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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Random Walks With Tweedie: A Unified View of Score-Based Diffusion Models [In the Spotlight]

We present a concise derivation for several influential score-based diffusion models that relies on only a few textbook results. Diffusion models have recently emerged as powerful tools for generating realistic, synthetic signals—particularly natural images—and often play a role in state-of-the-art algorithms for inverse problems in image processing. While these algorithms are often surprisingly simple, the theory behind them is not, and multiple complex theoretical justifications exist in the literature. Here, in this study, we provide a simple and largely self-contained theoretical justification for score-based diffusion models that is targeted towards the signal processing community. This approach leads to generic algorithmic templates for training and generating samples with diffusion models. We show that several influential diffusion models correspond to particular choices within these templates and demonstrate that alternative, more straightforward algorithmic choices can provide comparable results. This approach has the added benefit of enabling conditional sampling without any likelihood approximation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Matrix Diffusion Controls Mountain Hillslope Groundwater Ages and Inferred Storage Dynamics

Groundwater age distributions provide fundamental insights on coupled water and biogeochemical processes in mountain watersheds. Field-based studies have found mixtures of young and old-aged groundwater in mountain catchments underlain by bedrock; yet, the processes that dictate these groundwater age distributions are poorly understood. In this work, we use the coupled ParFlow-CLM integrated hydrologic and EcoSLIM particle tracking models to simulate groundwater age distributions on a lower montane hillslope in the East River Watershed, Colorado (USA). We develop a convolution-based approach to propagate fracture-matrix diffusion processes to the EcoSLIM advection-dominated age distributions. We compare observed 3 H and 4 He concentrations from two groundwater wells against model predictions that have varying advective transport times and matrix diffusion magnitudes. Based on a Monte Carlo analysis that considers uncertain matrix and fracture parameters, we find that matrix diffusion is needed to jointly predict 3 H and 4 He observations at both wells. The advection-dominated age distributions lack adequate mixing of young and old-aged water to capture the observed co-occurrence of 3 H and 4 He. The model scenario that best matches the 3 H, 4 He, and water level observations when considering both advective flowpath and matrix diffusion mixing processes has a dynamic bedrock groundwater reservoir that is susceptible to considerable storage losses during low-snow periods. This dynamic groundwater system amplifies the need to assimilate deeper bedrock groundwater into watershed hydro-biogeochemical predictions. This work further highlights the importance of considering matrix diffusion when interpreting environmental tracers in bedrock groundwater systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Anisotropic diffusion in media with absorbing traps (application to the Keller–Dykhne theorem)

Anisotropic diffusion in multidimensional media with absorbing traps is investigated. It is shown that the diffusion asymptotic forms of the survival probability over long time intervals are determined by a new effective diffusion coefficient. Exact expressions derived for the effective diffusion coefficient generalize the well-known Dykhne–Keller 2D results to the 3D case. In other words, the dynamic diffusion approach is used for obtaining a generalization of the Dykhne–Keller theorem to the 3D case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A Study of Ferrocene Diffusion in Toluene/Tween 20/1-Butanol/Water Microemulsions for Redox Flow Battery Applications

Redox flow batteries (RFBs) possess multiple advantages as a flexible energy storage solution. However, RFB researchers are still facing many challenges in finding an appropriate electrolyte. Microemulsions have recently been proposed as a promising alternative RFB electrolyte because of their ability to accommodate organic redox species with fast electron transfer rates that are not soluble in aqueous phase, while still offering the high conductivity of an aqueous salt electrolyte. In this work, we focused on understanding the transport of ferrocene (Fc) in a toluene/Tween 20/1-butanol/water model microemulsion and studied the compositional influence on Fc diffusion. The results show that Fc redistributes among the oil, surfactant, and water microenvironments, and the corresponding diffusion and partition coefficients are quantified. Thus, a tortuous path diffusion model is proposed to describe the mass transport of Fc to an electrode surface. Diffusion coefficients are also obtained by pulsed-field gradient nuclear magnetic resonance (PFG NMR), while the values for Fc diffusion are substantially higher than those from electrochemical measurements, suggesting that they measure samples in different ways. The current contributions from each microenvironment indicate that the Fc permeability is much higher in the oil, even though the electron transfer reaction is likely occurring in the surfactant.

