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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics

Process optimization of photovoltaic devices is a time-intensive, trial-and-error endeavor, which lacks full transparency of the underlying physics and relies on user-imposed constraints that may or may not lead to a global optimum. Herein, we demonstrate that embedding physics domain knowledge into a Bayesian network enables an optimization approach for gallium arsenide (GaAs) solar cells that identifies the root cause(s) of underperformance with layer-by-layer resolution and reveals alternative optimal process windows beyond traditional black-box optimization. Our Bayesian network approach links a key GaAs process variable (growth temperature) to material descriptors (bulk and interface properties, e.g., bulk lifetime, doping, and surface recombination) and device performance parameters (e.g., cell efficiency). For this purpose, we combine a Bayesian inference framework with a neural network surrogate device-physics model that is 100× faster than numerical solvers. With the trained surrogate model and only a small number of experimental samples, our approach reduces significantly the time-consuming intervention and characterization required by the experimentalist. As a demonstration of our method, in only five metal organic chemical vapor depositions, we identify a superior growth temperature profile for the window, bulk, and back surface field layer of a GaAs solar cell, without any secondary measurements, and demonstrate a 6.5% relative AM1.5G efficiency improvement above traditional grid search methods.

14 SOLAR ENERGY↗
DOE OSTI2024

Accelerating the design of lattice structures using machine learning

Lattices remain an attractive class of structures due to their design versatility; however, rapidly designing lattice structures with tailored or optimal mechanical properties remains a significant challenge. With each added design variable, the design space quickly becomes intractable. To address this challenge, research efforts have sought to combine computational approaches with machine learning (ML)-based approaches to reduce the computational cost of the design process and accelerate mechanical design. While these efforts have made substantial progress, significant challenges remain in (1) building and interpreting the ML-based surrogate models and (2) iteratively and efficiently curating training datasets for optimization tasks. Here, we address the first challenge by combining ML-based surrogate modeling and Shapley additive explanation (SHAP) analysis to interpret the impact of each design variable. We find that our ML-based surrogate models achieve excellent prediction capabilities (R 2 > 0.95) and SHAP values aid in uncovering design variables influencing performance. We address the second challenge by utilizing active learning-based methods, such as Bayesian optimization, to explore the design space and report a 5 × reduction in simulations relative to grid-based search. Collectively, these results underscore the value of building intelligent design systems that leverage ML-based methods for uncovering key design variables and accelerating design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

nEXO Team Active Georgetown University: Systems Integration and Test

The nEXO experiment is the “next” tonne-scale enriched xenon observatory which will be fielded deep underground to search for neutrinoless double-beta decay. The observation of neutrinoless double-beta decay is important to the low-energy physics community, and confirmation of the phenomenon will allow physicists to extend current physics models and propose new theories for the evolution of matter in our universe.

42 ENGINEERING↗
DOE OSTI2024

Finding ways to reduce nuclear waste: searching for the unknown one step at a time

