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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Requirements on the gain calibration for LiteBIRD polarisation data with blind component separation

The detection of primordial B modes of the cosmic microwave background (CMB) could provide information about the early stages of the Universe's evolution. The faintness of this signal requires exquisite calibration accuracy and control of instrumental systematic effects which otherwise could bias the measurements. In this work, we study the impact of an imperfect relative polarisation gain calibration on the recovered value of the tensor-to-scalar ratio r for the LiteBIRD experiment, through the application of the blind Needlet Internal Linear Combination (NILC) foreground-cleaning method. We derive requirements on the relative calibration accuracy of the overall polarisation gain (Δg ν ) for each LiteBIRD frequency channel. Our results show that minimum variance techniques, as NILC, are less sensitive to systematic gain calibration uncertainties compared to a parametric approach, if the latter is not equipped with a proper modelling of these instrumental effects. In this study, the most stringent requirements are found in the channels where the CMB signal is relatively brighter, with the tightest constraints at 166 GHz (Δg ν ≈ 0.16%). This differs from the outcome of an analogous analysis performed with a parametric method, where the tightest requirements are obtained for the foreground-dominated channels. Gain calibration uncertainties, corresponding to the derived requirements, are then simultaneously propagated into all frequency channels. By doing so, we find that the overall impact on estimated r is lower than the total gain systematic budget for LiteBIRD approximately by a factor 5, due to the correlations of the impacts of gain calibration uncertainties in different frequency channels. In order to decouple the systematic effect from the specific choice of the model, we derive the requirements assuming constant spectral parameters for the foreground emission. To assess the robustness of the obtained results against more realistic scenarios, we repeat the analysis assuming sky models of intermediate and high complexity. In these further cases, we adopt an optimised NILC pipeline, called the Multi-Clustering NILC (MC-NILC). We find that the impact of gain calibration uncertainties on r is lower than the LiteBIRD gain systematics budget for the intermediate-complexity sky model. For the high-complexity case, instead, it would be necessary to tighten the requirements by a factor 1.8.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Co-design of Advanced Architectures for Graph Analytics using Machine Learning

A graph is an excellent way of representing relationships among entities. We can use graph analytics to synthesize and analyze such relational data, and extract relevant features that are useful for various tasks such as machine learning. Considering the crucial role of graph analytics in various domains, it is important and timely to investigate the right hardware configurations that can achieve optimal performance for graph workloads on future high-performance computing systems. Design space exploration studies facilitate the selection of appropriate configurations (e.g. memory) to achieve a desired system performance. Recently, the approach of accelerating graph analytics using persistent non-volatile memory has gained a lot of attention. Traditional system simulators such as Gem5 and NVMain can be used to explore the design space of these advanced memory architectures for graph workloads. However, these simulators are slow in execution thus limiting the efficiency of design space exploration studies. To overcome this challenge, we proposed a machine learning based approach to co-design advanced memory architectures for graph workloads. We tested our approach with DRAM, non-volatile memory, and hybrid memory (DRAM+NVM) using a breadth first search benchmark algorithm. Our results showed the applicability of the proposed machine learning based approach to the co-design of the advanced memory architectures. In this paper, we provide recommendations on selecting advanced memory architectures to achieve desired performance for graph workloads. We also discuss the performances of different machine learning models that were considered in this study.

Kurte, Kuldeep↗
DOE OSTI2020

Quantifying Occupant Health and Productivity for Deep Retrofits: Beyond Traditional IEQ Studies

As energy-efficiency standards for both new construction and existing building renovations become more stringent, further reductions become less tractable and more expensive. With increasing interest and rising investment in healthy built environments, integrating energy efficiency with improved occupant experience (i.e., health, comfort, and work performance) offers a new path to drive deep energy retrofits. However, the difficulty in quantifying and verifying health and productivity gains from building upgrades leads to lower valuation of human benefits in practice. Building codes and standards have progressive energy targets but often give minimum requirements to occupant health for factors such as ventilation and thermal comfort. State and federal laws in the United States that govern the energy service performance contract (ESPC) have no clear and consistent guidance on quantifying non-energy benefits and incorporating them into a formal cost-effectiveness analysis. This paper presents a methodology to measure a building’s potential performance improvement regarding occupant health based on existing evidence correlating IEQ to occupant outcomes. Health improvement measures are integrated with a building energy model to identify and measure the impact of holistic improvement strategies. The net present value of these measures is determined based on the investment costs required to attain those improvements, energy savings, and personnel gains. We will discuss results from one pilot building, which showed nearly $50 per square foot 20-year net present value using the integrated approach.

