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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quantum‐Classical Simulation of Quantum Field Theory by Quantum Circuit Learning

Abstract Quantum circuit learning is employed to simulate quantum field theories (QFTs). Typically, when simulating QFTs with quantum computers, significant challenges are encountered due to the technical limitations of quantum devices when implementing the Hamiltonian using Pauli spin matrices. To address this challenge, quantum circuit learning is leveraged, employing a compact configuration of qubits and low‐depth quantum circuits to predict real‐time dynamics in quantum field theories. The key advantage of this approach is that a single‐qubit measurement can accurately forecast various physical parameters, including fully‐connected operators. To demonstrate the effectiveness of this method, it is used to predict quench dynamics, chiral dynamics and jet production in a 1+1‐dimensional model of quantum electrodynamics. It is found that our predictions closely align with the results of rigorous classical calculations, exhibiting a high degree of accuracy. This hybrid quantum‐classical approach illustrates the feasibility of efficiently simulating large‐scale QFTs on cutting‐edge quantum devices.

Ikeda, Kazuki [Department of Physics University of↗
DOE OSTI2020

A comparative experimental study of the hygroscopic and mechanical behaviors of electrospun nanofiber membranes and solution–cast films of polybenzimidazole

This article reports a comparative experimental study of the hygroscopic and mechanical behaviors of electrospun polybenzimidazole (PBI) nanofiber membranes and solution-cast PBI films. As-electrospun nonwoven PBI nanofiber mats (with the nanofiber diameter of ~250 nm) were heat-pressed under controlled temperature, pressure and duration for the study; lab-made solution-cast PBI films and commercially available PBI films (the PBI Performance Product Inc., Charlotte, NC) were used as the control samples. Thermogravimetric and microtensile tests were utilized to characterize the hygroscopic (moisture absorption) and mechanical properties of the PBI nanofiber membranes at varying heat-pressing conditions, which were further compared to those of solution-cast PBI films. Experimental results indicated that the PBI nanofiber membranes carried slightly higher thermal stability and less hygroscopic properties than those of solution-cast PBI films. In addition, heat-pressing conditions significantly influenced the mechanical properties of the resulting PBI nanofiber membranes. The stiffness and tensile strength increase with increasing either the heat-pressing pressure or duration, and relevant mechanisms were explored. Here, the present study provides a rational understanding of the hygroscopic and mechanical behaviors of electrospun PBI nanofiber membranes and solution-cast PBI films that are beneficial to their reliable cutting-edge applications in high-temperature filtration, polymer electrolyte membranes (PEMs), etc.

25 ENERGY STORAGE↗
DOE OSTI2024

Probing Basal and Prismatic Planes of Graphitic Materials for Metal Single Atom and Subnanometer Cluster Stabilization

Abstract Supported metal single atom catalysis is a dynamic research area in catalysis science combining the advantages of homogeneous and heterogeneous catalysis. Understanding the interactions between metal single atoms and the support constitutes a challenge facing the development of such catalysts, since these interactions are essential in optimizing the catalytic performance. For conventional carbon supports, two types of surfaces can contribute to single atom stabilization: the basal planes and the prismatic surface; both of which can be decorated by defects and surface oxygen groups. To date, most studies on carbon‐supported single atom catalysts focused on nitrogen‐doped carbons, which, unlike classic carbon materials, have a fairly well‐defined chemical environment. Herein we report the synthesis, characterization and modeling of rhodium single atom catalysts supported on carbon materials presenting distinct concentrations of surface oxygen groups and basal/prismatic surface area. The influence of these parameters on the speciation of the Rh species, their coordination and ultimately on their catalytic performance in hydrogenation and hydroformylation reactions is analyzed. The results obtained show that catalysis itself is an interesting tool for the fine characterization of these materials, for which the detection of small quantities of metal clusters remains a challenge, even when combining several cutting‐edge analytical methods.

Vidal, Mathieu↗
DOE OSTI2022

Hacking Limnology Workshop and DSOS22: Creating a Community of Practice for the Nexus of Data Science, Open Science, and the Aquatic Sciences

The 2nd Aquatic Ecosystem Modeling-Junior (AEMON-J) Hacking Limnology Workshop and 3rd Virtual Summit: Incorporating Data Science and Open Science in the Aquatic Sciences (DSOS) took place on 25–29 July 2022. These virtual events were developed to bring together researchers from diverse backgrounds to share developments in data-intensive research in the aquatic sciences and train participants in cutting-edge data analysis methods related to remote sensing, data pipelines, and modeling of aquatic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The United States Department of Energy and National Institutes of Health Collaboration: Medical Care Advances via Discovery in Physical Sciences

