SEARCH · Search NASA

Results for “ACCELERATION TOLERANCE”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10

All sources NASA NTRS DOE OSTI

DOE OSTI2026

Advances in genetic tools for metabolic engineering of non-conventional yeasts

Non-conventional yeasts are emerging as powerful alternatives to Saccharomyces cerevisiae for metabolic engineering, owing to their innate stress tolerance, broad substrate utilization, and distinctive metabolic capabilities. These attributes position them as promising chassis for producing biofuels, pharmaceuticals, and specialty chemicals. This review synthesizes recent advances in genetic toolkits for four such species—Pichia kudriavzevii (Issatchenkia orientalis), Starmerella bombicola, Debaryomyces hansenii, and Pachysolen tannophilus—highlighting progress across plasmid architectures (episomal and integrative), identification of autonomously replicating sequences and centromeric elements, and the development of safe-harbor genomic loci. We summarize promoter and terminator libraries enabling tunable expression, the expansion of auxotrophic and antifungal selection markers with recycling strategies, and the rapid adaptation of CRISPR-based systems (Cas9 and Cas12a) with optimized guide RNA expression, multiplex editing, and approaches that enhance homologous recombination (e.g., KU70/80 disruption). We also review landing-pad platforms for modular, repeated integrations and transposon-based tools (e.g., piggyBac) that facilitate multigene pathway assembly. Collectively, these innovations are accelerating design-build-test-learn cycles and enabling precise, scalable engineering of non-conventional yeasts. Remaining challenges—including limited species-specific episomal systems, variable transformation efficiencies, genome-stability concerns, and alternative codon usage—define clear priorities for future toolkit development. Together, these advances and open needs chart a path toward robust, sustainable biomanufacturing using diverse non-conventional yeast chassis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Electronic descriptors for dislocation deformation behavior and intrinsic ductility in bcc high-entropy alloys

Controlling the balance between strength and damage tolerance in high-entropy alloys (HEAs) is central to their application as structural materials. Materials discovery efforts for HEAs are therefore impeded by an incomplete understanding of the chemical factors governing this balance. Through first-principles calculations, this study explores factors governing intrinsic ductility of a crucial subset of HEAs—those with a body-centered cubic (bcc) crystal structure. Analyses of three sets of bcc HEAs comprising nine different compositions reveal that alloy chemistry profoundly influences screw dislocation core structure, dislocation vibrational properties, and intrinsic ductility parameters derived from unstable stacking fault and surface energies. Key features in the electronic structure are identified that correlate with these properties: the fraction of occupied bonding states and bimodality of the d-orbital density of states. The findings enhance the fundamental understanding of the origins of intrinsic ductility and establish an electronic structure–based framework for computationally accelerated materials discovery and design.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Degradable Biocomposite Thermoplastic Polyurethanes

