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DOE OSTI2025

SCCOUT: Surveying for Categorization and Control of Organism in Unwelcome Territory

Advancements in the fields of science, technology, and medicine have contributed largely to the growth of society over the last century. Thanks to these discoveries, all corners of the planet are connected both digitally and physically. Progress in the field of medicine has led to people living longer, fuller lives and a general increase in global population. Awareness of our world’s changing climate and the effects that has on local and global ecosystems has spurred great efforts to protect the environment. These discoveries along with many others have helped our world grow in a myriad of ways; however, certain efforts in agriculture, natural resource management, and ecosystem management have not scaled to accommodate this growth. Increasing prevalence and ease of dissemination of invasive plants and animals, diseases, and changing ecological conditions pose significant challenges to biodiversity, ecosystem health, and agricultural productivity. Moreover, as the world population grows, there are more people to feed and less viable farmland to produce food for them. Despite the increasing prevalence of these issues, methods for addressing and tracking them have stayed relatively the same for at least the last several decades.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Exploring Geologic Hydrogen: A New Frontier for Affordable, Reliable Energy Security

Recent successes in the exploration, drilling, and discovery of geologic hydrogen have generated notable excitement. This new energy resource has the potential to make an important contribution to our nation’s energy supply, resiliency, and security. Contemporary studies of geologic hydrogen have a common theme of suggesting places where it might be found or even more specifically, what rocks in what geologic formations may contribute to its formation — either naturally or via artificially induced means. This vital ongoing body of work sets the stage for imagining what may be possible with vast available quantities of naturally occurring hydrogen in the subsurface. While acknowledging current approaches to characterizing geologic hydrogen, this report advances the discussion by suggesting next steps, including the critical science and engineering necessary to make geologic hydrogen an affordable and reliable part of the U.S. energy portfolio.

08 HYDROGEN↗

DOE OSTI2025

Versatile & Intelligent Biodetection via Environmental Sensing (VIBES)

Reactive health monitoring strategies during events like the COVID-19 pandemic highlighted the need for predictive, threat-agnostic diagnostics that can detect both known diseases and novel chemical or biological threats. To address this, we investigated an optical biosensor as a breath volatile organic compound (VOC) analyzer, aiming to emulate biological olfaction. We assembled and validated the device with thin film metal coated substrate-based sensors. We immobilized small biological recognition elements on the substrates and delivered controlled concentrations of target VOCs. The sensor was irradiated with a visible laser and the sensor signal was recorded. We characterized the laser performance and tested 3 recognition elements for 2 VOCs with varying concentrations (1-100 ppm). We also evaluated enhancement of the signal using nanostructures on the metal film in comparison with planar film substrate. We demonstrated detecting ethanol reliably at concentrations as low as ~2 ppm along with preliminary detection of acetone (<100 ppm). We also found several unexpected factors that influence the sensor behavior that should be addressed to further refine the device’s performance. The nanostructures were, as expected, found to amplify the sensor signals. These findings demonstrate the feasibility of the optical bio-sensing modality for breath VOC monitoring at physiologically relevant levels. This positions LLNL to develop a low-cost, scalable, broad-spectrum health monitoring capability aligned with the Early Detection thrust of the Bioresilience Mission Focus Area and attract external funding.

47 OTHER INSTRUMENTATION↗

DOE OSTI2026

DISSPATCH H2: Assessing Subsurface Storage Potential for Hydrogen

This project evaluates the technical feasibility of long-term underground hydrogen storage in the Anadarko Basin, integrating subsurface science, reservoir engineering, and system-level analysis to build a cohesive understanding of how hydrogen may be stored and recovered in porous media. Although salt caverns currently dominate commercial-scale hydrogen storage, their limited geographic availability necessitates alternative options that can support a more resilient energy system. Depleted oil and gas reservoirs offer a widely distributed and potentially high-capacity solution, but their suitability depends on formation-specific geologic, petrophysical, microbial, and operational factors. This study provides the first coordinated assessment of these factors within the Simpson Group of Oklahoma.