25 ENERGY STORAGE↗
DOE OSTI2025

Ab Initio Insights to Metal Passivation: Diffusion and Defect Formation in Amorphous Zirconia and Alumina

Metal passivation refers to the formation of protective oxide films on metals, which shield them from further corrosion and oxidation, playing a crucial role in maintaining their stability. The mesoscopic Point Defect Model has successfully predicted passivity as a steady state process where oxide growth from oxygen vacancies at the metal/film interface competes with oxide dissolution at the film/environment interface. In this work, informed by the Point Defect Model parameters, we use first-principles calculations to calculate defect formation and atomic diffusion in amorphous materials and correlate these descriptors with the behavior and growth of the oxide film. Focusing on amorphous zirconia and alumina, we demonstrate that defect formation energies exhibit significant variability in amorphous systems. In alumina, vacancies dominate, with cation and anion vacancies occurring at comparable concentrations. Diffusion calculations for stoichiometric amorphous alumina and zirconia, as well as oxygen-deficient zirconia, reveal faster diffusion in the oxygen-deficient case, highlighting the impact of defects on transport. Comparison of calculated self-diffusion coefficients for the dominant defect species with experimentally measured oxide thicknesses shows a clear correlation, suggesting that first-principles-derived diffusivity information can serve as a key descriptor for surface passivation film growth.

Farnell, Mackinzie S. [University of California, B↗
DOE OSTI2015

A Process for Modelling Diffuse Scattering from Disordered Molecular Crystals, Illustrated by Application to Monoclinic 9-Chloro-10-methylanthracene

Diffuse scattering from a crystal contains valuable information about the two-body correlations (related to the nanoscale order) in the material. Despite years of development, the detailed analysis of single crystal diffuse scattering (SCDS) has yet to become part of the everyday toolbox of the structural scientist. Recent decades have seen the pair distribution function approach to diffuse scattering (in fact, total scattering) from powders become a relatively routine tool. However, analysing the detailed, complex, and often highly anisotropic three-dimensional distribution of SCDS remains valuable yet rare because there is no routine method for undertaking the analysis. At present, analysis requires significant investment of time to develop specialist expertise, which means that the analysis of diffuse scattering, which has much to offer, is not incorporated thorough studies of many compounds even though it has the potential to be a very useful adjunct to existing techniques. This article endeavours to outline in some detail how the diffuse scattering from a molecular crystal can be modelled relatively quickly and largely using existing software tools. It is hoped this will provide a template for other studies. To enable this, the entire simulation is included as deposited material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Diffuse Reflectance Spectroscopy and Principal Component Analysis to Retrospectively Determine Production History of Plutonium Dioxide

Diffuse reflectance spectroscopy measurements in the shortwave infrared (930–1600 nm) spectral region were acquired for Pu 2 (C 2 O 4 ) 3 •9H 2 O and its thermal decomposition product, PuO 2 . We analyzed a total of eight PuO 2 samples that were produced at different calcination temperatures (300, 350, 450, 525, 600, 675, 750, and 900 °C). Our goal was to identify spectroscopic fingerprints that could be used to gain retrospective information regarding the production parameters of these important nuclear compounds. The diffuse reflectance spectrum of Pu 2 (C 2 O 4 ) 3 •9H 2 O features several broad bands that currently preclude detailed analysis. However, all PuO 2 samples produced relatively sharp spectral features that got sharper and more intense for samples that were produced at higher calcination temperatures. The electronic band observed at 1433 nm in the diffuse reflectance spectra of PuO 2 was found to be a sensitive indicator of crystallinity; a result that is corroborated by ancillary Raman spectroscopy measurements. Principal component analysis of diffuse reflectance spectra was able to clearly rank and categorize PuO 2 samples based on the calcination temperature that was employed during their production. Thus, we show herein that important retrospective information pertaining to the process history of PuO 2 can be gained through the relatively simplistic combination of diffuse reflectance spectroscopy and principal component analysis. This discovery presents a new method for determining the provenance and process history of PuO 2 and should have an impact in the fields of nuclear forensics and nuclear nonproliferation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Understanding irradiation growth through atomistic simulations: Defect diffusion and clustering in α-zirconium and the influence of alloying elements - 2016-0093

