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DOE OSTI2022

Arbitrage and Capacity Firming in Coordination with Day-Ahead Bidding of a Hybrid PV Plant

A hybrid PV plant (HPP) combines a photovoltaic (PV) plant with a battery energy storage system (BESS), which is considered a promising step towards the future of renewable power plants by the U.S. Department of Energy. When the renewable penetration reaches a significant level, a hybrid PV plant can bid in as a controllable thermal plant in the future electricity market. In this study, a bidding and BESS scheduling model is proposed for the HPP. The robust optimization (RO) technique has been utilized to identify the worst-case scenario of uncertainties during the bidding process. To address the overly conservative issue of the single-stage RO, we have decoupled the BESS schedule for arbitrage and PV capacity firming by a two-stage RO formulation. By comparing the output of single-stage RO and two-stage RO, the two-stage RO bids and schedules in a more aggressive manner, which increases the income of HPP. Also, the penalty of under-generation is considered in our model so that the day-ahead bidding decision and arbitrage schedules can be adjusted based on the potential UNDER-GENERATION penalty. Because the proposed model is non-convex and contains multi-stages, the Column-and-Constraint Generation (C&CG) algorithm is applied to the model as the solution. The proposed model has shown better economic performance compared to a state-of-art single-stage bidding method in case studies.

BESS scheduling↗

DOE OSTI2025

Identifying a next-generation antimalarial trioxolane in a landscape of artemisinin partial resistance

For over two decades, artemisinin-based combination therapy (ACT) has been the standard of care for the treatment of uncomplicated falciparum malaria. However, artemisinin partial resistance (ART-R) is now prevalent in Southeast Asia and has emerged in eastern Africa, threatening ACT efficacy. Artefenomel, a synthetic 1,2,4-trioxolane, exhibits an extended pharmacokinetic exposure profile that predicts for efficacy against ART-R parasites. Unfortunately, the development of artefenomel was halted recently after almost a decade in the clinic. Here, we describe studies of an artefenomel-adjacent chemotype that combines potent in vitro activity against clinical ART-R parasites, an extended pharmacokinetic profile with single-exposure efficacy in a murine malaria model, and enhanced stability in human microsomes and hepatocytes. Overall, our studies reveal a heretofore underexplored trioxolane chemotype with the potential to address ART-R in a next-generation trioxolane development candidate.

Science & Technology - Other Topics↗

DOE OSTI2023

Scalable Incremental Checkpointing using GPU-Accelerated De-Duplication

Writing large amounts of data concurrently to stable storage is a typical I/O pattern of many HPC workflows. This pattern introduces high I/O overheads and results in increased storage space utilization especially for workflows that need to capture the evolution of data structures with high frequency as checkpoints. In this context, many applications, such as graph pattern matching, perform sparse updates to large data structures between checkpoints. For these applications, incremental checkpointing techniques that save only the differences from one checkpoint to another can dramatically reduce the checkpoint sizes, I/O bottlenecks, and storage space utilization. However, such techniques are not without challenges: it is non-trivial to transparently determine what data has changed since a previous checkpoint and assemble the differences in a compact fashion that does not result in excessive metadata. State-of-art data reduction techniques (e.g., compression and de-duplication) have significant limitations when applied to modern HPC applications that leverage GPUs: slow at detecting the differences, generate a large amount of metadata to keep track of the differences, and ignore crucial spatiotemporal checkpoint data redundancy. This paper addresses these challenges by proposing a Merkle tree-based incremental checkpointing method to exploit GPUs' high memory bandwidth and massive parallelism. Experimental results at scale show a significant reduction of the I/O overhead and space utilization of checkpointing compared with state-of-the-art incremental checkpointing and compression techniques.

