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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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NASA NTRS2012

The XMM-Newton Survey of the Small Magellanic Cloud

Context. Although numerous archival XMM-Newton observations existed towards the Small Magellanic Cloud (SMC) before 2009, only a fraction of the whole galaxy had been covered. Aims. Between May 2009 and March 2010, we carried out an XMM-Newton survey of the SMC, to ensure a complete coverage of both its bar and wing. Thirty-three observations of 30 different fields with a total exposure of about one Ms filled the previously missing parts. Methods. We systematically processed all available SMC data from the European Photon Imaging Camera. After rejecting observations with very high background, we included 53 archival and the 33 survey observations. We produced images in five different energy bands. We applied astrometric boresight corrections using secure identifications of X-ray sources and combined all the images to produce a mosaic covering the main body of the SMC. Results. We present an overview of the XMM-Newton observations, describe their analysis, and summarize our first results, which will be presented in detail in follow-up papers. Here, we mainly focus on extended X-ray sources, such as supernova remnants (SNRs) and clusters of galaxies, that are seen in our X-ray images. Conclusions. Our XMM-Newton survey represents the deepest complete survey of the SMC in the 0.15−12.0 keV X-ray band. We propose three new SNRs that have low surface brightnesses of a few 10−14 erg cm−2 s−1 arcmin−2 and large extents. In addition, several known remnants appear larger than previously measured at either X-rays or other wavelengths extending the size distribution of SMC SNRs to larger values.

global↗
NASA NTRS2018

High-Efficiency Flexible Multilevel Photon Sieves by Single-Step Laser-Based Fabrication and Optical Analysis

Over the past several decades, the need for high-resolution, high-efficiency, lightweight, high contrast focusing optics has continued to increase due to their applications in fields such as astronomy, spectroscopy, free-space optical communications, defense, and remote sensing. In recent years, photon sieve planar diffractive optics have been developed on flexible, lightweight polyimide substrates. However, transmission efficiencies have continuously been very low (~1-4%), thus impeding the widespread use of photon sieves in practical applications. Here, we present a flexible, lightweight, N = 4 level phase photon sieve with over 25% transmission efficiency; nearly triple that of any other photon sieve reported thus far. In this study, the photon sieve was fabricated via a novel pulsed laser ablation method using an ultraviolet source, and the total time to fabricate a ~3 sq cm sample was tens of seconds. Theoretical analysis of the photon sieve was carried out via the FDTD method, and was in very good agreement with experimental results. We also calculated via FDTD modeling the behavior of higher step (N = 8, 16, 32) photon sieves for further enhanced efficiencies, and show a fundamental limit on photon sieve efficiency of 70% in the limit of increasing step number. This multilevel photon sieve represents a new step in high-resolution diffractive optics, moving towards efficiencies suitable for widespread applications.

Julian, Matthew N.↗
NASA NTRS2025

On the Characterization and Mitigation of Noise in Space-borne Microwave Sounding Instruments

Space-borne microwave sounding instruments have become vital data sources for weather prediction and climate change studies. Among the various radiometer configurations, the total power microwave radiometer is particularly appealing for current and future operational satellites due to its superior sensitivity and simple design. However, its performance is vulnerable to degradation caused by receiver gain fluctuations, electronic 1/f noise, and other time varying receiver characteristics. For Numerical Weather Prediction (NWP) users, 1/f noise introduces inter-channel correlations, complicating the assimilation of affected observations and reducing their accuracy. Addressing this noise issue in ground data processing system is essential to enhance the utility of microwave sounding data. This paper focuses on the characterization and mitigation of noise in current and future microwave sounding instruments, with particular emphasis on the impact of 1/f noise. Various methods are applied to quantitatively characterize noise features in both frequency and time domains. Additionally, the influence of calibration parameters on 1/f noise are analyzed. Based on these findings, we propose a mitigation algorithm for reducing noise during the on-orbit calibration of microwave sounding instruments, aiming to improve the quality of retrieved data for operational use.