In my home country, Venezuela, research has been stagnant. Due to the political turmoil and the crisis, many educated people have left the country in search for a better life. This has caused a deficit in any technological and scientific advances, making Venezuela one of the first South American countries to have its rate of publications decline by 29% in 2013. Currently, Venezuela lacks the infrastructure and the means to keep up with the research progress as compared to other countries in South America, such as Brazil. Since coming to the United States (US), and currently working for a national laboratory, the active research environment endorses a wide range of careers and engineering programs that allow researchers to thrive at any given field. Researchers have access to funds and tools to succeed in developing materials for the future. There are 17 national laboratories in the US, and all of these have a different research focus/objective. As examples, Los Alamos National Laboratory and Sandia National Laboratory focus is on national homeland security, weapon science, radiation effects, among others. Argonne National Laboratory focuses on nuclear energy, energy storage, high performance computing, etc. At Idaho National Laboratory (INL) the research focuses on innovating nuclear energy and clean energy resources, critical infrastructure materials, along with fuel cycle solutions to manage, dispose and find ways to recycle current and future radiological waste. Compared to other national laboratories, INL focuses slightly more on applied processes and how nuclear energy can be innovated to next reactor design and technologies. The research being conducted at INL made me apply for a Seaborg distinguished postdoctoral position. For the position itself, the researcher must submit a proposal related to actinide chemistry on a research field area. In this position, 50% of my time will be focused on my own proposal. The proposal that I am working on is focused on the innovation of nuclear energy and fuel cycle recycling, which is why I was mainly interested on working at this national laboratory. To give a bit more context of what my proposal is about, a little bit of background is necessary: After the nuclear fuel (UO2) is used in a reactor, the fuel matrix is then characterized by various fission products (FP). Among these FP (including rare earth elements, alkali/alkaline earths, and actinides), many can potentially be recovered through nuclear reprocessing technologies. In pyroprocessing, the used nuclear fuel undergoes electrochemical dissolution into a molten chloride salt mixture in an electrorefiner. Initially, uranium is reduced onto an inert cathode by applied potentials. However, numerous remaining FPs accumulate in the melt and pose challenges for recovery by an inert electrode, particularly the rare earth elements (e.g., Nd, Gd, Pr, Sm) due to their multivalent oxidation states and tendencies toward side reactions, leading to their dissolution in the electrolyte. These recovery challenges result in inefficiencies and necessitate the continual discarding of the molten chloride salt, thereby generating additional waste. Furthermore, the presence of rare earth elements and other fission products in the molten salt electrolyte alters its physical and chemical properties, affecting both uranium recovery efficiency and the longevity of the molten chloride salt. To improve the recovery efficiency of the FP, specifically rare earth elements, I am investigating the fundamental interactions between rare earth elements in the molten chloride salt and their metallic form. The kinetic pathways and the chemical reactions of these elements will give insights on how the recovery efficiency can be improved. The interactions and speciation of these elements are being studied by spectro-electrochemistry at high temperature environments in quartz and other ceramic materials (e.g., alumina crucibles). Some of the challenges I am facing specifically relates the reactivity of some of these elements with different glass and crucible materials. Although my research focuses on fundamental science, it will benefit the applied process by generating new scientific knowledge and closing the gap for an efficient recycling of the waste: one step at a time.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Rapid design of top-performing metal-organic frameworks with qualitative representations of building blocks

Abstract Data-driven materials design often encounters challenges where systems possess qualitative (categorical) information. Specifically, representing Metal-organic frameworks (MOFs) through different building blocks poses a challenge for designers to incorporate qualitative information into design optimization, and leads to a combinatorial challenge, with large number of MOFs that could be explored. In this work, we integrated Latent Variable Gaussian Process (LVGP) and Multi-Objective Batch-Bayesian Optimization (MOBBO) to identify top-performing MOFs adaptively, autonomously, and efficiently. We showcased that our method (i) requires no specific physical descriptors and only uses building blocks that construct the MOFs for global optimization through qualitative representations, (ii) is application and property independent, and (iii) provides an interpretable model of building blocks with physical justification. By searching only ~1% of the design space, LVGP-MOBBO identified all MOFs on the Pareto front and 97% of the 50 top-performing designs for the CO 2 working capacity and CO 2 /N 2 selectivity properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Event Detection System in the NEXT-White Detector

This article describes the event detection system of the NEXT-White detector, a 5 kg high pressure xenon TPC with electroluminescent amplification, located in the Laboratorio Subterráneo de Canfranc (LSC), Spain. The detector is based on a plane of photomultipliers (PMTs) for energy measurements and a silicon photomultiplier (SiPM) tracking plane for offline topological event filtering. The event detection system, based on the SRS-ATCA data acquisition system developed in the framework of the CERN RD51 collaboration, has been designed to detect multiple events based on online PMT signal energy measurements and a coincidence-detection algorithm. Implemented on FPGA, the system has been successfully running and evolving during NEXT-White operation. The event detection system brings some relevant and new functionalities in the field. A distributed double event processor has been implemented to detect simultaneously two different types of events thus allowing simultaneous calibration and physics runs. This special feature provides constant monitoring of the detector conditions, being especially relevant to the lifetime and geometrical map computations which are needed to correct high-energy physics events. Other features, like primary scintillation event rejection, or a double buffer associated with the type of event being searched, help reduce the unnecessary data throughput thus minimizing dead time and improving trigger efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A Nonlocal-Gradient Descent Method for Inverse Design in Nanophotonics

