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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dataset of solution-based inorganic materials synthesis procedures extracted from the scientific literature

The development of a materials synthesis route is usually based on heuristics and experience. A possible new approach would be to apply data-driven approaches to learn the patterns of synthesis from past experience and use them to predict the syntheses of novel materials. However, this route is impeded by the lack of a large-scale database of synthesis formulations. In this work, we applied advanced machine learning and natural language processing techniques to construct a dataset of 35,675 solution-based synthesis procedures extracted from the scientific literature. Each procedure contains essential synthesis information including the precursors and target materials, their quantities, and the synthesis actions and corresponding attributes. Every procedure is also augmented with the reaction formula. Through this work, we are making freely available the first large dataset of solution-based inorganic materials synthesis procedures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Physics-informed neural networks for heterogeneous poroelastic media

This study presents a novel physics-informed neural network (PINN) framework for modeling poroelasticity in heterogeneous media with material interfaces. The approach introduces a composite neural network (CoNN) where separate neural networks predict displacement and pressure variables for each material. While sharing identical activation functions, these networks are independently trained for all other parameters. To address challenges posed by heterogeneous material interfaces, the CoNN is integrated with the Interface-PINNs (I-PINNs) framework (Sarma et al., Comput. Methods Appl. Mech. Eng. 429: 117135, 2024), allowing different activation functions across material interfaces. Further, this ensures accurate approximation of discontinuous solution fields and gradients. Performance and accuracy of this combined architecture were evaluated against the conventional PINNs approach, a single neural network (SNN) architecture, and the eXtended PINNs (XPINNs) framework through two one-dimensional benchmark examples with discontinuous material properties. The results show that the proposed CoNN with I-PINNs architecture achieves an RMSE that is two orders of magnitude better than the conventional PINNs approach and is at least 40 times faster than the SNN framework. Compared to XPINNs, the proposed method achieves an RMSE at least one order of magnitude better and is 40% faster.

42 ENGINEERING↗
DOE OSTI2022

Trust and consequences: Role of community science, perceptions, values, and environmental justice in risk communication

Risk communication is often viewed as imparting information and perhaps as a two-way dialogue. Risk communication inadequacies on the part of both “communicator” and “community members” can lead to adverse consequences and amplify environmental justice disparities. The paper suggests a transformational approach where risk communicators must learn to trust community experts and their knowledge base (and act upon it), where risk information imparted by risk communicators addresses what communities are most concerned about (as well as risk from specific chemicals or radionuclides), and where risk information and assessments address underlying issues and disparities, as well as cultural traditions (among others). Providing risk probabilities is no longer sufficient; western science may not be enough, and community and native scientific knowledge is needed. Risk communication (or information transfer) for environmental risks that are ongoing usually applies to low-income, minority communities—people living in dense inner cities, rural communities, Native American communities—or to people living near a risky facility. Communication within this context requires mutual trust, listening and respect, as well as acceptance of indigenous and community knowledge as equally valuable. Examples are given to illustrate a community perspective.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Nuclear data uncertainty propagation and modeling uncertainty impact evaluation in neutronics core simulation

Uncertainty analysis is a critical requirement in reactor simulation as it is used to quantify the reliability of best-estimate calculation. A comprehensive uncertainty analysis should characterize all sources of uncertainties in a computationally-feasible and scientifically-defendable manner. Here we employ a well-established reduced order modeling (ROM) based uncertainty quantification methodology to propagate uncertainties throughout neutronic calculations. ROM relies on recent advances in randomized data mining techniques applied to large data streams. In our proposed implementation, the nuclear data uncertainties are first propagated from multi-group level through lattice physics calculation to generate few-group parameter uncertainties, described using a vector of mean values and a covariance matrix. Employing an ROM-based compression of the covariance matrix, the few-group uncertainties are then propagated through downstream core simulation in a computationally efficient manner. This straightforward approach, albeit efficient as compared to brute force forward and/or adjoint-based methods, often employs a number of assumptions that have been unquestioned in the literature of neutronic uncertainty analysis. This manuscript argues that these assumptions could introduce another source of uncertainty referred to as modeling uncertainties, whose magnitude needs to be quantified in tandem with nuclear data uncertainties. Thus, our primary goal is to explore the interactions between these two uncertainty sources in order to assess whether modeling uncertainties have an impact on parameter uncertainties. To explore this endeavor, the impact of a number of modeling assumptions on core attributes uncertainties is quantified. The study employs a CANDU reactor model, with Serpent and NEWT as lattice physics solvers and NESTLE-C as core simulator. The modeling assumptions investigated include those related with the uncertainty propagation method employed, e.g., deterministic vs. stochastic, the few-group energy structure employed to represent the cross-sections, the resonance treatment in lattice physics calculation, the reference values for the cross-section, and the number of samples employed to render ROM compression. Results indicate that some of the modeling assumptions could have a non-negligible impact on the core responses propagated uncertainties, highlighting the need for a more comprehensive approach to combine parameter and modeling uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Sequence length scaling in vision transformers for scientific images on frontier