Keene, Kevin M.↗
DOE OSTI2023

The Regenerative Current Mirror: A Very Low Power Front-End Amplifier for Silicon Pixel Detectors

In pixelized detectors, reducing power consumption in the front- end ASIC chips becomes a crucial demand. Optimization based on mature pre-amplifier schemes today is unlikely to bring sufficient improvements. A new CMOS front-end gain stage topology with very low power consumption called regenerative current mirror is developed to fulfill the demand. The circuit takes advantage of high-speed performance of current amplification while operating with relatively low bias current. The regenerative current mirror uses a NMOS current mirror and a PMOS current mirror, both with nominal gain of 1, to form a loop-back topology that provides a positive feedback. An NMOS FET with an external adjustable voltage applied to it gate terminal is used to limit open loop gain of the current mirrors to be slightly lower than 1. This yields a net gain of the positive feedback loop to be much larger than 1 while operating the current mirrors under relatively low bias currents. Simulation shows that in 65 nm fabrication process, the power consumption of the gain stages suitable for silicon pixel detectors can be controlled < 10 micro-Watts per channel. Another novel low-power circuit called Pseudo-Thyristor presented in another document will replace traditional discriminator and the Regenerative Current Mirror plus Pseudo- Thyristor will provide a full solution for the silicon pixel low-power frontend ASIC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Co-optimization of fuel properties, combustion system geometry, and injection strategy for conventional diesel fuel

Here, studies have shown that fuel properties can impact an engine’s operation in several ways, including ignition delay, sooting tendency, mixture formation, and combustion temperature. In mixing-controlled compression ignition (MCCI) engines, the fuel system design and piston bowl geometry significantly affect combustion performance and emissions. Based on current information, it is difficult to draw conclusions about fuel property effects and sensitivities. The central fuel hypothesis approach used in the US Department of Energy Co-Optima program has worked well for spark ignition fuels: identifying critical fuel property ranges is sufficient to screen fuel blends that are expected to maximize efficiency and reduce pollutant emissions. However, for MCCI-relevant fuels, the information gained from past studies is not sufficient to build such a merit function or to allow for performing a similar screening of fuel blends. It is hypothesized that a co-optimization of a fuel’s physical and chemical properties, combustion system geometry, and injection strategy could leverage synergies between the effects of the fuel properties and geometries, resulting in improved performance over state-of-the-art. A machine learning–assisted unconstrained global optimization algorithm was used to explore a design space comprising 23 independent variables. The results show that physical property effects were minimal even for large variations in fuel properties, and the only interaction effect that was observed was the effect of varied fuel density parameters on fuel/air mixture formation. Nevertheless, these interactions were not sufficient in magnitude to significantly affect optimization results. Therefore, analysis of the results suggests that fuel physical properties cannot be leveraged in a co-optimization context to increase engine efficiency.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Laser-plasma instabilities in long scale-length plasmas relevant to shock-ignition

We present 2D particle-in-cell simulations of laser-plasma instabilities (LPI) performed using conditions relevant to experiments on the OMEGA and NIF laser facilities. The laser intensity used is 2×10 15 W cm -2 , which allows comparison with previous experiments and simulations investigating shock ignition, though this is a relatively low intensity for the scheme. We find that the large convective gain of the instabilities leads to dynamics that are largely controlled by pump depletion and to scattering or absorption by LPIs predominantly occurring away from the quarter-critical density. The two-plasmon decay (TPD) instability is dominant for OMEGA-type conditions and remains important at the NIF-scale. In both cases, most absorption from TPD occurs near its Landau cutoff density, and we examine its nonlinear dynamics in this region, focusing on the ion-acoustic waves responsible for saturation. For NIF-type conditions, stimulated Raman scattering (SRS) and stimulated Brillouin scattering divert significant fractions of laser energy, and we find that SRS backscatter can occur with high gain at low densities due to kinetic effects. An in-depth analysis of hot-electron production is performed to identify the main sources and their characteristic electron temperature. For both simulations presented, the overall hot-electron temperature lies between 30 and 35 keV. This is relatively low and will likely increase shock pressure; however, the distributions also contain a significant number of high-energy (E k >100 keV) electrons that would likely cause unacceptable preheat. We, therefore, suggest some strategies that may be utilized to minimize this high-energy component. I. INTROD