In this project, the team developed tough and degradable biocomposite thermoplastic polyurethanes (TPUs) by incorporating bacterial spores into TPUs as a biofunctional living filler. The team screened various bacteria and selected the Bacillus subtilis ATCC 6633 strain as the final candidate, primarily due to its genomic availability, sporulation ability and TPU assimilation activity. The heat-shock tolerance of ATCC 6633 spores was further improved through evolutionary engineering via Adaptive Laboratory Evolution (ALE), demonstrating a 17.7-fold enhanced germination efficiency post heat-shock treatment compared to the wild-type strain (WT). The team fabricated biocomposite TPUs by incorporating lyophilized powder of heat-shock tolerized (HST) spores during the hot melt extrusion (HME) of TPU at 135 °C. The baseline TPU used in this project is a commercially available soft-grade TPU (BCF45) manufactured by BASF. Colony forming unit (CFU) assays quantified that WT and HST spores in the TPU matrix retained approximately 20% and 100% survivability, respectively, after HME. Tensile testing demonstrated that the spores behaved as a polymer-reinforcing filler, positively affecting the overall tensile properties of the biocomposite TPU. For example, biocomposite TPU with WT and HST spores (BC TPU WT and BC TPU HST , respectively) exhibited up to 25% and 37% improved toughness, respectively, compared to TPU without spores. BC TPU HST showed remarkably improved disintegration in autoclaved compost (92% mass loss in 5 months), which simulated a microbially poor environment for TPU degradation. When compared to TPU without spores (44% mass loss in 5 months) the acceleration of degradation is marked. Respirometry confirmed that 72% of BC TPU HST was biomineralized into CO2 within 6 months, indicating that spores in the biocomposite TPU were germinated by utilizing nutrients in the autoclaved compost, facilitating TPU degradation at the end of the material's life. The team demonstrated the scale-up of biocomposite TPU fabrication using continuous extrusion and injection molding techniques. Processing conditions optimized in a lab-scale microcompounder were successfully transferred to a continuous extruder with a 30-fold increased throughput. Biocomposite TPUs prepared using these industry-relevant processes showed comparable toughness improvements to samples prepared in the lab-scale extruder. Excitingly, following compounding in the pilot-extruder the composite material could be injection molded, while retaining high spore viability and similar toughness improvements. The team also found that spores in biocomposite TPU served as antioxidants, preventing toughness decay during the recycled extrusion of BC TPU HST . Long-term storage tests over one year showed that the addition of spores had no negative effect on the longevity of the TPU. Furthermore, the team demonstrated the fabrication of spore-bearing biocomposite polymers with other polyesters such as PBAT, PLA, and PCL. We obtained promising preliminary data that showed overall toughness improvements for all polymers with spore addition. Finally, life cycle assessment (LCA) and techno-economic analysis (TEA) were carried out, which indicated minimal additional cost of fabrication. Overall, a tough and degradable biocomposite thermoplastic was successfully developed through this project, with all tasks completed successfully, achieving >100% of the objectives.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Multigene engineering in plants: Technologies, applications, and future prospects

The emerging bioeconomy presents a promising solution to both economic and environmental challenges. Within the bioeconomy, plants serve as a renewable, sustainable, and cost-effective source of foods, fuels, chemicals, and materials. However, traditional breeding and single-gene engineering approaches fall short in addressing complex traits (e.g., drought tolerance, disease resistance, yield, nutrient use efficiency) which are controlled by multiple genes. The complexity of plant biology often necessitates the use of multigene engineering (MGE), which involves simultaneous ectopic expression, up/down-regulation, or editing of multiple genes, to enhance plant traits relevant to the bioeconomy. These genes may be associated with distinct traits or function as components of specific metabolic and regulatory pathways. This review summarizes current technologies for MGE within the synthetic biology-driven Design-Build-Test-Learn (DBTL) framework, detailing its four key stages: Design – gene construct development; Build – DNA assembly and plant transformation; Test – the molecular, biochemical, and physiological characterization of engineered plants; and Learn – computational modeling to refine, multiplex and iterate the process. Despite good progress in the applications of MGE in biofortification, metabolic engineering, and stress resilience, challenges remain in construct stability, coordinated gene expression, and regulatory predictability. We identified optimization paths and future directions to accelerate MGE deployment in sustainable agriculture, with possible societal benefits including reduced production costs, increased yield, and improved food and nutritional security.