Vision Transformers (ViTs) are pivotal for foundational models in scientific imagery, including Earth science applications, due to their capability to process large sequence lengths. While transformers for text have inspired scaling sequence lengths in ViTs, adapting these for ViTs introduces unique challenges. We develop distributed sequence parallelism for ViTs, enabling them to handle up to 1M tokens. Our approach, leveraging DeepSpeed-Ulysses and Long-Sequence-Segmentation with model sharding, is the first to apply sequence parallelism in ViT training, achieving a 94% batch scaling efficiency on 2,048 AMD-MI250X GPUs. Evaluating sequence parallelism in ViTs, particularly in models up to 10B parameters, highlighted substantial bottlenecks. We countered these with hybrid sequence, pipeline, and flash attention strategies, to scale beyond single GPU memory limits. Our method significantly enhances climate modeling accuracy by 20% in temperature predictions, marking the first training of a vision transformer model to convergence with a sequence length of 188K tokens, using full self-attention.

Tsaris, Aristeidis (aris) [ORNL] (ORCID:0000000277↗
DOE OSTI2023

Prevalence of Listeria monocytogenes , Salmonella spp., Shiga toxin-producing Escherichia coli , and Campylobacter spp. in raw milk in the United States between 2000 and 2019: A systematic review and meta-analysis

Raw (unpasteurized) milk is available for sale and direct human consumption within some states in the United States (US); it cannot be sold or distributed in interstate commerce. Raw milk may contain pathogenic microorganisms that, when consumed, may cause illness and sometimes may result in death. No comprehensive review for prevalence and levels of the major bacterial pathogens in raw milk in the US exists. The objective of the present research was to systematically review the scientific literature published from 2000 to 2019 to estimate the prevalence and levels of Listeria monocytogenes, Salmonella spp., Shiga toxin-producing Escherichia coli (STEC), and Campylobacter spp. in raw milk in the US. Peer-reviewed studies were retrieved systematically from PubMed®, Embase®, and Web of ScienceTM. The unique complete nonduplicate references were uploaded into the Health Assessment Work Collaborative (HAWC). Based on the selection criteria, twenty studies were included in the systematic review and meta-analysis. Comprehensive Meta-Analysis (CMA) was used for statistical analyses, specifically, random effects meta-analyses were used to synthesize raw bulk tank milk (BTM) and milk filters (MF) data. Data from studies using culture and non–culture-based detection methods were included. Forest plots generated in CMA (Biostat, Englewood, NJ) were used to visualize the results. The average prevalence (event rate) of L. monocytogenes, Salmonella spp., STEC, and Campylobacter spp. in raw BTM in the US was estimated at 4.3% (95% confidence intervals [CIs], 2.8–6.5%), 3.6% (95% CIs, 2.0–6.2%), 4.3% (95% CIs, 2.4–7.4%), and 6.0% (95% CIs, 3.2–10.9%), respectively. Estimated prevalence was generally larger in MF than in BTM. There was not enough data to perform a meta-analysis for the prevalence or levels of pathogens in raw milk from retail establishments or other milk categories.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Perovskite- and Dye-Sensitized Solar-Cell Device Databases Auto-generated Using ChemDataExtractor

The number of scientific publications reporting cutting-edge third-generation photovoltaic devices is increasing rapidly, owing to the pressing need to develop renewable-energy technologies that address the climate-change crisis. Consequently, the field could benefit from a central repository where photovoltaic-performance metrics, such as the power-conversion efficiency (η) are recorded. We present two automatically generated databases that contain photovoltaic properties and device material data for dye-sensitized solar cells (DSCs) and perovskite solar cells (PSCs), totalling 660,881 data entries representing 57,678 photovoltaic devices. The databases were generated by applying the text-mining toolkit ChemDataExtractor on a corpus of 25,720 articles. A multi-faceted evaluation, incorporating manual and automatic methods, was applied to ensure that the data contained therein were of the highest quality, with precision metrics ranging from 73.1% to 95.8%. The DSC database contains 475,045 entries representing 41,680 devices, and the PSC database contains 185,836 entries representing 15,818 devices. The databases are available in MongoDB and JSON formats, which can be queried in Python, R, Java and MATLAB for data-driven photovoltaic materials discovery.