03 NATURAL GAS↗

DOE OSTI2026

Stakeholder-guided holistic, Adaptive Framework for enhancing community Energy Resilience (SAFER) (Final Technical Report)

The Stakeholder-guided holistic, Adaptive Framework for enhancing community Energy Resilience (SAFER) project advances resilience science and engineering by addressing challenges in rural Kansas communities where aging infrastructure, extreme weather, and socioeconomic disparities heighten vulnerability to energy disruptions. Traditional approaches often focus on technical performance while overlooking community concerns and priorities. SAFER responds by integrating community perspectives with advanced analytical frameworks to create a holistic model for measuring and improving resilience. Project objectives included developing novel resilience metrics, advancing modeling frameworks that capture interdependencies across infrastructures, and embedding community-centric indicators directly into planning processes for distributed energy resources. The key technical innovations included the creation of self-organizing map (SOM)-based indices for objective resilience quantification, hetero-functional graph theory (HFGT) models linking power, water, transportation, and community assets, and graph neural network (GNN) tools for identifying critical nodes in complex systems. Community-centric energy planning was demonstrated through optimal siting and sizing of (photovoltaic) PV and battery storage, ensuring resilience enhancements also addressed energy burden and energy insecurity. SAFER engaged community partners in Dodge City and Ford County through surveys, focus groups, and workshops, generating more than 600 responses that established baseline measures of energy burden, financial insecurity, and willingness-to-pay to avoid outages. This data, organized in terms of a community capitals framework, informed the development of weighted reliability indices that better reflect community costs than traditional utility metrics. SAFER’s GNN-based critical node identification framework identified expert-labelled critical nodes with over 99% accuracy, while also uncovering additional functionalities essential for proactive resilience planning. The project’s models demonstrated that optimal PV and storage deployment could improve resilience indices by over 11 percent, with dispatch strategies further enhancing outcomes, confirming both the technical effectiveness and economic feasibility of these approaches. Through its combined emphasis on rigorous modeling, community-focused planning, and community engagement, SAFER advances the state of resilience research while delivering direct benefits to rural communities. The project provides tools, guidelines, and resilience heatmaps that help utilities, local governments, and residents better anticipate disruptions, prioritize investments, and strengthen the capacity to withstand and recover from energy-related hazards. Furthermore, the developed HFG and GNN frameworks are designed for transferability, allowing them to be adapted for resilience planning in other communities with minimal retraining. This inductive learning capability provides a scalable pathway to extend the SAFER project’s impact. Thus, creating a foundation for a nationally applicable model of infrastructure resilience. Additionally, the HFG can also be extended to include other FEMA community lifelines.

14 SOLAR ENERGY↗

DOE OSTI2026

Evaluating Polymer Properties with Different Additives for Carbon Capture and Other Applications

Anthropogenic climate change is one of this generation’s most pressing concerns, with the potential to completely alter the delicate balance we’ve struck with nature. Already, global temperatures have risen 1.29°C, leading to disrupted weather systems, extinctions, increased risks of wildfires, and sea level rise, to name a few effects. Carbon dioxide emission from the combustion of fossil fuels and other industrial activity is a large driver of this phenomenon, as it absorbs heat before it can be radiated away from Earth, trapping it. Carbon dioxide has reached unprecedented levels in our atmosphere, showing a 50% increase from preindustrial averages to a whopping 430 ppm. Thus, reducing the amount of carbon dioxide via carbon capture technology is an important endeavor that serves to benefit everyone. The Microencapsulated CO 2 Sorbent (MECS) team at Lawrence Livermore National Laboratory (LLNL) has turned to microencapsulation to approach this endeavor. Microcapsules provide an attractive approach to carbon capture, combining large surface areas for more efficient mass transfer, regenerative abilities, reduced solvent loss, and improved handling. Additionally, while existing carbon capture technology relies on industrial plants, capsules could present a modular approach to carbon capture, reducing the need for extensive physical infrastructure. The MECS team’s design consists of a polymer membrane that contains a liquid carbon sequestering sorbent, aqueous sodium carbonate. The carbon capturing reaction occurs in three distinct steps, the first of which is the dissolution of carbon dioxide into the sorbent solution and its conversion into carbonic acid (H 2 CO 3 ), shown in equations 1 and 2 respectively. Because this step hinges upon the ability of carbon dioxide to reach the solution inside the capsule, it is necessary that the microcapsule shell is permeable to carbon dioxide gas. The MECS team produces these microcapsules using the in-air droplet encapsulation apparatus (IDEA) shown in figure 1, which can produce uniform micron-scale droplets at speeds much faster than traditional single-dispersal microfluidic-based techniques. The IDEA Is 100 times faster than these current techniques and can reach up to 1000 times their speed when incorporating a multi-nozzle design. Additionally, because droplets are produced in-air via vibration, IDEA can decrease post-processing times and material waste by 99% and can fabricate microgels that are 10 to 100 times more viscous than can be produced via traditional microfluidics. While this design represents a breakthrough in the throughput, efficiency, and tunability of microcapsule production, it imposes a major constraint on the microcapsule curing process. Because microcapsule shells are crosslinked with UV light while falling 30 cm through the air, this gives them a reaction window of approximately 0.2 seconds. Thus, the system and shell formulations must be optimized such that the shells can be fully crosslinked within this very narrow window, prompting investigations into curing behavior.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Encoding trade-offs and design toolkits in quantum algorithms for discrete optimization: coloring, routing, scheduling, and other problems