AI-aided plant engineering↗

DOE OSTI2026

Total Cost of Ownership Reduction Using Passive Pre-Chamber Ignition in Natural Gas Engines

Spark plug durability is a factor affecting the total cost of ownership (TCO) of spark-ignited natural gas engines, with some heavy-duty platforms requiring plug replacement after only 750 hours of operation. The high ignition energy demand under lean or diluted conditions accelerates electrode wear, shortening plug life and increasing maintenance frequency. This work evaluates passive pre-chamber (PC) ignition operating at lowered spark energies as a strategy to reduce spark energy requirements and extend plug durability, thereby lowering TCO. Experiments were conducted on a medium-duty Cummins 6.7L ISB engine at 1600 RPM and 50% load under varying exhaust gas recirculation (EGR) dilution levels (0–40%). Two passive pre-chambers with 1.1 mm and 1.6 mm nozzle diameters were compared with conventional spark ignition (SI). SI was operated with a fixed coil dwell of 4 ms (~90 mJ), while the PC configuration was tested across 2–4 ms dwell times (~30–90 mJ). Cylinder pressure analysis revealed that PC ignition sustained stable combustion at significantly lower spark energies than SI, with improved combustion stability at ~30 mJ compared with SI at ~90 mJ. The PC system also extended the dilution tolerance beyond that achievable with SI, while delivering up to ~2% higher indicated thermal efficiency and reducing the COV by nearly 90% at 30% EGR. A TCO analysis was conducted to assess the economic benefit of adopting a passive PC system operating at reduced spark energies compared to SI. It was found that adopting a passive PC system could reduce TCO by approximately $11,000 per engine over a five-year operational period, primarily due to fuel savings, extended spark plug life, and reduced maintenance frequency. These projections were weighed against the additional hardware cost of the pre-chamber, yielding a rapid estimated return on investment of ~300 operating hours. Therefore, this work motivates continued research and development of passive PC technology and its commercial adoption in natural gas engines used in transportation applications.

Dhotre, Akash [University of Minnesota]↗

DOE OSTI2020

Microstructure Experiments-Enabled MARMOT Simulations of SiC/SiC-based Accident Tolerant Nuclear Fuel System

We have undertaken an experimental-computational project that addresses a few key technology gaps associated with the use of SiC/SiC composites for light water reactor fuel cladding. Two principal endeavors in this project are to assess the irradiation-induced microstructural changes and swelling in SiC/SiC composites, and to characterize and model the porous oxide surface layer (when exposed to steam) along SiC recession that is detrimental to the clad integrity under accident conditions. The project tasks are: (i) ion irradiation and characterization (University of Tennessee, Knoxville), (ii) mechanical tests and analysis (University of South Carolina), (iii) steam exposure tests (Oak Ridge National Laboratory), (iv) electron microscopy and spectroscopic characterization (NC State University), (v) x-ray microscopy and reconstruction (University of South Carolina and NC State University), (vi) phase field modeling and simulations (NC State University and Idaho National Laboratory). The effects of 10 MeV Au ion irradiation at 350°C on the microstructure evolution in SiC/SiC composites are investigated at doses up to 400 displacements per atom (dpa) at the University of Tennessee, Knoxville. Atomic force microscopy and optical profilometry reveal irradiation induced axial and radial shrinkage of the fibers for doses greater than 10 dpa. Based on detailed electron microscopy characterization, the primary cause of the fiber shrinkage is attributed to irradiation-induced loss of carbon packets. Additionally, the multilayer PyC interface is observed to portray high resistance to irradiation damage. The mechanical response and failure mechanisms of un-irradiated samples is also assessed through loading tests and X-ray imaging at the University of South Carolina. Steam exposure tests are performed at the Oak Ridge National Laboratory in a facility that represents a reactor pressure vessel under a loss-of-coolant-accident scenario. The samples that are analyzed methodically in this report are tested for 32/31 hours at 1200°C with a velocity of 0.25 cm/s for the pressures: 0.1 MPa, 0.45 MPa, 0.92 MPa and 1.38 MPa. Scanning/transmission electron microscopy analysis conducted at the NC State University (NCSU) shows that the oxide layer thickness increases with the steam pressure. While the oxide layer is crystalline (α- cristobalite) for the pressures 0.45 MPa, 0.92 MPa and 1.38 MPa, the layer is amorphous at 0.1 MPa. Results from Raman spectroscopy have also confirmed the formation of α-cristobalite phase of SiO₂. The abrupt increase in the integrated Raman intensity ratio between steam pressures 0.1 and 0.45 MPa suggests the onset of accelerated crystallization. Non-destructive three dimensional X-ray microscopy/tomography (XCT) and computational image processing techniques are employed by the University of South Carolina to probe the porous oxidation features on SiC samples at varying pressures. Interestingly, most pores are observed to be located away from the surface as well as the oxide-SiC interface. The average oxide layer thickness assessed from the XCT analysis is seen to be in excellent agreement with the values determined through scanning electron microscopy analysis for the highest pressures where the oxide layer is relatively more uniform. A phase-field model developed by the NC State University and Idaho National Laboratory for simulating oxidation of SiC by steam captures the paralinear kinetics of SiC oxidation with a high degree of fidelity. Results from quasi-one-dimensional and two dimensional simulations show that the pores with oxidizing species lead to a higher volatilization rate. These simulations indicate that the enhanced apparent volatilization rates at higher pressures observed in experiments can be rationalized by the increased volatilization from the pores. The project team has also successfully developed the capability to import images from experiments for realistic evolution of the oxidizing microstructure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Irradiation Effects on Stability of δ-UZr2 phase in U-50 wt% Zr Alloy

