Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Extreme Environment”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Technical report Letter: RAFM, ODS steels and MMLC for Nuclear energy application

The lifetime, thermodynamic efficiency, safety and economic viability of new generation fission and fusion reactor concepts can largely be tied to the mechanical performance and stability of structural alloys under extreme environments. In this context, engineered nano materials could have broad-reaching impact on the future of advanced nuclear fuel-cycle and reactors. These systems are characterized by a large number density of interfaces which are efficient sinks for point defects and moderately biased; therefore limiting the deleterious effects of irradiation. Broadly, nuclear nano-technology deals with the use of the latest engineered-nanomaterials for improving the nuclear power performances and safety in all areas of nuclear energy production to bring new generations of nuclear power units. New advanced fuel assembly designs also have implications for securities and safeguards. To support the readiness for potential future license applications, an understanding of the technologies that would enable new reactor designs in the areas of component performance and domestic safeguards is necessary. This technical report letter work explores the technical issues and potential regulatory considerations associated with developing and adopting fuel claddings made of advanced nano- materials. Specifically three classes of nanomaterials are considered: (i) reduced activation ferritic/martensitic (RAFM) steels, (ii)oxide dispersed steels (ODS) and (iii) multi-metallic layered composites (MMLC).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Revolutionizing Materials Design: The Intersection of Quantum Mechanics and Data Modeling

The field of materials design is currently experiencing a notable evolution, driven by the convergence of sophisticated computational methodologies based on first principles and data-driven modeling approaches. I will review our recent endeavors employing AI/ML to expedite first-principles simulations and mitigate traditional methods' temporal and spatial limitations. Central to our efforts is developing and utilizing ML interatomic potentials (MLPs) across a diverse spectrum of materials. We show that MLPs serve as invaluable tools for navigating the complexities of the simulations, such as understanding the behavior of MgO at extreme environments of ~1 terapascal and temperatures >10,000 Kelvin. Moreover, we show that MLPs can provide precise details of the intricate dynamics governing the oxidation processes of binary alloy systems due to the competition between surface segregation and reconstruction tendencies. In summation, advancements in MLPs open the door to fresh possibilities in material modeling and, ultimately, discovery.

Saidi, Wissam↗
DOE OSTI2025

Multi-physics Topology OPtimization and Additive Manufacturing for High-temperature Heat Exchangers

This research significantly advances the understanding of high-temperature heat exchanger design through an integrated approach that combines topology optimization (TO), triply periodic minimal surface (TPMS) structures, additive manufacturing (AM) and thermohydraulic testing. Each of these components contributes uniquely to a unified, high-performance design, fabrication and testing workflow. Topology optimization serves as the foundation of the design methodology by providing a systematic way to determine the most effective material layout for separating hot and cold fluids while maximizing thermal performance. The researchers introduced a novel three-material optimization framework using two density fields to represent hot fluid, cold fluid, and solid domains. This approach enables automated discovery of optimal shapes and flow paths that cannot be intuitively designed, especially under constraints imposed by manufacturing technologies. Furthermore, constraints such as minimal wall thickness and overhang angles were embedded into the optimization process, ensuring that resulting designs are not only thermally efficient but also manufacturable using modern additive techniques. In parallel, the study delves into the use of Gyroid-based TPMS geometries for constructing the core of the heat exchanger. TPMS structures are known for their high surface area, excellent fluid mixing capabilities, and minimal pressure drop characteristics. The researchers applied a data-driven modeling framework using Heteroscedastic Sparse Gaussian Process Regression (HSGPR) combined with genetic algorithms. This allowed for the rapid evaluation and optimization of key geometric parameters such as frequency, iso-value, and phase shift. The result was a set of Gyroid structures tailored for high heat transfer and low flow resistance, demonstrating clear improvements over conventional straight-channel designs. After the designing process, additive manufacturing played a critical role by turning these highly complex, optimized geometries into physical components. Utilizing Laser Powder Bed Fusion (LPBF) with Haynes 282, the study demonstrated the feasibility of fabricating these heat exchangers at high precision. Post-processing methods, including dilation-erosion operations, were applied to ensure local features adhered to self-supporting constraints. The fabricated structures were then subjected to thermohydraulic testing under conditions representative of supercritical CO 2 Brayton cycles, validating the predicted performance and confirming the viability of the full design-to-fabrication pipeline. Finally, thermohydraulic testing across the above studies served as a crucial experimental validation of advanced heat exchanger. Under consistent high-temperature and high-pressure conditions using supercritical CO 2 , the testing demonstrated that both TO and Gyroid-based TPMS designs significantly outperformed conventional straight-channel HXs. The TO design achieved a 115% increase in UA and NTU and a 27.6% boost in gravimetric power density, while the data-driven optimized Gyroid design delivered a 166% increase in UA and NTU and improved effectiveness from 68.7% to 86.1%. These results validate the simulation models, confirm the manufacturability of complex geometries under AM constraints, and provide key insights into design-performance trade-offs, thereby advancing the development of high-efficiency, compact heat exchangers for extreme environments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of Multimaterial Graded Structure from Superalloys to Refractory Alloys