14 SOLAR ENERGY↗
DOE OSTI2022

F*** workflows: when parts of FAIR are missing

The FAIR principles for scientific data (Findable, Accessible, Interoperable, Reusable) are also relevant to other digital objects such as research software and scientific workflows that operate on scientific data. The FAIR principles can be applied to the data being handled by a scientific workflow as well as the processes, software, and other infrastructure which are necessary to specify and execute a workflow. The FAIR principles were designed as guidelines, rather than rules, that would allow for differences in standards for different communities and for different degrees of compliance. There are many practical considerations which impact the level of FAIR-ness that can actually be achieved, including policies, traditions, and technologies. Because of these considerations, obstacles are often encountered during the workflow lifecycle that trace directly to shortcomings in the implementation of the FAIR principles. Here, we detail some cases, without naming names, in which data and workflows were Findable but otherwise lacking in areas commonly needed and expected by modern FAIR methods, tools, and users. We describe how some of these problems, all of which were overcome successfully, have motivated us to push on systems and approaches for fully FAIR workflows.

Wilkinson, Sean↗
DOE OSTI2022

Environmental and Energy Research at the Texas Center for Advanced Scientific Computing and Modeling (CASCaM)

The funding enabled the creation of the (University of North) Texas Center for Advanced Scientific Computing and Modeling (CASCaM). Due to its success, CASCaM has continued to grow beyond the initial team focused on the biological and environmental research discussed herein, with investments by the University of North Texas in new faculty and researchers who contribute to CASCaM research. CASCaM is now a sustainable effort, with researchers across multiple fields including chemistry, physics, biology, mechanical engineering, materials science, and other fields, with multiple researchers engaged in a broad variety of research, including other DOE projects. Over 20 PI’s and ~100 researchers are engaged in CASCaM research. The overall goal of the research effort was to provide greater understanding about carbon capture, storage, and utilization. As part of this effort, the development of computational methods and identification of novel strategies to support the CO2 and CO studies were necessary. Three primary themes were investigated: carbon dioxide and CO catalysis; protein- and amino acid-based strategies towards carbon dioxide capture, storage, and utilization; and, finally, the methodology improvements for modeling carbon dioxide chemistry

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Benzenesulfonamide Derivatives as Complexants and Extractants for Addressing the Mercury Problem at the Savannah River Site

