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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Anderson acceleration stability in NDA-accelerated k-eigenvalue problems

Anderson acceleration (AA) has been used to improve the stability and convergence rate of multiphysics iterative methods for reactor analysis. Most applications studied assume a tightly converged solution for the different physics problems, and AA is usually applied to state variables like temperature, density, and heat generation rate. In this paper, we study the theoretical performance of AA in NDA-accelerated k-eigenvalue problems. The problems and algorithms studied are simplified from the coupled iteration scheme adopted by MPACT and many other high-fidelity whole-core reactor codes. Compared to previous analyses of AA for these iteration schemes, we study the case with a partially converged neutronics solution and possibly partially converged nonlinear diffusion acceleration (NDA)/coarse mesh finite difference (CMFD) solutions. We observe that the performance of the iteration scheme with AA is very sensitive to the initial guess and is affected by the partially converged CMFD solutions. When the NDA solution is fully converged, using AA cannot achieve the optimal convergence rate in large-sized problems. Conversely, if the NDA solution is partially converged, the iteration scheme with AA can diverge or converge extremely slowly. It is found that the loss of robustness for AA is due to the fact that it is applied to the iterative subspace of state variables rather than the fundamental unknowns of the governing equations. To improve the robustness, the scalar flux should also be considered in the implementation of AA. After considering the residuals of flux, we observe that the stability is regardless of the partial convergence of NDA solutions. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Synthesizing Highly Crystalline Graphite Powder from Bulk Polyethylene Waste for Lithium-Ion Battery Anodes

Upcycling plastic waste into graphite can potentially be used, in conjunction with other methods, to manage existing waste materials and diversify graphite supply chains. However, synthesizing large quantities of crystalline graphite powder from plastic waste, particularly polyethylene (PE), remains a challenge because PE decomposes into light gases during thermal processing and simple methods do not exist at any appreciable size scale to address this challenge. In this work, a method is developed for air processing bulk forms of PE waste to create stable carbon char that does not readily decompose during high-temperature processing. This method employs solid additives in the form of salts, which are combined with the PE melt during air processing to increase the effective surface area of the melt and improve the oxygen-driven chemistry that stabilizes PE for high-temperature processing. After removal of the solid salt additives from the PE-derived char, it is converted into a highly crystalline bulk graphite powder using an Fe-based catalytic process. The PE-derived graphite anode in a lithium-ion coin cell showed a specific capacity of 345 mAh/g at 0.05C with an initial Coulombic efficiency of 87% and reversible capacity retention of ~100% at different current rates. It also showed a specific capacity of up to 313 mAh/g at 0.5 discharge/charge cycles per hour (0.5C) and Coulombic efficiency of 99.9% after 250 cycles, indicating excellent electrochemical performance as an anode material for lithium-ion batteries. This method illustrates that there are opportunities for upcycling large quantities of PE waste to produce graphite powders suitable for use in LIBs.

25 ENERGY STORAGE↗
DOE OSTI2022

Carbon nanofibers (CNFs) dispersed in ultra-high performance concrete (UHPC): Mechanical property, workability and permeability investigation

This paper presents experimental data on the effect of carbon nano-fiber (CNF) dispersion on mechanical behavior, workability, and permeability of ultra-high-performance concrete containing CNF (UHPC-CNF). The addition of CNFs in concrete has been shown to provide improved performance. However, an inhomogeneous distribution of CNFs in the cement matrix can result in no impact or decreased mechanical performance. Due to the van der Waal's forces and hydrophobic surface properties of the CNFs, good dispersion in mix fluids and cement paste is challenging. Experimental studies of UHPC-CNF with different dispersion methods are provided. Further mixing with optimized UHPC paste allowed for the investigation of the optimal dosage of CNFs, impact on porosity, compressive strength, flexural strength, hydration rate, and slump. Scanning electron microscopy (SEM) analysis visually revealed the effect of dispersion. Our results indicate that shear mixing and subsequent ultrasonic dispersion with chemical surfactants can provide a well-dispersion liquid admixture of CNFs resulting in high mechanical performance of UHPC-CNFs composites. The water permeability and chloride resistance of optimized UHPC-CNFs composites were further evaluated with the wicking test and ponding test to reveal improved performance for these properties as well.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Effect of Noninvasive Follicular Thyroid Neoplasm with Papillary-Like Nuclear Features (NIFTP) on Malignancy Rates in Thyroid Nodules: How to Counsel Patients on Extent of Surgery