This research focused on developing hybrid microstructures for extreme environments where zone-specific performance is essential. Traditional structural applications rely on single alloy compositions, often requiring compromises in cost, corrosion resistance, or high-temperature stability, while dissimilar welding leads to abrupt material transitions and potential mechanical weaknesses. By employing a combinatorial approach, this study enabled a gradual transition of chemistries across components, allowing site-specific tailoring of microstructures. Leveraging additive manufacturing’s flexibility, this concept facilitated multi-material alloying and optimized fabrication strategies, unlocking new capabilities in high-performance applications while reducing manufacturing costs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Supply Chain Improvement & Process Modification Printing in Tantalum

Refractory metals and alloys are distinguished by their exceptional thermophysical properties, including high melting and recrystallization temperatures, remarkable strength, and superior corrosion resistance, all of which surpass those of conventional alloys. These unique characteristics position these materials as ideal candidates for applications in extreme environments. However, their potential has historically been underexploited due to limitations in processing capabilities. Recent advancements in melt-based additive manufacturing (AM) processes present opportunities to overcome these limitations. Previous Sandia studies have successfully characterized pure tantalum produced through laser powder bed fusion (LPBF) externally at Castheon, revealing that LPBF-fabricated tantalum exhibits properties exceeding those of wrought materials. This promising outcome sparked increased interest in the internal additive manufacturing of tantalum. This project aimed to establish the new SLM 280 machine at SNL-CA to successfully produce the first tantalum prints and characterize the material. Additionally, efforts were made to enhance the machine by incorporating Inert equipment to minimize oxygen content within the print volume. The results demonstrated that internally manufactured LPBF tantalum not only met but exceeded the standards of wrought materials, even prior to the integration of the additional equipment. The inert equipment is almost successfully integrated and ready for use. Future research should focus on understanding how this equipment influences the process-structure-property relationships, as well as further optimizing the printing parameters for tantalum.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Establishing defect-property relationships for 2D-nanomaterials (Final technical report)

Studies of new families of two-dimensional nanomaterials (2DNMs) have established that they possess unique properties that diverge from those of their bulk counterparts. This project aimed to determine how tolerant 2DNMs are to extreme photon and particle fluxes and to identify the mechanisms governing their radiation response. Early work indicated that graphene is not as representative of other 2DNMs as previously assumed; however, the origin of this difference remained unclear. To address these knowledge gaps, this project investigated the physical processes occurring at multiple length scales in transition metal dichalcogenides (TMDs) and quantified their structural stability and property evolution under far-from-equilibrium conditions. In-situ and ex-situ ion and electron irradiations were performed to directly control and monitor defect formation in TMDs. Complementary density functional theory (DFT) and molecular dynamics (MD) simulations were employed to elucidate the mechanisms of defect generation and evolution. The outcomes of this work established mechanistic understanding of irradiation-induced defect formation in 2DNMs, quantified the radiation tolerance of TMDs, and built a fundamental knowledge base for correlating defect structures with material properties. Collectively, these results provide new insights into the stability of low-dimensional materials in extreme environments and enable the predictive design of radiation-tolerant 2DNMs.

2D materials↗
DOE OSTI2026

Low Temperature Tantalum Electrodeposition: Enabling Next Generation Coatings

This project aimed to identify the ligand and solvation conditions necessary for the electrodeposition of refractory metals from low-temperature organic electrolytes. Tantalum (Ta) was chosen as a specific exemplar for programmatic purposes. It was hoped that a deeper understanding of these relationships could facilitate the innovative application of refractory metal coatings on thermally sensitive and geometrically intricate components used in extreme environments related to energy generation and storage, nuclear deterrence, aerospace, defense, and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Detection of trace contaminants released from rapidly heated pulsed power electrodes by laser diagnostics

Development of a capability to measure trace gas contaminants released from pulsed power electrodes would immediately impact Sandia pulsed power research. These releases occur during ultra-fast heating of metal electrodes during pulsed power discharges and can lead to substantial power losses through plasma formation. Detection of contaminants is a formidable challenge due to the need for in-situ spatially and temporally resolved measurements of trace gases in the extreme environment of ultra-fast heated metal surfaces. We investigate the feasibility of laser diagnostics for detecting contaminants, including H-atom, OH, and H 2 O. Laser-induced fluorescence and photofragmentation fluorescence showed significant plasma emission interferences and did not yield any detectable H-atom, OH, or H 2 O. Our newly developed H-atom detection using femtosecond degenerate four-wave mixing suppressed interferences and enabled detection of H-atoms. A few shots showed large signals in the near-surface region of metal foils, suggesting the formation of a wave of H-atoms from the metal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Quantum Computing Strategy 2026

