Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Materials science”

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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Synthesis of inter‐lanthanide sesquioxides LnLn'O 3 by polymeric steric entrapment

Lanthanide oxides are well known in the fields of optical, electronic, and magnetic materials. Even so, there are many application spaces yet to be explored. Previous modeling of inter-lanthanide sesquioxides, in which the compound contains two lanthanide cations, predicts the lowest level energy structure as a function of chemistry, which this work seeks to verify. Three materials of interest, ErLuO 3 , LaLuO 3 , and SmLuO 3 , were synthesized for the first time by the polymeric steric entrapment (PSE) method. X-ray diffraction confirms the stable state predictions of ErLuO 3 and SmLuO 3 forming a bixbyite type structure and LaLuO 3 forming a perovskite type structure. This work demonstrates PSE as a viable and reliable route toward the synthesis of these unique materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Laboratory Directed Research and Development Program: FY 2024 Completed Projects Report

Oak Ridge National Laboratory (ORNL) is the US Department of Energy’s (DOE’s) largest multiprogram science, technology, and energy laboratory. It possesses distinctive capabilities in a variety of fields, such as neutron science, computing, advanced materials, and nuclear science and technology. Using these capabilities, ORNL conducts basic and applied research and development (R&D) to support DOE’s overarching mission “to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.” As a national resource, ORNL also applies its capabilities and skills to the specific needs of other federal agencies and customers through the DOE Strategic Partnership Projects (SPP) Program. Information about the laboratory and its programs is available on the ORNL website. The Laboratory Directed Research and Development (LDRD) Program at ORNL operates under the authority of DOE Order 413.2C, Laboratory Directed Research and Development,3 which establishes DOE’s requirements for the program while providing the laboratory director broad flexibility for program implementation. The LDRD Program funds are obtained through a charge to all laboratory programs. Although it represents a relatively small portion of the overall research budget, the LDRD Program plays an essential role in maintaining the laboratory’s ability to respond to national needs. The program allows ORNL to improve its distinctive capabilities and to enhance its ability to conduct cutting-edge R&D. In accordance with the DOE order, R&D projects funded through the LDRD Program at ORNL support the goals of • maintaining the scientific and technical vitality of the laboratory; • enhancing the laboratory’s ability to address future DOE missions; • fostering creativity and stimulating exploration of forefront areas of science and technology; • serving as a proving ground for new concepts in R&D; and • supporting high-risk, potentially high-value R&D. This report provides an overview of the LDRD Program at ORNL in FY 2024 and contains summaries of all the LDRD research projects that concluded between October 1, 2023, and September 30, 2024.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Laboratory Directed Research and Development Program: FY 2025 Completed Projects

Oak Ridge National Laboratory (ORNL) is the US Department of Energy’s (DOE’s) largest multiprogram science, technology, and energy laboratory. It possesses distinctive capabilities in a variety of fields, such as neutron science, computing, advanced materials, and nuclear science and technology. Using these capabilities, ORNL conducts basic and applied research and development (R&D) to support DOE’s overarching mission “to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.” As a national resource, ORNL also applies its capabilities and skills to the specific needs of other federal agencies and customers through the DOE Strategic Partnership Projects (SPP) Program. Information about the laboratory and its programs is available on the ORNL website. The Laboratory Directed Research and Development (LDRD) Program at ORNL operates under the authority of DOE Order 413.2C, Laboratory Directed Research and Development, which establishes DOE’s requirements for the program while providing the laboratory director broad flexibility for program implementation. The LDRD Program funds are obtained through a charge to all laboratory programs. Although it represents a relatively small portion of the overall research budget, the LDRD Program plays an essential role in maintaining the laboratory’s ability to respond to national needs. The program allows ORNL to improve its distinctive capabilities and enhance its ability to conduct cutting-edge R&D. In accordance with the DOE order, R&D projects funded through the LDRD Program at ORNL support the goals of • maintaining the scientific and technical vitality of the laboratory, • enhancing the laboratory’s ability to address future DOE missions, • fostering creativity and stimulating exploration of forefront areas of science and technology, • serving as a proving ground for new concepts in R&D, and • supporting high-risk, potentially high-value R&D. This report provides an overview of the LDRD Program at ORNL in FY 2025 and contains summaries of all the LDRD research projects that concluded between October 1, 2024, and September 30, 2025.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Laboratory Directed Research and Development Program: FY 2025 Completed Projects