Local-gradient-based optimization approaches lack nonlocal exploration abilityrequired for escaping from local minima when searching non-convex landscapes.A directional Gaussian smoothing (DGS) approach was recently proposed in [29]and used to define a truly nonlocal gradient, referred to as the DGS gradient, inorder to enable nonlocal exploration in high-dimensional black-box optimization.Promising results show that replacing the traditional local gradient with the nonlocalDGS gradient can significantly improve the performance of gradient-based methodsin optimizing highly multi-modal loss functions. However, the current DGS methodis designed for unbounded and uncontrained optimization problems, making itinapplicable to real-world engineering optimization problems where the tuningparameters are often bounded and the loss function is usually constrained byphysical processes. In this work, we propose to extend to the DGS approachto the constrained inverse design framework in order to find better optima ofmulti-modal loss functions. A series of adaptive strategies for smoothing radiusand learning rate updating are developed to improve the computational efficiencyand robustness. Our methodology is demonstrated by an example of designing ananoscale wavelength demultiplexer, and shows superior performance compared tothe state-of-the-art approaches. By incorporating volume constraints, the optimizeddesign achieves an equivalently high performance but significantly reduces theamount of material usage.

Bi, Sirui↗
DOE OSTI2022

Engineering magnetic topological insulators in Eu 5 M 2 X 6 Zintl compounds

Magnetic topological insulators provide a prominent material platform for quantum anomalous Hall physics and axion electrodynamics. However, the lack of material realizations with cleanly gapped surfaces hinders technological utilization of these exotic quantum phenomena. Here, using the Zintl concept and the properties of nonsymmorphic space groups, we computationally engineer magnetic topological insulators. Specifically, we explore Eu 5 M 2 X 6 (M=metal, X=pnictide) Zintl compounds and find that Eu 5 Ga 2 Sb 6 , Eu 5 Tl 2 Sb 6 , and Eu 5 In 2 Bi 6 form stable structures with nontrivial Z 2 indices. We also show that epitaxial and uniaxial strain can be used to control the Z 2 index and the bulk energy gap. Lastly, we discuss experimental progress towards the synthesis of the proposed candidates and provide insights that can be used in the search for robust magnetic topological insulators in Zintl compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Survey of the Worldwide Supply Chain of Commodities Needed for a Quantum Technology Program

Quantum Information Science (QIS) is an emerging technology being pursued by fundamental science research groups worldwide, as well as commercial companies and government programs. There are a variety of QIS disciplines, including quantum computing, quantum sensing and quantum encryption. Some of the commodities needed for a robust quantum laboratory are particular to quantum phenomenon, but in general the equipment needed is similar to that needed for a typical high - technology lab (e.g. oscilloscopes, lasers, vacuum chambers, etc.). This study focuses on identifying commodities manufactured worldwide that would be needed for a robust quantum lab. The authors' own knowledge of needed equipment and primary vendors was used as a starting point, follow ed by extensive internet searching and utilization of buyer's guides to create a large spreadsheet of most of the components needed, the company offering the components, and country of manufacture. With this extensive spreadsheet, stakeholders can identify commodities that would be needed for a quantum lab oratory and potentially identify market choke points.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Colossal Cryogenic Electro‐Optic Response Through Metastability in Strained BaTiO 3 Thin Films

The search for thin film electro-optic materials that can retain superior performance under cryogenic conditions has become critical for quantum computing. Barium titanate thin films show large linear electro-optic coefficients in the tetragonal phase at room temperature, which is severely degraded down to ≈200 pm V −1 in the rhombohedral phase at cryogenic temperatures. There is immense interest in manipulating these phase transformations and retaining superior electro-optic properties down to liquid helium temperature. Utilizing the thermodynamic theory of optical properties, a large low-temperature electro-optic response is designed by engineering the energetic competition between different ferroelectric phases, leading to a low-symmetry monoclinic phase with a massive electro-optic response. The existence of this phase is demonstrated in a strain-tuned BaTiO 3 thin film that exhibits a linear electro-optic coefficient of 2516 ± 100 pm V −1 at 5 K, which is an order of magnitude higher than the best reported performance thus far. Importantly, the electro-optic coefficient increases by 100 × during cooling, unlike the conventional films, where it degrades. Further, at the lowest temperature, significant higher order electro-optic responses also emerge. These results represent a new framework for designing materials with property enhancements by stabilizing highly tunable metastable phases with strain.