Irradiation-induced structural changes of α-zirconium alloys and in particular the effect of iron were investigated by molecular dynamics simulations using embedded atom potentials derived from first-principles calculations. The simulations revealed that at temperatures between 500 and 600 K self-interstitial atoms (SIAs) diffuse rapidly in a cooperative movement, preferably parallel to basal planes (a directions; ), forming nano-clusters with an extension in and . Vacancies diffuse more slowly than SIAs and remain isolated for a longer period of time. Nano-clusters associated with SIAs cause a pronounced overall expansion in a directions, as well as local strains. Under compressive strain in the c direction, vacancy diffusivity increases in the c direction. In contrast, the diffusivity of SIAs increases in the c direction under a tensile strain in the c direction. SIA nano-clusters are highly mobile within basal planes. Vacancy clusters grow by merging, leading to a contraction in the a direction, compensating for the expansion caused by SIA nano-clusters and possibly contributing to the plateau in growth after the initial rapid expansion. At the onset of breakaway growth, possibly due to stress buildup, the vacancy nano-clusters can condense into c loops, thereby diminishing the compensation effect. The alloying elements iron, nickel, chromium, and niobium liberated from secondary phase particles under irradiation or already in solution are attracted to vacancies and SIAs and are found inside vacancy and SIA loops. The interaction of alloying elements with defect clusters is discussed, with a particular focus on iron. Iron has been found to promote cluster formation in zirconium, and the structures of zirconium-iron clusters have been analyzed. Tin is repelled by SIA clusters and only weakly attracted by vacancies. Niobium impedes the diffusion of SIAs (and therefore may increase annihilation rates with nearby vacancies) and does not destabilize vacancy or SIA clusters. Ab initio calculations of the dimensional and elastic coefficients of the intermetallic phases occurring in secondary phase particles, such as Zr{sub 2}Fe and Zr{sub 3}Fe, are presented, allowing an assessment of local strains in a zirconium matrix. Thus, novel results from extended molecular dynamics simulations provide new insights and contribute to a deeper understanding of the complex mechanisms causing irradiation-induced dimensional changes and the breakaway growth of zirconium alloys. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2018

Modeling Radionuclide Releases from TRISO Particles by Simultaneous Diffusion Through and Corrosion of the Silicon Carbide Barrier Layer

TRISO nuclear fuel particles that are less than 1 mm in diameter are designed with multiple barrier layers to retain fission products both during reactor operations and for long-term geological disposal. The primary barrier is a 35 μm thick silicon carbide (SiC-a highly impermeable semi-metal) layer for which data are available on the diffusion of short-lived fission products at high temperatures (> 1000 °C). However, for a geological repository, this layer may contact brine and hence corrode even at ambient temperatures. As an initial approach to assess the effectiveness of the SiC barrier for geological repositories, ranges of fission product diffusivities and corrosion rates for SiC are modeled concurrently with the simultaneous effect of radioactive decay. Using measured corrosion rates of SiC, if the diffusivity is more than about 10 -20 m 2 /s, fission product releases may occur before the SiC barrier has corroded to the point of breach. For diffusivities less than about 10 -21 m 2 /s there may not be significant diffusional releases prior to SiC barrier removal/breach by corrosion. This work shows the importance of estimating diffusivities in SiC at geological repository temperatures, and highlights the relevance of evaluating the porosity/permeability evolution of the SiC layer in a geologic environment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Neptunium(IV) Diffusion through Bentonite Clay