U-50wt%Zr is a candidate metallic nuclear fuel with potential application in light water reactors due to its excellent thermal properties and high radiation tolerance. The Zr-rich UZr fuels possess greater swelling resistance and fission gas release characteristics compared with U-rich UZr fuels. In this current study, the δ-phase U-50wt%Zr is proton irradiated at room temperature to 1 displacement per atom (dpa) to provide insights on phase stability under irradiation conditions. High resolution characterization of Transmission Electron Microscopy (TEM) and Atom Probe Tomography (APT) characterization techniques are used to elucidate microstructural changes due to irradiation. TEM and APT results show highly oriented bcc β-Zr-rich platelet precipitates nucleating adjacent to α-U phases inside the UZr 2 matrix. Formation of this platelet morphology is characteristic of Widmänstatten structure which can be attributed to a variety of factors such as differences in thermal expansion coefficient between the phases, grain size, alloy composition, and cooling rate. The phases present are distinctly different than those observed through in situ annealing, but irradiation accelerates diffusion and phase separation kinetics. These microstructural changes in U-50wt%Zr are different from those achieved by pure thermodynamic or high temperature heavy ion irradiation experiments. Finally, our work, together with previous ones, highlight the necessity to study the U-Zr phase diagram under non-equilibrium thermodynamics conditions to support this material's deployment as a viable nuclear fuel form.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Test cavity and Iris-to-Coax transition for tuning and high-power verification of SNS DTL iris couplers

The Spallation Neutron Source (SNS) Drift Tube Linac (DTL) employs iris couplers to efficiently deliver RF power into the accelerating structure. To support the development, tuning, and high‑power conditioning of these couplers prior to installation in the actual DTLs, a dedicated test cavity and an iris‑to‑coaxial transition structure have been designed. This work presents the electromagnetic design, simulation, and optimization of the test setup, enabling precise characterization of the iris coupler’s performance. The transition structure allows for tuning of the iris opening dimensions without requiring a waveguide taper or full‑size waveguide transitions, while maintaining impedance matching between the coaxial feed and the iris geometry to minimize reflection and power loss. During low‑power tests, the iris opening di-mensions can be evaluated using the iris‑to‑coax transi-tion attached to the test cavity. For high‑power condi-tioning, full‑size waveguides with ceramic vacuum win-dows are connected to the test cavity to replicate opera-tional conditions. Key design parameters were optimized using computer-aided simulation, and sensitivity studies were conducted to assess the impact of mechanical toler-ances on RF performance. The resulting test platform provides a reliable and efficient means for tuning and validating iris couplers, contributing to improved opera-tional stability in the SNS DTL.