barium titanate↗
DOE OSTI2023

Postdisaster Routing of Movable Energy Resources for Enhanced Distribution System Resilience: A Deep Reinforcement Learning-Based Approach

The deployment of movable energy resources (MERs) can be an effective strategy to restore critical loads to enhance power system resilience when no other energy sources are available after the occurrence of an extreme event. Since the optimal locations of MERs following an extreme event are dependent on system operating states (e.g., the loads at each node, on/off status of system branches, and so on), existing analytical and population-based approaches must repeat the entire analysis and calculation when the system operating states change. On the contrary, if deep reinforcement learning (DRL)-based algorithms are sufficiently trained with a wide range of scenarios, they can quickly find optimal or near-optimal locations irrespective of changes in system states. A deep Q-learning-based approach is proposed for optimal MER deployment to enhance power system resilience. MERs can be also utilized to complement other types of resources, if available. The proposed approach operates in two stages after the occurrence of extreme events. In the first stage, the distribution network is represented as a graph, and the network is then reconfigured using tie switches by using Kruskal’s spanning forest search algorithm (KSFSA). To maximize critical load recovery, the optimal or near-optimal locations of MERs are chosen in the second stage. Further, case studies on a 33-node distribution system and a modified IEEE 123-node system demonstrate the effectiveness of the proposed approach for postdisaster routing of MERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Progress from ASDEX Upgrade experiments in preparing the physics basis of ITER operation and DEMO scenario development

An overview of recent results obtained at the tokamak ASDEX Upgrade (AUG) is given. A work flow for predictive profile modelling of AUG discharges was established which is able to reproduce experimental H-mode plasma profiles based on engineering parameters only. In the plasma center, theoretical predictions on plasma current redistribution by a dynamo effect were confirmed experimentally. For core transport, the stabilizing effect of fast ion distributions on turbulent transport is shown to be important to explain the core isotope effect and improves the description of hollow low-Z impurity profiles. The L–H power threshold of hydrogen plasmas is not affected by small helium admixtures and it increases continuously from the deuterium to the hydrogen level when the hydrogen concentration is raised from 0 to 100%. One focus of recent campaigns was the search for a fusion relevant integrated plasma scenario without large edge localised modes (ELMs). Results from six different ELM-free confinement regimes are compared with respect to reactor relevance: ELM suppression by magnetic perturbation coils could be attributed to toroidally asymmetric turbulent fluctuations in the vicinity of the separatrix. Stable improved confinement mode plasma phases with a detached inner divertor were obtained using a feedback control of the plasma β. The enhanced D α H-mode regime was extended to higher heating power by feedback controlled radiative cooling with argon. The quasi-coherent exhaust regime was developed into an integrated scenario at high heating power and energy confinement, with a detached divertor and without large ELMs. Small ELMs close to the separatrix lead to peeling-ballooning stability and quasi continuous power exhaust. Helium beam density fluctuation measurements confirm that transport close to the separatrix is important to achieve the different ELM-free regimes. Based on separatrix plasma parameters and interchange-drift-Alfvén turbulence, an analytic model was derived that reproduces the experimentally found important operational boundaries of the density limit and between L- and H-mode confinement. Feedback control for the X-point radiator (XPR) position was established as an important element for divertor detachment control. Stable and detached ELM-free phases with H-mode confinement quality were obtained when the XPR was moved 10 cm above the X-point. Investigations of the plasma in the future flexible snow-flake divertor of AUG by means of first SOLPS-ITER simulations with drifts activated predict beneficial detachment properties and the activation of an additional strike point by the drifts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Metal Alloy and RHEA Additive Manufacturing for Nuclear Energy and Aerospace Applications

An open-literature search was conducted to consider the current status of the additive manufacturing (AM) industry with respect to metal alloys and refractory high entropy alloys (RHEAs). Key areas of interest include methodologies and applications that are suitable for the nuclear and aerospace industries, as well as other industrial applications. We investigated various promising 3D metal technologies, with emphasis on cost, operation, throughput, maintenance, and output volume size. In addition, technical issues and the current status of the metal printing market are summarized. The project scope also included the manufacturing of open-literature RHEA test coupons at Sandia's laser engineered net shape (LENS) machine.

