete, (ii) pharmaceutical materials, and (iii) high explosive materials. The literature for rocks/concrete is extensive and dates back over 80 years; despite this there is no consensus on the validity/accuracy of the BD technique or the optimal variant of the BD technique to employ. The pharmaceutical literature is the opposite, being limited in scope and quantity of studies. BD literature on high explosive materials falls in between, not as impressive as in the rocks/concrete community but more substantiative than in the pharmaceutical community. After the review of the literature practical parameters for HE BD testing and recommended future work is discussed.

Brazil disk↗
DOE OSTI2023

Wind turbine main bearing rating lives as determined by IEC 61400‐1 and ISO 281: A critical review and exploratory case study

Abstract This paper studies the rating lives of wind turbine main bearings, as determined by the IEC 61400‐1 and ISO 281 standards. A critical review of relevant bearing life theory and turbine design requirements is provided, including discussion on possible shortcomings such as the existence (or not) of the bearing fatigue load limit and the validity of assuming linear damage accumulation. A detailed exploratory case study is then undertaken to determine rating lives for two models of main bearing in a 1.5 MW wind turbine. Rating life assessment is carried out under different conditions, including various combinations of main bearing temperature, wind field characteristics, lubricant viscosity, and contamination levels. Rating lives are found to be sufficiently above the desired 20‐year design life for both bearing models under expected operating conditions. For the larger bearing, operational loads are shown to be below or close to the bearing fatigue load limit a vast majority of the time. Key sensitivities for rating life values are temperature and contamination. Overall, the results of this study suggest that an ISO 281 rating life assessment does not account for reported rates of main bearing failures in 1 to 3 MW wind turbines. It is recommended that a similar analysis be undertaken for ISO/TS 16281 rating lives, along with further efforts to identify principal root causes of main bearing failures in future work, possibly leading to a new application standard specific to this component. It is also recommended that the impacts of partial wake impingement on main bearing rating lives are investigated.

17 WIND ENERGY↗
DOE OSTI2022

Long-range fermions and critical dualities

We construct long-range fermionic models with the Gross-Neveu and Gross­Neveu-Yukawa interaction, and argue that their critical regimes are equivalent. To this end, we calculate various CFT data in ϵ- and 1/N-expansion, and demonstrate their agreement in the overlapping regimes of validity.

1/N Expansion↗
DOE OSTI2023

Rapidly Changing Range Limits in a Warming World: Critical Data Limitations and Knowledge Gaps for Advancing Understanding of Mangrove Range Dynamics in the Southeastern USA

Climate change is altering species’ range limits and transforming ecosystems. For example, warming temperatures are leading to the range expansion of tropical, cold-sensitive species at the expense of their cold-tolerant counterparts. In some temperate and subtropical coastal wetlands, warming winters are enabling mangrove forest encroachment into salt marsh, which is a major regime shift that has significant ecological and societal ramifications. Here, we synthesized existing data and expert knowledge to assess the distribution of mangroves near rapidly changing range limits in the southeastern USA. We used expert elicitation to identify data limitations and highlight knowledge gaps for advancing understanding of past, current, and future range dynamics. Mangroves near poleward range limits are often shorter, wider, and more shrublike compared to their tropical counterparts that grow as tall forests in freeze-free, resource-rich environments. The northern range limits of mangroves in the southeastern USA are particularly dynamic and climate sensitive due to abundance of suitable coastal wetland habitat and the exposure of mangroves to winter temperature extremes that are much colder than comparable range limits on other continents. Thus, there is need for methodological refinements and improved spatiotemporal data regarding changes in mangrove structure and abundance near northern range limits in the southeastern USA. Advancing understanding of rapidly changing range limits is critical for foundation plant species such as mangroves, as it provides a basis for anticipating and preparing for the cascading effects of climate-induced species redistribution on ecosystems and the human communities that depend on their ecosystem services.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Rapid Evaluation and Response to Impacts on Critical End-Use Loads Following Natural Hazard-Driven Power Outages: A Modular and Responsive Geospatial Technology

The disparate nature of data for electric power utilities complicates the emergency recovery and response process. The reduced efficiency of response to natural hazards and disasters can extend the time that electrical service is not available for critical end-use loads, and in extreme events, leave the public without power for extended periods. This article presents a methodology for the development of a semantic data model for power systems and the integration of electrical grid topology, population, and electric distribution line reliability indices into a unified, cloud-based, serverless framework that supports power system operations in response to extreme events. An iterative and pragmatic approach to working with large and disparate datasets of different formats and types resulted in improved application runtime and efficiency, which is important to consider in real time decision-making processes during hurricanes and similar catastrophic events. This technology was developed initially for Puerto Rico, following extreme hurricane and earthquake events in 2017 and 2020, but is applicable to utilities around the world. Given the highly abstract and modular design approach, this technology is equally applicable to any geographic region and similar natural hazard events. In addition to a review of the requirements, development, and deployment of this framework, technical aspects related to application performance and response time are highlighted.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Chapter Ten - Power, Buildings, and Other Critical Networks: Integrated Multisystem Operation

The electrifying transportation sector, the increasing grid interactivity of the built environment, the rapidly expanding number of devices within the Internet-of-Things, and the overall trend toward highly connected systems and interdependent networks is revolutionizing the operation of the electric power grid. While these changes are presenting grid operators with new challenges to ensure an efficient, reliable, and sustainable operation of the grid, they also enable a new suite of resources that can be utilized for assisting the grid in times of need. In this chapter, we explore how these recent changes and trends are affecting modern power systems and discuss the benefits and challenges of an increasingly electrified and interconnected world. We will observe how various critical infrastructure, that is, buildings, water and gas, transportation, and telecommunication networks are highly dependent on power network operations but, with improved coordination and control, can also provide valuable assets to the grid in times of need.

electricity markets↗