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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhancing Power Resilience for Remote Communities: A Comprehensive Renewable Energy Solution for Itbayat Island

The island of Itbayat, Philippines, faces significant challenges in maintaining a reliable and resilient power supply due to its current reliance on a vulnerable power distribution system managed by a local electric cooperative. The existing infrastructure, which includes diesel generators and a radial network configuration with some above-ground lines, is highly susceptible to frequent typhoons and adverse weather conditions. These factors, combined with inadequate staffing and high operational costs, result in frequent power outages that disrupt daily life and hinder economic development. This white paper proposes a comprehensive solution to enhance the resilience and reliability of Itbayat's power system by integrating renewable energy sources, specifically solar photovoltaic (PV) systems, battery storage, and a microgrid controller. The proposed solution aims to reduce dependency on diesel fuel, optimize energy use, and provide a sustainable and robust power supply for the island. Key components of the solution include: 1. Solar PV Installation: Deploying solar PV panels to harness abundant solar energy, reducing reliance on diesel fuel. 2. Battery Storage Systems: Installing battery storage to store excess solar energy and ensure a continuous power supply during low solar generation periods. 3. Microgrid Controller: Implementing a microgrid controller to manage and optimize the integration of solar PV, battery storage, and existing diesel generators. The proposed solution addresses several critical issues, including system vulnerability, generator dependency, and operational inefficiencies. By adopting this innovative approach, Itbayat Island can achieve a more resilient, efficient, and sustainable energy infrastructure, ensuring a stable power supply for its residents and enhancing overall energy security.

14 SOLAR ENERGY↗
DOE OSTI2025

Development and Demonstration of a Prototype Molten Salt Sampling System

Molten salt reactors (MSRs) offer potential operability and safety advantages when compared to commercial light water reactors (LWRs). However, operating experience with MSRs is sparse in comparison to what exists for LWRs. Further, the chemical and isotopic composition of the fuel and/or coolant salt is dynamic and difficult to characterize continuously, posing potential safety, operability, and safeguards unknowns that need to be addressed. A molten salt sampling system (MSSS) is regarded as a necessary subsystem within first generation MSRs used to obtain samples of salt for chemical and isotopic analysis in support of the need to monitor and control salt composition during operation. The MSSS is being developed using the Safety-in-Design (SiD) methodology, which incorporates incremental integration of safety analysis into the design process. The MSSS conceptual design emerging from the application of the early stages of the SiD methodology consists of a sample collection system and its housing, a freeze port, and inert gas control and delivery systems. This article describes the prototypes developed to test the functions of these MSSS subsystems, presents the results of testing in both dry and molten salt environments (including reliability data collection performed in accordance with the principles of SiD and the development of a semiquantitative fault tree model), and summarizes the opportunities for future design and testing enhancements based on the results of prototype testing.

molten salt reactor↗
DOE OSTI2025

Considerations for Maritime Nuclear Technologies, Economic Viability and Public Acceptance

The Maritime Nuclear Application Group (MNAG) is a working group convened by the National Reactor Innovation Center at Idaho National Laboratory (INL), the American Bureau of Shipping, and Morgan, Lewis, and Bockius LLP. This report documents an MNAG examination of considerations relevant to implementing nuclear technology in commercial maritime applications. In general, two types of use case are examined: maritime nuclear power plants and nuclear reactors used on board shipping vessels for propulsion and other ship needs. The report finds that there may be economic benefits related to maritime nuclear technologies, including the flexible deployment of maritime nuclear reactors, which would allow them to complement land-based nuclear projects, and operational differences for nuclear cargo ships that may lead to an overall increase in revenue. High-level analyses in this report show that, based on general small modular reactor and microreactor cost estimates developed by INL, maritime nuclear reactors may be economically competitive for electricity production in remote regions and for use in the propulsion of large cargo ships. Besides economic viability, public acceptance will be key to implementing maritime nuclear technologies. The report discusses the public’s current perception of nuclear technologies. Engaging with the public will be important to improving this perception. The report discusses some key benefits and risks associated with maritime nuclear technologies. Benefits include the creation of jobs, the production of reliable energy, and the potential to improve air quality. Risks that concern the public are the potential for radioactive releases during operation and decommissioning, as well as those related to waste management. Communicating the benefits and the risks of maritime nuclear technologies will be essential to improving public perception.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A DATA EFFICIENT SPARSE MODELING FRAMEWORK FOR POWER ESTIMATION IN WATER TREATMENT SENSING OPERATIONS