Purpose: To investigate the impact of the nomenclature change to “noninvasive follicular thyroid neoplasm with papillary-like nuclear features” (NIFTP) on reported malignancy rates following thyroidectomy. Methods: Retrospective cohort study of patients with thyroid nodules sampled preoperatively with fine-needle aspiration (FNA) and subsequently removed at one tertiary-care hospital from 4/2016 to 2/2017. Surgical procedure, anatomic pathology, thyroid cytopathology classification, and demographic characteristics were recorded. Results: Thyroidectomy was performed in 353 patients. Twenty-six patients (7.3%) had NIFTP on anatomic pathology. Preoperative FNA demonstrated atypia of undetermined significance (AUS/Bethesda III) in 13 (50%), suspicious for malignancy (SUS/Bethesda V) in 6 (23%), suspicious for follicular neoplasm (SFN/Bethesda IV) in 4 (15%), benign/Bethesda I in 2 (8%), and malignant/Bethesda VI in 1 (4%). Invasive malignancy rates across cytologic categories changed as follows: benign (n = 74) from 4 to 1%, AUS (n = 85) from 33 to 18% (p < 0.05), SFN (n = 58) from 29 to 22%, SUS (n = 33) from 91 to 73% (p < 0.05), and malignant (n = 99) from 99 to 98%. Overall decrease in invasive malignancy was 7.3% for the entire population and 13.1% for indeterminate preoperative FNA cytology (Bethesda III–V). Among 26 NIFTP patients, 17 had thyroid lobectomy (TL) and 9 underwent total thyroidectomy (TT). Eight of the nine patients with TT could have been definitively treated with TL, an 89% decrease. Conclusions: The NIFTP nomenclature change led to an overall decrease in the malignancy rate at our institution, especially for Bethesda III–V categories. Patients may be counseled toward more conservative surgical options if NIFTP is in the differential.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Influence of Ink Formulation and Drying Conditions on Ionomer Distribution in High-Performance Roll-to-Roll-Coated Gas-Diffusion Electrodes

To enable mass production of fuel cell membrane electrode assemblies (MEAs) catalyst layers production will require continuous roll-to-roll (R2R) coating processes. Gas diffusion electrodes (GDEs) are advantageous for mass production because the catalyst layer can be directely coated on the microporous layer of the gas diffusion media without the need for a decal-transfer process. It is known that the water-to-alcohol ratio in the catalyst ink influences the interactions of the ionomer with the catalyst leading to different distributions of ionomer in spray-coated catalyst layers. It is also known that during drying of colloidal mixtures, like fuel cell inks, factors such as drying rate, particle size, and agglomeration influence how the materials distribute themselves throughout the thickness of the dired film. Thus far there have only been limited studies to understand how process conditions such as ink formulation and drying temperature influence the distribution of ionomer and catalyst coated using scalable methods. This understanding is especially important for GDEs since it is known that having a sufficient amount of ionomer at the catalyst layer-membrane interface is critical for high performance. In this study we have focused on determining how the ratio of water to 1-propanol in the catalyst ink ink and drying temperature influence the distribution of ionomer throughout the thickness of the catalyst layer. Using a combination of Kelvin probe and x-ray photoelectron spectroscopy we show that an ionomer-rich surface is promoted by a higher drying rate and a water-rich catalyst ink. In contrast, a 1-propanol catalyst ink leads to a lower concentration of ionomer on the top surface. Using x-ray computed tomography, we are able to characterize the ionomer distribution throughout the thickness of the layer. We find that, in addition to promoting an ionomer-rich top surface, water-rich inks lead to a more homogenous distribution of ionomer, whereas a 1-propanol-rich ink leads to a more irregular distribution. It is found that MEA performance is improved by selecting conditions and ink formulations that promote ionomer enrichment at the top surface to facilitate a good interface with the membrane. MEAs prepared with a 75 wt% water catalyst ink with a 0.9 I/C have equivalent performance to spray-coated GDEs. Critically, these R2R-coated GDEs do not need an additional ionomer overlayer like the spray-coated GDEs do, reducing the number of processing steps in a manufacturing setting. This work shows that with the appropriate selection of materials, ink formulation, and processing conditions gas-diffusion electrodes are a viable pathway for fuel cell manufacturing.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2026