Challenging combinatorial optimization problems are ubiquitous in science and engineering. Several quantum methods for optimization have recently been developed, in different settings including both exact and approximate solvers. Addressing this field of research, this manuscript has three distinct purposes. First, we present an intuitive method for synthesizing and analyzing discrete (i.e., integer-based) optimization problems, wherein the problem and corresponding algorithmic primitives are expressed using a discrete quantum intermediate representation (DQIR) that is encoding-independent. This compact representation often allows for more efficient problem compilation, automated analyses of different encoding choices, easier interpretability, more complex runtime procedures, and richer programmability, as compared to previous approaches, which we demonstrate with a number of examples. Second, we perform numerical studies comparing several qubit encodings; the results exhibit a number of preliminary trends that help guide the choice of encoding for a particular set of hardware and a particular problem and algorithm. Our study includes problems related to graph coloring, the traveling salesperson problem, factory/machine scheduling, financial portfolio rebalancing, and integer linear programming. Third, we design low-depth graph-derived partial mixers (GDPMs) up to 16-level quantum variables, demonstrating that compact (binary) encodings are more amenable to QAOA than previously understood. We expect this toolkit of programming abstractions and low-level building blocks to aid in designing quantum algorithms for discrete combinatorial problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

A perfused multi-well bioreactor platform to assess tumor organoid response to a chemotherapeutic gradient

There is an urgent need to develop new therapies for colorectal cancer that has metastasized to the liver and, more fundamentally, to develop improved preclinical platforms of colorectal cancer liver metastases (CRCLM) to screen therapies for efficacy. To this end, we developed a multi-well perfusable bioreactor capable of monitoring CRCLM patient-derived organoid response to a chemotherapeutic gradient. CRCLM patient-derived organoids were cultured in the multi-well bioreactor for 7 days and the subsequently established gradient in 5-fluorouracil (5-FU) concentration resulted in a lower IC 50 in the region near the perfusion channel versus the region far from the channel. We compared behaviour of organoids in this platform to two commonly used PDO culture models: organoids in media and organoids in a static (no perfusion) hydrogel. The bioreactor IC 50 values were significantly higher than IC 50 values for organoids cultured in media whereas only the IC 50 for organoids far from the channel were significantly different than organoids cultured in the static hydrogel condition. Using finite element simulations, we showed that the total dose delivered, calculated using area under the curve (AUC) was similar between platforms, however normalized viability was lower for the organoid in media condition than in the static gel and bioreactor. Our results highlight the utility of our multi-well bioreactor for studying organoid response to chemical gradients and demonstrate that comparing drug response across these different platforms is nontrivial.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

On the Viability of Quantum Annealers to Solve Fluid Flows

This paper explores the suitability of upcoming novel computing technologies, particularly adiabatic annealing based quantum computers, to solve fluid dynamics problems that form a critical component of several science and engineering applications. For our experiments, we start with a well-studied one-dimensional simple flow problem, and provide a framework to convert such problems in continuum to a form amenable for deployment on such quantum annealers. Since the DWave annealer returns multiple states sampling the energy landscape of the problem, we explore multiple solution selection strategies to approximate the solution of the problem. We analyze the continuum solutions obtained both qualitatively and quantitatively as well as their sensitivities to the particular solution selection scheme.