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Core performance predictions in projected SPARC first-campaign plasmas with nonlinear CGYRO

This work characterizes the core transport physics of SPARC early-campaign plasmas using the PORTALS-CGYRO framework. Empirical modeling of SPARC plasmas with L-mode confinement indicates an ample window of breakeven (Q > 1) without the need of H-mode operation. Extensive modeling of multi-channel (electron energy, ion energy, and electron particle) flux-matched conditions with the nonlinear CGYRO code for turbulent transport coupled to the macroscopic plasma evolution using PORTALS reveals that the maximum fusion performance to be attained will be highly dependent on the near-edge pressure. Stiff core transport conditions are found, particularly when fusion gain approaches unity, and predicted density peaking is found to be in line with empirical databases of particle source-free H-modes. Impurity optimization is identified as a potential avenue to increase fusion performance while enabling core-edge integration. Extensive validation of the quasilinear TGLF model builds confidence in reduced-model predictions. The implications of projecting L-mode performance to high-performance and burning-plasma devices is discussed, together with the importance of predicting edge conditions.

Rodriguez-Fernandez, P. (ORCID:0000000273611131)↗
DOE OSTI2022

High Efficiency InGaN LEDs Emitting in Green, Amber and Beyond (Final Report)

This project focuses on developing high efficiency light emitting diodes (LEDs) with green, amber, and longer wavelengths using two compatible material systems based on III-nitride and II-IV-nitride semiconductor heterostructures. The proposed approach uses low-indium-content InGaN and ZnGeN 2 or ZnSnN 2 heterostructure quantum wells (QWs) as the active regions for high efficiency green and amber LEDs, and therefore to advance high efficiency color-mixed white LED technology. This approach takes advantage of the increased flexibility, afforded by the incorporation of the II-IV-nitrides into the III-nitride layers, to tune the QW active region to lower the emission wavelengths and to increase the electron-hole wave function overlap. This strategy paves a new way to extend the InGaN QW LED emission wavelength without using high-indium-content InGaN. An industrially preferable metalorganic chemical vapor deposition (MOCVD) method was used to develop the growth of ZnGeN 2 and ZnSnN 2 that are compatible with the InGaN growth. The unique dual chamber MOCVD instrument at OSU was used in this project. This program created an opportunity for the two institutions (The Ohio State University and Case Western Reserve University) with complementary expertise to perform this work. Two graduate students (Md Rezaul Karim (OSU) and Benthara Hewage Dinushi Jayatunga (CWRU)) gained experience in MOCVD growth and various characterization methods including scanning electron microscopy, x-ray diffraction spectroscopy, x-ray photoemission spectroscopy, Hall measurements, cathodoluminescence and photoluminescence. Both students successfully defended their PhD dissertations in April/May 2021. Both Karim and Jayatunga have joined Intel as engineers in June/July 2021. Another two graduate students Kaitian Zhang (OSU) and Chenxi Hu (CWRU) joined the project team since spring 2021 to continue on this project. They were trained on MOCVD epitaxy of InGaN QWs and materials characterization including SEM, AFM, PL, CL, XRD, Hall measurements and electroluminescence. A third student, Vijay Gopal Thirupakuzi Vangipuram (OSU), who joined the group in fall 2021 to perform LED fabrication and characterization. The key research accomplishments of the project include: (1) Successful development of MOCVD epitaxy of single crystalline ZnGeN 2 and ZnSnN 2 . MOCVD growth parameters that determine the stoichiometry of ZnGeN 2 and ZnSnN 2 films were identified. (2) Experimentally determined the band offsets between GaN/ZnGeN 2 and GaN/ZnGaSnN 2 hetero-interfaces, which agree very well with the theoretical predictions. (3) Demonstrated the incorporation of thin ZnGeN 2 layer in InGaN QWs. Proof-of-concept of the InGaN-ZnGeN 2 QW design demonstrated as much as 80 nm of red shift without increasing In composition or QW thickness. (4) InGaN/ZnGeN 2 QWs emitting at 480 nm achieved IQE of 47%. Resulted from this project, 7 journal articles were published, and 9 conference papers were presented.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The physics of gain relevant to inertial fusion energy target designs