Preparation and Photocatalytic Hydrogen Production of TiO 2 /(AlMnCoNiZn) 3 O 4 Nanocomposites

Photocatalytic water splitting is a promising strategy for addressing the global energy crisis and environmental pollution. In this study, spinel-type high-entropy oxide (HEO) nanoparticles, (AlMnCoNiZn) 3 O 4 , were successfully synthesized via a solution combustion method. TiO 2 /(AlMnCoNiZn) 3 O 4 nanocomposites with varying molar ratios were subsequently fabricated through solid-state sintering, and their photocatalytic water-splitting performance was systematically investigated. The hydrogen production rate initially increased and then decreased with increasing TiO 2 content. The optimal nanocomposite achieved a hydrogen evolution rate of 1450 μmol·h −1 ·g −1 under simulated sunlight irradiation, which is 2.2 times higher than that of pure TiO 2 nanoparticles. In addition, the TiO 2 /(AlMnCoNiZn) 3 O 4 nanocomposites exhibited significantly improved photocorrosion resistance compared with TiO 2 nanoparticles. After 12 h irradiation under a 500-W high-pressure mercury lamp, the hydrogen production rates of the nanocomposites and pure TiO 2 retained 79.3% and 5.47% of their initial values, respectively. These results demonstrate the important role of (AlMnCoNiZn) 3 O 4 and other HEOs in enhancing the photocatalytic performance of nanoheterojunction catalysts. Lastly, this work broadens the potential applications of (AlMnCoNiZn) 3 O 4 and related HEO materials in the field of photocatalysis.

Heterojunction↗
DOE OSTI2017

Detecting population-environmental interactions with mismatched time series data

Time series analysis is an essential method for decomposing the influences of density and exogenous factors such as weather and climate on population regulation. However, there has not been much work focused on understanding how well commonly collected data can reconstruct the effects of environmental factors on population dynamics. We show that, analogous to similar scale issues in spatial data analysis, coarsely sampled temporal data can fail to detect covariate effects when interactions occur on timescales that are fast relative to the survey period. We propose a method for modeling mismatched time series data that couples high-resolution environmental data to low-resolution abundance data. We illustrate our approach with simulations and by applying it to Florida's southern Snail kite population. Our simulation results show that our method can reliably detect linear environmental effects and that detecting nonlinear effects requires high-resolution covariate data even when the population turnover rate is slow. In the Snail kite analysis, our approach performed among the best in a suite of previously used environmental covariates explaining Snail kite dynamics and was able to detect a potential phenological shift in the environmental dependence of Snail kites. Our work provides a statistical framework for reliably detecting population–environment interactions from coarsely surveyed time series. An important implication of this work is that the low predictability of animal population growth by weather variables found in previous studies may be due, in part, to how these data are utilized as covariates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Stable Cycling with Intimate Contacts Enabled by Crystallinity–Controlled PTFE–Based Solvent–Free Cathodes in All–Solid–State Batteries

All-solid-state batteries (ASSBs) employing Li-metal anodes and inorganic solid electrolytes are attracting great attention due to high safety and energy density for next-generation energy storage devices. However, the volume change of cathode active materials can cause contact loss, resulting in charge carrier isolation, heterogeneous current distribution, and poor electrochemical properties in ASSBs. Here, a simple, yet effective, solvent-free electrode engineering approach with polytetrafluoroethylene (PTFE) as a binder for ASSBs is reported, enabling intimate contact and stable interfaces with the cathode. It is substantiated that the crystallinity of PTFE can be controlled depending on the heat history, and highly crystalline PTFE displays robust mechanical properties. High-nickel LiNi 0.8 Mn 0.1 Co 0.1 O 2 cathode prepared with crystalline PTFE show improved cycle and rate performances in ASSBs. In addition, it is revealed that the intimate contact between cathode particles with a stable cathode electrolyte layer is maintained during cycling by postmortem studies. Furthermore, this simple engineering method can be applied to prepare cathodes with a variety of active materials and solid electrolytes in ASSBs.