42 ENGINEERING↗

DOE OSTI2024

A Portable Miniature Cryogenic Environment for In Situ Neutron Diffraction

Neutron diffraction instruments offer a platform for materials science and engineering studies at extended temperature ranges far from ambient. As one of the widely used neutron sample environment types, cryogenic furnaces are usually bulky and complex, and they may need hours of beamtime overhead for installation, configuration, cooling, and sample change, etc. To reduce the overhead time and expedite experiments at the state-of-the-art high-flux neutron source, we developed a low-cost, miniature, and easy-to-use cryogenic environment (77–473 K) for in situ neutron diffraction. A travel-size mug serves for the environment where the samples sit inside. Immediate cooling and an isothermal dwell at 77 K are realized on the sample by direct contact with liquid N 2 in the mug. The designed Al inserts serve as the holder of samples and heating elements, alleviate the thermal gradient, and clear neutron pathways. Both a single-sample continuous measurement and multi-sample high-throughput measurements are demonstrated in this environment. High-quality and refinable in situ neutron diffraction patterns are acquired on model materials. The results quantify the orthorhombic-to-cubic phase transformation process in LiMn 2 O 4 and differentiate the anisotropic lattice thermal expansions and bond length evolutions between rhombohedral perovskite oxides with composition variation.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Modeling of Induction Motors and Variable Speed Drives for Multi-Domain System Simulations Using Modelica and the OpenIPSL Library

This paper introduces an innovative method for characterizing, implementing, and validating both three-phase and single-phase induction motor models, accompanied by a variable speed drive model. The primary goal is to investigate interactions between the electrical power grid and other dynamic domains (e.g., thermofluidic) that impact motor/load drive behavior. Our approach involves establishing a mechanical interface based on a physically meaningful equation linking motor torque/speed to the electrical model in the phasor domain. This allows seamless integration of diverse domain subsystems into a unified multi-domain model using Modelica v4.0.0 and the OpenIPSL library v3.0.1, overcoming co-simulation limitations. The proposed model, which requires only one Modelica-compliant tool for simulation, introduces additional dynamics through the mechanical interface, enabling explicit simulation of load disturbances based on constitutive physics. This deepens our understanding of dynamic interactions between the electrical power domain and other subsystems connected through the motor. We detail the modeled components using mathematical equations and textual descriptions, emphasizing the Modelica modeling approach. Simulation examples validate the implementation, demonstrating the multi-domain modeling capabilities of the newly developed components.

Computer Science↗

DOE OSTI2024

An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies

The adoption of electric vehicles (EVs) has emerged as a solution to reduce greenhouse gas emissions in the transportation sector, which has motivated the implementation of public policies to promote their use in several countries. However, the high adoption of EVs poses challenges for the electricity sector, as it would imply an increase in energy demand and possible impacts on the power quality (PQ) of the power grid. Therefore, it is important to conduct EV integration studies in the power grid to determine the amount that can be incorporated without causing problems and identify the areas of the power sector that will require reinforcements. Accurate EV load patterns are required for this type of study that, through mathematical modeling, reflect both the dynamic behavior and the factors that influence the decision to recharge EVs. This article aims to present an overview of EVs, examine the different factors considered in the literature for modeling EV load patterns, and review modeling methods. EV load modeling methods are classified into deterministic, statistical, and machine learning. The article shows that each modeling method has its advantages, disadvantages, and data requirements, ranging from simple load modeling to more accurate models requiring large datasets.