Tan, Nigel↗

DOE OSTI2021

HAIMOS Ensemble Forecasts for Intra-day and Day- Ahead GHI, DNI and Ramps

The objective of this research is to develop a hybrid physics-based/data-driven forecast model to improve direct normal and global horizontal irradiance (DNI and GHI) prediction for horizons ranging from 1 to 72 hours. Project objectives also address key gaps in state-of-the-art solar forecasting: accurate probabilistic solar forecasts and the forecasting of large irradiance ramps (ramp onset and magnitude). The proposed model ensembles Numerical Weather Prediction (NWP) forecasts, determinist physics-based algorithms, and new-generation cloud cover products (high-resolution rapid refresh satellite images and Large Eddy Simulations). The result is the Hybrid Adaptive Input Model Objective Selection (HAIMOS) ensemble model. HAIMOS blends state of the art machine learning methodologies with physics-based models for cloud cover and cloud optical depth forecasts. The technical activities followed a two-pronged strategy. First, the preprocessing of data, the selection of inputs to the nonlinear approximators, the type of approximator and objective functions, and post-processing ensembling techniques included in HAIMOS were all optimized adaptively to find the best model for a specific goal (reduce DNI/GHI forecast error, improve the prediction of ramp onset, etc.). Second, a large effort was put in improving cloud identification and the forecast of cloud cover and cloud optical depth. To this end, new-generation cloud parametrization products were developed in this work. These include improved algorithms to assist in cloud identification, cloud classification and cloud parametrization from satellite images – three key factors in the accuracy of 1 to 6-hours irradiance forecasts and prediction of ramp onset. Furthermore, we also included cloud information extracted from high resolution rapid refresh satellite images (GOES-16) and Large Eddy Simulations (LES). LES was used to model the atmosphere in detail over locations of interest and produce cloud optical depth forecasts. Once these data streams were validated, they were used as input data to the HAIMOS forecast. The model was developed using data from several climatologically distinct locations with potential for high solar penetration. In the last year of the project, we conducted a validation campaign according to the guidelines stipulated by the Topic Area 1 project as described in the FOA. This effort brings, for the first time, proven machine-learning methodologies for generating state-of-the-art solar forecasts interweaved with detailed physics-based models for cloud detection, and cloud optical depth forecasts. HAIMOS will generate accurate irradiance probabilistic forecast to assist in reducing solar generation prediction error. Globally optimized solar forecast models are more likely to impact solar energy stakeholders. The goal of this project was to increase the state-of-the-art forecast skill from their present values of 10 to 35%. At the end of the project, we achieved between 30% and 50% forecast skill across a wide range of horizons for both GHI and DNI.

14 SOLAR ENERGY↗

DOE OSTI2025

Effect of in utero and lactational exposure to antiretroviral therapy on the gut microbial composition and metabolic function in aged rat offspring

Despite the highly effective impact of antiretroviral therapy (ART) in reducing mother-to-child transmission of human immunodeficiency virus (HIV), there are concerns of long-term impacts of ART on the health of the offspring. The implications of perinatal exposure to antiviral drugs on the gut bacterial population and metabolic function in the offspring is unclear but may influence health outcomes given the various reported effects of the microbiome in human health. This study aims to gain insight into the potential effect ofin uteroand lactational exposure to ART on gut microbiota populations and short‐chain fatty acids (SCFAs) production in aged rat offspring. Pregnant rats were administered a combination of antiretroviral drugs (abacavir/dolutegravir/lamivudine) at two different dose levels during gestation and throughout lactation, and the fecal bacterial abundance and SCFA levels of the offspring were analyzed when they reached 12 months of age. Our results showed dose-dependent and sex-based differences in fecal microbial abundance at various taxonomic levels. Specifically, we found a decline inFirmicutesin males, and an increase inActinobacteriaamong males and females. Furthermore, a sex-specific distribution reorganization ofLactobacillus,Bifidobacterium, andAkkermansiawas identified. No significant difference in the concentration of prominent SCFAs and IgA levels were identified. These findings provide preliminary information indicating the need to evaluate perinatal effects of ART more comprehensively on the gut bacterial and metabolic function in future studies, and their potential role in offspring health outcomes.