In inertial confinement fusion, pellets of deuterium tritium fuel are compressed and heated to the conditions where they undergo fusion and release energy. The target gain (ratio of energy released from the fusion reactions to the energy in the drive source) is a key parameter in determining the power flow and economics of an inertial fusion energy (IFE) power plant. In this study, the physics of gain is explored for laser-direct-drive targets with driver energy at the megajoule scale. This analysis is performed with the assumption of next-generation laser technologies that are expected to increase convergent drive pressures to over 200 Mbar. This is possible with the addition of bandwidth to the laser spectrum and by employing focal-spot zooming. Simple physics arguments are used to derive scaling laws that describe target gain as a function of laser energy, adiabat, ablation pressure, and implosion velocity. Scaling laws are found for the unablated mass, ablation pressure, areal density, implosion velocity, and in-flight aspect ratio. Furthermore, those scaling laws are then used to explore the design space for IFE targets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Validation of (not-historical) large-event near-fault ground-motion simulations for use in civil engineering applications

Ground-motion simulations generated from physics-based wave propagation models are gaining increasing interest in the engineering community for their potential to inform the performance-based design and assessment of infrastructure residing in active seismic areas. A key prerequisite before the ground-motion simulations can be used with confidence for application in engineering domains is their comprehensive and rigorous investigation and validation. This article provides a four-step methodology and acceptance criteria to assess the reliability of simulated ground motions of not historical events, which includes (1) the selection of a population of real records consistent with the simulated scenarios, (2) the comparison of the distribution of Intensity Measures (IMs) from the simulated records, real records, and Ground-Motion Prediction Equations (GMPEs), (3) the comparison of the distribution of simple proxies for building response, and (4) the comparison of the distribution of Engineering Demand Parameters (EDPs) for a realistic model of a structure. Specific focus is laid on near-field ground motions (<10km) from large earthquakes (M w 7), for which the database of real records for potential use in engineering applications is severely limited. The methodology is demonstrated through comparison of (2490) near-field synthetic records with 5 Hz resolution generated from the Pitarka et al (2019) kinematic rupture model with a population of (38) pulse-like near-field real records from multiple events and, when applicable, with NGA-W2 GMPEs. Lastly, the proposed procedure provides an effective method for informing and advancing the science needed to generate realistic ground-motion simulations, and for building confidence in their use in engineering domains.

42 ENGINEERING↗
DOE OSTI2022

National energy savings potential of cellular shades: A measurement and simulation study

Windows are major contributors to energy demand in residential homes because of their inferior thermal resistance compared with the opaque envelope, and sometimes from unwanted solar heat gain. Window attachments can help mitigate the energy demand by controlling the solar heat gains and enhancing window thermal resistance. Cellular shades have the potential of superior thermal performance compared with generic shades because of its honeycomb structure. Here, in this study, the team analyzed the energy savings potential of cellular shades in residential homes via experimental testing for two heating seasons and energy simulations. Five shading devices—three single-cell and two double cellular/cell-in-cell shades—were used to compare the performance with generic horizontal venetian blinds using two nearly identical side-by-side rooms in a residential home. The experimental testing showed daily heating energy savings in the range of 17%–36% compared with the case without shades. The experimental testing data also exhibited improvements in thermal comfort when using cellular shades. Additionally, energy simulations were performed to evaluate the energy savings potential of the cellular shades using a residential prototype home, which demonstrated energy savings up to 9 kWh/m2/year in cold climates. The total site energy savings for heating and cooling from cellular shades was up to ~9% for the home with a heat pump and up to ~15% for a home with a gas furnace compared with cases without any shading devices. The energy savings at a national scale were up to 14.6 TWh assuming a 20% penetration rate in residential homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Numerical assessment of fault impact on caprock seals during CO 2 sequestration