Lee, Sung-Woo [ORNL] (ORCID:000000030915835X)↗

DOE OSTI2020

A pathway to synthesizing single-crystal Fe and FeCr films

Nuclear reactor environments provide a unique scientific and engineering challenge wherein materials must tolerate prolonged exposure to concurrent irradiation, elevated temperatures, and corrosive media. However, uncontrolled variability in material composition and structure often prohibits truly single-variable experiments that can reveal basic aspects of environmental damage. Here, Magnetron sputtering is used to provide a more controlled model system for these fundamental studies, yielding reproducible single-crystal Fe and FeCr thin films containing 8 and 18 at.% Cr. Electron microscopy is used to determine the systematic correlations between growth conditions and the resulting film microstructure and surface morphology. It is found that the substrate temperature and applied radio frequency (RF) bias can be tuned to obtain consistent homogeneous and single crystal films with a minimal amount of Ar impurities from the RF bias process. Epitaxial, single-crystal Fe films are obtained on MgO substrates at 500 °C with 10 Watt (W) RF bias deposition. However, when Cr is alloyed with Fe, higher substrate temperatures (600 °C) and applied RF biases (15 W) are required to achieve a similar epitaxial single-crystal FeCr film. Accelerated molecular dynamics simulations reveal that Cr impedes surface transport, explaining the need for higher temperature and bias during the growth of the Cr-bearing films.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Assisted migration in a warmer and drier climate: less climate buffering capacity, less facilitation and more fires at temperate latitudes?

Assisted tree migration has been proposed as a conceptual solution to mitigate lags in biotic responses to anthropogenic climate change. The rationale behind this concept is that tree species currently growing under warmer and drier climates will be more resistant and resilient to the new climatic conditions than tree species naturally growing in currently wetter and colder climates. However, we hypothesize that, by being more stress‐tolerant to warmer and drier conditions, translocated species should exhibit different functional attributes, which could induce important ecological and societal costs and overcome the desired benefits of maintaining wood production and other ecosystem services. We used principal component analysis (PCA) to analyze variation in seven traits of 106 tree and tall shrub species from contrasting latitudinal distributions in western North America and Europe to predict the potential functional changes of forest ecosystems due to the translocation of tree species from low to high latitudes. We show that species from both continents differed primarily by their position on the leaf economy spectrum (LES) and their size traits. Even though, in Europe, differences in LES were significantly correlated to species southern latitudinal positions, in both continents differences in size traits were significantly correlated to latitude. These results suggest that assisted migration by translocating more conservative species of shorter stature in currently cooler climates should decrease the buffering capacity of forest canopies, decrease facilitation for understory species, and increase wildfire risks, whose effects have the potential to accelerate climate warming through negative atmospheric feedback processes. As an alternative solution to assisted migration that may accelerate rather than mitigate climate change, we recommend that foresters gradually diversify the vertical structure and layering of the existing forest canopy to maintain a sustainable water cycle and energy balance between the soil, the tree and the atmosphere without increasing the wildfire risk.

Environmental Sciences & Ecology↗

DOE OSTI2025

Defect modeling in semiconductors: the role of first principles simulations and machine learning

Abstract Point defects in semiconductors dictate their electronic and optical properties. Vacancies, interstitials, substitutional defects, and defect complexes can form in the semiconductor lattice and significantly impact its performance in applications such as solar absorption, light emission, electronics, and catalysis. Understanding the nature and energetics of point defects is essential for the design and optimization of next-generation semiconductor technologies. Here, we provide a comprehensive overview of the current state of research on point defects in semiconductors, focusing on the application of density functional theory (DFT) and machine learning (ML) in accelerating the prediction and understanding of defect properties. DFT has been instrumental in accurately calculating defect formation energies, charge transition levels, and other defect-related properties such as carrier recombination rates and lifetimes, and ion migration barriers. ML techniques, particularly neural networks, have emerged as powerful tools for enabling rapid prediction of defect properties at DFT-accuracy in order to overcome the expense of using large supercells and advanced functionals. We begin this article with a discussion of different types of point defects and complexes, their impact on semiconductor properties, and the experimental and DFT approaches typically used for their characterization. Through multiple case studies, we explore how DFT has been successfully applied to understand defect behavior across a variety of semiconductors, and how ML approaches integrated with DFT can efficiently predict defect properties and facilitate the discovery of new materials with tailored defect behavior. Overall, the advent of ‘DFT+ML’ promises to drive advancements in semiconductor technology, catalysis, and renewable energy applications, paving the way for the development of high-performance semiconductors which are defect-tolerant or have desirable dopability.