With increasing freshwater scarcity, advanced process design mechanisms such as Closed-Circuit Reverse Osmosis (CCRO) and Digital/Physical Twin systems are gaining traction in water treatment and reuse operations. While digital and physical twin models enable improved system insight and control, their development is often expensive and computationally intensive, requiring large volumes of synthetic or experimental data to characterize underlying process dynamics. This work introduces a sparse surrogate modeling framework to estimate power consumption from measured flow and pressure variables, along with their nonlinear polynomial and interaction expansions. To ensure model reliability and reduce overfitting, a two-stage pipeline is proposed. First, a dynamic data filtering algorithm is employed to remove uninformative observations and transient operational states. Second, a sparse penalized regression technique is applied to select a minimal set of parsimonious features. The proposed model achieves high sparsity, retaining only 7 out of 34 candidate features (≈79.41% sparsity) while delivering a root mean square error (RMSE) of 0.072 on the test dataset.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2024

b ¯ b ¯ u d and b ¯ b ¯ u s tetraquarks from lattice QCD using symmetric correlation matrices with both local and scattering interpolating operators

We study the b ¯ b ¯ u d tetraquark with quantum numbers I ( J P ) = 0 ( 1 + ) as well as the b ¯ b ¯ u s tetraquark with quantum numbers J P = 1 + using lattice QCD. We improve on existing work by including both local and scattering interpolating operators on both sides of the correlation functions and use symmetric correlation matrices. This allows not only a reliable determination of the energies of QCD-stable tetraquark ground states, but also of low-lying excited states, which are meson-meson scattering states. The latter is particularly important for future finite-volume scattering analyses. Here, we perform chiral and continuum extrapolations of just the ground-state energies, for which finite-volume effects are expected to be small. Our resulting tetraquark binding energies, − 100 ± 10 − 51 + 36 MeV for b ¯ b ¯ u d and − 30 ± 3 − 31 + 11 MeV for b ¯ b ¯ u s , are consistent with other recent lattice-QCD predictions. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2026

SANDWake3D

SAND2026-23958O SANDWake3D models atmospheric surface layers and turbine wakes using a 3D parabolic RANS solver. This Python-based tool uses an efficient method to simulate wakes, capturing complex wake behaviors such as wind shear, veer, and atmospheric stratification, naturally. It has been calibrated and validated against higher-fidelity large eddy simulations (LES), providing reliable results for wind energy and atmospheric research applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
DOE OSTI2024

An Approach to Shared Research Systems

World-leading research requires state-of-the-art systems for research and innovation. Operational excellence is the key component of scientific excellence by implementing ubiquitous security, repeatable processes, streamlined policies, and reliable and robust infrastructure. Building a research environment to meet these needs is a complex and expensive task. In many cases, it can be financially advantageous for one or more programs, projects, and/or stakeholder(s) to pool resources to build a shared research system to meet common goals. However, such a system brings some unique challenges that need to be addressed. This document describes the process to mitigate these challenges by documenting how the interested parties contribute to the overall success of the system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Residential Vehicle-to-Home Backup Power Capabilities: Key Findings from a ComEd Beneficial Electrification R&D Pilot