Quantum computing (QC) is a rapidly maturing technology with the potential for revolutionary impacts on stockpile stewardship science and national security. Recent developments in fault-tolerant architectures have compressed vendor roadmaps, and predictions of a production-ready quantum computer by the mid-2030s are becoming increasingly credible. This strategy provides a roadmap for integrating QC into the Advanced Simulation and Computing (ASC) program by investing in four strategic focus areas: 1. Develop Capabilities in Mission-Relevant Quantum Applications: ASC will prioritize developing quantum-ready applications in mission areas that have shown significant promise for quantum advantage, including simulations of materials in extreme environments, nuclear dynamics, solving linear and nonlinear partial differential equations, and uncertainty quantification. These applications directly support stockpile stewardship science and modernization objectives. 2. Conduct R&D in Algorithms, Software, and Hardware: Sustained research into quantum algorithms, robust software tools, and quantum hardware is essential. ASC will develop efficient quantum algorithms; invest in quantum compilers, debuggers, and performance tools; and explore specialized quantum hardware tailored to NNSA’s unique requirements. 3. Engage with Vendors and Partners: Early and active collaboration with commercial quantum hardware vendors and academic partners is critical. Through testbeds, co-design agreements, and quantum demonstration facilities, ASC will influence hardware design, gain early access to emerging technologies, and ensure that quantum platforms evolve to meet mission needs. 4. Build Knowledge, Experience, and Workforce: Expanding and upskilling the quantum-trained workforce is essential to long-term success. This includes hiring, internal training, university outreach, and postdoctoral support to ensure ASC maintains the expertise required to operate, program, and integrate quantum systems as they become available. While quantum computing will never replace classical computing, it has the potential to solve certain problems with speed and accuracy that would be unachievable using any conceivable classical high-performance computing (HPC) system. By investing strategically in QC, ASC will help propel the emergent QC industry, maintain U.S. technological leadership, ensure mission readiness, and position itself to rapidly adopt quantum technologies as they mature.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Optimization of Functionally Graded Materials Using Additive Manufacturing: An Integrated Experimental and Computational Approach (Abbreviated Final Report)

Many advanced technologies, such as next-generation energy systems, aerospace vehicles, and defense platforms, require materials that can withstand extreme environments, including high temperatures, corrosion, and radiation, while remaining strong and lightweight. Traditionally, joining different materials to achieve these properties introduces weak, failure-prone interfaces and defects that limit performance. Our research aimed to overcome this challenge by using additive manufacturing, specifically directed energy deposition, to create functionally graded materials—components with smooth transitions between different metals. This approach eliminates sharp boundaries and allows for tailored material properties throughout a part.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rapid Oxidation of Uranium Steel Alloys: Combustion Synthesis

This project explored the use of combustion synthesis as a rapid, high-temperature method for oxidizing uranium-bearing steel alloys. Traditional laboratory-scale synthesis methods often fail to replicate the thermal and kinetic conditions experienced by real-world particulates, particularly those formed under rapid quenching or high-temperature scenarios. Combustion synthesis offers a promising alternative by enabling fast, localized heating and flexible precursor selection. A series of targeted experiments were conducted using a U 2 NiCrFe 4 alloy as the precursor. The alloy was oxidized using combustion synthesis reactions fueled by uranyl nitrate and glycine, achieving peak temperatures exceeding 1,200 °C. Postreaction analysis using scanning electron microscopy (SEM), elemental mapping, and Raman spectroscopy revealed the formation of iron-based oxides, with limited but detectable evidence of uranium oxide phases such as UO 2 . The results indicate that under the rapid reaction and cooling conditions of combustion synthesis, iron oxides form preferentially, but uranium oxide formation is kinetically limited. These findings validate combustion synthesis as a viable method for simulating the oxidation behavior of uranium steels in extreme environments and lay the groundwork for future studies aimed at enhancing uranium oxide formation through higher temperatures or modified precursor compositions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