Rahman, Md Habibur (ORCID:000000027705984X)↗

DOE OSTI2024

Summary Report on Ion Irradiation Study of Ceramic Coating on Suppressing FCCI

Advanced cladding is critical for advanced nuclear reactors with an enhanced performance in radiation tolerance and neutron transparency. Using advanced cladding will ensure the adequate thermal conductivity and mechanical stability of the cladding base material, corrosion resistance, high-temperature coolant compatibility of the cladding surface, and chemical stability in the cladding inner wall against fuel cladding chemical interaction (FCCI). An innovative cladding with a three-layer structure (i.e., a modified surface, a clad base material, and a modified inner wall) promises to meet all these requirements. Initial research and development (R&D) regarding this innovative cladding seek to demonstrate the effectiveness of a thin ceramic coating in suppressing FCCI under ion irradiation to high dose. This United States (U.S.) Department of Energy (DOE)–Office of Nuclear Energy (NE) project report summarizes the results of recent ion irradiation studies of diffusion-couple samples with details of an ion irradiation experiment, the characterization of the interface microstructure of cerium (Ce)/titanium nitride (TiN)/oxide-dispersion strengthened (ODS), Ce/TiN/iron (Fe), Ce/ODS, and Ce/Fe samples irradiated with 80 million electron-volts (MeV) of xenon (Xe) ions to 100 displacements per atom (dpa) at 500?C using the Argonne Tandem Linac Accelerator System (ATLAS) facility at Argonne National Laboratory (ANL). The results of the ODS-substrate sample are encouraging and demonstrate the effectiveness of a thin ceramic coating on FCCI mitigation under irradiation. The results from an Fe-substrate sample revealed a complex microstructure, and the root cause is discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2026

CAHS: Context-Aware Homology Search

Protein homology search is foundational to bioinformatics: it supports annotation transfer, structure/function inference, and evolutionary analysis over rapidly expanding sequence repositories (e.g., UniProtKB). Profile hidden Markov models (pHMMs), as implemented in HMMER, remain the most widely trusted approach because they provide statistically calibrated E-values; however, their gap behavior is fixed once a profile is trained, despite biological evidence that insertion/deletion tolerance varies across flexible loops and intrinsically disordered regions. We present CAHS (Context-Aware Homology Search), a lightweight query-time adapter for pHMM search that incorporates learned and biologically motivated signals without changing HMMER's downstream search pipeline or its calibrated E-value reporting. Given a query sequence, CAHS computes per-residue representations from a protein language model and a disorder predictor, maps these to profile coordinates, and modulates only match-state transition rows (gap-open and gap-extension probabilities) while preserving Plan7 constraints. We comprehensively evaluate CAHS across six structurally diverse protein families and multi-domain architectures against a 570k-sequence target corpus. CAHS expands detection capability, retrieving thousands of additional remote homologs at relaxed thresholds by maintaining alignment quality through flexible regions. For multi-domain proteins, context-aware modulation resolves 94% of fragmented alignments. Crucially, CAHS preserves hit-set invariance at stringent operating points (E<10-10), demonstrating increased statistical confidence without inflating false positives. Furthermore, sharper statistical distinction between homologs and background noise during early filter stages yields up to a 3.87× acceleration in end-to-end wall-clock time on high-performance computing clusters. Overall, CAHS illustrates a practical AI-for-science design pattern: augmenting a trusted probabilistic model with query-specific learned signals to improve interpretable, reproducible inference in data-rich biology.

