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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Controlling interactions between high-frequency phonons and single quantum systems using phononic crystals

The ability to control phonons in solids is key in many fields of quantum science, ranging from quantum information processing to sensing. Phonons often act as a source of noise and decoherence when solid-state quantum systems interact with the phonon bath of their host matrix. In this study, we demonstrate the ability to control the phononic local density of states of the host matrix using phononic crystals and measure its positive impact on single quantum systems. We design and fabricate diamond phononic crystals with features down to around 20 nm, resulting in a high-frequency complete phononic bandgap from 50 to 70 GHz. The engineered local density of states is probed using single silicon-vacancy colour centres embedded in the phononic crystals. We observe an 18-fold reduction in the phonon-induced orbital relaxation rate of the emitters compared to bulk, thereby demonstrating that the phononic crystal suppresses spontaneous single-phonon processes. Furthermore, we show that our approach can efficiently suppress single-phonon-emitter interactions up to 20 K, allowing the investigation of multi-phonon processes in the emitters. Our results represent an important step towards the realization of efficient phonon-emitter interfaces that can be used for quantum acoustodynamics and quantum phononic networks.

quantum information↗
DOE OSTI2024

KLOKKOS: Automated test generation for performance-portable programs

SAND2024-13830O The KLOKKOS project provides a suite of test generation and validation tools to increase maintainability and portability of Kokkos programs. KLOKKOS, a portmanteau of Klee and Kokkos, is developing an automated test generation for performance-portable programs using Clang/low-level virtual machine (LLVM) and formal methods. KLOKKOS is based on several topics in computer science: the development of symbolic and concolic analysis of LLVM and C++ codes, formal semantics and type theory, C++ templates and language features, LLVM compiler infrastructure, and data parallel primitives. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525

SciDAC↗
DOE OSTI2020

Metamaterials for Mechanically Directing Cell Phenotype

Recently, abundant research has begun to reveal how microscale surface topography can influence a wide range of cell phenotypes in vitro, such as cell mobility, cell size and cell viability (Flemming et al. 1999, Nikkhah et al. 2012, Wang et al. 2016). However, while these studies shed some light on cell interactions with 2D surfaces of different length scales, cells in vivo experience their surroundings in 3D. Therefore, investigations into cell interactions with varying 3D microstructures are needed to gain biologically relevant insight into how microarchitecture and feature size influences cell behavior. Understanding this relationship between 3D microstructure and cell behavior will have a huge impact on tissue engineering and mechanobiology. Until now, the ability to fabricate complex 3D microstructures for cell behavior studies has been limited. This study harnessed LLNL’s Projection Micro-Stereolithography (PμSL) capability to probe the effects of micron-scale changes in 3D architecture on cell phenotype. Furthermore, our studies explored the application of external forces—such as cyclic loading and flow-induced shear stress—to cell-seeded 3D microstructures to further examine cell behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Performance Analysis of PIConGPU: Particle-in-Cell on GPUs using NVIDIA’s NSight Systems and NSight Compute