Research & Experimental Medicine↗

DOE OSTI2021

Staged progression epidemic models for the transmission of invasive nontyphoidal Salmonella (iNTS) with treatment

We develop and analyze a stage-progression compartmental model to study the emerging invasive nontyphoidal Salmonella (iNTS) epidemic in sub-Saharan Africa. iNTS bloodstream infections are often fatal, and the diverse and non-specific clinical features of iNTS make it difficult to diagnose. We focus our study on identifying approaches that can reduce the incidence of new infections. In sub-Saharan Africa, transmission and mortality are correlated with the ongoing HIV epidemic and severe malnutrition. We use our model to quantify the impact that increasing antiretroviral therapy (ART) for HIV infected adults and reducing malnutrition in children would have on mortality from iNTS in the population. We consider immunocompromised subpopulations in the region with major risk factors for mortality, such as malaria and malnutrition among children and HIV infection and ART coverage in both children and adults. We parameterize the progression rates between infection stages using the branching probabilities and estimated time spent at each stage. We interpret the basic reproduction number R 0 as the total contribution from an infinite infection loop produced by the asymptomatic carriers in the infection chain. The results indicate that the asymptomatic HIV+ adults without ART serve as the driving force of infection for the iNTS epidemic. We conclude that the worst disease outcome is among the pediatric population, which has the highest infection rates and death counts. Our sensitivity analysis indicates that the most effective strategies to reduce iNTS mortality in the studied population are to improve the ART coverage among high-risk HIV+ adults and reduce malnutrition among children.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Elevated Temperature Graphite Mechanical Testing

High purity graphite will be used for core components within most High Temperature Reactor (HTR) designs. Several "high tech” industries currently utilize synthetic, high-purity, commercially available graphite components to fabricate photovoltaic cells, semi-conductors, optical fibers, and other high value electronic industry products. New advanced HTR designs are also interested in using these graphite grades for long-term, internal core component applications. Consequently, the US Department of Energy, Advanced Reactor Technologies (DOE-ART) program has spent several years testing different high purity graphite grades for potential use within these new nuclear reactor designs. A significant part of that effort has been in the development and improvement of American Society for Testing and Materials (ASTM) test standards specifically for nuclear graphite grades. Nearly all ASTM test standards have either been developed or improved by the DOE-ART program over the past 25 years. The ART program continues to assist in the development of new ASTM test standards in support of the future commercial HTR fleet currently being designed and built in the USA. The newest effort undertaken by ART is the development of high temperature mechanical testing practices that may be acceptable for a future ASTM test standard (or guide) for this critical material property measurement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

High-Temperature Gas-Cooled Reactor Research Survey and Overview: Preliminary Data Platform Construction for the Nuclear Energy University Program

Since the U.S. Department of Energy Office of Nuclear Energy initiated the Nuclear Energy University Program (NEUP) in 2009, there are 29 NEUP projects focusing on high-temperature gas-cooled reactor (HTGR) research up to July 2022. The resultant research product, either experimental or computational, were published as final NEUP reports, journal articles and conference proceedings. However, these federally funded products have been scattered and sometimes cannot be easily accessed. To improve access to this valuable HTGR validation data and optimize the return on the significant investment made by the Department of Energy, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program started a survey of completed and ongoing HTGR NEUP projects to develop a public-access database specific for HTGRs applications that can be used to retrieve computational fluid dynamics and system code validation data. This effort will help guide future NEUP-funded research, define new state of the ART Phenomena Identification and Ranking Table (PIRT), and promote the usage of this data in the codes validation matrices. This report provides an overview of the NEUP-funded HTGR-related research projects from Fiscal Year (FY) 2009–2021 and identifies validation knowledge gaps still existing in HTGR thermal-fluid research. A preliminary data platform has been developed for the 29 NEUP projects investigating HTGR thermal hydraulics, including their final reports as well as the available scientific publications. As an ultimate goal for this work, the ART-GCR program will create a central database at Idaho National Laboratory to identify, organize, and store these datasets generated by experimental investigations or computational models, experimental facility descriptions, and publicly-available academic products from the HTGR-related NEUP projects and provide future guidance for the storage and transmission of important project documentations for later NEUP projects as well.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Single-Step Conversion of Ethanol to n-Butene over Ag-ZrO2/SiO2 Catalysts