Bhattaram, Swethasree [Georgia Institute of Techno↗

DOE OSTI2025

Mechanical Design of the PIP-II ORBUMP Pulsed Dipole Magnet

The Proton Improvement Plan-II (PIP-II) is a vital upgrade to Fermilab's accelerator complex. The upgrade is designed to power the world s most intense high-energy neutrino beam in future experiments. The magnet pulse repetition rate of the PIP-II injection system is being upgraded from 15 Hz to 20 Hz and requires a roughly 30% increase in the magnetic field of the new Orbital Bump (ORBUMP) magnets in the Booster. The magnet is secured in a vacuum box and the core is made up of 0.127 mm thick, low carbon steel laminations with a C-5 inorganic coating. The core is clamped using external tie bars welded to the core end plates. ANSYS Finite Element Analysis (FEA) was used to evaluate the clamping design to minimize the deflection of the core post welding of the tie bars. The water-cooled single turn coil is electrically isolated from the core using virgin PEEK insulating material in the gap. An investigation into the high voltage performance of the virgin PEEK insulator was conducted. The design of the coil which shapes the magnetic field by acting as the pole tips is critical for the integrated field homogeneity. The coil manufacturing tolerances and fabrication techniques were evaluated to ensure the magnetic properties of the magnet could be obtained. The ORBUMP magnet mechanical design is presented in this paper.

Karas, Dino [Fermilab] (ORCID:0000000304340670)↗

DOE OSTI2020

QCOR; A Language Extension Specification for the Heterogeneous Quantum-Classical Model of Computation

Quantum computing (QC) is an emerging computational paradigm that leverages the laws of quantum mechanics to perform elementary logic operations. Existing programming models for QC were designed with fault-tolerant hardware in mind, envisioning stand-alone applications. However, the susceptibility of near-term quantum computers to noise limits their stand-alone utility. To better leverage limited computational strengths of noisy quantum devices, hybrid algorithms have been suggested whereby quantum computers are used in tandem with their classical counterparts in a heterogeneous fashion. This modus operandi calls out for a programming model and a high-level programming language that natively and seamlessly supports heterogeneous quantum-classical hardware architectures in a single-source-code paradigm. Motivated by the lack of such a model, we introduce a language extension specification, called QCOR, which enables single-source quantum-classical programming. Programs written using the QCOR library–based language extensions can be compiled to produce functional hybrid binary executables. After defining QCOR’s programming model, memory model, and execution model, we discuss how QCOR enables variational, iterative, and feed-forward QC. Additionally, QCOR approaches quantum-classical computation in a hardware-agnostic heterogeneous fashion and strives to build on best practices of high-performance computing. The high level of abstraction in the language extension is intended to accelerate the adoption of QC by researchers familiar with classical high-performance computing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

High-temperature superconducting CORC ® wires with record-breaking axial tensile strain tolerance present a breakthrough for high-field magnets