calibration↗
NASA NTRS1988

High-temperature shock formation of N2 and organics on primordial Titan

Theoretical models suggest that the initial form of nitrogen in Titan's atmosphere may have been NH3. The possible importance of strong shocks produced during high-velocity impacts accompanying the late stages of accretion are investigated as a method for converting NH3 to N2, of which Titan's atmosphere is now primarily composed. The focused beam of a high-power laser is used to simulate the effects of an impact in Titan's atmosphere. For mixtures of 10, 50, and 90 percent NH3, yields of 0.25, 1, and 6 x 20 to the 17th molecules of N2 per joule, respectively, were obtained. It is also found that the yield of HCN is comparable to that for N2. Several other hydrocarbons are produced, many with yields in excess of theoretical high-temperature-equilibrium models. The above yields, when combined with models of the satellite's accretion, result in a total N2 production comparable to that present in TItan's atmosphere and putative ocean.

Mckay, Christopher P.↗
NASA NTRS2012

Lightning Jump Algorithm and Relation to Thunderstorm Cell Tracking, GLM Proxy and Other Meteorological Measurements

The lightning jump algorithm has a robust history in correlating upward trends in lightning to severe and hazardous weather occurrence. The algorithm uses the correlation between the physical principles that govern an updraft's ability to produce microphysical and kinematic conditions conducive for electrification and its role in the development of severe weather conditions. Recent work has demonstrated that the lightning jump algorithm concept holds significant promise in the operational realm, aiding in the identification of thunderstorms that have potential to produce severe or hazardous weather. However, a large amount of work still needs to be completed in spite of these positive results. The total lightning jump algorithm is not a stand-alone concept that can be used independent of other meteorological measurements, parameters, and techniques. For example, the algorithm is highly dependent upon thunderstorm tracking to build lightning histories on convective cells. Current tracking methods show that thunderstorm cell tracking is most reliable and cell histories are most accurate when radar information is incorporated with lightning data. In the absence of radar data, the cell tracking is a bit less reliable but the value added by the lightning information is much greater. For optimal application, the algorithm should be integrated with other measurements that assess storm scale properties (e.g., satellite, radar). Therefore, the recent focus of this research effort has been assessing the lightning jump's relation to thunderstorm tracking, meteorological parameters, and its potential uses in operational meteorology. Furthermore, the algorithm must be tailored for the optically-based GOES-R Geostationary Lightning Mapper (GLM), as what has been observed using Very High Frequency Lightning Mapping Array (VHF LMA) measurements will not exactly translate to what will be observed by GLM due to resolution and other instrument differences. Herein, we present some of the promising aspects and challenges encountered in utilizing objective tracking and GLM proxy data, as well as recent results that demonstrate the value added information gained by combining the lightning jump concept with traditional meteorological measurements.

Schultz, Christopher J.↗
NASA NTRS2013

Application of CO2 Snow Jet Cleaning in Conjunction with Laboratory Based Total Reflection X-Ray Fluorescence

The Genesis mission was the first mission returning solar material to Earth since the Apollo program [1,2]. Unfortunately the return of the space craft on September 8, 2004 resulted in a crash landing, which shattered the samples into small fragments and exposed them to desert soil and other debris. Thus only small fragments of the original collectors are available, each having different degrees of surface contamination. Thorough surface cleaning is required to allow for subsequent analysis of solar wind material embedded within. An initial cleaning procedure was developed in coordination with Johnson Space Center which focused on removing larger sized particulates and a thin film organic contamination acquired during collection in space [3]. However, many of the samples have additional residues and more rigorous and/or innovative cleaning steps might be necessary. These cleaning steps must affect only the surface to avoid leaching and re-distribution of solar wind material from the bulk of the collectors. To aid in development and identification of the most appropriate cleaning procedures each sample has to be thoroughly inspected before and after each cleaning step. Laboratory based total reflection X-ray fluorescence (TXRF) spectrometry lends itself to this task as it is a non-destructive and surface sensitive analytical method permitting analysis of elements from aluminum onward present at and near the surface of a flat substrate [4]. The suitability of TXRF has been demonstrated for several Genesis solar wind samples before and after various cleaning methods including acid treatment, gas cluster ion beam, and CO2 snow jet [5 - 7]. The latter one is non-invasive and did show some promise on one sample [5]. To investigate the feasibility of CO2 snow jet cleaning further, several flown Genesis samples were selected to be characterized before and after CO2 snow application with sample 61052 being discussed below.

