Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “science & technology”

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 379 records · Page 21

Overview of the Magnetic Resonance Capabilities at INL

The aim of this presentation is to give a broad overview of the magnetic resonance capabilities at Idaho National Laboratory and how the technique is implemented within the different directorates at the lab. Historically, the high-field NMR instrumentation has been used by our Energy & Environment Science and Technology (EES&T) directorate primarily as a characterization tool for synthetic chemistry work, but we have been actively trying to expand the use of the instrumentation into our Nuclear Science and Technology (NS&T) and National and Homeland Security (NHS) directorates. The expanded scope of work has ranged from solid-state characterization of biomass, analysis of electrolyte materials from lithium ion batteries, quantification of extracted critical materials, and measurement of metal-ligand complexes using ligands proposed for use in the nuclear fuel cycle.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

Smart Droplets Stabilized by Designer Surfactants: From Biomimicry to Active Motion to Materials Healing

The science and technologies of emulsion droplets have been a long‐term focus of extensive research endeavors for their practical utility across a breadth of industries, including pharmaceutical products, oil recovery processes, and the food sciences. However, with advances in materials chemistry and characterization tools, new emerging areas are arising with a focus on “smart droplets”. The versatility of emulsion droplets across is based on their ability to partition and create isolated systems with properties defined by the liquid–liquid interface, while preparative routes allow manipulation of droplet size, stability, and encapsulated contents. As described in this article, significant efforts are being devoted to creating new types of droplets by “activating” this interface through the incorporation of reactive structures that trigger droplet response to applied or environmental stimuli (e.g., pH, temperature, salt, or external fields). Moreover, parallels between droplets and live cells inspire efforts to conceive systems that resemble biological motifs or that can produce cellular behaviors that imitate biology (e.g., swarming, communication, or motion). Here, the authors highlight recent advances in smart droplets, with emphasis on organic, polymer, and/or particle surfactants that give rise to inter‐droplet communication (via aggregation, fusion, division, or mass transfer), droplet vehicles for controlled delivery, autonomous droplet motion, and tunable emulsion inversion. Especially emphasized is the macromolecular design to produce reactive and functional surfactants, which are crucial to responsive droplet behavior and their underlying mechanisms. More generally, the exquisite interplay between materials science and biology inspires the review of this research area that provides unique opportunities for insight and inspiration into the capabilities of new droplet designs.

36 MATERIALS SCIENCE↗

Correction to Norm-conserving pseudopotentials and basis sets to explore Lanthanide chemistry in complex environments

Correction was made to the funding and acknowledgment: Funding V.-A.G. was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division. R.R. and M.-T.N. were supported by the Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory (PNNL) CheMSR Agile Investment. PNNL is operated by DE-AC05-76RLO01830. J.-B.L. and J.L. were supported by the National Natural Science Foundation of China (Nos. 21433005, 91645203, and 21590792). D.C.C. was supported by Research and Innovation at the University of Nevada, Reno. ACKNOWLEDGMENTS The research was performed using resources available through Research Computing at Pacific Northwest National Laboratory (PNNL), Tsinghua National Laboratory for Information Science and Technology and the Computational Chemistry Laboratory under Tsinghua Xuetang Talents Program, and University of Nevada, Reno High Performance Computing. J.- B.L. and J.L. acknowledge discussions with Dr. Yang-Gang Wang (Southern University of Science and Technology).

Lu, Jun-Bo↗

A statistical representation of bond coating oxidation under environmental barrier coatings

Environmental barrier coatings (EBCs) protect SiC-based ceramic matrix composites (CMCs) in turbine hot sections from high-temperature volatilization in combustion gases. The formation of a SiO 2 thermally grown oxide (TGO) is expected under the EBC after long-term operation. The oxidation resistance of the EBC is understood as a life-limiting factor for the CMC, and this work predicts long-term oxidation behavior under EBCs through a simple statistical approach. Specimens were exposed to 1350°C isothermal conditions for 100-h thermal cycles in flowing steam for up to 1000 h. The EBC morphology, SiO 2 thickness, and SiO 2 cracking behavior were assessed. Using thousands of SiO 2 thickness measurements across many millimeters of the interface, a realistic representation of the entire TGO was captured via a lognormal distribution. The lognormal fit parameters were extrapolated out to 25 000 h to assess the degree of SiO 2 growth, the spread of SiO 2 thicknesses related to the rough oxidizing interface, and percentages of the intermediate bond coating consumed. In conclusion, local interfacial defects from the coating deposition process are identified as local failure points for EBC—CMC systems.