Oak Ridge National Laboratory (ORNL) is the US Department of Energy’s (DOE’s) largest multiprogram science, technology, and energy laboratory. It possesses distinctive capabilities in a variety of fields, such as neutron science, computing, advanced materials, and nuclear science and technology. Using these capabilities, ORNL conducts basic and applied research and development (R&D) to support DOE’s overarching mission “to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.” As a national resource, ORNL also applies its capabilities and skills to the specific needs of other federal agencies and customers through the DOE Strategic Partnership Projects (SPP) Program. Information about the laboratory and its programs is available on the ORNL website.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Self-Driving Microscopy for AI/ML-Enabled Physics Discovery and Materials Optimization

Materials are the bedrock of economy and foundation for all real-world technologies. The viability of space travel, grid energy storage, solar to fuels conversion, methane removal, and photovoltaic energy solutions hinge on the discovery and optimization of novel materials and rapid scaling toward manufacturing. The last 20 years have seen an exponential growth in the theoretical predictive capability for crystalline materials and small molecules. However, it is only in the last five years that we have seen the rapid expansion of high-throughput synthesis enabled by laboratory robotics and microfluidics, as well as a resurgence of combinatorial synthesis (Abolhasani and Kumacheva 2023; Epps and Abolhasani 2021; Jiang et al. 2022; Rajan 2008; Soldatov et al. 2021; Szymanski et al. 2023). Combinatorial synthesis, microfluidics, and ultimately dip-pen megalibraries have demonstrated the ability to “write” multicomponent nanomaterials at high throughput scale, generating millions of material examples in the 3D, 4D, and 5D composition spaces (Chen et al. 2016, 2019; Jibril et al. 2022).

36 MATERIALS SCIENCE↗
DOE OSTI2025

NDMAS

Overview of Current ART-GCR Data: Fuel Fabrication, Irradiation Monitoring (Fuel & Graphite – near real-time for HDG-1), Post-Irradiation Examination (Fuel & Graphite), Graphite Characterization (Baseline and Irradiated), High Temperature Metals Mechanical Tests, Design, Methods, and Validation Data, Japan Atomic Energy Agency’s High Temperature Test Reactor (HTTR), Argonne National Laboratory’s Natural convection Shutdown heat removal Test Facility (NSTF), Oregon State University’s High Temperature Test Facility (HTTF), Generation IV International VHTR Materials Handbook, Additional related data, and Advanced Test Reactor operations (near real-time).

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Integrated Approach to Post-Irradiation Examination of Nuclear Materials at Idaho National Laboratory

Idaho national Laboratory (INL) is the U.S. lead national laboratory for the Department of Energy’s Office of Nuclear Energy (DOE-NE), providing much of the nuclear research, development and demonstration capability needed to move nuclear innovation forward to deployment. INL’s Materials and Fuels Complex hosts a unique combination of personnel, facilities and infrastructure and offers the ability to perform post-irradiation examinations (PIE) of nuclear materials spanning multiple length scales. The ability to combine engineering-scale analysis and sub-microscopic characterization provides valuable insights into fuel and structural material behavior and degradation mechanisms. The holistic approach is used to accelerate these materials demonstration and deployment. Selected studies will be presented, highlighting the impact of these techniques on improving fuel reliability, safety, and efficiency, thereby advancing the development of sustainable and advanced nuclear energy technologies.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Explainable machine learning reveals that local structural motifs encode the thermodynamic state across the CuZr metallic glass-forming range