This report summarizes key findings from a collaborative technical study of residential, non-grid-tied vehicle-to-home (V2H) backup power systems in Commonwealth Edison’s (ComEd’s) service territory. The work integrates (1) a feeder-level technoeconomic analysis (TEA) using historical outage-event data and simulated electric-vehicle (EV) driving/charging profiles to estimate potential reliability and customer interruption-cost impacts under V2H and vehicle-to-grid (V2G) adoption scenarios; (2) controlled laboratory performance testing of a representative V2H backup ecosystem to characterize transfer-to-backup behavior, sustained power delivery, efficiency trends, and repeatable reliability limitations; and (3) a cybersecurity assessment aligned with NIST Cybersecurity Framework (CSF) 2.0 and ISO/SAE 21434 to evaluate interface-level risk drivers and identify program-relevant mitigations. Results indicate that V2H can provide measurable resilience value, but outcomes are strongly context dependent on outage patterns and the share of events that are “V2H-applicable.” Typical transfer-to-backup behavior clustered on the order of minutes, but rare long-delay edge cases were observed (including an event approaching 30 minutes) and should be treated as a reliability risk. High-power testing showed that peak-rated output is not necessarily continuously deliverable; stable operation may require operation below nameplate ratings and attention to thermal and installation constraints. The cybersecurity assessment highlights a broad attack surface spanning commissioning, home networks, embedded services, and cloud/OTA pathways, motivating minimum controls for secure onboarding, signed updates, patch cadence, and coordinated vulnerability response for any scaled deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Challenges, Technological Pathways and Trade-Offs of Perovskite Solar Modules for Long-Term Operation

Perovskite solar modules (PSMs) have emerged as a promising photovoltaic technology due to their high efficiency, low fabrication cost and compatibility with lightweight and flexible applications. However, ensuring long-term reliable performance under real-world conditions remains a critical barrier to commercialization. PSMs degrade through mechanisms that differ substantially from those affecting established technologies such as silicon, particularly under environmental stressors like ultraviolet light, oxygen, temperature cycling and reverse bias. Here we provide an analysis of the degradation pathways specific to perovskite modules and discuss why standard accelerated tests often fail to predict outdoor performance. We conceptualize challenges across material, device and module levels and evaluate strategies to mitigate ion migration, interfacial breakdown and encapsulation failure. By highlighting the need for realistic testing protocols and durable materials, we propose a framework highlighting key challenges, technological pathways and the trade-offs required to extend perovskite module lifetimes towards long-term operation, aiming to guide the development of PSMs capable of a 30-year operational lifetime.

14 SOLAR ENERGY↗
DOE OSTI2025

Experimental Comparison of Elastomeric Materials for Hydraulic Seal Durability under Reciprocating Conditions

Wave Energy Converters (WECs) rely on hydraulic Power Take-Off (PTO) systems to transform the kinetic energy of ocean waves into electricity, where hydraulic seals play a critical role in preventing fluid leakage and ensuring watertight operation under harsh marine conditions. However, seal degradation due to wear, fatigue, and corrosion remains a key challenge limiting system reliability and increasing maintenance costs. In this study, the tribological performance of elastomeric materials for hydraulic sealing applications that are based on commercial polyurethane and custom-compounded Ethylene Propylene Diene Monomer (EPDM) is investigated. Using a CSM tribometer, reciprocating wear tests were conducted in accordance with ASTM G133 under dry sliding conditions, with normal loads ranging from 3 to 10 N, and sliding speeds of 10 to 30 mm/s. Coefficient of friction (COF), specific wear rate, and worn surface morphology are evaluated to understand how load, velocity, and material composition affect seal durability. Improved wear stability and high Shore A hardness (93–94) were demonstrated by the commercial thermoplastic polyurethane (Duralast 4203 and 4758). EPDM-based compounds showed different filler-dependent behaviors, formulations filled with carbon black (E3) had the lowest wear rate (1.45 × 10?4 mm³ N?¹ m?¹) and increased load-bearing capacity, while samples modified with silica and plasticizer (E4, E5) had better conformability and damping but less hardness. Compounded EPDMs showed wider deformation zones because of their lower modulus and filler-matrix interfacial fluctuations, while commercial grades exhibited shallower wear scars (= 380 µm), according to optical profilometry. The Archard model-based lifetime estimation showed that, under 10 N and 30 mm/s, operational endurance ranged from 3.1 to 6.2 years. Because of its low wear rate and steady interfacial behavior, E3 had the longest anticipated life. For medium-load hydraulic sealing applications, these results demonstrate the possibility of customized EPDM formulations as affordable substitutes for commercial polyurethanes. They also offer a quantitative foundation for material selection and lifespan prediction.