PIConGPU, Particle In Cell on GPUs, is an open source simulations framework for plasma and laser-plasma physics used to develop advanced particle accelerators for radiation therapy of cancer, high energy physics and photon science. While PIConGPU has been optimized for at least 5 years to run well on NVIDIA GPU-based clusters, there has been limited exploration by the development team of potential scalability bottlenecks using recently updated and new tools including NVIDIA’s NVProf tool and the brand-new NVIDIA NSight Suite (Systems and Compute) tools. PIConGPU is a highly optimized application that runs production jobs at scale on a system Oak Ridge Leadership Facility’s (OLCF) Summit supercomputer (using the full machine at 4600 nodes; at 98% of GPU utilization on all ~28000 NVIDIA Volta GPUs). PIConGPU has been selected as one of the the eight applications for OLCF’s coveted Center for Accelerated Application Readiness (CAAR) program aimed at the facility’s Frontier supercomputer (OLCF’s first exascale system to launch in 2021), to partner with our vendors (primary vendors: AMD and Cray/HPE) ensuring that Frontier will be able to perform large-scale science when it opens to users in 2022. To this effect, performance engineers on the PIConGPU team wanted to dive deep into the application to understand at the finest granularity, which portions of the code could be further optimized to exploit the hardware on Summit at it’s maximum potential and also to elucidate which key kernels should be tracked and optimized for the CAAR effort to port this code to Frontier. Any bottlenecks that are observed via performance profiling on Summit are likely to also impact scalability on the Frontier-dev system and the Frontier Early Access (EA) system. Additionally, the engineers wanted to take a closer look at the newest NVIDIA profiling tools which allows us to identify the most useful features on these tools and will provide an opportunity to compare it to new AMD and Cray’s performance analysis tool releases and provide feedback to our vendor partners on what features are most important and mission critical for CAAR efforts. The primary goal of this report is to focus on the evaluation of PIConGPU’s most time-intensive kernels using NVProf and NSight Suite. Three kernels, Current Deposition (also known as Compute Current), Particle Push (Move and Mark), and Shift Particles are known to be some of the most time-consuming kernels in PIConGPU. The Current xi Deposition kernel and Particle Push kernel both set up the particle attributes for running any physics simulation with PIConGPU, so it is crucial to improve the performance of these two kernels. In this report, we measure single GPU metrics for the three kernels, offer high level takeaways from the conducted analysis, and compare the profiling data from NSight Compute to that of NVProf. This analysis was performed using a grid size of 240 x 272 x 224, and 10 time steps with the Mid-November Figure of Merit (FOM) run setup. The Traveling Wave Electron Acceleration (TWEAC) science case used in this run is a representative science case for PIConGPU. This execution can also be used for baseline analysis on AMD MI50/ MI60 systems. As of the time of writing, the PIConGPU application has limited use for features of NSight Systems, so this report will mainly focus on insights garnered from NSight Compute. For this analysis, we run the “full” metric set available in NSight Compute version 2020.1.2 and use NSight Systems version 2020.3.1 to generate the application timeline.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Deuteron-Deuteron Elastic and Three and Four-Body Breakup Scattering Using the Faddeev-Yakubovskii Equations

The deuteron-deuteron elastic and three and four-body breakup scattering cross section have been calculated using the Faddeev-Yakubovskii (FY) chain-of-partition momentum-space equations. In this calculation the initial two-cluster potential is split into separable and non-separable components, and the effective potential is reduced to elastic two-body and three and four-body breakup open-channels and a closed-channel many-body contribution. The closed-channel contribution is determined by minimizing a variational bound. The Coulomb interaction was included by expanding the initial and final Coulomb states in a Coulomb-Sturmian basis. The three sets of chain-of-partition integral equations were solved for the elastic and three and four-body breakup scattering amplitudes. The calculations were performed for the S = 2 spin/L = 0 angular-momentum state. The elastic and double-breakup calculations were performed for energies up to E = 5.48 MeV, while the single-breakup calculations were performed for energies up to E = 4.17 MeV. In the case of elastic scattering, the calculated scattering length of 5 a dd = 7.8 ± 0.3 fm is in good agreement with a FY cluster reduction calculation. The calculated phase shift is smaller than that predicted by the resonating group model and this difference is believed to be due to the differences in the potential and calculation methods. The breakup cross sections were calculated as a function of initial deuteron momentum and fragmented-deuteron momentum. Here, the d+d → d+n+p cross sections were compared with neutron yield measurements and, while the measurements also included the L > 0 components, the general features were consistent. Estimates of the calculational uncertainties/bias are provided.