Ethanol is a promising platform molecule for production of a variety of fuels and chemicals. Of particular interest is producing middle distillate fuels (i.e., jet and diesel blendstock) from renewable ethanol feedstock. State-of-the-art alcohol-to-jet technology requires multiple process steps based on catalytic dehydration of ethanol to form ethylene, followed by sometimes a multi-step oligomerization, and then hydrotreatment and distillation. Here we report on a new catalytic route in which ethanol is directly converted to n-butene (1- and 2-butene mixtures) over Ag-ZrO2/SBA-16, thus offering the potential for a reduction in the number of required processing steps versus conventional alcohol-to-jet technology. This catalyst system provides the balanced metal and Lewis acid sites required to selectively facilitate a cascading sequence of reactions that includes dehydrogenation, aldol condensation, Meerwein–Ponndorf–Verley reduction, dehydration, and hydrogenation. High conversion and selectivity toward either n-butene or 1,3-butadiene is achieved by tuning the hydrogen feed partial pressure and other process/catalyst parameters. With sufficient hydrogen partial pressure 1,3-butadiene is completely and selectively hydrogenated to form n-butene. The reaction mechanism was elucidated through operando-nuclear magnetic resonance investigations coupled with reactivity measurements. Combined experimental-computational investigation reveals how changes in silver and zirconium composition and the silver oxidation state affects reactivity under controlled hydrogen partial pressures and after prolonged run times. Finally, catalyst effectiveness also was demonstrated when using wet ethanol feed, thus highlighting process flexibility in terms of feedstock purity requirements. This work was financially supported by the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office, and was performed at the Pacific Northwest National Laboratory (PNNL) under Contract No. DE-AC05-76RL01830 and the National Renewable Energy Laboratory under Contract No. DE-AC36- 08GO28308. Part of the work conducted by S. A. Akhade was performed under the auspices of the U.S. DOE at Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344. This work was partly supported through the PNNL-WSU Distinguished Graduate Research Program for ADW. NMR and XPS experiments were performed using EMSL (grid.436923.9), a DOE Office of Science User Facility sponsored by the Office of Biological and Environmental Research

Dagle, Vanessa↗

DOE OSTI2021

The Quest for Functional Oxide Cathodes for Magnesium Batteries: A Critical Perspective

The Mg battery is an energy storage technology which has garnered significant interest in recent years. Mg batteries incorporating a metal oxide cathode (MOC) are potential candidates to supersede the state-of-the-art Li-ion battery in energy density, cost, and sustainability. However, there are significant discrepancies in reported performances and reactivities of Mg battery MOCs, with detailed analyses revealing that parasitic electrolyte reactions can contribute almost entirely to the measured capacity. This Perspective describes a holistic approach. encompassing elemental, redox, and structural probes-which is vital to robustly confirm and quantify Mg intercalation in MOCs. It critically surveys recent literature for applications of this approach to reveal true state-of-the-art MOCs for Mg batteries. We also suggest testing and analysis protocols to ensure fair comparison of future reports with these state-of-the-art materials.

25 ENERGY STORAGE↗

DOE OSTI2020

A machine learning Automated Recommendation Tool for synthetic biology

Abstract Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long development times. Here, we present the Automated Recommendation Tool (ART), a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic biology in a systematic fashion, without the need for a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. We demonstrate the capabilities of ART on simulated data sets, as well as experimental data from real metabolic engineering projects producing renewable biofuels, hoppy flavored beer without hops, fatty acids, and tryptophan. Finally, we discuss the limitations of this approach, and the practical consequences of the underlying assumptions failing.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Axion Dark Matter Experiment: Detailed design and operations

Axion dark matter experiment ultra-low noise haloscope technology has enabled the successful completion of two science runs (1A and 1B) that looked for dark matter axions in the 2.66–3.1 μeV mass range with Dine–Fischler–Srednicki–Zhitnisky sensitivity. Therefore, it is the most sensitive axion search experiment to date in this mass range. Here, we discuss the technological advances made in the last several years to achieve this sensitivity, which includes the implementation of components, such as the state-of-the-art quantum-noise-limited amplifiers and a dilution refrigerator. Furthermore, we demonstrate the use of a frequency tunable microstrip superconducting quantum interference device amplifier in run 1A, and a Josephson parametric amplifier in run 1B, along with novel analysis tools that characterize the system noise temperature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Complex decay dynamics of HIV virions, intact and defective proviruses, and 2LTR circles following initiation of antiretroviral therapy