DOE Fellow, Silvina A. Di Pietro, completed a 10-week internship at Lawrence Livermore National Laboratory (LLNL) in Livermore, California. The objective of the study was to determine the diffusion profile of neptunium (Np) in bentonite clay (potential geo-engineered barrier for nuclear waste repositories). Under the mentorship of Drs. Claudia Joseph (Karlsruhe Institute of Technology, Germany) and Mavrik Zavarin, she prepared a series of core abrasion peeling samples. This procedure was a continuation of a Np diffusion experiment conducted by Dr. Joseph during her post-doc residency at LLNL in the year 2016. The second part of the experiment (from now on will be referred as abrasive peeling) focuses on understanding (1) the Np movement through the clay core and (2) the influence of temperature (25°C, 65°C, and 85°C) for the Np transport across the clay core under anaerobic conditions. End of 2016, the diffusion core samples were embedded in epoxy resin to stabilize them for long-term. The abraded core powder samples vary in material (epoxy vs. clay), Np activity and concentration, temperature exposed during the diffusion experiment, and mass, or amount of clay peeled off. Throughout the course of the 10-week internship program at LLNL, the experiments implemented and discussed in this report aimed to answer the questions: (1) How is the Np(IV) diffusion profile through bentonite influenced by the temperature? and (2) Will Np(IV) migrate through the geoengineered barrier of a nuclear waste repository? In addition, Ph.D. candidate Di Pietro received invaluable guidance in experimental design and development that will benefit her ongoing research endeavors.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

DRIFT: Diffusivity Regulation of Isotopes by nanoconFinementT

Spontaneous isotope fractionation has been reported under nanoconfinement conditions in naturally occurring systems, but the origin of this phenomena is currently unknown. Two existing hypotheses have been proposed, one based on changes in the solvation environment of the isotopes that reduces the non-mass dependent hydrodynamics contribution to diffusion. The other is that isotopes have mass-dependent surface adsorption, varying their total diffusion through nanoconfined channels. To investigate these hypotheses, benchtop experiments, nuclear magnetic resonance (NMR) spectroscopy, and molecule scale modeling were applied. Classical molecular dynamics simulations identified that the Na + and Cl - hydration shells across the three different salt solutions ( 22 Na 35 Cl, 23 Na 35 Cl, 24 Na 35 Cl) did not vary as a function of the Na + isotope, but that there was a significant pore size effect, with larger hydration shells at larger pore sizes. Additionally, while total adsorption times did not vary as a function of the Na + isotope or pore size, the free ion concentration, or those adsorbed on the surface for <5% of the simulation time did exhibit isotope dependence. Experimentally, challenges occurred developing a repeatable experiment, but NMR characterization of water diffusion rates through ordered alumina membranes was able to identify the existence of two distinct water environments associated with water inside and outside the pore. Further NMR studies could be used to confirm variation in hydration shells and diffusion rates of dissolved ions in water. Ultimately, mass-dependence adsorption is a primary driver of variations in isotope diffusion rates, rather than variation in hydration shells that occur under nanoconfinement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Model Parameter Development for Complex Materials: Species-Specific Diffusion Barriers in 316 Stainless Steel from Systematic DFT Calculations

Vacancy-mediated diffusion barriers in 316 stainless steel have been systematically calculated using density functional theory to provide essential parameters for mesoscale microstructure evolution models. A statistical sampling approach employing 210 nudged elastic band calculations across multiple special quasi-random structures captures the effects of local chemical environments in this concentrated alloy. The computational methodology addresses challenges specific to chemically disordered systems, including proper magnetic treatment throughout multi-step calculations and validation against experimental structural properties. The calculated activation barriers reveal clear species-dependent diffusion behavior with the hierarchy Ni >> Fe ˜ Cr >> Mo. Nickel exhibits the highest barriers (0.74–1.31 eV, mean 1.045 eV), confirming its role as the slowest-diffusing major component. Iron and chromium show similar moderate barriers averaging 0.587 eV and 0.522 eV, respectively. Remarkably, molybdenum demonstrates exceptionally low barriers (0.12–0.28 eV, mean 0.194 eV), suggesting much higher mobility than previously recognized and potentially significant implications for precipitation kinetics and microstructure evolution. The barrier ranges remain consistent across different 316 SS compositions, supporting parameter transferability for modeling applications. The overall mean barrier of 0.64 eV provides a practical approximation for phase field simulations, while species-specific values enable detailed treatments of diffusion-controlled processes. This systematic approach establishes a validated framework for generating diffusion parameters in other concentrated alloys where experimental data are limited, while providing the first systematic set of species-specific barriers for predictive modeling of 316 stainless steel microstructure evolution.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Atomic Diffusivities of Yttrium, Titanium and Oxygen Calculated by Ab Initio Molecular Dynamics in Molten 316L Oxide-Dispersion-Strengthened Steel Fabricated via Additive Manufacturing