42 ENGINEERING↗
DOE OSTI2021

Fracture Mechanics—Theory, Modeling and Applications

The field of fracture mechanics was developed during the throes of World War II, and since then, it has been a very active area of research. This is a very energetic and vibrant field because fracture processes are relevant for a vast range of engineering applications spanning different temporal and length scales. Depending on the application, material fracture and fragmentation may be either a desirable feature (for example, for the purpose of hydraulic fracturing operations), or something that is to be avoided at all costs (for example, in key components of mechanical systems). In some other instances, fractures are already present and must be accommodated through novel design (for example, in the case of earthquake ruptures occurring in the Earth’s crust). Because of this wide spectra of motivation, there is a continuous need for the fracture mechanics research community to gain more insight on how fractures are created, evolve, and interact with themselves and with material microstructures. In addition, there are still many remaining questions about how fracture propagation, growth, and interaction impact overall material behavior, and how to develop accurate models to predict this behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Expanding thermite reactions for downhole applications

Methods and apparatus for forming platforms and flow control features in underground wells is described, using modified thermite reactions to form a ceramic plug in place. The reactive package is engineered to expand laterally, filling the well, and may be used to form a ceramic bridge plug, porous ceramic screen sections, or mitigate lost circulation of drilling fluids. These objectives are achieved through the design of the reactive package and through use of carefully chosen reaction additives that control the molten product rheology, solidification temperature, and pore generations and sustainment.

Lowry, William Edward↗
DOE OSTI2024

Assessment and Usage of In-Situ Monitoring Data for American Society of Mechanical Engineers Part Qualification

In-situ monitoring and anomaly detection are important components for qualification of directed energy deposition (DED) additive manufacturing (AM) processes and components. The use of in-situ monitoring requires an understanding of anomalies that can be identified during the process and how those anomalies correlate to mechanical properties of the component post-production. There is also a need to qualify the algorithms and software used to interpret the process signals for DED AM. There is no single process signal that can be used with a single algorithm that will identify all anomalies that will translate to a defect in a process. The process signals are affected by changes in material, location, resolution, acquisition rate, component geometry, and the machine itself. It is observed that multiple process signals are required to identify relevant features that can be correlated to mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Engineered Catalyst Support with Improved Durability at Higher Weight Percentage of Platinum

Proton Exchange Membrane (PEM) fuel cells are a suitable electrochemical power source for heavy duty vehicle (HDV) applications due to their high efficiency and durability. The cathode of the fuel cell uses a higher geometric loading of platinum (∼0.2 to 0.4 mg Pt /cm 2 ) for the electrocatalysis of the kinetically sluggish Oxygen Reduction Reaction (ORR) which requires higher weight percent loading of the metal (∼50%) on the carbon support to decrease the catalyst layer thickness and hence, the reactant transport losses. The conventionally used supports for platinum catalyst, such as the KetjenBlack TM type high surface area carbon (HSC) features limited mesopore area for the dispersion of Pt nanoparticles leading to increased aggregation and poor durability. Here, we show a new class of carbon materials known as the Engineered Catalyst Support (ECS) developed by Pajarito Powder with higher mesopore fraction for the dispersion of higher weight percentage of Pt nanoparticles. ECS materials can disperse up to 50% Pt by weight of the catalyst thereby enabling lower catalyst layer thickness with higher performance retained after durability test. A comprehensive set of physico-chemical and electrochemical studies in membrane electrode assembly (MEA) are reported to understand the performance and durability of Pt/ECS catalysts.

08 HYDROGEN↗
DOE OSTI2021

Physics guided machine learning using simplified theories

Recent applications of machine learning, in particular deep learning, motivate the need to address the generalizability of the statistical inference approaches in physical sciences. In this Letter, we introduce a modular physics guided machine learning framework to improve the accuracy of such data-driven predictive engines. The chief idea in our approach is to augment the knowledge of the simplified theories with the underlying learning process. To emphasize their physical importance, our architecture consists of adding certain features at intermediate layers rather than in the input layer. To demonstrate our approach, we select a canonical airfoil aerodynamic problem with the enhancement of the potential flow theory. We include the features obtained by a panel method that can be computed efficiently for an unseen configuration in our training procedure. By addressing the generalizability concerns, our results suggest that the proposed feature enhancement approach can be effectively used in many scientific machine learning applications, especially for the systems where we can use a theoretical, empirical, or simplified model to guide the learning module.

