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

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At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Savannah River Site Composite Analysis (FY2019 Annual Review)

The Savannah River Site (SRS) is a Department of Energy (DOE) site encompassing approximately 310 square miles in South Carolina. It is bounded on the southwest by the Savannah River (SR) and is situated approximately 12 miles south of Aiken, South Carolina, and 15 miles southeast of Augusta, Georgia. Construction of and subsequent operations at the SRS began in 1951 under the direction of the Atomic Energy Commission. The primary mission of the SRS was to produce tritium and plutonium for the national nuclear weapons complex. Between 1953 and 1955, SRS brought five reactors and various support facilities into operation in support of its primary mission. Support facilities included two chemical separations plants, a heavy water extraction plant, a nuclear fuel and target fabrication facility, a tritium extraction facility and waste management facilities. With the declining need for a large nuclear weapons stockpile since the end of the Cold War, many SRS facilities no longer produce or process nuclear materials. All reactors were shut down by 1993. However, the SRS Tritium Extraction Facility continues to supply DOE with tritium. Additionally, operations at the K-Area Complex currently provide interim safe storage for much of DOE’s excess plutonium (Pu) and high enriched uranium, in a building which formerly housed K Reactor. As the SRS mission has changed, many surplus facilities are being dispositioned safely and economically. SRS has completed extensive decommissioning activities in D-Area, M-Area, P-Area, R-Area, and T-Area, with groundwater (GW) remediation ongoing. High-level waste tanks continue to be emptied and closed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1999

New frontiers in design synthesis

The Intelligent Synthesis Environment (ISE), which is one of the major strategic technologies under development at NASA centers and the University of Virginia, is described. One of the major objectives of ISE is to significantly enhance the rapid creation of innovative affordable products and missions. ISE uses a synergistic combination of leading-edge technologies, including high performance computing, high capacity communications and networking, human-centered computing, knowledge-based engineering, computational intelligence, virtual product development, and product information management. The environment will link scientists, design teams, manufacturers, suppliers, and consultants who participate in the mission synthesis as well as in the creation and operation of the aerospace system. It will radically advance the process by which complex science missions are synthesized, and high-tech engineering Systems are designed, manufactured and operated. The five major components critical to ISE are human-centered computing, infrastructure for distributed collaboration, rapid synthesis and simulation tools, life cycle integration and validation, and cultural change in both the engineering and science creative process. The five components and their subelements are described. Related U.S. government programs are outlined and the future impact of ISE on engineering research and education is discussed.

User-Computer Interface↗
DOE OSTI2017

Snowmelt controls on concentration-discharge relationships and the balance of oxidative and acid-base weathering fluxes in an alpine catchment, East River, Colorado: ACID-BASE VERSUS OXIDATIVE WEATHERING FLUXES

Although important for riverine solute and nutrient fluxes, the connections between biogeochemical processes and subsurface hydrology remain poorly characterized. We investigate these couplings in the East River, CO, a high-elevation shale-dominated catchment in the Rocky Mountains, using concentration-discharge (C-Q) relationships for major cations, anions, and organic carbon. Dissolved organic carbon (DOC) displays a positive C-Q relationship with clockwise hysteresis, indicating mobilization and depletion of DOC in the upper soil horizons and emphasizing the importance of shallow flowpaths during snowmelt. Cation and anion concentrations demonstrate that carbonate weathering, which dominates solute fluxes, is promoted by both sulfuric acid derived from pyrite oxidation in the shale bedrock and carbonic acid derived from subsurface respiration. Sulfuric acid weathering dominates during baseflow conditions when waters infiltrate below the inferred pyrite oxidation front, whereas carbonic acid weathering plays a dominant role during snowmelt as a result of shallow flowpaths. Differential C-Q relationships between solutes suggest that infiltrating waters approach calcite saturation before reaching the pyrite oxidation front, after which sulfuric acid reduces carbonate alkalinity. This reduction in alkalinity results in CO 2 outgassing when waters equilibrate to surface conditions, and reduces the riverine export of carbon and alkalinity by roughly 33% annually. In conclusion, future changes in snowmelt dynamics that control the balance of carbonic and sulfuric acid weathering may substantially alter carbon cycling in the East River. Ultimately, we demonstrate that differential C-Q relationships between major solutes can provide unique insights into the complex subsurface flow and biogeochemical dynamics that operate at catchment scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