Over several months, representatives from the U.S. Department of Energy (DOE) Office of Science and National Institutes of Health (NIH) had a number of meetings that lead to the conclusion that innovations in the Nation's health care could be realized by more directed interactions between NIH and DOE. It became clear that the expertise amassed and instrumentation advances developed at the DOE physical science laboratories to enable cutting-edge research in particle physics could also feed innovation in medical healthcare. To meet their scientific mission, the DOE laboratories created advances in such technologies as particle beam generation, radioisotope production, high-energy particle detection and imaging, superconducting particle accelerators, superconducting magnets, cryogenics, high-speed electronics, artificial intelligence, and big data. To move forward, NIH and DOE initiated the process of convening a joint work- shop which occurred on July 12th and 13th, 2021. Here, this Special Report presents a summary of the findings of the collaborative workshop and introduces the goals of the next one.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

The melt memory effects in polymer crystallization

This paper presents a systematic review of the literature on the melt memory effects observed in polymers, an area that has engendered considerable debate for over 50 years. Recent advances in experimental techniques have provided fresh insights into how a polymer's thermal history influences its recrystallization behavior. It has been observed that given other conditions unchanged, the crystallization temperature during recrystallization decreases with an increase in the melt temperature T s above the melting point T m until a critical melt temperature is attained. This phenomenon also extends to the half-time of crystallization and the secondary structures, such as lamellar thickness, of semi-crystalline polymers. Despite these findings, a comprehensive constitutive model that encapsulates polymer melt memory effects remains elusive. Cutting-edge instrumentation, including in situ small and wide-angle X-ray scattering, temperature-controlled Fourier transform infrared spectroscopy, and flash differential scanning calorimetry, have posed significant challenges to the traditional nucleation and growth models established in the 1970s. These models are foundational to our understanding of polymer crystallization, which is an integral part of polymer processing and production. In this review, the historical contours of this discourse are traced, with an examination of both the recent experimental breakthroughs and theoretical advancements pertinent to polymer melt memory effects. In conclusion, this paper delves into the prevailing theories of polymer nucleation and crystallization and engages with theoretical discussions and numerical simulations that attempt to elucidate and rationalize these melt memory phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optimizing Microenvironment of Asymmetric N,S-Coordinated Single-Atom Fe via Axial Fifth Coordination toward Efficient Oxygen Electroreduction

We report single-atom catalysts (SACs) are attractive candidates for oxygen reduction reaction (ORR). The catalytic performances of SACs are mainly determined by the surrounding microenvironment of single metal sites. Microenvironment engineering of SACs and understanding of the structure–activity relation-ship is critical, which remains challenging. Herein, a self-sacrificing strategy is developed to synthesize asymmetric N,S-coordinated single-atom Fe with axial fifth hydroxy (OH) coordination (Fe-N 3 S 1 OH) embedded in N,S codoped porous carbon nanospheres (Fe-N/S-C). Such unique penta-coordination microenvironment is determined by cutting-edge techonologies aiding of systematic simulations. The as-obtained Fe-;N/S-C exhibits superior catalytic ORR activity, and showcases a half-wave potential of 0.882 V surpassing the benchmark Pt/C. Moreover, theoretical calculations confirmed the axial OH in Fe-N 3 S 1 OH can optimize 3d orbitals of Fe center to strengthen O 2 adsorption and enhance O 2 activation on Fe site, thus reducing the ORR barrier and accelerating ORR dynamics. Furthermore, Fe-N/S-C containing H 2 -O 2 fuel cell performs a high peak power density of 512 mW cm -2 , and Fe-N/S-C based Zn-air batteries show the peak power density of 203 and 49 mW cm -2 in liquid and flexible all-solid-state configurations, respectively. This study offers a new platform for fundamentally understand the axial fifth coordination in asymmetrical planar single-atom metal sites for electrocatalysis.

microenvironment↗
DOE OSTI2024

A Difluoro‐Methoxylated Ending‐Group Asymmetric Small Molecule Acceptor Lead Efficient Binary Organic Photovoltaic Blend