SiO 2↗

B‐Staging and Crosslinking of Polycarbosilane at Room Temperature: Cure Mechanism and Properties

The viscosity of polycarbosilane (PCS) polymers is not advantageous for free forming. Various fillers and heat are used to obtain a formable paste. Due to the low yield stress, structures and preforms tend to slump or resin will flow out, especially during the curing of the polymer. B-staging of PCS allows for a more stable structure from room temperature until the full cure of the allyl groups occurs with heat. Additionally, hydrosilation is an effective means of crosslinking at room temperature and controlling viscosity. A network structure was formed in SMP-10 using silane and a vinyl-based crosslinker to bridge each polymer chain. Pt addition catalysts were added to enhance the increase in viscosity to make a lightly crosslinked gel to aid in thickening and forming and to improve the ceramic yield at 1000°C. In conclusion, this enables several options for controlling rheology and improving the properties of preceramic polymers to avoid slumping during curing.

inorganic polymers↗

Transferable predictions of energetic and structural properties for refractory solid solution alloys across chemical compositions

We present a data-efficient approach to train graph neural networks (GNNs) on density functional theory (DFT) data for accurate and transferable predictions of energetic and structural properties of refractory solid solution alloys in the niobium-tantalum-vanadium (Nb-Ta-V) chemical space. We start by training the GNN model only on DFT data that describes refractory binary alloys niobium-tantalum (Nb-Ta), niobium-vanadium (Nb-V), and tantalum-vanadium (Ta-V) to predict formation enthalpy and root mean squared displacement. Once trained, the GNN predictions are tested on DFT data describing refractory ternary alloys Nb-Ta-V. While, unsurprisingly, direct transferability from binary to ternary is not sufficiently accurate, augmenting the training with only 1% of the available ternary data (uniformly distributed across the entire range of chemical compositions) improves significantly the quality of the GNN predictions. For comparison, we assess the transferability in the opposite direction by training GNN models on ternary Nb-Ta-V data and making predictions on binaries Nb-Ta, Nb-V, and Ta-V, which exhibits notably higher predictive errors. The proposed methodology, which favors transferability from lower-component to higher-component alloys, offers an efficient path towards avoiding the curse of dimensionality incurred when collecting DFT data for discovery and design of multi-component disordered alloys.

Density functional theory calculations↗

November 2022 NS&T Highlights

These are the highlights for the Nuclear Science and Technology organization for the month of November.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Lawrence Livermore National Laboratory (LLNL) Laboratory Directed Research and Development (LDRD) Annual Report (FY 2023)

As Lawrence Livermore National Laboratory’s most significant resource for supporting internally directed research and development, the LDRD Program provides investments in cutting-edge science and technology that allow the Laboratory to attract and retain the world’s most talented scientists and engineers and enables them to expand the frontiers of knowledge and anticipate emerging national security challenges. In this annual report, we summarize how Lawrence Livermore National Laboratory (LLNL) uses LDRD investments to advance our knowledge in strategic science and technology domains, develop our world-class workforce, and foster innovation in key programmatic areas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Roadmap for Quantum Interconnects

Created by Q-NEXT, a U.S. Department of Energy (DOE) National Quantum Information Science Research Center, this document is a roadmap for quantum interconnects research and its impact for quantum information science and technology. It is the outcome of the collective work of a large team of Q-NEXT members and participants from academia, industry and DOE national laboratories. The roadmap addresses the role of quantum interconnects in three emerging areas of quantum information: computing, communication and sensing. It reviews the materials, components and systems used for these purposes; summarizes relevant scientific questions and issues; and addresses the most pressing research needs. The document then distills these considerations into recommendations for strategic science and technology research imperatives for the next decade. In addition to informing Q-NEXT’s internal activities, the roadmap has also been created with a broader objective of developing a guide for key issues and research needed over the next decade for the worldwide scientific and engineering community interested in quantum information.

42 ENGINEERING↗

An on-chip phased array for non-classical light

Abstract Quantum science and technology can offer fundamental enhancements in sensing, communications and computing. The expansion from wired to wireless links is an exciting prospect for quantum technologies. For classical technologies, the advent of phased arrays enabled directional and adaptive wireless links by manipulating electromagnetic waves over free space. Here we demonstrate a phased array system on a chip that can receive, image and manipulate non-classical light over free space. We use an integrated photonic-electronic system with more than 1000 functional components on-chip to detect squeezed light. By integrating an array of 32 sub-wavelength engineered metamaterial antennas, we demonstrate a direct free-space-to-chip interface for reconfigurable quantum links. On the same chip, we implement a large-scale array of quantum-limited coherent receivers that can resolve non-classical signals simultaneously across 32 channels. With coherent readout and manipulation of these signals, we demonstrate 32-pixel imaging and spatially configurable reception of squeezed light over free space. Our work advances wireless quantum technologies that could enable practical applications in quantum communications and sensing.