ExaWind: Open‐source CFD for hybrid‐RANS/LES geometry‐resolved wind turbine simulations in atmospheric flows

Abstract Predictive high‐fidelity modeling of wind turbines with computational fluid dynamics, wherein turbine geometry is resolved in an atmospheric boundary layer, is important to understanding complex flow accounting for design strategies and operational phenomena such as blade erosion, pitch‐control, stall/vortex‐induced vibrations, and aftermarket add‐ons. The biggest challenge with high‐fidelity modeling is the realization of numerical algorithms that can capture the relevant physics in detail through effective use of high‐performance computing. For modern supercomputers, that means relying on GPUs for acceleration. In this paper, we present ExaWind, a GPU‐enabled open‐source incompressible‐flow hybrid‐computational fluid dynamics framework, comprising the near‐body unstructured grid solver Nalu‐Wind, and the off‐body block‐structured‐grid solver AMR‐Wind, which are coupled using the Topology Independent Overset Grid Assembler. Turbine simulations employ either a pure Reynolds‐averaged Navier–Stokes turbulence model or hybrid turbulence modeling wherein Reynolds‐averaged Navier–Stokes is used for near‐body flow and large eddy simulation is used for off‐body flow. Being two‐way coupled through overset grids, the two solvers enable simulation of flows across a huge range of length scales, for example, 10 orders of magnitude going from O(μm) boundary layers along the blades to O(10 km) across a wind farm. In this paper, we describe the numerical algorithms for geometry‐resolved turbine simulations in atmospheric boundary layers using ExaWind. We present verification studies using canonical flow problems. Validation studies are presented using megawatt‐scale turbines established in literature. Additionally presented are demonstration simulations of a small wind farm under atmospheric inflow with different stability states.

17 WIND ENERGY↗
DOE OSTI2023

Complementarity and the unitarity of the black hole S -matrix

Recently, Akers et al. proposed a non-isometric holographic map from the interior of a black hole to its exterior. Within this model, we study properties of the black hole S-matrix, which are in principle accessible to observers who stay outside the black hole. Specifically, we investigate a scenario in which an infalling agent interacts with radiation both outside and inside the black hole. Because the holographic map involves postselection, the unitarity of the S-matrix is not guaranteed in this scenario, but we find that unitarity is satisfied to very high precision if suitable conditions are met. If the internal black hole dynamics is described by a pseudorandom unitary transformation, and if the operations performed by the infaller have computational complexity scaling polynomially with the black hole entropy, then the S-matrix is unitary up to corrections that are superpolynomially small in the black hole entropy. Furthermore, while in principle quantum computation assisted by postselection can be very powerful, we find under similar assumptions that the S-matrix of an evaporating black hole has polynomial computational complexity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Association with pedogenic iron and aluminum: effects on soil organic carbon storage and stability in four temperate forest soils

Soil organic carbon (SOC) can be stabilized via association with iron (Fe) and aluminum (Al) minerals. Fe and Al can be strong predictors of SOC storage and turnover in soils with relatively high extractable metals content and moderately acidic to circumneutral pH. Here we test whether pedogenic Fe and Al influence SOC content and turnover in soils with low Fe and Al content and acidic pH. In soils from four sites spanning three soil orders, we quantified the amount of Fe and Al in operationally-defined poorly crystalline and organically-complexed phases using selective chemical dissolution applied to the soil fraction containing mineral-associated carbon. We evaluated the correlations of Fe and Al concentrations, mean annual precipitation (MAP), mean annual temperature (MAT), and pH with SOC content and 14C-based turnover times. We found that poorly crystalline Fe and Al content predicted SOC turnover times (p < 0.0001) consistent with findings of previous studies, while organically-complexed Fe and Al content was a better predictor of SOC concentration (p < 0.0001). Greater site-level MAP (p < 0.0001) and colder site-level MAT (p < 0.0001) were correlated with longer SOC turnover times but were not correlated with SOC content. Our results suggest that poorly crystalline Fe and Al effectively slow the turnover of SOC in these acidic soils, even when their combined content in the soil is less than 2% by mass. However, in the strongly acidic Spodosol, organo-metal complexes tended to be less stable resulting in a more actively cycling mineral-associated SOC pool.