Abstract Developing a new end group for synthesizing asymmetric small molecule acceptors (SMAs) is crucial for achieving high‐performance organic photovoltaics (OPVs). Herein, an asymmetric small molecule acceptor, BTP‐BO‐4FO, featuring a new difluoro‐methoxylated end‐group is reported. Compared to its symmetric counterpart L8‐BO, BTP‐BO‐4FO exhibits an upshifted energy level, larger dipole moment, and more sequential crystallinity. By adopting two representative and widely available solvent additives (1‐chloronaphthalene (CN) and 1,8‐diiodooctane (DIO)), the device based on PM6:BTP‐BO‐4FO (CN) photovoltaic blend demonstrates a power conversion efficiency (PCE) of 18.62% with an excellent open‐circuit voltage (V OC ) of 0.933 V, which surpasses the optimal result of L8‐BO. The PCE of 18.62% realizes the best efficiencies for binary OPVs based on SMAs with asymmetric end groups. A series of investigations reveal that optimized PM6:BTP‐BO‐4FO film demonstrates similar molecular packing motif and fibrillar phase distribution as PM6:L8‐BO (DIO) does, resulting in comparable recombination dynamics, thus, similar fill factor. Besides, it is found PM6:BTP‐BO‐4FO possesses more efficient charge generation, which yields betterV OC –J SC balance. This study provides a new ending group that enables a cutting‐edge efficiency in asymmetric SMA‐based OPVs, enriching the material library and shed light on further design ideas.

Chemistry↗
DOE OSTI2024

Advanced multimaterial shape optimization methods as applied to advanced manufacturing of wind turbine generators

Abstract Currently, many utility‐scale wind turbine generator original equipment manufacturers are dependent on imported rare earth permanent magnets, which are susceptible to market risks from cost instability. To lower the production costs of these generators and stay competitive in the market, several small wind manufacturers are pursuing continuous improvements to both generator design and manufacturing. However, traditional design and manufacturing methods have yielded marginal improvements in wind power performance. This work presents novel methods to redesign a baseline 15‐kW wind turbine generator with reduced rare‐earth permanent magnets by leveraging cutting‐edge three‐dimensional (3D) printed polymer‐bonded permanent magnets and steel. Symmetric, asymmetric, and multimaterial‐magnet parametrization methods are introduced for shape optimization. We extend the symmetric and asymmetric methods to the back iron in the stator to further investigate the impact and opportunities for performance improvements with lesser active materials. We employ a design‐of‐experiments approach with parametric computer‐aided design for shape generation and evaluate different designs by magneto‐thermal modeling and finite‐element analysis. We use adaptive sampling technique to identify better performing designs with lesser magnet mass, higher efficiency, and lower cogging torque when compared with the baseline generator. Asymmetric pole designs resulted in a magnet mass in the range of 4.77–5.37 kg, which was 27%–35% lighter than the baseline generator, suggesting that a new design freedom exists that can be enabled by advanced manufacturing, such as 3D printing. Shaping the back iron in the stator resulted in material savings in electrical steel of up to 14.62 kg, which was 20% lighter than the baseline stator. We conducted a structural analysis to evaluate an optimized asymmetric rotor design from the point of view of mechanical integrity and air‐gap stiffness. The magnetically optimal shape profile was shown as having a positive impact on the radial stiffness, and an optimal solution was discovered to reduce the structural mass by nearly 30 kg, which was 29% lighter than the baseline.

17 WIND ENERGY↗
DOE OSTI2020

Magnesium Technology 2020

Magnesium and its alloys are being investigated widely for applications that require extraordinarily high strength-to-weight ratio, vibration damping, electromagnetic shielding, reduction in carbon footprint, sustainability improvements, and low toxicity. In the past decade or so, this drive has led to increased adoption of magnesium and its alloys in everyday products and it is no longer regarded as an esoteric material. The overarching goal of its widespread adoption and replacement of conventional materials such as steel and aluminum alloys has been restricted because of the cost of the material, limited sources of primary material, alloying constraints, high chemical reactivity, and challenges associated with its plasticity. Researchers, scientists, engineers, and economists from industry, government agencies and laboratories, and academic institutions alike are actively developing roadmaps for next-generation products and addressing these challenges as quickly as possible through unique and innovative methods. The TMS Magnesium Committee has been actively involved in providing a platform to these entities for disseminating the latest information, developments, and cutting-edge research and development, and showcasing the latest research and development trends related to magnesium and its alloys through the Magnesium Technology Symposium, which takes place every year at the TMS Annual Meeting. This proceedings volume retains the essence of this longstanding tradition. The twenty-first volume in the series, Magnesium Technology 2020, is the proceedings of the Magnesium Technology Symposium held during the 149th TMS Annual Meeting & Exhibition in San Diego, CA, February 23–27, 2020. The volume captures commentaries and papers from 15 different countries. The papers have been categorized systematically based on topics pertaining to magnesium production, casting and solidification, thermomechanical processing, deformation mechanisms, modeling, corrosion, and applications. The symposium began with keynote sessions that featured several distinguished invited speakers from government organizations and academia, who provided their perspectives on the state of the art, goals, and opportunities in magnesium alloy research and development. Dr. Carlos Tomé from Los Alamos National Laboratory, U.S. Department of Energy, discussed 3D characterization of mechanical twins across grain boundaries. This was followed by a talk on hierarchically structured ultrafine-grained magnesium alloys by Dr. Rajiv Mishra from the University of North Texas, USA, who presented an example of using friction stir additive manufacturing for implementing such microstructures at a component level. Dr. Mark Horstemeyer from Liberty University, USA, presented an overview of fatigue modeling to capture the corrosion-fatigue behavior of magnesium alloys. The final talk in this session was presented by Dr. Bin Jiang from Chongqing University, China, who presented a novel extrusion approach for achieving high-strength magnesium alloy plates.