Mercury (Hg) is a major global pollutant arising from both natural and anthropogenic sources. Its widespread use in medicinal and industrial applications makes it a common chemical exposure and environmental pollutant. It can exist in several forms which include: Metallic mercury (Hg{sup 0}), mercurous (Hg{sub 2}{sup 2+}), mercuric salts (Hg{sup 2+}), and organic mercury (e.g. CH{sub 3}Hg{sup +}), with the latter being the most toxic of all the species. Due to mercury's high toxicity, new approaches towards its detection has received significant attention in the scientific community. Mercury exposure at the Savannah River Site (SRS) has been a recent concern especially with increasing amounts of organic mercury in the saltstone. It originates mainly from its use as an acidic dissolution catalyst of aluminum cladding from target fuels within the uranium and plutonium processing operations [1]. It is present to an amount of about 60 metric tons in the high-level waste (HLW) tanks. Organic Mercury species have been found in low activity waste (LAW) at the site that eventually ends up in the saltstone. Therefore, there is a need for: i) Converting organic mercury to other less toxic forms and ii) Complexation and removal of Hg prior of disposal of LAW in saltstone. Various methods have been developed for selective sensing of mercury in the presence of other toxic metals. These methods include using ligands that can form organo-soluble metal complexes with different optical and spectroscopic properties that can be used for toxic metal sensing. In 2005, our group pioneered an ion-exchange extraction method, in which o-phenylenediamine-derived disulfonamides were used to complex and selectively extract and sense Pb{sup 2+} from aqueous solutions into an organic phase [2,3]. Herein, a disulfonamide and a bis-dansylamide have been shown to extract, complex and sense Hg(II). Ligand 1: The crystal structure of the disulfonamide-Hg complex confirms the complexation of Hg(II) with the ligand. Complexation was corroborated by the {sup 1}H-NMR spectra obtained after contacting solutions of various concentrations of Hg{sup 2+} with 2 mM ligand in chloroform. Distinct resonances are observed at Hg/L ratio of 0.5 that are also observed for the isolated 1:2 complex. In the presence of excess mercury, new resonances, as well as the movement of Et{sub 3}N resonances indicate the formation of a different Hg-sulfonamide-triethylamine complex, presumably having 1:1 Hg:L stoichiometry. The electronic spectra of aqueous phases after extraction show that there was no free ligand absorption at 0.5 eq of Hg, indicating a complete complexation. Complexation was also confirmed by the UV-visible titrations with Hg{sup 2+} at constant ligand concentration. pH-dependent extraction carried out shows that extraction of Hg(II) by ligand 1 was over 90% for most alkaline pHs. Ligand 2: The crystal structure of the Ligand 2 complex formed with Hg(OAc){sub 2} shows a remarkable coordination pattern with 4:2 metal:ligand stoichiometry. The fluorescent bis-dansyl disulfonamide derivative was found to complex and sense HgCl{sub 2} and Hg(OAc){sub 2} by demonstrating fluorescence quenching upon Hg(II) addition in comparison with other metals (Zn(II), Cd(II), Pb(II)). No were observed for Cu(II), Ag(I) and Co(II). We have shown the complexation of Hg(II) by a disulfonamide and a bis-dansyl disulfonamide ligand using several spectroscopic methods. Ligand 1 was able to extract mercury into chloroform and form a complex in the presence of excess mercury by synergistic complexation with triethylamine acting as a co-ligand. X-ray and NMR both confirm a 1:2 HgL{sub 2} stoichiometry. Ligand 2 can be used for sensing of Hg(II) as fluorescence quenching was observed after addition of Hg(II)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

A review of carbon monitoring in wet carbon systems using remote sensing

Carbon monitoring is critical for the reporting and verification of carbon stocks and change. Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and change of carbon stocks within and across various systems. We designate the use of the term wet carbon system to the interconnected wetlands, ocean, river and streams, lakes and ponds, and permafrost, which are carbon-dense and vital conduits for carbon throughout the terrestrial and aquatic sections of the carbon cycle. We reviewed wet carbon monitoring studies that utilize earth observation to improve our knowledge of data gaps, methods, and future research recommendations. To achieve this, we conducted a systematic review collecting 1622 references and screening them with a combination of text matching and a panel of three experts. The search found 496 references, with an additional 78 references added by experts. Our study found considerable variability of the utilization of remote sensing and global wet carbon monitoring progress across the nine systems analyzed. The review highlighted that remote sensing is routinely used to globally map carbon in mangroves and oceans, whereas seagrass, terrestrial wetlands, tidal marshes, rivers, and permafrost would benefit from more accurate and comprehensive global maps of extent. We identified three critical gaps and twelve recommendations to continue progressing wet carbon systems and increase cross system scientific inquiry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Absolute intensity calibration for carbon-edge soft X-ray scattering

Resonant soft X-ray scattering (RSOXS) has become a premier probe to study complex three-dimensional nanostructures in soft matter through combining the robust structural characterization of small-angle scattering with the chemical sensitivity of spectroscopy. This technique borrows many of its analysis methods from alternative small-angle scattering measurements that utilize contrast variation, but thus far RSOXS has been unable to reliably achieve an absolute scattering intensity required for quantitative analysis of domain compositions, volume fraction, or interfacial structure. Here, a novel technique to calibrate RSOXS to an absolute intensity at the carbon absorption edge is introduced. It is shown that the X-ray fluorescence from a thin polymer film can be utilized as an angle-independent scattering standard. Verification of absolute intensity is then accomplished through measuring the Flory–Huggins interaction parameter in a phase-mixed polymer melt. As a result, the necessary steps for users to reproduce this intensity calibration in their own experiments to improve the scientific output from RSOXS measurements are discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Assessment of Modeling and Simulation Technical Gaps in Safety Analysis of High Burnup Accident-Tolerant Fuels