36 MATERIALS SCIENCE↗
DOE OSTI2024

CRISPR-COPIES: an in silico platform for discovery of neutral integration sites for CRISPR/Cas-facilitated gene integration

Abstract The CRISPR/Cas system has emerged as a powerful tool for genome editing in metabolic engineering and human gene therapy. However, locating the optimal site on the chromosome to integrate heterologous genes using the CRISPR/Cas system remains an open question. Selecting a suitable site for gene integration involves considering multiple complex criteria, including factors related to CRISPR/Cas-mediated integration, genetic stability, and gene expression. Consequently, identifying such sites on specific or different chromosomal locations typically requires extensive characterization efforts. To address these challenges, we have developed CRISPR-COPIES, a COmputational Pipeline for the Identification of CRISPR/Cas-facilitated intEgration Sites. This tool leverages ScaNN, a state-of-the-art model on the embedding-based nearest neighbor search for fast and accurate off-target search, and can identify genome-wide intergenic sites for most bacterial and fungal genomes within minutes. As a proof of concept, we utilized CRISPR-COPIES to characterize neutral integration sites in three diverse species: Saccharomyces cerevisiae, Cupriavidus necator, and HEK293T cells. In addition, we developed a user-friendly web interface for CRISPR-COPIES (https://biofoundry.web.illinois.edu/copies/). We anticipate that CRISPR-COPIES will serve as a valuable tool for targeted DNA integration and aid in the characterization of synthetic biology toolkits, enable rapid strain construction to produce valuable biochemicals, and support human gene and cell therapy applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Nuclear Sciences References (NSR)

Nuclear Science literature database, containing about 250,000 articles covering more than 120 years of nuclear science research. Approximately 80 journals are routinely scanned for relevant articles; it also includes PhD thesis and private communications. Each article in NSR is assigned a distinctive 8-character primary key, known as ‘key number’, and a set of keywords that briefly describe the article's content. These keywords follow strict rules since they are used in web search forms. Typically, an article is incorporated in NSR within a few weeks after its web publication. About 4,000 articles are added per year. All the compilation effort is supported by the US Nuclear Data Program and coordinated by the National Nuclear Data Center at Brookhaven National Laboratory, which is also responsible for its web dissemination.

Basic Nuclear Research, Applied Nuclear Technologi↗
DOE OSTI2022

Pair Invariant Mass to Isolate Background in the Search for the Chiral Magnetic Effect in Au+Au Collisions at √sNN = 200 GeV

Quark interactions with topological gluon configurations can induce local chirality imbalance and parity violation in quantum chromodynamics, which can lead to the chiral magnetic effect (CME)-an electric charge separation along the strong magnetic field in relativistic heavy-ion collisions. The CME-sensitive azimuthal correlator observable (Delta gamma) is contaminated by background arising, in part, from resonance decays coupled with elliptic anisotropy (v(2)). We report here differential measurements of the correlator as a function of the pair invariant mass (m(inv)) in 20-50% centrality Au + Au collisions at root s(NN) = 200 GeV by the STAR experiment at the BNL Relativistic Heavy Ion Collider. Strong resonance background contributions to Delta gamma. are observed. At large m(inv) where this background is significantly reduced, the Delta gamma. value is found to be significantly smaller. An event-shape-engineering technique is deployed to determine the v(2) background shape as a function of m(inv). We extract a v(2)-independent and m(inv)-averaged signal Delta gamma(sig) = (0.03 +/- 0.06 +/- 0.08) x 10(-4), or (2 +/- 4 +/- 5)% of the inclusive Delta gamma (m(inv) > 0.4 GeV/c(2)) = (1.58 +/- 0.02 +/- 0.02) x 10(-4), within pion p(T) = 0.2-0.8 GeV/c and averaged over pseudorapidity ranges of -1 < eta < -0.05 and 0.05 < eta < 1. This represents an upper limit of 0.23 x 10(-4), or 15% of the inclusive result, at 95% confidence level for the m(inv)-integrated CME contribution.