Metallic glasses derive their properties from the statistics of local atomic motifs rather than from long-range order, yet a quantitative, chemistry-specific link between motif populations and the underlying glassy state has remained elusive. In this work we combine large-scale molecular dynamics, Voronoi tessellation, deep neural networks, and SHapley Additive exPlanations (SHAP) to identify which local structural motifs define the glassy state of Cu—Zr metallic glasses. A dataset of 17,180 atomistic configurations spanning ten compositions (Cu 20 Zr 80 –Cu 80 Zr 20 ) and four quench rates (10 9 –10 12 K/s) is used to train a feed-forward neural network that regresses temperature across the 50–2000 K liquid–supercooled–glass range, achieving a mean absolute error of 19.89 K and R 2 = 0.9974, confirming that the local structural state is faithfully encoded in motif-level structure. SHAP analysis then reveals that a tightly coupled near-icosahedral family of motifs (coordination numbers (CN) 11–13, including the full icosahedron 001200 and its single-atom-perturbation sibling 10930) collectively encodes the thermodynamic state of the system across the full glass-forming range. The CN = 11–13 ordered members carry negative SHAP values at high populations, tracking the most deeply-quenched configurations, while 10930 shows the reversed signature consistent with its role as a soft-spot host whose population shrinks as the icosahedral network deepens. The analysis demonstrates that explainable machine learning can isolate the minimal motif vocabulary defining the glassy state and recovers the near-icosahedral building blocks previously identified by data-driven analyses of Cu—Zr. The approach provides a general, chemistry-specific route for characterizing the structural state of disordered materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data

Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Role of Elemental Substitution on Hydrogen Incorporation in Characteristic Ti/Fe-Based Oxides

Elemental substitution is well-known to benefit hydrogen storage in the intermetallic compound TiFe; however, the impact of these substituents on the native and passivating surface oxide has not been well-established. Here, we perform density functional theory calculations on several characteristic oxides that are likely to form on exposed TiFe surfaces, specifically, TiO 2 , FeO, TiFeO 3 , and Ti 4 Fe 2 O. In TiO 2 and TiFeO 3 , additional acceptor species substituting for Ti can increase the solubility of protonic hydrogen (H i + ), likely enhancing hydrogen permeation of the oxide layer. In FeO, few dopants will act as acceptors, and hydrogen will incorporate as substitutional H O + , which is likely to be less mobile and will hinder hydrogen permeation. Finally, we find that Ti 4 Fe 2 O, which is thermodynamically metastable, may be stabilized by defects under O-poor conditions, although the presence of certain substitutional elements can destabilize it. In general, Mn, V, and Cr are among the best substituents for enhancing hydrogenation through the oxide layer. In conclusion, our results help to explain what features make additional elements particularly effective for enabling reversible hydrogen storage in TiFe, and they can guide further technological development of high-performing TiFe-based alloys for future energy applications.

organic↗
DOE OSTI2025

Charting the chemical space of Zintl phases with graph neural networks and bonding insights

A large number of Zintl phases have been discovered by solid-state chemists driven by empirical knowledge, chemical intuition and in some cases, through serendipitous accidents. These discoveries have only scratched the surface, given the vast compositional and structural diversity that Zintl phases can accommodate. The large chemical space of Zintl phases, as well as intermetallic compounds in general, remain under-explored. Here, we use graph neural networks and the upper bound energy minimization approach to efficiently scan a large chemical space of >90 000 hypothetical Zintl phases and accurately discover 1810 new thermodynamically stable phases with 90% precision, as validated with first-principles calculations. We show that our approach is more than 2× more accurate in predicting DFT stability than M3GNet (40% precision) on the same dataset. Using a random forest model and SHAP analysis, we demonstrate the critical role of ionic bonding in the thermodynamic stability of Zintl phases. Our results not only expand the known chemical landscape of Zintl phases but also highlight the efficacy of machine learning frameworks combined with domain knowledge in uncovering chemically meaningful insights across complex intermetallics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Materials for Energy Management across the Electromagnetic Spectrum (MEMES) (LDRD Report)

Electrification of the United States has been a major driver of economic growth, powering industrialization, modern manufacturing, and the digital economy. Today, further economic and environmental benefits can be realized by improving the energy efficiency of the technologies we have come to rely on. This project focused on enhancing the energy efficiency of two cornerstone technologies of modern society: electronic displays and building climatization. While these two technologies operate in different parts of the electromagnetic spectrum (the visible and infrared, respectively), they share a common potential technological solution: electrically-driven displays that change reflectivity. In this work, we developed the first multipixel multicolor reflective display that achieves multi-colorization with fast-changing structural color. In the course of this demonstration, we quantified the structural changes that occur across different time and length scales and resolved device sealing issues, enabling operation of these devices over months (as opposed to days previously). We furthermore developed two reflectivity changing devices in the infrared and demonstrated how these technologies can be used to reduce climatization demands for both smart window and smart wall technologies. Implementing such a device in a scaled down mock room resulted in 10 degree Celsius change.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Thermodynamics and transport in molten chloride salts and their mixtures

Relationship between thermophysical properties and phonon mean free path. Heat capacity, viscosity, and thermal conductivity in ionic liquids decrease as mean free path decreases and dynamics become less “solid-like” and collect motion diminishes.