25 ENERGY STORAGE↗
DOE OSTI2018

Controllable synthesis of CNT@ZnO composites with enhanced electrochemical properties for lithium-ion battery

Highlights: • The optimized CNT@ZnO composites deliver 709.2 mAh g{sup −1} at 100 mA g{sup −1} after 50 cycles. • The structure of CNT@ZnO composites has the advantages of both ZnO and MWCNTs. • The optimized CNT@ZnO composites are promising anode materials for LIBs. - Abstract: The design and synthesis of anode materials with novel structures are one of crucial issues for developing next-generation lithium-ion battery. In this work, carbon nanotube@zinc oxide (CNT@ZnO) composites are synthesized by a liquid-phase method using CNTs as a conductive support. The design of CNT@ZnO composites combines the advantages of both ZnO nanoparticles and CNTs. The optimized CNT@ZnO composite exhibits the superior cycling and rate performance. It could deliver a discharge capacity of 709.2 mAh g{sup −1} at 100 mA g{sup −1} after 50 cycles. The electrochemical results indicate that the as-synthesized CNT@ZnO composite is superior in enhancing the electrochemical performance of ZnO-based anode materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Functional protein mining with conformal guarantees

Molecular structure prediction and homology detection offer promising paths to discovering protein function and evolutionary relationships. However, current approaches lack statistical reliability assurances, limiting their practical utility for selecting proteins for further experimental and in-silico characterization. To address this challenge, we introduce a statistically principled approach to protein search leveraging principles from conformal prediction, offering a framework that ensures statistical guarantees with user-specified risk and provides calibrated probabilities (rather than raw ML scores) for any protein search model. Our method (1) lets users select many biologically-relevant loss metrics (i.e. false discovery rate) and assigns reliable functional probabilities for annotating genes of unknown function; (2) achieves state-of-the-art performance in enzyme classification without training new models; and (3) robustly and rapidly pre-filters proteins for computationally intensive structural alignment algorithms. Our framework enhances the reliability of protein homology detection and enables the discovery of uncharacterized proteins with likely desirable functional properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Tuning electrochemical and transport processes to achieve extreme performance and efficiency in solid oxide cells

Solid oxide cells (SOCs) have important applications as fuel cells and electrolyzers. The application for storage of renewable electricity is also becoming increasingly relevant; however, it is difficult to meet stringent area-specific resistance (ASR) and long-term stability targets needed to achieve required efficiency and cost. Here we show a new SOC that utilizes a very thin Gd-doped ceria (GDC)/yttria-stabilized zirconia (YSZ) bi-layer electrolyte, Ni–YSZ cell support with enhanced porosity, and electrode surface modification using PrO x and GDC nanocatalysts to achieve unprecedented low ASR values < 0.1 Ω cm 2 , fuel cell power density ~3 W cm –2 , and electrolysis current density ~4 A cm –2 at 800 °C. Besides this exceptionally high performance, fuel cell and electrolysis life tests suggest very promising stability in fuel cell and steam electrolysis modes. Furthermore, electrochemical impedance spectroscopy analysis done using a novel impedance subtraction method shows how rate-limiting electrode processes are impacted by the new SOC materials and design.

25 ENERGY STORAGE↗
DOE OSTI2026

Two-Level Sketching Alternating Anderson Acceleration for Complex Physics Applications

We present a novel two-level sketching extension of the Alternating Anderson–Picard (AAP) method for accelerating fixed-point iterations in challenging single- and multiphysics simulations governed by discretized PDEs. Our approach combines a static, physics-based projection that reduces the least-squares (LS) problem to the most informative field (e.g., via Schur-complement insight) with a dynamic, algebraic sketching stage driven by a backward stability analysis under Lipschitz continuity. We introduce inexpensive estimators for stability thresholds and cache-aware randomized selection strategies to balance computational cost against memory access overhead. The resulting algorithm solves reduced LS systems in place, minimizes memory footprints, and seamlessly alternates between low-cost Picard updates and Anderson mixing. Implemented in Julia, our two-level sketching AAP achieves up to 50% time-to-solution reductions compared to standard Anderson acceleration—without degrading convergence rates—on benchmark problems including Stokes, 𝑝-Laplacian, bidomain, and Navier–Stokes formulations at varying problem sizes. These results demonstrate the method’s robustness, scalability, and potential for integration into high-performance scientific computing frameworks. Our implementation is available open source in the AAP.jl library.