Science & Technology - Other Topics↗

Accelerating Discovery to Deployment: Argonne's Materials Engineering Research Facility (MERF) and Its Role in Scaling Materials Technologies for Water and Resource Solutions

The U.S. Department of Energy (DOE) national laboratories represent a unique class of government‐owned, contractor‐operated research institutions dedicated to conducting research and development (R&D) related activities that address national priorities, supporting and advancing the DOE mission. They play a vital role in sustaining U.S. innovation capacity, stewarding the nation's technical base, and nurturing science and technologies. In this perspective, we highlight the processing science and scaleup capabilities of the Materials Engineering Research Facility (MERF) at DOE's Argonne National Laboratory to demonstrate how DOE National Laboratories bridge fundamental science and applied technology development to accelerate deployment. Case studies are presented on selective membranes for critical mineral recovery, sensors for per‐ and polyfluoroalkyl substances (PFAS) detection, surface functionalization via atomic layer deposition (ALD) and sequential infiltration synthesis (SIS), and lithium recovery from battery recycling waste streams using a novel electrodialysis process. These examples underscore MERF's role in translating innovative technologies into practical solutions for renewable water and critical resource recovery, which also leverage Argonne's analytical and computational capabilities. This perspective also outlines mechanisms for collaborating with the DOE national laboratories to strengthen partnerships across government, the national laboratories, academia, and industry.

36 MATERIALS SCIENCE↗

MS25: Materials Science-Focused Benchmark Data Set for Machine Learning Interatomic Potentials

Here, we present MS25, a benchmark data set for evaluating machine learning interatomic potentials (MLIPs) across diverse materials-relevant systems including MgO surfaces, liquid water, zeolites, a catalytic Pt surface reaction, high-entropy alloys (HEAs), and disordered Zr-oxides. Five MLIP architectures (MACE, NequIP, Allegro, MTP, and Torch-ANI) are trained and tested, focusing not only on traditional metrics (energies, forces, and stresses) but also explicitly validating derived physical observables such as lattice constants, volumes, and reaction barriers. We find that most models reach comparable accuracy on standard error metrics across the simple systems, although equivariant MLIPs offer 1.5–2× improvements over nonequivariant MLIPs in energy and force error for structurally complex or compositionally disordered environments such as HEAs and Zr–O systems. Our analysis highlights that low errors in energy and force predictions do not guarantee reliable observables, emphasizing the necessity of explicit validation. We demonstrate limitations in cross-framework transferability, as models trained on one zeolite framework (CHA) fail to reliably generalize to predictions of structurally distinct frameworks (e.g., MFI). Size-extensive tests show some dependence on system size for MgO, resulting from forced periodicity. The HEA and Zr–O data sets are identified as challenging tests for future benchmarks and MLIP model architecture developments as they show significant differentiation in error between MLIP architectures and are still relatively difficult at 1000 training images. Moving forward, we recommend that benchmarking efforts shift their focus from marginal accuracy improvements in energy and force errors toward identifying and understanding model failure modes, rigorously assessing transferability, and evaluating how their errors affect observable predictions. For researchers looking to choose an MLIP architecture, we suggest selecting equivariant MLIP architectures if the complexity of the system is a challenge. For simple materials problems, auxiliary features such as integration with molecular dynamics engines, trade-offs between computational data set generation cost vs MLIP inference speed, and framework integration may play a more important decision factor than small differences in error metrics that are unlikely to matter for production-level research.

chemical structure↗

Perspectives on the FESAC transformative enabling capabilities: Priorities, plans, and Status

In early 2017, the Fusion Energy Sciences Advisory Committee (FESAC), an advisory committee to the United States Department of Energy, was charged with identifying transformative enabling capabilities (TECs) “that could promote efficient advance toward fusion energy, building on burning plasma science and technology.” A subcommittee with broad expertise was formed and sought feedback from scientific experts, including experts from outside the fusion community. Three workshops were conducted, and a report was approved by FESAC in 2018 that identified four of the “most promising” TECs: advanced algorithms, high-critical-temperature superconductors, advanced materials and manufacturing, and novel technologies for tritium fuel cycle control. In addition, one “promising” TEC was identified: fast flowing liquid metal plasma-facing components. This paper will give details on the promising TECs and an overview on considerations of these TECs in the United States since the publication of the report.