Coupled fluid-flow and geomechanical analysis of caprock integrity has gained a lot of attention among scientists and researchers investigating the long-term performance of geologic carbon storage systems. Reactivation of pre-existing fractures within the caprock or re-opening of faults can create permeable pathways which can influence the seal integrity. Stability of the caprock during and after injection of super-critical CO 2 , and the impact of pre-existing fractures in the presence or absence of one or multiple faults have been investigated in this study. The impact of the wellbore orientation and the injection rate are among other key factors in understanding the structural trapping mechanisms within such geological formations. In this study, we numerically investigated the impact of each of these factors. This study revealed the interplay between joints and faults and how different leakage pathways are formed and under which scenario they play a dominant role in terms of CO 2 leakage. Finally, this study also highlights the role of one versus multiple faults in the domain and the importance of the fault hydrological property in forming leakage pathway.

58 GEOSCIENCES↗
DOE OSTI2025

Linking structure to performance: Characterization of porous transport layers for high-pressure water electrolysis

Proton exchange membrane (PEM) water electrolysis is a promising technology to produce cost-efficient hydrogen. PEM electrolyzers offer a large current density range and the ability to operate at differential pressure which can be used to minimize both capital and operational expenditures. However, directly producing pressurized hydrogen at the cathode results in pushing the membrane against the anode porous transport layer (PTL). This can lead to detrimental effects, such as membrane deformation or ruptures, which depend on membrane properties as well as PTL material properties such as pore size, structure, and morphology. In this work, a range of sinter and felt-based commercial PTLs are evaluated for their contributions to the cell's electrochemical and H 2 crossover performance at cathode pressures up to 30 bar. X-ray tomography and post-operando optical microscopy are used to assess the morphology of the PTLs, and the PTL induced deformation experienced by the catalyst coated membrane (CCM), respectively. PTL samples with lower porosity were found to reduce both the cell voltage and the amount of H 2 permeating from the cathode to the anode exhaust, which was ascribed to improved catalyst layer contact and reduced membrane deformation, respectively. The best performing PTLs improved electrolyzer efficiency by ~1.5 kWh/kg H2 . Specifically, 1 kWh/kg H2 was gained due to reducing membrane deformation and decreasing H 2 crossover. The remainder 0.5 kWh/kg H2 were achieved by improving the electrical contact at the electrode/PTL interface which decreased cell voltage.

08 HYDROGEN↗
DOE OSTI2020

In-situ and in-operando analysis of voltage losses using sense wires for proton exchange membrane water electrolyzers

Proton exchange membrane water electrolyzer development requires understanding processes at the materials and interface levels to reach the required performance and lifetime targets for increasing market penetration. To achieve the required progress, it is critical to develop advanced in-situ diagnostics that allow observation of the changes that come with the reduction of catalyst loading combined with long-term intermittent operation. This work presents an internal voltage sensing method that enables observing internal voltage drops in an operating electrolyzer cell. It allows the total cell resistance to be separated into anode, CCM, and cathode resistance. The method is demonstrated by operating cells with different anode porous transport layers (PTLs). The changing properties of the PTLs result in significant variations of the resistances. Enhancing the PTL properties with a protective coating reduces the anode resistance significantly. In addition to these observations, the method enables a real-time monitoring of resistance related values that impact performance in water electrolyzers. Long-term experiments with the method allow us to gain insights into processes that occur during operation such as conditioning or degradation. The internal voltage sensing method presented in this study is a novel technique for diagnosing, analyzing, and optimizing water electrolyzers and other energy conversion devices.

42 ENGINEERING↗
DOE OSTI2020

An algorithm for resolving intragranular orientation fields using coupled far-field and near-field high energy $\mathrm{X}$-ray diffraction microscopy

Here, we present a novel algorithm for reconstructing spatial intragranular lattice orientation fields using both far-field and near-field high energy X-ray diffraction microscopy (HEDM) measurements. An established far-field indexing algorithm is modified to include lattice orientation distribution information (grain orientation envelopes) in addition to average grain orientations. The near-field data reduction algorithm utilizes this enriched far-field orientation data as a seed for reconstructing intragranular spatial maps of lattice orientation from the diffraction images. The primary benefit of the new algorithm is a significant decrease in the number of trial calculations that must be performed in the reconstruction process compared to existing methodologies while maintaining scalability. The resulting gains in efficiency facilitate the use of relatively modest computational resources and improve throughput at the point of measurement. We provide two example applications: volumetric orientation field reconstructions for a Ti-Al alloy both before and after the application of 3% uniaxial strain. The results showcase the efficiency of the new method and the ability to resolve subtle changes in microstructure, which are associated with incipient plastic deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hexadecapole strength in the rare isotopes 74,76 Kr