Barnafi, Nicolas [University of Chile, Santiago]↗
DOE OSTI2024

Wind Turbine Design Guideline DG03: Yaw and Pitch Bearings

This design guideline describes the design criteria, calculation methods, and applicable standards recommended for use in performance and life analyses of ball and roller (rolling) bearings for yaw and pitch motion support in wind turbine applications. The formulae presented here for rolling bearing analytical methods and bearing-life ratings are consistent with methods currently used by wind turbine designers and rolling bearing manufacturers. The original yaw and pitch bearing design guideline was first drafted in 1999 by industry members and finally published in 2009 by the National Renewable Energy Laboratory. It was conceived as the third in a series of design guidelines, but it was the only one actually published by NREL and since has been known by the name "DG03." Other design guidelines were started, but instead of being published by NREL, they eventually became some of the International Electrotechnical Commission wind turbine standards in use today. This updated design guideline includes advances in research and field experiences made between 2009 and 2023. A better understanding of the operating conditions and damage mechanisms, advances in computational design, and publicly available test results facilitate more reliable yaw and pitch bearing designs.

17 WIND ENERGY↗
DOE OSTI2021

A Possible Neutron-Antineutron Oscillation Experiment at PF1B at the Institut Laue Langevin

We consider a possible neutron–antineutron ($n-\overline{n}$) oscillation experiment at the PF1B instrument at Institut Laue Langevin. It can improve the best existing constraint on the transition rate and also allow the testing of the methods and instrumentation which would be needed for a later larger-scale experiment at ESS. The main gain factors over the most competitive experiment, performed earlier at PF1 instrument at ILL, are: a more intense neutron beam and a new operating mode based on coherent n and $\overline{n}$ mirror reflections. The installation of such an experiment would need a temporary replacement of the existing ballistic neutron guide by a specially designed n/$\overline{n}$ guide with a gradually increasing cross section and a specially selected coating as well as the development and construction of an advanced $\overline{n}$ annihilation detector with a high efficiency and low background. The overall gain factor could reach up to an order of magnitude and depends on the chosen experiment configuration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Inverse Compton Cooling in the Coronae of Simulated Black Hole Accretion Flows

Here we present a formulation for a local cooling function to be employed in the diffuse, hot corona region of 3D GRMHD simulations of accreting black holes. This new cooling function calculates the cooling rate due to inverse Compton scattering by considering the relevant microphysics in each cell in the corona and approximating the radiation energy density and Compton temperature thereby integrating over the thermal seed photon flux from the disk surface. The method either assumes the ion and electron temperatures are equal (1T) or calculates them separately (2T) using an instantaneous equilibrium approach predicated on the actual relevant rate equations (Coulomb and Compton). The method is shown to be consistent with a more detailed ray-tracing calculation where the bulk of the cooling occurs, but is substantially less costly to perform. As an example, we apply these methods to a harm3d simulation of a 10M⊙, non-spinning black hole, accreting at nominally 1% the Eddington value. This new approach leads to radiative efficiency values sime65% above Novikov–Thorne, with a larger fraction of total cooling in the corona as compared to simulations performed using the original target-temperature cooling function. Time-averaged post-processing reveals that the continuum spectral observations predicted from these simulations are qualitatively similar to actual X-ray binary data, especially so for the 1T approach, which yields a harder power-law component (Γ = 2.25) compared to the 2T version (Γ = 2.53).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Optimizing Optical Searches for Supermassive Black Hole Binaries in Active Galactic Nuclei Light Curves: Fourier versus Bayesian Periodicity Detection