Schmeling, M.↗
NASA NTRS2013

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters : Synthetic Sensor Radiance Formulation - Pt. 1

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

Simulations↗
DOE OSTI2023

Effects of processing on the efficacy and metabolites of Cistanche tubulosa using ultra‐performance liquid chromatography coupled with quadrupole time‐of‐flight mass spectrometry

Abstract Cistanche tubulosa (CT), a well‐known traditional Chinese medicine, has always been processed with rice wine for the treatment of kidney‐yang deficiency syndrome (KYDS) since time immemorial. To explore the effect of processing on the efficacy and metabolites of CT in vivo , a comprehensive method using ultra‐performance liquid chromatography coupled with quadrupole time‐of‐flight mass spectrometry was established for the analysis of the altered endogenous metabolites in response to the intervention of the raw and processed CT in KYDS model and the metabolites of the absorbed compounds in rats after gastric perfusion. It was shown that CT could improve KYDS, and the effect of the processed product was more significant. A total of 47 differential metabolites were identified in urine. Pathway analysis proved that purine metabolism; alanine, aspartate, and glutamate metabolism; and citrate cycle were the main pathways. Furthermore, 53 prototypes and 48 metabolites have been detected in rats. This was the first systematic research focus on the metabolites of raw and processed CT in vivo , which could provide a scientific basis for explaining the increasing efficiency of the processed CT. Moreover, it provides a valuable strategy for analyzing the chemical components and metabolites of other TCM prescriptions.

Lei, Huibo↗
NASA NTRS2013

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters: Equivalent Sensor Radiance Formulation - Part 1

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Simulations↗
DOE OSTI2022

Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy (Workshop Report)

The US Department of Energy’s (DOE’s) Advanced Manufacturing Office held the virtual workshop entitled “Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy” in November and December 2020. The workshop brought together participants from universities/laboratories, industries, equipment manufacturers, technology vendors, nongovernmental organizations, and subject-matter experts to discuss transformative technologies and strategies to substantially improve the performance (e.g., energy productivity, thermal efficiency, reduced greenhouse gas [GHG] emissions, reduced number of process steps) of thermal processing systems in the industrial sector. The US industrial sector accounts for 32% of the nation’s primary energy use (including feedstocks), and refining, chemicals, pulp and paper, iron and steel, and food products represent the top energy-consuming sectors. Thermal processing or process heating represents the largest energy use category; it accounts for 63% of all energy use in manufacturing. Additionally, thermal processing is the largest contributor of carbon dioxide (CO2) generation, resulting from combustion of fuels and process related chemical reactions, such as in the case of cement and lime production. The challenge of achieving net-zero industrial GHG emissions is colossal considering the established industrial base that depends mainly on carbon-based processes and energy sources; the time frame and cost to replace carbon-based energy sources and feedstocks; and the long-term outlook for development with large-scale adaptation of alternative non carbon–based technologies. The goals of the DOE Advanced Manufacturing Office Thermal Process Intensification Workshop were as follows: (1) Identify R&D gaps and opportunities to facilitate transformative improvement in industrial thermal processes beyond current technologies and allow for entirely new methods for processing materials; (2) Gain insight into new and innovative approaches to thermally intensify processes, reduce heat demand, harness waste heat, and use fuels and hydrocarbon feedstocks more efficiently; (3) Identify the R&D pathways to thermal process intensification (TPI) with the highest potential for impact and adoption by the industrial sector; (4) Define areas of research, development, and demonstration (RD&D) activities to accelerate development and application of emerging and transformative technologies to intensify thermal processes in industry. The scope and focus of the workshop were defined to meet these goals. Based on the available data for energy use and GHG emissions, the industries that collectively use more than 80% of the total process heating energy consumption were selected as primary focus areas. The chosen industries were combined into the following four groups based on similarities in their thermal processes: high-temperature metal processing (iron and steel industry, alumina-aluminum industry); high-temperature nonmetal and mineral processing (cement and glass industry); medium- to low-temperature thermal processing (food processing and pulp and paper industry as part of forest products sector); and hydrocarbon processing (petroleum refining and chemical industry). Furthermore, all potential TPI technologies associated with the processes defined were considered as part of the workshop. Different types of TPI technologies possible in industrial in the document.