Adam, J.↗
DOE OSTI2024

Spectacular Nucleosynthesis from Early Massive Stars

Abstract Stars that formed with an initial mass of over 50 M ⊙ are very rare today, but they are thought to be more common in the early Universe. The fates of those early, metal-poor, massive stars are highly uncertain. Most are expected to directly collapse to black holes, while some may explode as a result of rotationally powered engines or the pair-creation instability. We present the chemical abundances of J0931+0038, a nearby low-mass star identified in early follow-up of the SDSS-V Milky Way Mapper, which preserves the signature of unusual nucleosynthesis from a massive star in the early Universe. J0931+0038 has a relatively high metallicity ([Fe/H] = −1.76 ± 0.13) but an extreme odd–even abundance pattern, with some of the lowest known abundance ratios of [N/Fe], [Na/Fe], [K/Fe], [Sc/Fe], and [Ba/Fe]. The implication is that a majority of its metals originated in a single extremely metal-poor nucleosynthetic source. An extensive search through nucleosynthesis predictions finds a clear preference for progenitors with initial mass >50 M ⊙ , making J0931+0038 one of the first observational constraints on nucleosynthesis in this mass range. However, the full abundance pattern is not matched by any models in the literature. J0931+0038 thus presents a challenge for the next generation of nucleosynthesis models and motivates the study of high-mass progenitor stars impacted by convection, rotation, jets, and/or binary companions. Though rare, more examples of unusual early nucleosynthesis in metal-poor stars should be found in upcoming large spectroscopic surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Mortality among workers at the Los Alamos National Laboratory, 1943–2017

During World War II (WWII), the Manhattan Engineering District established a secret laboratory in the mountains of northern New Mexico. The mission was to design, construct and test the first atomic weapon, nicknamed ‘The Gadget’ that was detonated at the TRINITY site in Alamogordo, NM. After WWII, nuclear weapons research continued, and the laboratory became the Los Alamos National Laboratory (LANL). The mortality experience of 26,328 workers first employed between 1943 and 1980 at LANL was determined through 2017. Included were 6157 contract workers employed by the ZIA Company. Organ dose estimates for each worker considered all sources of exposure, notably photons, neutrons, tritium, 238Pu and 239Pu. Vital status determination included searches within the National Death Index, Social Security Administration and New Mexico State Mortality Files. Standardized Mortality Ratios (SMR) and Cox regression models were used in the analyses. Most workers (55%) were hired before 1960, 38% had a college degree, 25% were female, 81% white, 13% Hispanic and 60% had died. Vital status was complete, with only 0.1% lost to follow-up. The mean dose to the lung for the 17,053 workers monitored for radiation was 28.6 weighted-mGy (maximum 16.8 weighted-Gy) assuming a Dose Weighting Factor of 20 for alpha particle dose to lung. The Excess Relative Risk (ERR) at 100 weighted-mGy was 0.01 (95%CI -0.02, 0.03; n = 839) for lung cancer. The ERR at 100 mGy was -0.43 (95%CI -1.11, 0.24; n = 160) for leukemia other than chronic lymphocytic leukemia (CLL), -0.06 (95%CI -0.16, 0.04; n = 3043) for ischemic heart disease (IHD), and 0.29 (95%CI 0.02, 0.55; n = 106) for esophageal cancer. Among the 6499 workers with measurable intakes of plutonium, an increase in bone cancer (SMR 2.44; 95%CI 0.98, 5.03; n = 7) was related to dose. The SMR for berylliosis was significantly high, based on 4 deaths. SMRs for Hispanic workers were significantly high for cancers of the stomach and liver, cirrhosis of the liver, nonmalignant kidney disease and diabetes, but the excesses were not related to radiation dose. There was little evidence that radiation increased the risk of lung cancer or leukemia. Esophageal cancer was associated with radiation, and plutonium intakes were linked to an increase of bone cancer. IHD was not associated with radiation dose. More precise evaluations will await the pooled analysis of workers with similar exposures such as at Rocky Flats, Savannah River and Hanford.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