Jordon, J. Brian↗
DOE OSTI2022

Understanding and Leveraging the I/O Patterns of Emerging Machine Learning Analytics

The scientific community is currently experiencing unprecedented amounts of data generated by cutting-edge science facilities. Soon facilities will be producing up to 1 PB/s which will force scientist to use more autonomous techniques to learn from the data. The adoption of machine learning methods, like deep learning techniques, in large-scale workflows comes with a shift in the workflow’s computational and I/O patterns. These changes often include iterative processes and model architecture searches, in which datasets are analyzed multiple times in different formats with different model configurations in order to find accurate, reliable and efficient learning models. This shift in behavior brings changes in I/O patterns at the application level as well at the system level. These changes also bring new challenges for the HPC I/O teams, since these patterns contain more complex I/O workloads. In this paper we discuss the I/O patterns experienced by emerging analytical codes that rely on machine learning algorithms and highlight the challenges in designing efficient I/O transfers for such workflows. We comment on how to leverage the data access patterns in order to fetch in a more efficient way the required input data in the format and order given by the needs of the application and how to optimize the data path between collaborative processes. We will motivate our work and show performance gains with a study case of medical applications.

Gainaru, Ana↗
DOE OSTI2020

KOTO vs. NA62 dark scalar searches

The two kaon factories, KOTO and NA62, are at the cutting edge of the intensity frontier, with an unprecedented numbers of long lived and charged Kaons,~10 13 , being measured and analyzed. These experiments have currently a unique opportunity to search for dark sectors. In this paper, we demonstrate that searches done at KOTO and NA62 are complementary, both probing uncharted territories. We consider two qualitatively different physics cases. In the first, we analyze models of axion-like-particles (ALP) which couple to gluons or electroweak gauge bosons. In the second, we introduce a model based on an approximate strange flavor symmetry that leads to a strong violation of the Grossman-Nir bound. For the first scenario, we design a new search strategy for the KOTO experiment,K L → π 0 a →4γ. Its expected sensitivity on the branching ratio is at the level of 10 -9 . This demonstrates the great potential of KOTO as a discovery machine. In addition, we revisit other bounds on ALPs from Kaon factories, highlighting the main sources of theoretical uncertainty, and collider experiments, and show new projections. For the second scenario, we show that the model may be compatible with the preliminary analysis of the KOTO-data that shows a hint for New Physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

N-jettiness beam functions at N3LO

We present the first complete calculation for the quark and gluon N -jettiness ( $$ {\mathcal{T}}_N $$ T N ) beam functions at next-to-next-to-next-to-leading order (N 3 LO) in perturbative QCD. Our calculation is based on an expansion of the differential Higgs boson and Drell-Yan production cross sections about their collinear limit. This method allows us to employ cutting edge techniques for the computation of cross sections to extract the universal building blocks in question. The class of functions appearing in the matching coefficents for all channels includes iterated integrals with non-rational kernels, thus going beyond the one of harmonic polylogarithms. Our results are a key step in extending the $$ {\mathcal{T}}_N $$ T N subtraction methods to N 3 LO, and to resum $$ {\mathcal{T}}_N $$ T N distributions at N 3 LL' accuracy both for quark as well as for gluon initiated processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Transverse momentum dependent PDFs at N3LO