42 ENGINEERING↗
NASA NTRS2007

Aqueous Alteration of Basalts: Earth, Moon, and Mars

The geologic processes responsible for aqueous alteration of basaltic materials on Mars are modeled beginning with our knowledge of analog processes on Earth, i.e., characterization of elemental and mineralogical compositions of terrestrial environments where the alteration and weathering pathways related to aqueous activity are better understood. A key ingredient to successful modeling of aqueous processes on Mars is identification of phases that have formed by those processes. The purpose of this paper is to describe what is known about the elemental and mineralogical composition of aqueous alteration products of basaltic materials on Mars and their implications for specific aqueous environments based upon our knowledge of terrestrial systems. Although aqueous alteration has not occurred on the Moon, it is crucial to understand the behaviors of basaltic materials exposed to aqueous environments in support of human exploration to the Moon over the next two decades. Several methods or indices have been used to evaluate the extent of basalt alteration/weathering based upon measurements made at Mars by the Mars Exploration Rover (MER) Moessbauer and Alpha Particle X-Ray Spectrometers. The Mineralogical Alteration Index (MAI) is based upon the percentage of total Fe (Fe(sub T)) present as Fe(3+) in alteration products (Morris et al., 2006). A second method is the evaluation of compositional trends to determine the extent to which elements have been removed from the host rock and the likely formation of secondary phases (Nesbitt and Young, 1992; Ming et al., 2007). Most of the basalts that have been altered by aqueous processes at the two MER landing sites in Gusev crater and on Meridiani Planum have not undergone extensive leaching in an open hydrolytic system with the exception of an outcrop in the Columbia Hills. The extent of aqueous alteration however ranges from relatively unaltered to pervasively altered materials. Several experimental studies have focused upon the aqueous alteration of lunar materials and simulants (e.g., Keller and Huang, 1971; Eick et al., 1996). Lunar basalts are void of water and highly reduced, hence, these materials are initially very reactive when exposed to water under oxidizing conditions.

Ming, Douglas W.↗
DOE OSTI2020

Algorithm-Based Fault Tolerance for Convolutional Neural Networks

Convolutional neural networks (CNNs) are becoming more and more important for solving challenging and critical problems in many fields. CNN inference applications have been deployed in safety-critical systems, which may suffer from soft errors caused by high-energy particles, high temperature, or abnormal voltage. Of critical importance is ensuring the stability of the CNN inference process against soft errors. Traditional fault tolerance methods are not suitable for CNN inference because error-correcting code is unable to protect computational components, instruction duplication techniques incur high overhead, and existing algorithm-based fault tolerance (ABFT) techniques cannot protect all convolution implementations. In this paper, we focus on how to protect the CNN inference process against soft errors as efficiently as possible, with the following three contributions. (1) We propose several systematic ABFT schemes based on checksum techniques and analyze their fault protection ability and runtime thoroughly. Unlike traditional ABFT based on matrix-matrix multiplication, our schemes support any convolution implementations. (2) We design a novel workflow integrating all the proposed schemes to obtain a high detection/correction ability with limited total runtime overhead. (3) We perform our evaluation using ImageNet with well-known CNN models including AlexNet, VGG-19, ResNet-18, and YOLOv2. Here, experimental results demonstrate that our implementation can handle soft errors with very limited runtime overhead (4%~8% in both error-free and error-injected situations).