The United States nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor (LWR) nuclear power plants (NPPs), and it can be achieved more economically by using a risk-informed ecosystem, such as that being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program is promoting a wide range of research and development activities to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering second license renewal. The RISA Pathway has two main goals: The deployment of methodologies and technologies that enable better representation of safety margins and the factors that contribute to cost and safety, and; The development of advanced applications that enable cost-effective plant operation. As part of the RISA Pathway, the Enhanced Resilient Plant (ERP) project refers to an NPP where safety is improved by implementing various measures, such as accident-tolerant fuels (ATF), diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, incorporation of augmented or new passive cooling systems, and utilization of advanced battery technologies. The objective of the ERP research is to use novel methods and computational tools to enhance existing reactors’ safety while reducing operational costs. Many U.S. utilities are targeting implementation of ATFs instead of traditional fuel in the near future since ATFs offer benefits in terms of improved performance and cost savings. The robust properties of ATF make it possible to extend the refueling cycle from 18 to 24 months in addition to the opportunity to use less of fuel. Extensive safety assessments are required to support regulatory requirements and obtain the approvals to use ATFs and the ERP project support the industry by developing novel effective methodologies for safety evaluations. In this project, the technical gaps in the modeling and simulation of the high burnup (HBU) ATF were assessed in terms of the fuel cladding behavior during the postulated accident events. The issues were identified in modeling the cladding deformation, the hydrodynamic change due to cladding deformation and the critical heat flux (CHF). The RELAP5-3D cladding deformation model was assessed by multiple verification tests and validation with the instrumented fuel assembly (IFA) experiment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Abbreviated Technical Report: Experimentally Interrogating Detonation Chemistry on Sub-Nanosecond to Nanosecond Timescales

Direct experimental measurement of chemical reactions during high explosive detonation remains challenging. Theory and modeling have long preceded experiment in the fundamental physical and chemical kinetic properties of detonation, and experimentation at the relevant timescales are needed to both validate models and provide fundamental understanding of detonation. In this LDRD-ER project, two approaches, x-ray diffraction and core-level x-ray Raman, were developed and used to further experimental capabilities to address this gap. We further developed dynamic x-ray diffraction to directly detect nanodiamond formation during detonation, providing experimental data towards resolving longstanding controversy in the scientific literature, and although the full kinetics have not yet been fully mapped, diamond diffraction appears on the same timescales as detonation soot formation. In the second research thrust, we have developed core-level x-ray Raman for use with high explosives. This technique provides information analogous to x-ray absorption spectroscopy and electron energy loss spectroscopy, but uses inelastic scattering of hard x-rays that can interrogate chemistry around light elements much deeper into the material. The low cross section and requisite high solid angle collection have hindered its use for ultra-fast spectroscopy. We developed and tested a high-q spectrometer which will substantially increase cross section and signal-to-noise, showing this method will also not dramatically alter, compared to x-ray absorption, the most discriminating spectral features of C, N, and O from various high explosives and expected detonation products. We have also used x-ray Raman combined with OCEAN electronic structure calculations to explore dynamic photodegradation mechanisms in PETN and CL-20 explosives. This provides a pathway towards implementing capability to dynamically explore chemistry at an x-ray free electron laser.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Searches for New Long-Lived Particles and Upgrade to the ATLAS Inner Detector (Final Technical Report)

The search for new fundamental particles is one of the defining goals of the Large Hadron Collider (LHC). The discovery of the Higgs Boson by the ATLAS and CMS collaborations provided the capstone of the Standard Model of particle physics, but outstanding questions remain. Why does the Higgs boson have a mass of 125 GeV when its natural mass would be many orders of magnitude larger? Is there a universal symmetry which unites all three forces described by the Standard Model? Can that symmetry be extended to include gravity? Is dark matter, evidenced by astronomical observations, made of a particle that interacts via Standard Model forces with the rest of matter? Together, these motivations provide compelling arguments that new physical processes await discovery. This project addressed some outstanding questions about the fundamental particles and their interactions with the ATLAS experiment at the Large Hadron Collider. In particular, the project improved the discovery potential for new, long- lived particles produced via electroweak processes in proton-proton collisions and set world-leading limits on their existence for certain values of their potential mass and lifetime. To achieve this, the project developed new data analysis methods, developed new triggers to select events with new long-lived particles during data-taking of the ATLAS experiment, and analyzed the largest proton–proton collision dataset ever produced. The project also supported significant development of the data acquisition software for the upgrade to the ATLAS inner detector, the Inner TracKer (ITk). The upgrade of the ATLAS inner detector is essential to the success of the entire Phase II physics program on ATLAS. Personnel supported by the project provided support for integration, assembly, and testing of the inner two layers of the ITk pixel system during its prototype and pre-production phase. Four PhD students and two post-doctoral scholars were supported by the grant and received invaluable scientific training as part of the research endeavor. The students and postdocs gained essential professional skills in the areas of advanced data analysis techniques, statistical analysis of data and simulation, programming in C++ and Python, hardware and instrumentation development, and presentation and collaboration skills. Additionally, approximately ten undergraduate students supported through other funding sources participated in research activities synergistic with the goals of this project, receiving essential mentorship from the personnel supported by this project.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Scientific frontiers of agrivoltaic cropping systems