Lumsdaine, Arnold↗

Twentieth Exotic Beam Summer School (EBSS2023)

The study of unstable nuclei with unusual ratios of protons to neutrons is one of the frontiers of science. Investigating these rare isotopes is critical for understanding the synthesis of the chemical elements in stellar explosions as well as the fundamental nature of the nuclear forces that bind atomic nuclei together. Scientific progress in this field is driven by the development of exotic beams in present and next-generation rare-isotope beam facilities including the Facility for Rare Isotope Beams (FRIB). Nuclear physics is a broad discipline, influencing our knowledge on subjects as diverse as weakly-bound nuclei, many-body quantum theory, the super heavy elements, and the inner structure of neutron stars. Applications based on nuclear science and technologies include medical diagnostics and therapies, materials science, and national security. The major goal achieved in this project was to hold Exotic Beam Summer School 2023 (EBSS2023), the twentieth installment of EBSS series, July 9-15, 2023 at the Facility for Rare Isotope Beams on the campus of Michigan State University to educate and train the next generation of scientists that will drive research with rare-isotope beams. FRIB became operational in 2022 and is now providing beams of exotic nuclei that will ramp up to unmatched intensities, exceeding what is available today by orders of magnitude. Beams available at FRIB are facilitating a wide variety of studies in nuclear structure, astrophysics, fundamental symmetries and societal applications. There is a large community of scientists interested in working with rare isotope beams; for example, the FRIB User Organization currently has over 1,700 members. In order to maximize the scientific output of FRIB, there must be a workforce continuously trained in both the physics of exotic beams and in the practical techniques of carrying out an experiment. This summer school series is designed to specifically address this need - to ensure that new generations of scientists from a broad range of institutions and backgrounds is trained, motivated, and equipped to push the field forward to new and important breakthroughs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Modeling the use of mobile modular gas samplers in near-field detection

The Wireless Independent Noble Gas Sampler (WINGS) is a mobile, modular gas sampling system designed for use in low infrastructure environments. In the case of a suspected underground nuclear explosion (UNE), WINGS units could be deployed to detect noble gases emanating from the suspected explosion site or identify gases originating from another source entering the local area from offsite. In conclusion, this work uses the atmospheric transport modeling tool inline WRF-HYSPLIT to test the effectiveness of WINGS units around a suspected UNE site as a function of sampler density and distance from the emission point of gases from a UNE.

Air sampling↗

Cryogenic tracer irradiation facility at the university of Texas at Austin

We report on a cryogenic gas irradiation facility in the 1.1 MW TRIGA reactor at The University of Texas at Austin. The system was designed to produce radioactive xenon and argon for environmental studies, and it can be applied to produce other gaseous radiotracers. The system design includes modeling accident scenarios to ensure operation does not risk damage to the reactor and minimizes risk of release of radioactive material. In conclusion, the SCALE code was used to model a 30-day irradiation of one liter of Xe-126 and the predicted activity is 0.9 Ci of Xe-127 at irradiation end.

Ar-37↗

In-service corrosion and grain boundary oxidation in neutron-irradiated 316 stainless steel baffle-former bolts

Reactor core internal components such as baffle-former bolts (BFBs) are subjected to significant mechanical stress, corrosive environment, and neutron irradiation from the reactor core during the plant operation. Over the long operation period, these conditions lead to potential degradation and of the bolts. In this work, characterization was performed on the oxidized surface of stainless steel BFBs harvested from a commercial pressurized water reactor (PWR) after 40 years of operation. The analysis shows that a complex multilayered surface oxide with six identified layers formed that is different from 2-layer structure commonly observed in model experiments. The oxide varies by composition – predominantly Fe, Cr, and Ni, grain size, and phase, and has features resembling both unirradiated and radiation/ corrosion experiments likely due to the low radiation flux compared to ion-irradiation or the test reactor radiation. In addition, grain boundary oxidative attack featured a pathway for Fe and other elements to move from the metal matrix to the outermost oxide. In conclusion, the results help assess PWR lifetime extension, put into context previous experimental studies, and provide input for designing experiments combining radiation and corrosion effects.

Baffle-former bolt↗

A visco-plastic constitutive model for accurate densification and shape predictions in powder metallurgy hot isostatic pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that produces near net shape parts with high material utilization and uniform microstructures. Despite being used frequently to produce small-scale components, the application of PM-HIP to large-scale components is limited due to inadequate understanding of its complex mechanisms that cause unpredictable post-HIP shape distortions. A computational model can provide necessary information about the intermediate and final stages of the HIP process that can help understand it better and make accurate predictions. Generally, two types of computational models are employed for PM-HIP of metal powders, namely, plastic and visco-plastic models. Between these, the plastic model is preferred due to its cheaper calibration approach requiring less experimental data. However, the plastic model sometimes produces incorrect predictions when slight variations of the HIP conditions are encountered in practical situations. Therefore, this work presents a visco-plastic model that addresses these limitations of the plastic model. A novel modified calibration approach is employed for the visco-plastic model that utilizes less experimental data than existing approaches. With the new approach, the data requirement is same for both plastic and visco-plastic models. This also enables a quantitative comparison of plastic and visco-plastic models, which have been only qualitatively compared in the past. When calibrated with the same experimental data, both the models are found to produce similar results. In conclusion, the calibrated visco-plastic model is applied to several complex geometries, and the predictions are found to be in good agreement with experimental observations.

Hot isostatic pressing↗