In persons living with HIV-1 (PLWH) who start antiretroviral therapy (ART), plasma virus decays in a biphasic fashion to below the detection limit. The first phase reflects the short half-life (<1 d) of cells that produce most of the plasma virus. The second phase represents the slower turnover (t 1/2 = 14 d) of another infected cell population, whose identity is unclear. Using the intact proviral DNA assay (IPDA) to distinguish intact and defective proviruses, we analyzed viral decay in 17 PLWH initiating ART. Circulating CD4 + T cells with intact proviruses include few of the rapidly decaying first-phase cells. Instead, this population initially decays more slowly (t 1/2 = 12.9 d) in a process that largely represents death or exit from the circulation rather than transition to latency. This more protracted decay potentially allows for immune selection. After ~3 mo, the decay slope changes, and CD4 + T cells with intact proviruses decay with a half-life of 19 mo, which is still shorter than that of the latently infected cells that persist on long-term ART. Two-long-terminal repeat (2LTR) circles decay with fast and slow phases paralleling intact proviruses, a finding that precludes their use as a simple marker of ongoing viral replication. Proviruses with defects at the 5' or 3' end of the genome show equivalent monophasic decay at rates that vary among individuals. Understanding these complex early decay processes is important for correct use of reservoir assays and may provide insights into properties of surviving cells that can constitute the stable latent reservoir.

2LTR circles↗

DOE OSTI2021

Production and tests of the ADDC for the Micromegas detector of the ATLAS New Small Wheel

The Large Hadron Collider (LHC) at CERN will perform a series of upgrades to allow luminosity increases during the next physics runs expected from 2022 on. These will also significantly increase the trigger rates of all the detectors. As part of the ATLAS Phase-I upgrade, the current Small Wheel muon detectors will be replaced with state-of-the-art New Small Wheel (NSW) detectors to cope with the increased luminosity of the LHC. The Address in Real Time Data Driver Card (ADDC) is designed to transmit the trigger data from the resistive Micro-Mesh Gaseous Structure (Micromegas) detectors of the NSW. The ART ASIC on the ADDC is a customdesigned chip to receive theAddress in Real Time (ART) signals from theVMMfront-end ASIC and perform hit-selection processing. The processed trigger data is then sent to the Trigger Processor (TP) through optical links. A total of 512 ADDCs will be installed on the detector close to the front-end boards. Therefore, those cards must be able to work properly in a high radiation and magnetic field environment. Furthermore, after four rounds of prototyping, the ADDC production was launched in January of 2019. 600 ADDC boards have been produced and tested with an automated test stand. This test setup can simulate the front-end signals and provide "Level-1 Data Driver Card" (L1DDC) functions as well as part of the TP functions. Thus, the ADDC functionality and stability can be verified without the remaining NSW electronics. This paper describes the ADDC hardware prototype development, radiation and integration testing, and the ADDC automated production test procedure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

K-RET: knowledgeable biomedical relation extraction system

Abstract Motivation Relation extraction (RE) is a crucial process to deal with the amount of text published daily, e.g. to find missing associations in a database. RE is a text mining task for which the state-of-the-art approaches use bidirectional encoders, namely, BERT. However, state-of-the-art performance may be limited by the lack of efficient external knowledge injection approaches, with a larger impact in the biomedical area given the widespread usage and high quality of biomedical ontologies. This knowledge can propel these systems forward by aiding them in predicting more explainable biomedical associations. With this in mind, we developed K-RET, a novel, knowledgeable biomedical RE system that, for the first time, injects knowledge by handling different types of associations, multiple sources and where to apply it, and multi-token entities. Results We tested K-RET on three independent and open-access corpora (DDI, BC5CDR, and PGR) using four biomedical ontologies handling different entities. K-RET improved state-of-the-art results by 2.68% on average, with the DDI Corpus yielding the most significant boost in performance, from 79.30% to 87.19% in F-measure, representing a P-value of 2.91×10−12. Availability and implementation https://github.com/lasigeBioTM/K-RET.