Simulations predict that supermassive black hole binaries (SMBHBs) will exhibit periodic brightness variations that may exceed the stochastic variability intrinsic to active galactic nuclei (AGN). In this paper, we simulate SMBHBs with damped random walk (DRW) AGN variability and an added sinusoidal signal from the orbital motion, and test three methods—a generalized Lomb–Scargle periodogram (GLSP), a nested Bayesian sampler (NBS), and a weighted wavelet z-transform (or WWZ)—to determine which is best at recovering the periodicity. Our simulated light curves follow the properties of the Catalina Real-Time Transient Survey (or CRTS), Legacy Survey of Space and Time (LSST), and Zwicky Transient Facility (ZTF) to best inform current and future SMBHB searches. We map a broad range of parameter space and identify which DRW-only light curves best mimic periodicity and pass each method’s model selection. The NBS performs best at detecting periodicity and filtering out DRW-only light curves. Combined candidate selection with both the NBS and GLSP significantly reduces false-positive rates (FPRs) with marginal impact on true-positive rates (TPRs). With this joint model selection pipeline, we find the lowest FPRs in ZTF-like simulations and the highest detection rates in LSST-like simulations. Using a modified computation of the false-alarm probability with GLSP, we efficiently triage LSST AGN light curves (∼10 7 light curves in ∼10–30 hr) and achieve TPRs and FPRs of ∼40% and ∼0.5%, respectively.

Banaszak, Sebastian M. [Vanderbilt Univ., Nashvill↗
DOE OSTI2022

The HUNTER Dynamic Human Reliability Analysis Tool: Development of a Module for Performance Shaping Factors

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) in communication with a variety of methods and tools. This paper explores how we developed one of the HUNTER modules: namely, the Individual module for evaluating performance shaping factors (PSFs). A PSF is any factor that influences human performance (e.g., workload or complexity). In the existing HRA, they are used to highlight human errors and adjust error probabilities. We consider the eight PSFs suggested in the Standardized Plant Analysis Risk-HRA (SPAR-H) method, a representative HRA method widely used in the nuclear field. To support our dynamic modeling using the eight SPAR-H PSFs, we reviewed the human performance literature and developed data-based mathematical models to rate and quantify PSFs in the context of dynamic HRA. We also designed the Individual module to consist of two functions: (1) the PSF qualification function for automatically or manually evaluating PSF levels, and (2) the PSF quantification function for dynamically or statically determining PSF multiplier values and integrating them to adjust human error probabilities (HEPs). How each function works in regard to the SPAR-H PSFs, and how the PSFs serve to adjust the HEPs, were investigated via literature review and are discussed in this paper.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Integrated Plastic Substrates for OLED Lighting

OLED lighting has immense potential as aesthetically pleasing, energy-efficient general illumination. Unlike other light sources, such as incandescents, fluorescents, and inorganic LEDs, OLEDs naturally emit over a large-area surface. They are glare free, do not need to be shaded, and are cool to the touch, requiring no heatsink. The best efficiencies and lifetimes reported are on par with or better than current forms of illumination. However, the cost for OLED lighting remains high – so much so that these products are not market competitive and there is very low consumer demand. We believe that flexible, plastic-based devices will highlight the advantages of aesthetically-pleasing OLED lighting systems while paving the way for lowering both materials and manufacturing costs. These flexible devices require new development in substrate and support technology, which was the focus of the work reported here. The project team, led by Sinovia Technologies, has developed integrated plastic substrates to serve as supports for flexible OLED lighting. The substrates created in this project would enable large-area, flexible devices and are specified to perform three functions. They include a barrier to protect the OLED from moisture and oxygen-related degradation, a smooth, highly conductive transparent electrode to enable large-area device operation, and a light scattering layer to improve emission efficiency. Through the course of this project, integrated substrates were fabricated, characterized, evaluated for manufacturing feasibility and cost, and used in white OLED demonstrations to test their impact on flexible OLED lighting. Our integrated substrates meet or exceed the DOE specifications for barrier performance in water vapor and oxygen transport rates, as well as the transparency and conductivity of the anode film. We find that these integrated substrates can be manufactured in a completely roll-to-roll, high throughput process and have developed and demonstrated manufacturing methods that can produce thousands of feet of material without defects. We have evaluated the materials and manufacturing costs of these films at scale and find that they meet the current and future cost targets for bringing down the cost of OLED lighting while enabling future roll-to-roll manufacturing of the complete device. And finally, we have demonstrated that the inherent light-scattering properties of our films enhance white OLED emission efficiency from 20% to 50% depending on the metric. This work has shown that these substrates can be created, manufactured, and will perform as needed to enable flexible OLED lighting to enter the marketplace.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