Cuprate high-temperature superconductors (HTS), such as RE-Ba 2 Cu 3 O 7–δ (REBCO, RE = rare earth), (Bi,Pb) 2 Sr 2 Ca 2 Cu 3 O 10–x and Bi 2 Sr 2 CaCu 2 O 8–x , have enabled the development of high-field superconducting magnets capable of generating magnetic fields far exceeding 20 T. The brittle nature of HTS requires elaborate means to protect them against the high stresses and strains associated with high-field magnet operation, and so far, has prevented reliable high-field HTS magnets from becoming a reality. Here we report a more than tenfold increase in the irreversible strain limit under axial tension (epsilonirr) to over 7% in optimized high-current conductor on round core (CORC®) conductors, compared to the REBCO tapes from which the CORC® conductor is wound. Minimizing the tape winding pitch of the helical wind mechanically decouples the brittle REBCO film from the overall conductor. The REBCO tapes behave as springs, limiting the rate at which applied strain is transferred to the ceramic film. In addition, high-strength alloy cores allow the critical stress (ϵ crit ) under axial tension at which initial degradation of CORC® conductors occurs to exceed 600 MPa, making them one of the strongest superconductors available. Mechanically decoupling the ceramic REBCO films from the overall CORC® conductor allows effective protection against the high operating stresses in high-field magnets. Furthermore, this breakthrough presents a monumental shift for HTS magnet technology, bringing reliable high-field superconducting magnets for compact fusion machines, the next generation of particle accelerators, and 40–60 T research solenoids within reach.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Analyzing inference workloads for spatiotemporal modeling

Ensuring power grid resiliency, forecasting climate conditions, and optimization of transportation infrastructure are some of the many application areas where data is collected in both space and time. Spatiotemporal modeling is about modeling those patterns for forecasting future trends and carrying out critical decision-making by leveraging machine learning/deep learning. Once trained offline, field deployment of trained models for near real-time inference could be challenging because performance can vary significantly depending on the environment, available compute resources and tolerance to ambiguity in results. Users deploying spatiotemporal models for solving complex problems can benefit from analytical studies considering a plethora of system adaptations to understand the associated performance-quality trade-offs. To facilitate the co-design of next-generation hardware architectures for field deployment of trained models, it is critical to characterize the workloads of these deep learning (DL) applications during inference and assess their computational patterns at different levels of the execution stack. In this paper, we develop several variants of deep learning applications that use spatiotemporal data from dynamical systems. We study the associated computational patterns for inference workloads at different levels, considering relevant models (Long short-term Memory, Convolutional Neural Network and Spatio-Temporal Graph Convolution Network), DL frameworks (Tensorflow and PyTorch), precision (FP16, FP32, AMP, INT16 and INT8), inference runtime (ONNX and AI Template), post-training quantization (TensorRT) and platforms (Nvidia DGX A100 and Sambanova SN10 RDU). Overall, our findings indicate that although there is potential in mixed-precision models and post-training quantization for spatiotemporal modeling, extracting efficiency from contemporary GPU systems might be challenging. Instead, co-designing custom accelerators by leveraging optimized High Level Synthesis frameworks (such as SODA High-Level Synthesizer for customized FPGA/ASIC targets) can make workload-specific adjustments to enhance the efficiency.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Input to the European strategy for particle physics: strong-field quantum electrodynamics

This document sets out the intention of the strong-field QED community to carry out, both experimentally and numerically, high-statistics parametric studies of quantum electrodynamics in the non-perturbative regime, at fields approaching and exceeding the critical or ‘Schwinger’ field of QED (F qed ≈ m 2 c 3 / eh ≈ 1.3 x 10 18 V/m) in the rest frame of a charged particle. In this regime, several exotic and fascinating phenomena are predicted to occur that have never been directly observed in the laboratory. These include Breit–Wheeler pair production, vacuum birefringence, and quantum radiation reaction. This experimental programme will also serve as a stepping stone towards studies of elusive phenomena such as elastic scattering of real photons and the conjectured perturbative breakdown of QED at extreme fields. State-of-the-art high-power laser facilities in Europe and beyond are starting to offer unique opportunities to study this uncharted regime at the intensity frontier, which is highly relevant also for the design of future multi-TeV lepton colliders. A transition from qualitative observational experiments to quantitative and high-statistics measurements can only be performed with large-scale collaborations and with systematic experimental programmes devoted to the optimisation of several aspects of these complex experiments, including detector developments, stability and tolerances studies, and laser technology.

Sarri, G. [Queen’s University Belfast (United King↗