Durability↗
DOE OSTI2024

Formally Verified ZTA Requirements for OT/ICS Environments with Isabelle/HOL

The clean energy transformation includes the integration of distributed energy resources with the power grid, which has led to a substantial increase in the complexity of power grids infrastructure and the underlying operational technology environment. Power grids infrastructure represents an operational technology environment that has become a system of systems, integrating heterogeneous devices which are both software-and hardware-intensive; as a result, there are increasing demands to exploit advances in the commodity of software-hardware infrastructures to improve energy systems requirements such as cybersecurity and resilience. In such a setting, system requirements at different levels mix, which leads to vulnerabilities and undesirable outcomes. The use of formal methods to characterize and prove system requirements removes ambiguity, increases automation, and provides high levels of assurance and reliability. In this paper, we contribute a methodology and a framework for the system-level verification of zero trust architecture requirements in operational technology environments. We define a formal specification for the core functionalities of operational technology environments, the corresponding invariants, and security proofs. Of particular note is our modular approach for the formal verification of asynchronous interactions in operational technology environments. The formal specification and the proofs have been mechanized using the interactive theorem proving environment Isabelle/HOL.

formal methods↗
DOE OSTI2026

Synthetic data-driven deep learning for label-free autonomous atomic force microscopy

Atomic force microscopy (AFM) is a widely used tool for nanoscale characterization across materials science, energy research, and biology. However, its adoption in high-throughput materials discovery and statistically driven studies remains limited by a strong dependence on expert operator input and by the scarcity of annotated experimental AFM datasets needed to enable data-driven automation. Here, we introduce SimuScan, a synthetic-data–driven framework that enables reliable AFM feature identification, segmentation, and targeted imaging without requiring large manually labeled experimental datasets. SimuScan generates tunable, high-fidelity synthetic AFM images of defined morphologies while incorporating realistic experimental artifacts, including tip–sample convolution, noise, flattening distortions, and surface debris. These datasets are shown to support scalable, label-free training of modern deep learning models for AFM analysis. When integrated into data-driven AFM workflows, SimuScan-trained models can locate and analyze nanoscale structures across large datasets and guide targeted follow-up imaging. We validate this approach on nanostructured surfaces, DNA assemblies, and bacterial cells, demonstrating robust generalization across diverse sample types with minimal operator intervention. More broadly, this work establishes a general strategy for generating explicitly conditioned, task-relevant synthetic data to improve the reliability of downstream models in autonomous microscopy.

Millan-Solsona, Ruben [Oak Ridge National Laborato↗
DOE OSTI2025

A High-Voltage High-Current Benchtop Test Stand for Solid-State Switch Testing at the SNS

Solid-state switches already replaced thyratrons in the SNS extraction kicker power supplies, offering improved efficiency and reliability. However, recent supply chain disruptions, combined with a self-firing issue, led us to explore alternative solutions. A vendor-developed MOS-Gated Thyristor switch was introduced but ultimately failed during testing. To investigate the failure and assess possible improvements, a benchtop test stand was constructed to evaluate the performance of a single stage board. This test stand features a Pulse Forming Network (PFN) that operates at 6 kV and 6 kA, with a repetition rate exceeding 60 Hz, simulating real operational conditions. By utilizing this setup, we seek to gain a better understanding of the failure mechanisms, refine the switch designs, and ultimately develop a more reliable alternative for the extraction kicker power supplies.

Bullman, Austin [ORNL]↗
DOE OSTI2024

Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration

Geologic carbon sequestration (GCS) is a safety-critical technology that aims to reduce the amount of carbon dioxide in the atmosphere, which also places high demands on reliability. Multiphase flow in porous media is essential to understand CO 2 migration and pressure fields in the subsurface associated with GCS. However, numerical simulation for such problems in 4D is computationally challenging and expensive, due to the multiphysics and multiscale nature of the highly nonlinear governing partial differential equations (PDEs). It prevents us from considering multiple subsurface scenarios and conducting real-time optimization. Here, we develop a Fourier-enhanced multiple-input neural operator (Fourier-MIONet) to learn the solution operator of the problem of multiphase flow in porous media. Fourier-MIONet utilizes the recently developed framework of the multiple-input deep neural operators (MIONet) and incorporates the Fourier neural operator (FNO) in the network architecture. Once Fourier-MIONet is trained, it can predict the evolution of saturation and pressure of the multiphase flow under various reservoir conditions, such as permeability and porosity heterogeneity, anisotropy, injection configurations, and multiphase flow properties. Compared to the enhanced FNO (U-FNO), the proposed Fourier-MIONet has 90% fewer unknown parameters, and it can be trained in significantly less time (about 3.5 times faster) with much lower CPU memory (<15%) and GPU memory (<35%) requirements, to achieve similar prediction accuracy. In addition to the lower computational cost, Fourier-MIONet can be trained with only 6 snapshots of time to predict the PDE solutions for 30 years. Furthermore, we observed that Fourier-MIONet can maintain good accuracy when predicting out-of-distribution (OOD) data. The excellent generalizability of Fourier-MIONet is enabled by its adherence to the physical principle that the solution to a PDE is continuous over time. Furthermore, the developed Fourier-MIONet makes it possible to solve the long-time evolution of geological carbon sequestration in a large-scale three-dimensional space accurately and efficiently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A large interlaboratory electron diffraction study of monolayer graphene