Agrivoltaic (AV) systems integrate agriculture with electricity conversion through photovoltaic (PV) modules. Compared with conventional ground-mounted PV systems, AV systems can reduce land-use competition and offer agronomic and economic advantages, such as more stable crop production and additional farm income. However, AV systems can decrease agricultural performance and are typically 20-90% costlier to install than conventional PV systems. Here, in this Review, we analyse the implementation of AV cropping systems to preserve agricultural activities and highlight challenges and barriers. The global electricity potential of AV systems is ~66-385 PWh annually, depending on PV technology and installation density, if deployed in the most suitable areas, without accounting for grid availability. Scaling up has been hindered by crop selection for shading conditions, decreased energy conversion per unit of land area and issues with social acceptance, landscape impact and environmental sustainability. These issues can be addressed by developments such as wavelength-selective PV; system configurations, such as optimizing module spacing to reduce shading; and operational methods, such as optimizing tracking strategies and integrating agricultural infrastructure. Cross-sector policies can support AV systems by addressing the needs of diverse stakeholders over shared land resources. Further development will require collaboration among the design, performance, deployment and systems research communities.

14 SOLAR ENERGY↗
DOE OSTI2023

Metal forming and working of stabilized nanocrystalline Cu-Ta for electrical contacts

The commercialization of nanocrystalline metals and alloys is currently entering a renaissance period. Many of the processing and consolidation challenges that have haunted them are now more fully understood, opening the doors for stabilized nanocrystalline metals to be produced on a bulk scale. While challenges remain, the increased volume at which these materials are being supplied is for the first time allowing for investigations into more traditional methods of metal working, such as extruding, rolling, forming, and forging. Recently, the manufacturing science has been developed to allow nanocrystalline Cu-Ta alloys to progress to this point. This article therefore builds upon the last decade of evolutionary progression within the family of stabilized nanocrystalline Cu-Ta alloys by presenting some of the first findings related to scaled powder synthesis, production of billets, thin sheets, and foils. Here, the mechanical performance and physical properties relevant to forming electrical contacts and pins including, tensile, J-integral fracture toughness, Charpy Impact, bi-axial tension, and conductivity are reported. This introductory investigation into forming such a novel material, provides evidence to these alloys potential at bridging the gap between being a scientific curiosity to that of a real engineering material.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The Influence of Residual Copper Catalyst on the Polymer-to-Ceramic Conversion of a Click-Derived Polycarbosilane

Preceramic polymers (PCPs) are a key class of materials for the preparation of advanced ceramic components. Following conventional polymer processing and subsequent pyrolysis, polymer-derived ceramic (PDC) fibers, monoliths, and composites offer novel engineering opportunities for aerospace applications. Despite the rapidly emerging commercial applications of PDCs, many basic scientific questions remain regarding the structural transformation of the polymer to the final ceramic and how processing variables affect PDC materials properties. PCPs prepared using a mild and scalable copper (Cu) catalyzed azide/alkyne “click” reaction have been demonstrated as a unique class of material that can bind with transition metals, ultimately producing ultrahigh temperature ceramics (UHTCs) upon pyrolysis. Unexpectedly, it was found that the removal of residual Cu catalyst from a model click-derived polycarbosilane PCP significantly reduced the ceramic yield during pyrolysis. Herein, we report the influence of Cu impurities on polycarbosilane-derived SiC ceramics and present a mechanistic understanding of the unintended role of Cu in the polymer-to-ceramic conversion process. Synchrotron-based scattering and spectroscopy methods were implemented to track the evolution of different atomic species and local structures as well as the influence of Cu toward atomic-scale structures in the final ceramics. It was determined that Cu impurities catalyze the formation of silicon carbide through the formation of an intermediate molten copper/copper silicide, ultimately increasing the ceramic yield. Overall, this contribution highlights the need to carefully assess the interplay between the chemistries needed for PCP synthesis and their potential influence on final PDCs following processing.

Ponder, Jr., James F. [Air Force Research Laborato↗