Oxide-dispersion-strengthened (ODS) steels have long been viewed as a prime solution for harsh environments. However, conventional manufacturing of ODS steels limits the final product geometry, is difficult to scale up to large components, and is expensive due to multiple highly involved, solid-state processing steps required. Additive manufacturing (AM) can directly incorporate dispersion elements (e.g., Y, Ti and O) during component fabrication, thus bypassing the need for an ODS steel supply chain, the scale-up challenges of powder processing routes, the buoyancy challenges associated with casting ODS steels, and the joining issues for net-shape component fabrication. In the AM process, the diffusion of the dispersion elements in the molten steel plays a key role in the precipitation of the oxide particles, thereby influencing the microstructure, thermal stability and high-temperature mechanical properties of the resulting ODS steels. In this work, the atomic diffusivities of Y, Ti, and O in molten 316L stainless steel (SS) as functions of temperature are determined by ab initio molecular dynamics simulations. The latest Vienna Ab initio Simulation Package (VASP) package that incorporates an on-the-fly machine learning force field for accelerated computation is used. At a constant temperature, the time-dependent coordinates of the target atoms in the molten 316L SS were analyzed in the form of mean square displacement in order to obtain diffusivity. The values of the diffusivity at multiple temperatures are then fitted to the Arrhenius form to determine the activation energy and the pre-exponential factor. Given the challenges in experimental measurement of atomic diffusivity at such high temperatures and correspondingly the lack of experimental data, this study provides important physical parameters for future modeling of the oxide precipitation kinetics during AM process.

Chemistry↗
DOE OSTI2017

Non-kinematic Flux-transport Dynamos Including the Effects of Diffusivity Quenching

Turbulent magnetic diffusivity is quenched when strong magnetic fields suppress turbulent motion in a phenomenon known as diffusivity quenching. Diffusivity quenching can provide a mechanism for amplifying magnetic field and influencing global velocity fields through Lorentz force feedback. To investigate this effect, we conducted mean field flux-transport dynamo simulations that included the effects of diffusivity quenching in a non-kinematic regime. We found that toroidal magnetic field strength is amplified by up to approximately 1.5 times in the convection zone as a result of diffusivity quenching. This amplification is much weaker than that in kinematic cases as a result of Lorentz force feedback on the system’s differential rotation. While amplified toroidal fields lead to the suppression of equatorward meridional flow locally near the base of the convection zone, large-scale equatorward transport of magnetic flux via meridional flow, which is the essential process of the flux-transport dynamo, is sustainable in our calculations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Diffusion coefficients in the envelopes of white dwarfs

The diffusion of elements is a key process in understanding the unusual surface composition of white dwarfs and their spectral evolution. The diffusion coefficients of Paquette et al. have been widely used to model diffusion in white dwarfs. In this work, we perform new calculations of the coefficients of interdiffusion and ionic thermal diffusion with (1) a more advanced model that uses a recent modification of the calculation of the collision integrals that is more suitable for the partially ionized, partially degenerate, and moderately coupled plasma and (2) classical molecular dynamics. The coefficients are evaluated for silicon and calcium in white dwarf envelopes of hydrogen and helium. A comparison of our results with Paquette et al. shows that the latter systematically underestimates the coefficient of interdiffusion yet provides reliable estimates for the relatively weakly coupled plasmas found in nearly all types of stars, as well as in white dwarfs with hydrogen envelopes. In white dwarfs with cool helium envelopes (${T}_{\mathrm{eff}}$ < 15,000 K), the difference grows to more than a factor of two. We also explored the effect of the ionization model used to determine the charges of the ions and found that it can be a substantial source of discrepancy between different calculations. Finally, we consider the relative diffusion timescales of Si and Ca in the context of the pollution of white dwarf photospheres by accreted planetesimals and find factor of ≳3 differences between calculations based on Paquette et al. and our model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series