42 ENGINEERING↗
DOE OSTI2021

Piston Bowl Geometry Effects on Gasoline Compression Ignition in a Heavy-Duty Diesel Engine

A design optimization campaign was conducted to search for improved combustion profiles that enhance gasoline compression ignition in a heavy-duty diesel engine with a geometric compression ratio of 17.3. A large-scale design of experiments approach was used for the optimization, employing three-dimensional computational fluid dynamics simulations. The main parameters explored include geometric features, injector specifications, and swirl motion. Both stepped-lip and re-entrant bowls were included in order to assess their respective performance implications. A total of 256 design candidates were prepared using the software package CAESES for automated and simultaneous geometry generation and combustion recipe perturbation. The design optimization was conducted for three engine loads representing light to medium load conditions. The design candidates were evaluated for fuel efficiency, emissions, fuel-air mixing, and global combustion behavior. Simulation results showed that the optimum designs were all stepped-lip bowls, due to improvements in fuel-air mixing, as well as reduced heat loss and emissions formation. Improvements in indicated specific fuel consumption of up to 3.2% were achieved while meeting engine-out NOx emission targets of 1-1.5 g/kW center dot h. Re-entrant bowls performed worse compared to the baseline design, and significant performance variations occurred across the load points. Specifically, the re-entrant bowls were on par with the stepped-lip bowls under light load conditions, but significant deteriorations occurred under higher load conditions. As a final task, selected optimized designs were then evaluated under full-load conditions.

CFD↗
DOE OSTI2021

Initial framework for engineering-scale statistical creep-fatigue modeling

This report describes the integration of new solid and interface-cohesive mechanics systems into MOOSE. The purpose of these new systems is to support the ability of MOOSE to run full-field crystal plasticity finite element method simulations of key material processes in high temperature metallic materials. These simulations could be used to help accurately predict the performance of key high temperature structural materials in future advanced nuclear reactor components. Previous work implemented preliminary versions of many of these systems in MOOSE Apps. The current work reports on their integration into the main MOOSE tensor mechanics module along with associated improvements to the basic formulations and numerical implementations. Finally, the report provides an example of the full-field crystal plasticity simulations now possible in MOOSE, including examples of realistic geometries requiring millions of degrees of freedom to resolve the microstructural features and macroscale geometry.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Engineered Barrier System Research Activities at LBNL (FY2020 Progress Report)

The design of a radioactive waste repository typically involves a multi-barrier system, including the natural barrier system (NBS), i.e., the host rock and its surrounding subsurface environment, and an engineered barrier system (EBS). The EBS is to be constructed from the man-made, engineered materials placed within a repository. The repository includes the waste form, waste canisters, buffer materials, backfill, and seals. The most common buffer material for EBS is compacted bentonite, which features low permeability and high retardation of radionuclides. Extensive studies concerning the behavior of bentonite backfill in crystalline and argillite/shale geologic environments for nuclear waste disposal have been conducted by means of laboratory experiments, numerical modeling, and large-scale in situ tests in Underground Research Laboratories (URLs) in Switzerland, France, Belgium, and Japan. This report includes the results of LBNL’s research activities conducted according to the objectives and scope of the work packages “SF-20LB01030802 Engineered Barrier System R&D - LBNL” and “SF-20LB01030806 Engineered Barrier System International Collaborations - LBNL” of the Spent Fuel and Waste Science and Technology (SFWST) (formerly called Used Fuel Disposal) Campaign of the Department of Energy’s (DOE) Office of Nuclear Energy. LBNL research studies included laboratory scale tests and modeling of the evolution of the EBS bentonite and associated coupled processes, and impacts of high temperature on parameters and processes relevant to the performance of crystalline and argillite repositories, including the evaluation of the technical basis for applying the maximum allowable temperature. The results of these studies are being addressing the technical elements necessary to evaluate the EBS design concepts. Emphasis is on the study of thermal, mechanical, and chemical processes that influence the performance of EBS, and the development of modeling capability for reliable assessment of these processes, and ultimately supporting the development of the GDSA model with detailed coupled THMC process models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Harnessing Aromatic‐Histidine Interactions through Synergistic Backbone Extension and Side Chain Modification