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Kinetic structure of rotational discontinuities: Implications for the magnetopause

Magnetic field rotations in the high ion beta magnetosheath that are part of the magnetopause structure are expected to have only a small normal component. We have studied the properties of rotational discontinuities (RDs) under these conditions, viewed as the limit of weak intermediate shocks (ISs), by performing hybrid simulations with a reflecting wall boundary condition (piston method). With this dynamic formation, the sense and size of rotation are not arbitrarily predetermined, but rather evolve from the given upstream (magnetosheath) and downstream (magnetospheric) boundary conditions, similar to what takes place at the magnetopause. This work focuses on several aspects: the observed minimum shear of RDs, their width, their internal signature, and their relation to ISs in isotropic plasmas. Our simulation results are in agreement with the minimum shear observations, that is, the RDs choose the sense of rotation that corresponds to the minimum angle between the upstream and downstream field vector. The RDs are stable, with a unique scale size. Typical gradient scale half widths are one to four ion inertial lengths with a total width up to ten times of that, in agreement with magnetopause observations. We develop a generalized fluid theory of RDs and discuss the characteristic internal signatures of the rotational layer, comparing the kinetic simulation results to predictions from the generalized fluid theory. The results show that ion inertia, anisotropic pressure, finite Larmor radius effects, nonzero ion heat flux, and reflected ions all contribute to the signatures of RDs on kinetic scales. The RDs may have upstream or downstream wave trains, which become weak for high ion beta and small normal components of the magnetic field. We explain the presence and direction of wave trains in terms of the kinetic properties of the Alfven/ion-cyclotron mode. Away from the RD limit there is a smooth transition to weak intermediate shocks, which have small jumps close to expected Rankine-Hugoniot values. Apart from that, there are few kinetic plasma signatures that distinguish RDs from their neighboring ISs. However, noncoplanar ISs evolve in time into thin RDs. Using the properties of RDs and ISs, we make specific suggestions how these discontinuities can be distinguished observationally in the case of an isotropic plasma.

Krauss-Varban, D.↗
DOE OSTI2025

Plasma GFAP for populational enrichment of clinical trials in preclinical Alzheimer's disease

Abstract INTRODUCTION Cognitively unimpaired (CU) amyloid beta (Aβ)+ individuals with elevated plasma glial fibrillary acidic protein (GFAP) have an increased risk of Alzheimer's disease (AD)‐related progression. We tested the utility of plasma GFAP for population enrichment CU populations in clinical trials. METHODS We estimated longitudinal progression, effect size, and costs of hypothetical clinical trials designed to test an estimated 25% drug effect on reducing tau positron emission tomography (PET) accumulation in the medial temporal lobe (MTL) and temporal neocortical region (NEO‐T). RESULTS CU GFAP+/Aβ+ individuals present an increased annual rate of change and effect size in tau PET MTL and tau PET NEO‐T compared to the other groups. An enrichment strategy selecting CU GFAP+/Aβ+ individuals would require a smaller sample size (≈ 57% reduction) and fewer Aβ PET scans (≈ 74% reduction) than trials enriched with Aβ PET alone, reducing total clinical trial costs by up to 64%. DISCUSSION Our results suggest that clinical trials focusing on preclinical AD recruiting Aβ+ individuals with elevated GFAP levels would improve cost effectiveness. Highlights Cognitively unimpaired (CU) glial fibrillary acidic protein (GFAP)+/amyloid beta (Aβ)+ shows increased changes in tau positron emission tomography (PET) . CU GFAP+/Aβ+ enriched clinical trials require a reduced sample size compared to Aβ+ only. CU GFAP+/Aβ+ enrichment reduces Aβ PET scans required and costs. CU GFAP+/Aβ+ enrichment allows the selection of individuals at early stages of the Alzheimer's disease continuum.