Abstract. Improving the quantification of soil thermal and physical properties is key to achieving a better understanding and prediction of soil hydro-biogeochemical processes and their responses to changes in atmospheric forcing. Obtaining such information at numerous locations and/or over time with conventional soil sampling is challenging. The increasing availability of low-cost, vertically resolved temperature sensor arrays offers promise for improving the estimation of soil thermal properties from temperature time series, and the possible indirect estimation of physical properties. Still, the reliability and limitations of such an approach need to be assessed. In the present study, we develop a parameter estimation approach based on a combination of thermal modeling, sliding time windows, Bayesian inference, and Markov chain Monte Carlo simulation to estimate thermal diffusivity and its uncertainty over time, at numerous locations and at an unprecedented vertical spatial resolution (i.e., down to 5 to 10 cm vertical resolution) from soil temperature time series. We provide the necessary framework to assess under which environmental conditions (soil temperature gradient, fluctuations, and trend), temperature sensor characteristics (bias and level of noise), and deployment geometries (sensor number and position) soil thermal diffusivity can be reliably inferred. We validate the method with synthetic experiments and field studies. The synthetic experiments show that in the presence of median diurnal fluctuations ≥ 1.5 ∘C at 5 cm below the ground surface, temperature gradients > 2 ∘C m−1, and a sliding time window of at least 4 d the proposed method provides reliable depth-resolved thermal diffusivity estimates with percentage errors ≤ 10 % and posterior relative standard deviations ≤ 5 % up to 1 m depth. Reliable thermal diffusivity under such environmental conditions also requires temperature sensors to be spaced precisely (with accuracy to a few millimeters), with a level of noise ≤ 0.02 ∘C, and with a bias defined by a standard deviation ≤ 0.01 ∘C. Finally, the application of the developed approach to field data indicates significant repeatability in results and similarity with independent measurements, as well as promise in using a sliding time window to estimate temporal changes in soil thermal diffusivity, as needed to potentially capture changes in bulk density or water content.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series: Supporting Data

This dataset consists of soil temperature time series that were used to estimate soil thermal diffusivity and its uncertainty trough the probabilistic modelling approach developed and presented in the article named "Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series" and published in Earth Surface Dynamics. There are two compressed (.zip) files that contains synthetic (Synthetic_soiltemp_Teller.zip) and field (Field_soiltemp_Teller.zip) data. There is one MATLAB file that requires MATLAB to execute but any text editor can open it. The Synthetic_soiltemp_Teller.zip file includes 5 comma-delimited data files (.csv) each of which contains soil temperature time series generated through forward modeling (i.e., heat-conduction process in a heterogeneous medium using an explicit finite difference method) to mimic various types of temperature gradients, trend and fluctuations. These synthetic soil temperatures were used to investigate the impact of different environmental conditions on the uncertainty of thermal diffusivity estimates. The Field_soiltemp_Teller.zip file contains 28 comma-delimited data files (.csv) out of which (a) 27 files includes soil temperature time series recorded from 27 temperature probes located in a site along Teller Road about 40 km northwest of Nome, Alaska (64.72°N, 165.94°W), (b) one includes the name and coordinates of the 27 probes. These field soil temperatures were used to infer soil thermal diffusivity at numerous locations and depths in a discontinuous permafrost environment, and to evaluate the links between the estimated soil thermal diffusivity values and soil physical properties. The comma-delimited data files (.csv) of the synthetic and field soil temperature time series includes date and time (UTC) in the first column and soil temperature from 5 cm below the ground surface to 1.05 m depth (with 5 or 10 cm spacing between sensors) in the other columns. The measurements were acquired every 15 minutes. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Photovoltaic structures having multiple absorber layers separated by a diffusion barrier

Photovoltaic structures having multiple absorber layers separated by a diffusion barrier are provided. In one aspect, a method of forming an absorber on a substrate includes: depositing a first layer of light absorbing material on the substrate; depositing a diffusion barrier; depositing a second layer of light absorbing material on the diffusion barrier, wherein the first layer of light absorbing material has a different band gap from the second layer of light absorbing material; and annealing the absorber, wherein the diffusion barrier prevents diffusion of elements between the first layer of light absorbing material and the second layer of light absorbing material during the annealing. A solar cell and method for formation thereof are also provided.

Antunez, Priscilla D.↗