ORNL Design Engineering Library: Validated Thermoelectric Digital Twins

Radioisotope thermoelectric generators (RTGs) serve a crucial role in supplying thermal and electrical energy for reliable and long-duration power in remote and extreme environments. The thermal energy is provided by the decay of radioisotopes and is converted into electrical energy using the steady-state thermoelectric process by exploiting the Seebeck effect. Maintaining a thermal gradient through the material is necessary to drive current production. Modern predictive multi-physics tools are able to effectively describe the complex and strongly coupled phenomena needed for accurate model-based system engineering efforts needed to develop higher performing RTGs. Experimental validation of model simulations is essential to confirm the accuracy, reliability, and applicability of predictive multiphysics tools. Validation fosters confidence among users, helps meet regulatory requirements, and contributes to the ongoing improvement of simulation techniques, ultimately leading to better, safer, and more efficient designs and processes. Validated models can then be used as digital twins and can be interrogated to understand and quantify the performance gaps between theoretical and physical systems. These insights can be used to build higher performing systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Robustness and printed sensor qualification

A limiting factor of additive manufactured (AM) sensors for in-pile applications is the development of appropriate interconnection and packaging strategies that can maintain reliable performance in extreme environments. Failure mechanisms in these harsh conditions could include, but not limited to, materials interaction (i.e., intermetallic formation) and coefficient of thermal expansion (CTE) mismatch between the individual components of the sensors. To mitigate premature failure and enable the successful sustained operation of AM sensors, non-destructive qualification tests are used as an intermediate process control step used for verifying robustness and reliability of the sensor before they are deployed. A materials system of interest is the use of barium strontium titanium oxide (BST) films on stainless steel 316L (SS316L) substrate. Due to BST’s high dielectric constant and tunable dielectric properties, there is an interest for its application as an insulation/encapsulation layer for capacitive strain gauges when printed on structural materials. Previous work on the BST/SS316L material system, however, showed that the BST cracks when exposed to temperatures up to 600 °C due to CTE mismatch between the printed BST film and the metallic substrate. When comparing different fabrication techniques, less surface cracking was observed in the samples that deposited thinner (i.e., 2-20 μm) than samples that were thicker (i.e., 135 µm – 300 µm). The objective of this report is to establish a qualification process that will determine and address any challenges (i.e., mechanical failure of thick prints) of the AM sensor prior to its application in experimental tests. To demonstrate the qualification process in this report, laser spallation and uniaxial tensile tests using dynamic and quasi-static loading, respectively, will be discussed.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

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

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

36 MATERIALS SCIENCE↗
DOE OSTI2025

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

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

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

NSUF RTE completion report for 23-4780: Microstructural Defect Induced Thermal Conductivity Reduction in Uranium Nitride and Thorium Nitride

Uranium nitride (UN) is known to have a higher thermal conductivity than traditional oxide fuels, which could lead to a more efficient energy transport and lower local temperature during its lifetime. But the thermal transport performance of UN in extreme environments has not been systematic studied. This study investigated the irradiation induced microstructural defects in UN and the impacts on thermal conductivity. The samples were produced by spark plasma sintering at University of Texas-San Antonio (UTSA), Los Alamos National Laboratory (LANL), and Idaho National Laboratory (INL). Thermal conductivity of UN before and after 2MeV proton irradiation were measured by using laser metrology at INL in a temperature range of 77-295K. Thermal conductivity measurements in this wide, cryogenic temperature range is critical to understand the phonon scattering mechanisms between the thermal energy carrier, phonons, and different types of irradiation-induced defects. In order to ensure the measurements were conducted in the same grains and minimize the impact of the local heterogeneities, the measurement locations were highlighted by fiducial marks using the focused ion beam (FIB) with grain orientation identified using the electron backscatter diffraction (EBSD) at the Center of Advanced Energy Studies (CAES). Irradiation experiment was conducted at the Ion Beam Laboratory at Texas A&M University (TAMU). A total of 6 samples were irradiated with different irradiation doses and temperatures. After irradiation, the microstructure was characterized by using Transmission Electron Microscope (TEM) at CAES (also in the FIB marks).

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

ROADRUNNER MiniFuel Experiment: Readiness for Insertion

The Research On ADvancing the peRformance of UraNium Nitrides in Extreme enviRonments (ROADRUNNER) campaign is a collaborative irradiation experiment designed to evaluate the performance of uranium nitride (UN) fuel fabricated with controlled variations in density and impurity content. Oak Ridge National Laboratory’s MiniFuel irradiation platform and the High Flux Isotope Reactor (HFIR) are being used to irradiate six targets containing 36 UN miniature disks. These targets have been assembled to systematically investigate burnup and temperature effects under accelerated irradiation conditions. This report documents the finalized test plan, describes the experiment assembly and subcapsule integration process, and confirms the readiness of all ROADRUNNER targets for HFIR insertion. All targets have passed quality control procedures, and five have begun irradiation. The campaign will provide critical performance data to support fuel model validation and future UN qualification efforts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