Standardisation of data collection and analysis is essential to enable commercialisation of 2D materials in a wide range of technologies. Selected area electron diffraction (SAED) in the transmission electron microscope (TEM) is one of the key methods for distinguishing monolayer from bilayer and few-layer graphene by comparing the 1st and 2nd order diffraction spot intensities. Yet there are many factors that can affect the reliability of data collection and interpretation, causing the measurement of monolayer samples to deviate from the literature boundary condition of $I_{\{\bar{2}110\}}$$/$$I_{\{1\bar{1}00\}}$ < 1 for monolayer graphene (1LG). Here we present the results of a large interlaboratory SAED comparison study, where 15 international laboratories measured and analysed nominally identical samples of chemical vapour deposited graphene. Large variations were observed in the measured ratios of diffraction spot intensities, with the largest variance associated with poor quality SAED data resulting from inadequate specimen handling and storage. To inform the reliable determination of monolayer thickness from SAED patterns we provide a description of best practice for specimen handling, TEM operation, data collection and analysis. This work was undertaken within VAMAS Technical Working Area 41: Graphene and related 2D materials—Project 9, the results of which have been directly incorporated into ISO/TS 21356–2 for the characterisation of graphene sheets. We find that when this methodology is followed, 1LG can be distinguished from bilayer or thicker material with high confidence where analysis of a single SAED pattern gives $I_{\{\bar{2}110\}}$$/$$I_{\{1\bar{1}00\}}$ < 1.2, even in the absence of precise specimen tilting.

2D materials↗
DOE OSTI2025

Traffic Shaping to Traffic Engineering in Time-Sensitive OT Network

Modern industrial automation systems increasingly depend on network infrastructures for time-critical communication, driving the need for solutions that guarantee timely and reliable data delivery. IEEE 802.1 Time-Sensitive Networking (TSN) holds significant promise for converging Information Technology (IT) and Operational Technology (OT) networks, enabling interoperability and supporting the coexistence of mixed-critical traffic crucial for Industry 4.0 and IIoT. To achieve deterministic communication, TSN employs various traffic shapers such as the Time-Aware Shaper (TAS), Asynchronous Traffic Shaper (ATS), and Credit-Based Shaper (CBS). However, the effective deployment of TSN in industrial automation faces several challenges. These include the non-trivial mapping of diverse industrial traffic types to specific shapers, the complexity of optimizing shaper configurations. We present a model for effective traffic engineering within TSN enabled OT Network. Our experiments also demonstrate how shaping of certain traffic types get affected in absence of precise time synchronization and propose possible solutions based on experiment results. Based on our experimental results we provide recommendations on how traffic type assignments should be done and which traffic shaping mechanisms should be used for a particular traffic type.

Sarker, Taposh Kumer [University of Texas at El Pa↗
DOE OSTI2025

Uncertainty Analyses of Molten Salt Property Measurements

Thermophysical and thermochemical property values of molten salts and associated uncertainties are used by reactor developers to evaluate reactor performance and model accident scenarios. These activities support fuel qualification objectives by demonstrating that fundamental safety functions (e.g., limit the release of radioactive materials, remove heat from the reactor, and control reactivity) can be performed effectively in a variety of conditions over the operating life of the reactor. Fuel qualification activities are still in the development phase due to a lack of reliable property data for salt mixtures being considered for use in molten salt reactors (MSR).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