In the Ge-Sr mass region, isotopes with neutron number N ≤ 40 are known to feature rapid shape changes with both nucleon number and angular momentum. To gain new insights into their structure, inelastic proton scattering experiments in inverse kinematics were performed on the rare isotopes 74,76 Kr. This work focuses on observables related to the J π = $4$$^{+}_{1}$ states of the Kr isotopes and, in particular, on the hexadecapole degree of freedom. By performing coupled-channels calculations, hexadecapole deformation parameters β 4 were determined for the J π = $4$$^{+}_{1}$ states of 74,76 Kr from inelastic proton scattering cross sections. Two possible coupled-channels solutions were found. A comparison to predictions from nuclear energy density functional theory, employing both non-relativistic and relativistic functionals, clearly favors the large, positive β 4 solutions. These β 4 values are unambiguously linked to the well deformed prolate configuration. Given the β 2 - β 4 trend, established in this work, it appears that β 4 values could provide a sensitive measure of the nuclear shell structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Estimating value of information for heliostat washing operations at solar thermal plants

Concentrating solar power (CSP) plants depend on thousands of heliostats whose reflectance declines as dust accumulates. Operators routinely measure reflectance to estimate soiling and, in turn, inform cleaning schedules, but the value of collecting more frequent or more accurate data has not been formally quantified. This study introduces a Monte Carlo discrete event simulation framework that integrates stochastic models of soiling, weather, and measurement error with a dynamic cleaning dispatch policy to estimate annual energy production and operations costs. Applied to two representative central-receiver field configurations, the results show that both the frequency and accuracy of reflectance measurements can meaningfully impact plant performance. In both case studies, reducing measurement intervals yields significant returns, with the energy gains greatly exceeding the cost of more frequent data collection. The simulation framework serves as a decision-support tool for CSP operators, allowing them to input site-specific soiling conditions, measurement accuracy, and survey frequency to evaluate the tradeoffs between data collection cost and energy recovery, and to identify measurement strategies that maximize plant profit.

14 SOLAR ENERGY↗
DOE OSTI2020

Transformation of Ferrihydrite to Goethite and the Fate of Plutonium

Understanding the interactions between plutonium and iron (oxy)hydroxide minerals is necessary to gain a predictive understanding of plutonium environmental mobility and to evaluate long-term performance of nuclear waste repositories. We investigated the fate of plutonium during the formation of ferrihydrite and its subsequent transformation into goethite. Ferrihydrite was synthesized with varying quantities of Pu(IV) following either a sorption or coprecipitation process; the ferrihydrite was then aged hydrothermally to yield goethite. Additionally, the synthesized materials were characterized via extended X-ray absorption fine structure spectroscopy, transmission electron microscopy, and acid leaching to elucidate the nature of plutonium association with ferrihydrite and goethite. In samples prepared following the sorption method, plutonium was identified in two different forms: a PuO 2 precipitate and a surface-sorbed plutonium complex. For the samples prepared via coprecipitation, no PuO 2 formation occurs in the ferrihydrite precursor and in the goethite experiments where plutonium concentration is ≤1000 ppm (mg kg –1 ). In these coprecipitation products, plutonium is strongly bound to the minerals either via formation of an inner sphere complex, or via an incorporation process. In the coprecipitation experiments, PuO 2 formation only occurs at the highest plutonium concentration (3000 ppm), suggesting that during ferrihydrite transformation into goethite, part of the plutonium can be remobilized to form PuO 2 nanoparticles. Collectively, our results demonstrate that the nature of plutonium associated with the precursor ferrihydrite (adsorbed vs coprecipitated) will have a direct impact on the association of plutonium with its alteration product (goethite). Furthermore, the data illustrate that some properties of plutonium association with the precursor ferrihydrite are retained through the transformation into goethite. These findings show that plutonium strongly associates with iron (oxy)hydroxides formed through coprecipitation processes and in these materials, plutonium can be strongly retained by the iron minerals.

54 ENVIRONMENTAL SCIENCES↗