Sousa, Diana F. (ORCID:0000000305979273)↗

DOE OSTI2025

Fundamental limit of jet tagging

Identifying the origin of high-energy hadronic jets (jet tagging) has been a critical benchmark problem for machine learning in particle physics. Jets are ubiquitous at colliders and are complex objects that serve as prototypical examples of collections of particles to be categorized. Over the last decade, machine learning-based classifiers have replaced classical observables as the state of the art in jet tagging. Increasingly complex machine learning models are leading to increasingly more effective tagger performance. Our goal is to address the question of convergence—are we getting close to the fundamental limit on jet tagging or is there still potential for computational, statistical, and physical insights for further improvements? We address this question using state-of-the-art generative models to create a realistic, synthetic dataset with a known jet tagging optimum. Various state-of-the-art taggers are deployed on this dataset, showing that there is a significant gap between their performance and the optimum. Our dataset and software are made public to provide a benchmark task for future developments in jet tagging and other areas of particle physics.

Artificial intelligence↗

DOE OSTI2022

Peer-to-Peer Communication Trade-Offs for Smart Grid Applications: Preprint

Peer-to-peer energy management systems for smart grids require developers to consider the trade-offs between the amount of communication traffic generated and the quality and speed of convergence of the control algorithms that are deployed. Employing a fully connected communication causes messages to scale exponentially with the number of nodes, while using a sparse connectivity causes less information dissemination leading to degradation of the algorithm performance. The best communication topology for a particular application lies somewhere in between and often requires empirical evaluation by application designers. Existing methods do not put focus on the needs for smart grid applications, which is information dissemination throughout the network and they do not provide a flexible solution for application developers to prototype and deploy different topologies without modifying the application code. This paper introduces a configurable virtual communication topology framework TopLinkMgr, allowing users to specify any chosen communication topology and deploy peer-to-peer applications using it. It also introduces a self-adaptive, fault-tolerant topology management algorithm, Bounded Path Dissemination that can ensure the dissemination of information to all peers within a specified threshold for a sparsely connected topology. Experiments show that the algorithm improves on convergence speed and accuracy over state-of-the-art methods and is also robust against node failures. The results indicate the possibility of achieving a close-to optimal convergence without overloading the network allowing the realization of peer-to-peer control platforms covering larger and more complex power systems.

Bounded Path Dissemination↗

DOE OSTI2021

Critical Current Distributions of Recent Bi-2212 Round Wires

Bi 2 Sr 2 CaCu 2 O 8+x (Bi-2212) is the only high-field, high-temperature superconductor (HTS) capable of reaching a critical current density J c (16 T, 4.2 K) of 6500 A·mm –2 in the highly desirable round wire (RW) form. However, state-of-the-art Bi-2212 conductors still have a critical current density (J c ) to depairing current density (J d ) ratio around 20 to 30 times lower than that of state-of-the-art Nb–Ti or REBCO. Previously, we have shown that recent improvements in Bi-2212 RW J c are due to improved connectivity associated with optimization of the heat treatment process, and most recently due to a transition to a finer and more uniform powder manufactured by Engi-Mat. One quantitative measure of connectivity may be the critical current (I c ) distribution, since the local I c in a wire can vary along the length due to variable vortex-microstructure interactions and to factors such as filament shape variations, grain-to-grain connectivity variations and blocking secondary phase distributions. Modeling the experimental V-I transition measured on a low resistance shunt as a complex sum of voltage contributions of individual filament and wire sub-sections allows a numerical extraction of the I c distribution from the d 2 V/dI 2 treatment of the V-I curves. Here we compare ~0.1 m length I c distributions of Bi-2212 RWs with recent state-of-the-art very high-J c Engi-Mat powder and lower J c and older Nexans granulate powder. We do find that the I c spread for Bi-2212 wires is about twice the relative standard of high-J c Nb–Ti well below H irr . We do not yet see any obvious contribution of the Bi-2212 anisotropy to the I c distribution and are rather encouraged that these Bi-2212 round wires show relative I c distributions not too far from high-J c Nb–Ti wires.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