Computer Science↗

DOE OSTI2024

Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids

In this study, we address the challenge of detecting and mitigating cyber attacks in the distributed cooperative control of islanded AC microgrids, with a particular focus on detecting False Data Injection Attacks (FDIAs), a significant threat to the Smart Grid (SG). The SG integrates traditional power systems with communication networks, creating a complex system with numerous vulnerable links, making it a prime target for cyber attacks. These attacks can lead to the disclosure of private data, control network failures, and even blackouts. Unlike machine learning-based approaches that require extensive datasets and mathematical models dependent on accurate system modeling, our method is free from such dependencies. To enhance the microgrid’s resilience against these threats, we propose a resilient control algorithm by introducing a novel trustworthiness parameter into the traditional cooperative control algorithm. Our method evaluates the trustworthiness of distributed energy resources (DERs) based on their voltage measurements and exchanged information, using Kullback-Leibler (KL) divergence to dynamically adjust control actions. We validated our approach through simulations on both the IEEE-34 bus feeder system with eight DERs and a larger microgrid with twenty-two DERs. The results demonstrated a detection accuracy of around 100%, with millisecond range mitigation time, ensuring rapid system recovery. Additionally, our method improved system stability by up to almost 100% under attack scenarios, showcasing its effectiveness in promptly detecting attacks and maintaining system resilience. These findings highlight the potential of our approach to enhance the security and stability of microgrid systems in the face of cyber threats.

Computer Science↗

DOE OSTI2021

Current Developments of Carbon Capture Storage and/or Utilization–Looking for Net-Zero Emissions Defined in the Paris Agreement

An essential line of worldwide research towards a sustainable energy future is the materials and processes for carbon dioxide capture and storage. Energy from fossil fuels combustion always generates carbon dioxide, leading to a considerable environmental concern with the values of CO2 produced in the world. The increase in emissions leads to a significant challenge in reducing the quantity of this gas in the atmosphere. Many research areas are involved solving this problem, such as process engineering, materials science, chemistry, waste management, and politics and public engagement. To decrease this problem, green and efficient solutions have been extensively studied, such as Carbon Capture Utilization and Storage (CCUS) processes. In 2015, the Paris Agreement was established, wherein the global temperature increase limit of 1.5 °C above pre-industrial levels was defined as maximum. To achieve this goal, a global balance between anthropogenic emissions and capture of greenhouse gases in the second half of the 21st century is imperative, i.e., net-zero emissions. Several projects and strategies have been implemented in the existing systems and facilities for greenhouse gas reduction, and new processes have been studied. This review starts with the current data of CO2 emissions to understand the need for drastic reduction. After that, the study reviews the recent progress of CCUS facilities and the implementation of climate-positive solutions, such as Bioenergy with Carbon Capture and Storage and Direct Air Capture. Future changes in industrial processes are also discussed.

Regufe, Maria João (ORCID:0000000327748302)↗

DOE OSTI2022

Fabrication of Black Body Grids by Thick Film Printing for Quantitative Neutron Imaging

Neutron imaging offers deep penetration through many high-Z materials while also having high sensitivity to certain low-Z isotopes such as 1H, 6Li, and 10B. This unique combination of properties has made neutron imaging an attractive tool for a wide range of material science and engineering applications. However, measurements made by neutron imaging or tomography are generally qualitative in nature due to the inability of detectors to discriminate between neutrons which have been transmitted through the sample and neutrons which are scattered by the sample or within the detector. Recent works have demonstrated that deploying a grid of small black bodies (BBs) in front of the sample can allow for the scattered neutrons to be measured at the BB locations and subsequently subtracted from the total measured intensity to yield a quantitative transmission measurement. While this method can be very effective, factors such as the scale and composition of the sample, the beam divergence, and the resolution and construction of the detector may require optimization of the grid design to remove all measurement biases within a given experimental setup. Therefore, it is desirable to have a method by which BB grids may be rapidly and inexpensively produced such that they can easily be tailored to specific applications. In this work, we present a method for fabricating BB patterns by thick film printing of Gd2O3 and evaluate the performance with variation in feature size and number of print layers with cold and thermal neutrons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Inherent Anharmonicity of Harmonic Solids