Cockrell, C. [Nuclear Futures Institute, Bangor Un↗
DOE OSTI2025

Upcycling Polynorbornene Derivatives into Chemically Recyclable Multiblock Linear and Thermoset Plastics

Synthetic polymers have found widespread use, but their ineffective end-of-life treatment is causing a significant environmental and human health crisis. Here, we demonstrate the upcycling of polynorbornene derivatives (pNBEs) through their deconstruction into distinct oligomeric buildings blocks that can be repolymerized into chemically recyclable pNBEs-like multiblock polymers via dehydrogenative polymerization. The resulting materials exhibit diverse mechanical properties, while integrating high melting temperatures (T m as high as 133 °C). Notably, this method could also enable the selective deconstruction of permanently cross-linked polydicyclopentadiene (pDCPD) thermosets into telechelic-OH functionalized oligomers, overcoming the significant challenges posed by their robust network structure in recycling and degradation. The resulting pDCPD oligomers can subsequently be repolymerized with macrodiols to create multiblock thermosets with tunable mechanical properties, including Young's modulus and tensile elongation. After use, upcycled plastics could be effectively deconstructed back to the oligomers for recovery and repolymerization. Overall, this work establishes an approach that can be utilized to upcycle pNBEs into previously inaccessible multiblock thermosets and thermoplastics with full recyclability, and may be generalizable to a range of polymers to shift their end-of-life waste disposal toward sustainable recovery and reuse.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nickel Sulfide-Nanowire-Filled Carbon Nanotubes as an Efficient Overall Water Splitting Electrocatalyst

Pursuing stable, efficient, and cost-effective nanostructured bifunctional electrocatalysts is crucial for advancing the electrochemical water splitting process and enabling clean hydrogen energy production. In recent years, considerable efforts have focused on developing highly efficient and durable commercial electrocatalysts for the oxygen evolution reaction (OER) and overall water splitting (OWS). This research introduces an OWS electrocatalyst-nickel sulfide-filled carbon nanotubes grown on a carbon cloth substrate (Ni 3 S 2 @CNTs/CC), synthesized via a one-step in-situ process. The synergistic integration of metal sulfide (Ni 3 S 2 ) and carbon nanotubes provides abundant active sites for catalytic reactions, ensuring a robust composite nanostructure with enhanced durability. Furthermore, the electrocatalytic performance for OER and OWS has been significantly improved by a simple acid treatment to the electrocatalysts, which introduces physical and chemical defects, particularly oxygen functional groups (the acid-treated sample is termed as Ni 3 S 2 @CNTs/CC-AT). As OER electrocatalysts, Ni 3 S 2 @CNTs/CC and Ni 3 S 2 @CNTs/CC-AT present overpotentials of 304 and 200 mV, respectively, for achieving a current density of 10 mA/cm 2 in the OER process. Furthermore, for complete water splitting in 1.0 M KOH electrolyte, Ni 3 S 2 @CNTs/CC and Ni 3 S 2 @CNTs/CC-AT exhibit potentials of 1.63 and 1.44 V, respectively, to achieve a current density of 10 mA/cm 2 when employed as both anode and cathode. Moreover, Ni 3 S 2 @CNTs/CC and Ni 3 S 2 @CNTs/CC-AT demonstrate durable nature for 22 and 20 h durability in the OER and OWS processes, respectively, offering a promising alternative to ruthenium- and iridium-based electrocatalysts for electrochemical hydrogen production through water splitting. In conclusion, the in-situ synthesis method and acid treatment strategy described in this research are promising approaches to fabricating high-performance encapsulated carbon-nanotube-based electrocatalysts.

36 MATERIALS SCIENCE↗