Neurosciences & Neurology↗
NASA NTRS1997

Geophysical Characterization of Some Terranes and the Geophysical Modeling of Candidate Suture Zones

Indian participation in this project was terminated during the last year by a sudden withdrawal of support by the Department of Science and Technology, India, to the Indian Institute of Geomagnetism, Bombay. As a result, significant changes in the project focus had to be undertaken. Much of the work carried out at Southern Illinois University at Carbondale during the first year of the project anticipated the Indian participation and included development of computer programs to be used on gravity and magnetic data from the Indian subcontinent and preparations for fieldwork, tutorials, and workshops in India. Despite these setbacks, which were beyond our control, a number of significant tasks have been accomplished during the project period. These include: (1) Completion of digitization of the regional Bouguer gravity anomaly map of India and the regional ground total intensity magnetic anomaly map of India at an overdetermined spacing of 0.05 degrees. (2) We investigated and assessed the limitations of the Euler method using environmental examples because detailed aeromagnetic maps of parts of India were not available for interpretation by this method. (3) We also undertook an assessment of a suture zone between the Nyaza Craton (Archean) and the Mozambique Belt (Pan African) in the Kenya Rift, Africa, using gravity anomalies and the lithospheric seismological models. (4) We studied Magsat and high-altitude (approx. 4 km) aeromagnetic data over Canada.

Ravat, D.↗
DOE OSTI2023

Control of multi-agent systems: Results, open problems, and applications

The purpose of this review article is to present some recent results on the modeling and control of large systems of agents. We focus on particular applications where the agents are capable of independent actions instead of simply reacting to external forces. In the literature, such agents were referred to as autonomous, intelligent, self-propelled, greedy, and others. The main applications we have in mind are social systems (as opinion dynamics), pedestrians’ movements (also called crowd dynamics), animal groups, and vehicular traffic. We note that the last three examples include physical constraints; however, the agents are able to inject energy into the system, thus preventing the typical conservation of momentum and energy. In addition, the control problems posed by such systems are new and require innovative methods. We illustrate some ideas developed recently, including the use of sparse controls, limiting the total variation of controls, and defining new control problems for measures. After reviewing various approaches, we discuss some future research directions of potential interest. The latter encompasses both new types of equations and new types of limiting procedures to connect several scales at which a system can be represented. We conclude by illustrating a recent real-life experiment using autonomous vehicles on an open highway to smooth traffic waves. This opens the door to a new era of interventions to control real-time multi-agent systems and to increase the societal impact of such interventions guided by control research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Integrated charging infrastructure planning and charging scheduling for battery electric bus systems

We report studies on the electric bus system planning problem have typically focused exclusively on either the deployment of charging infrastructure or the scheduling of charging events; few have examined the impact of charging facility deployment on charging activities. Considering the interdependence of system design and operational strategies, this study proposes a two-phase optimization framework for charging infrastructure planning and charging scheduling for battery electric bus systems. An integrated optimization model is first developed to simultaneously optimize charger deployment, on-board battery capacity, and charging schedules. A charging scheduling model is further proposed and a rolling horizon approach is utilized in the second phase to optimize the real-time charging scheduling of electric buses. Compared to existing electric bus system planning methods, the proposed integrated model can reduce the total system cost by 19.5%. In addition, compared to uncontrolled charging, the proposed rolling horizon-based charging strategy can reduce the total charging cost by 68.3%.

25 ENERGY STORAGE↗
DOE OSTI2024

Development of 211 At production at Crocker Nuclear Laboratory (Final Technical Report)

The focus of this effort was the development of the capability to produce and recover 211 At via the process 209 Bi(α, 2n) 211 At at the cyclotron at the Crocker Nuclear Laboratory at UC Davis. This effort required the design and fabrication of an internal production target, the development of a separation and processing area, and upgrades to the cyclotron to increase its reliability. There was a significant delay due to the pandemic lockdown, but ultimately we were able to produce and recover 211 At at the tens of µCi level using a wet chemistry method. Results of the project were presented at conference, but publication of a refereed article has been delayed by some discrepancies in understanding the calibration of total 211 At produced. We plan to repeat the production using internal funding, but first we want to revise our recovery to use a different technique, developed at the Texas A& M Cyclotron Institute.

07 ISOTOPE AND RADIATION SOURCES↗