Abstract Peptide engineering efforts have delivered drugs for diverse human diseases. Side chain alteration is among the most common approaches to designing new peptides for specific applications. The peptide backbone can be modified as well, but this strategy has received relatively little attention. Here we show that new and favorable contacts between a His side chain on a target protein and an aromatic side chain on a synthetic peptide ligand can be engineered by rational and coordinated side chain modification and backbone extension. Side chain modification alone was unsuccessful. Binding measurements, high‐resolution structural studies and pharmacological outcomes all support the synergy between backbone and side chain modification in engineered ligands of the parathyroid hormone receptor‐1, which is targeted by osteoporosis drugs. These results should motivate other structure‐based designs featuring coordinated side chain modification and backbone extension to enhance the engagement of peptide ligands with target proteins.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Harnessing Aromatic‐Histidine Interactions through Synergistic Backbone Extension and Side Chain Modification

Abstract Peptide engineering efforts have delivered drugs for diverse human diseases. Side chain alteration is among the most common approaches to designing new peptides for specific applications. The peptide backbone can be modified as well, but this strategy has received relatively little attention. Here we show that new and favorable contacts between a His side chain on a target protein and an aromatic side chain on a synthetic peptide ligand can be engineered by rational and coordinated side chain modification and backbone extension. Side chain modification alone was unsuccessful. Binding measurements, high‐resolution structural studies and pharmacological outcomes all support the synergy between backbone and side chain modification in engineered ligands of the parathyroid hormone receptor‐1, which is targeted by osteoporosis drugs. These results should motivate other structure‐based designs featuring coordinated side chain modification and backbone extension to enhance the engagement of peptide ligands with target proteins.

36 MATERIALS SCIENCE↗
DOE OSTI2021

ECNet is an evolutionary context-integrated deep learning framework for protein engineering

Abstract Machine learning has been increasingly used for protein engineering. However, because the general sequence contexts they capture are not specific to the protein being engineered, the accuracy of existing machine learning algorithms is rather limited. Here, we report ECNet (evolutionary context-integrated neural network), a deep-learning algorithm that exploits evolutionary contexts to predict functional fitness for protein engineering. This algorithm integrates local evolutionary context from homologous sequences that explicitly model residue-residue epistasis for the protein of interest with the global evolutionary context that encodes rich semantic and structural features from the enormous protein sequence universe. As such, it enables accurate mapping from sequence to function and provides generalization from low-order mutants to higher-order mutants. We show that ECNet predicts the sequence-function relationship more accurately as compared to existing machine learning algorithms by using ~50 deep mutational scanning and random mutagenesis datasets. Moreover, we used ECNet to guide the engineering of TEM-1 β-lactamase and identified variants with improved ampicillin resistance with high success rates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Gene editing and CRISPR in the clinic: current and future perspectives

Genome editing technologies, particularly those based on zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and CRISPR (clustered regularly interspaced short palindromic repeat DNA sequences)/Cas9 are rapidly progressing into clinical trials. Most clinical use of CRISPR to date has focused on ex vivo gene editing of cells followed by their re-introduction back into the patient. The ex vivo editing approach is highly effective for many disease states, including cancers and sickle cell disease, but ideally genome editing would also be applied to diseases which require cell modification in vivo. However, in vivo use of CRISPR technologies can be confounded by problems such as off-target editing, inefficient or off-target delivery, and stimulation of counterproductive immune responses. Current research addressing these issues may provide new opportunities for use of CRISPR in the clinical space. In this review, we examine the current status and scientific basis of clinical trials featuring ZFNs, TALENs, and CRISPR-based genome editing, the known limitations of CRISPR use in humans, and the rapidly developing CRISPR engineering space that should lay the groundwork for further translation to clinical application.

59 BASIC BIOLOGICAL SCIENCES↗