We compute the quark and gluon transverse momentum dependent parton distribution functions at next-to-next-to-next-to-leading order (N 3 LO) in perturbative QCD. Our calculation is based on an expansion of the differential Drell-Yan and gluon fusion Higgs production cross sections about their collinear limit. This method allows us to employ cutting edge multiloop techniques for the computation of cross sections to extract these universal building blocks of the collinear limit of QCD. The corresponding perturbative matching kernels for all channels are expressed in terms of simple harmonic polylogarithms up to weight five. As a byproduct, we confirm a previous computation of the soft function for transverse momentum factorization at N 3 LO. Our results are the last missing ingredient to extend the q T subtraction methods to N 3 LO and to obtain resummed q T spectra at N 3 LL' accuracy both for gluon as well as for quark initiated processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A Review of Coastal Fog Microphysics During C-FOG

The goal of this paper is to provide an overview the coastal fog microphysical measurements and to evaluate microphysical parameterizations based on the C-FOG (Toward Improving Coastal Fog Prediction) field project. C-FOG is designed to advance understanding of liquid fog formation, development, and dissipation over coastal environments to improve fog predictability and monitoring. The project took place in Eastern Canada (Nova Scotia, NS and Newfoundland, NL) coastlines and open water environments during August-October of 2018 where environmental conditions play an important role for late season’s fog formation. Visibility (Vis), wind speed (Uh), and turbulence along coastlines are the most critical weather- related parameters affecting marine transportation and aviation. In the analysis, microphysical observations are summarized first and then they are, together with 3D wind components, used for fog intensity (visibility) evaluation. Results suggest that detailed microphysical observations collected at the supersites and aboard Research Vessel (RV) Hugh R. Sharp are useful to develop microphysical parameterizations. The fog life cycle and turbulence kinetic energy dissipation rate were strongly related to each other. The magnitude of 3D wind fluctuations was higher during the formation and dissipation stages. An array of cutting-edge instruments used for data collection provided new insight into the variability and intensity of fog (visibility) and microphysics. It is concluded that further improvements in microphysical observations and parameterizations are needed to improve fog predictability of NWP (Numerical Weather Prediction) models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Frictionless knowledge injection for few-shot learning

Cutting-edge machine learning methods often require large volumes of curated training data, precluding their use in national security problems with rare events in massive datasets. We present a method for incorporating abstract knowledge into models tailored for sparse data. A subject matter expert defines salient concepts using data examples, which are encoded in the model’s embedding space. Models are then trained to respect these concepts. This method enables knowledge injection, yielding effective models with limited labeled data and the ability to assess model sensitivity for subject matter expertise across the nonproliferation mission space, as demonstrated with Raman spectra analysis.

Stomps, Jordan [ORNL] (ORCID:0000000178114479)↗
DOE OSTI2025

Uncertainty quantification for nuclear forensics with population analyses

Although neural networks offer cutting-edge predictive power, their deployment in high-consequence nuclear forensic applications is limited, partly because of their black-box nature. Incorporating robust uncertainty quantification methods into the predictive frameworks of neural networks is progress towards their future deployment in such scenarios. This work integrates uncertainty quantification into neural networks for nuclear reactor core-average burnup estimation from simulated environmental samples. We test two regimes (homogeneous and heterogeneous events) on DeepSets and Set Transformer architectures, we find both quantify predictive uncertainty effectively, but Set Transformer excels in partitioning latent events, offering superior predictive power and more informative uncertainty estimates.

Hatton, Conner [ORNL] (ORCID:0009000804970959)↗
DOE OSTI2020

Ad Hoc File Systems for High-Performance Computing

Storage backends of parallel compute clusters are still based mostly on magnetic disks, while newer and faster storage technologies such as flash-based SSDs or non-volatile random access memory (NVRAM) are deployed within compute nodes. Including these new storage technologies into scientific workflows is unfortunately today a mostly manual task, and most scientists therefore do not take advantage of the faster storage media. One approach to systematically include nodelocal SSDs or NVRAMs into scientific workflows is to deploy ad hoc file systems over a set of compute nodes, which serve as temporary storage systems for single applications or longer-running campaigns. This paper presents results from the Dagstuhl Seminar 17202 “Challenges and Opportunities of User-Level File Systems for HPC” and discusses application scenarios as well as design strategies for ad hoc file systems using node-local storage media. The discussion includes open research questions, such as how to couple ad hoc file systems with the batch scheduling environment and how to schedule stage-in and stage-out processes of data between the storage backend and the ad hoc file systems. Also presented are strategies to build ad hoc file systems by using reusable components for networking and how to improve storage device compatibility. Various interfaces and semantics are presented, for example those used by the three ad hoc file systems BeeOND, GekkoFS, and BurstFS. Their presentation covers a range from file systems running in production to cutting-edge research focusing on reaching the performance limits of the underlying devices.

97 MATHEMATICS AND COMPUTING↗