14C↗
DOE OSTI2017

Parallel accelerated cyclic reduction preconditioner for three-dimensional elliptic PDEs with variable coefficients

We present a robust and scalable preconditioner for the solution of large-scale linear systems that arise from the discretization of elliptic PDEs amenable to rank compression. The preconditioner is based on hierarchical low-rank approximations and the cyclic reduction method. The setup and application phases of the preconditioner achieve log-linear complexity in memory footprint and number of operations, and numerical experiments exhibit good weak and strong scalability at large processor counts in a distributed memory environment. Numerical experiments with linear systems that feature symmetry and nonsymmetry, definiteness and indefiniteness, constant and variable coefficients demonstrate the preconditioner applicability and robustness. Furthermore, it is possible to control the number of iterations via the accuracy threshold of the hierarchical matrix approximations and their arithmetic operations, and the tuning of the admissibility condition parameter. Together, these parameters allow for optimization of the memory requirements and performance of the preconditioner.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Reliable extrapolation of deep neural operators informed by physics or sparse observations

Deep neural operators can learn nonlinear mappings between infinite-dimensional function spaces via deep neural networks. As promising surrogate solvers of partial differential equations (PDEs) for real-time prediction, deep neural operators such as deep operator networks (DeepONets) provide a new simulation paradigm in science and engineering. Pure data-driven neural operators and deep learning models, in general, are usually limited to interpolation scenarios, where new predictions utilize inputs within the support of the training set. However, in the inference stage of real-world applications, the input may lie outside the support, i.e., extrapolation is required, which may result to large errors and unavoidable failure of deep learning models. Here, we address this challenge of extrapolation for deep neural operators. First, we systematically investigate the extrapolation behavior of DeepONets by quantifying the extrapolation complexity, via the 2-Wasserstein distance between two function spaces and propose a new strategy of bias–variance trade-off for extrapolation with respect to model capacity. Subsequently, we develop a complete workflow, including extrapolation determination, and we propose five reliable learning methods that guarantee a safe prediction under extrapolation by requiring additional information—the governing PDEs of the system or sparse new observations. The proposed methods are based on either fine-tuning a pre-trained DeepONet or multifidelity learning. We demonstrate the effectiveness of the proposed framework for various types of parametric PDEs. Furthermore, our systematic comparisons provide practical guidelines for selecting a proper extrapolation method depending on the available information, desired accuracy, and required inference speed.

42 ENGINEERING↗
DOE OSTI2024

Design and analysis of actively-cooled, edge-transport diagnostic for long-pulsed operation in WEST

Next step fusion devices that will operate in steady-state will require complex plasma-facing components (PFCs) that can survive the harsh environment over long timescales not common in current devices. This will require robust plasma facing surfaces that are integrated with active cooling systems. In a collaboration between CEA and ORNL, a plasma-interacting diagnostic is being designed for the W Environment in Steady-state Tokamak (WEST) in Cadarache, France which requires plasma-facing protection like those needed for steady-state PFCs. This integrated diagnostic studies edge transport and impurity migration within WEST, and is planned to include imbedded temperature Langmuir probe sensors, as well as removeable sample slots for ex-situ surface analysis of plasma-material interactions. The entire assembly is expected to move into the plasma edge for periods up to 1000 s having an energy removeable capability of ∼6 kW and seeing a peak heat flux of more than 7 MW/m2. The assembly compliments WEST high fluence campaigns that plan for multiple 1000 s pulses. Within these specifications, the assembly will require a refractory metal plasma facing surface and integral cooling in order to function within the limited space allotted for such diagnostics. Because of the limited space and linear actuator needs, additive manufacturing of the high heat flux working end of the assembly is being considered which could allow for precision cooling-channels and lighter weight designs. Conceptual design along with simulation and analysis results will be presented for this complex diagnostic with novel PFCs.