Atomic vibrations, in the form of phonons, are foundational in describing the thermal behavior of materials. The possible frequencies of phonons in materials are governed by the complex bonding between atoms, which is physically represented by a spring-mass model that can account for interactions (spring forces) between the atoms (masses). The lowest-order, harmonic , approximation only considers linear forces between atoms and is thought incapable of explaining phenomena like thermal expansion and thermal conductivity, which are attributed to nonlinear, anharmonic , interactions. Here, we show that the kinetic energy of atoms in a solid produces a pressure much like the kinetic energy of atoms in a gas does. This vibrational or phonon pressure naturally increases with temperature, as it does in a gas and therefore results in a thermal expansion. Because thermal expansion thermodynamically defines a Grüneisen parameter γ , which is a typical metric of anharmonicity, we show that even a harmonic solid will necessarily have some anharmonicity. A consequence of this phonon pressure model is a harmonic estimation of the Grüneisen parameter as γ ≈ 3 / 2 3 − 4 x 2 / 1 + 2 x 2 , where x = v t / v l is the ratio of the transverse and longitudinal speeds of sound. We demonstrate the immediate utility of this model by developing a high-throughput harmonic estimate of lattice thermal conductivity that is comparable to other state-of-the-art estimations. By linking harmonic and anharmonic properties explicitly, this study provokes new ideas about the fundamental nature of anharmonicity, while also providing a basis for new material engineering design metrics.

42 ENGINEERING↗

DOE OSTI2020

On the Convergence of Physics Informed Neural Networks for Linear Second-Order Elliptic and Parabolic Type PDEs

Physics informed neural networks (PINNs) are deep learning based techniques for solving partial differential equations (PDEs) encountered in computational science and engineering. Guided by data and physical laws, PINNs find a neural network that approximates the solution to a system of PDEs. Such a neural network is obtained by minimizing a loss function in which any prior knowledge of PDEs and data are encoded. Despite its remarkable empirical success in one, two or three dimensional problems, there is little theoretical justification for PINNs. As the number of data grows, PINNs generate a sequence of minimizers which correspond to a sequence of neural networks. We want to answer the question: Does the sequence of minimizers converge to the solution to the PDE? We consider two classes of PDEs: linear second-order elliptic and parabolic. By adapting the Schauder approach and the maximum principle, we show that the sequence of minimizers strongly converges to the PDE solution in C 0 . Furthermore, we show that if each minimizer satisfies the initial/boundary conditions, the convergence mode becomes H 1 . Computational examples are provided to illustrate our theoretical findings. To the best of our knowledge, this is the first theoretical work that shows the consistency of PINNs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Progress Towards Developing Neutron Tolerant Magnetostrictive and Piezoelectric Transducers

Current generation light water reactors (LWRs), sodium cooled fast reactors (SFRs), small modular reactors (SMRs), and next generation nuclear plants (NGNPs) produce harsh environments in and near the reactor core that can severely tax material performance and limit component operational life. To address this issue, several Department of Energy Office of Nuclear Energy (DOE-NE) research programs are evaluating the long duration irradiation performance of fuel and structural materials used in existing and new reactors. In order to maximize the amount of information obtained from Material Testing Reactor (MTR) irradiations, DOE is also funding development of enhanced instrumentation that will be able to obtain in-situ, real-time data on key material characteristics and properties, with unprecedented accuracy and resolution. Such data are required to validate new multi-scale, multi-physics modeling tools under development as part of a science-based, engineering driven approach to reactor development. It is not feasible to obtain high resolution/microscale data with the current state of instrumentation technology. However, ultrasound-based sensors offer the ability to obtain such data if it is demonstrated that these sensors and their associated transducers are resistant to high neutron flux, high gamma radiation, and high temperature. To address this need, the Advanced Test Reactor National Scientific User Facility (ATR-NSUF) is funding an irradiation, led by PSU, at the Massachusetts Institute of Technology Research Reactor to test the survivability of ultrasound transducers. As part of this effort, PSU and collaborators have designed, fabricated, and provided piezoelectric and magnetostrictive transducers that are optimized to perform in harsh, high flux, environments. Four piezoelectric transducers were fabricated with either aluminum nitride, zinc oxide, or bismuth titanate as the active element that were coupled to either Kovar or aluminum waveguides and two magnetostrictive transducers were fabricated with Remendur or Galfenol as the active elements. Pulse-echo ultrasonic measurements of these transducers are made in-situ. This paper will present an overview of the test design including selection criteria for candidate materials and optimization of test assembly parameters, data obtained from both out-of-pile and in-pile testing at elevated temperatures, and an assessment based on initial data of the expected performance of ultrasonic devices in irradiation conditions

Reinhardt1, Brian↗