Lumsdaine, Arnold↗
DOE OSTI2018

An adaptive, implicit, conservative, 1D-2V multi-species Vlasov–Fokker–Planck multi-scale solver in planar geometry

We consider a 1D-2V Vlasov–Fokker–Planck multi-species ionic description coupled to fluid electrons. We address temporal stiffness with implicit time stepping, suitably preconditioned. To address temperature disparity in time and space, we extend the conservative adaptive velocity-space discretization scheme proposed in [Taitano et al., J. Comput. Phys., 318, 391–420, (2016)] to a spatially inhomogeneous system. Here in this approach, we normalize the velocity-space coordinate to a temporally and spatially varying local characteristic speed per species. We explicitly consider the resulting inertial terms in the Vlasov equation, and derive a discrete formulation that conserves mass, momentum, and energy up to a prescribed nonlinear tolerance upon convergence. Our conservation strategy employs nonlinear constraints to enforce these properties discretely for both the Vlasov operator and the Fokker–Planck collision operator. Numerical examples of varying degrees of complexity, including shock-wave propagation, demonstrate the favorable efficiency and accuracy properties of the scheme.

1D2V↗
DOE OSTI2022

Continuous electrocoagulation-membrane distillation unit for treating hydraulic fracturing produced water

Hydraulic fracturing oil and gas produced water is frequently highly impaired. While it is often deep well injected, there is great interest in treating this water for beneficial uses. Given the complexity of these produced waters, multiple unit operations are necessary. Electrocoagulation has been considered as a promising pretreatment technology. Here electrocoagulation is considered as a pretreatment prior to membrane distillation. The focus of this work is on understanding the electrocoagulation process in order to design an integrated unit operation. Electrocoagulation is used to remove organic compounds that will foul the membrane leading to membrane failure during membrane distillation. Using aluminum or iron electrodes, half-cell reactions in the electrocoagulation cell and electrode potentials have been calculated. Electrocoagulation was conducted using a continuous electrocoagulation reactor with actual produced water using aluminum, iron or mixed aluminum and iron electrodes. Here, the results obtained here indicate that electrocoagulation can obtain good removal efficiency of total organic carbon (TOC) by using different reaction conditions. Removal of organic compounds is essential to minimize fouling during membrane distillation. Further the performance of the electrocoagulation process depends strongly on the quality of the feed water. Insoluble species were more effectively coagulated than dissolved organic species. Continuous electrocoagulation shows great potential as a scalable unit operation for pretreating hydraulic fracturing produced water.

42 ENGINEERING↗
DOE OSTI2026

Atomic-scale vacancy engineering unlocks basal-plane catalytic activity in metallic WSe 2 for reversible oxygen electrocatalysis

Two-dimensional metallic transition metal dichalcogenides offer high electrical conductivity and large surface areas for electrocatalysis, yet their inherent basal planes are catalytically inert. Here, we present an atomic-scale vacancy engineering strategy to activate the basal surfaces of metallic WSe 2 for reversible oxygen electrocatalysis. This approach, based on intentionally designed substitutional metal doping, promotes the spontaneous formation of selenium vacancies while preserving the metallic 1 T′ phase, thereby creating highly reactive and oxygen-affinitive sites. Density functional theory calculations reveal that these vacancy-mediated metal complexes dramatically lower the energy barriers for initial oxygen adsorption, enabling dissociative oxygen adsorption. Operando and ex-situ spectroscopic analyses confirm that vacancy-mediated metal complexes transform into dynamic Se/W-oxide intermediates under operating conditions. Se/W-oxides on the surface experimentally and theoretically prove electrocatalytic activity and reversibility. Applying this strategy in lithium–oxygen batteries, the basal-plane activated WSe 2 shows high discharge capacities (9868 mA h g −1 , corresponding to 3947 mA h g$^{-1}_{cathode}$), impressive cycle retention over 550 cycles at 1000 mA h g −1 , and outstanding rate–capability over a wide current–density range (100–3000 mA g −1 ) during 256 cycles.

2D materials↗
DOE OSTI2018

Attribution of gamma-ray background collected by a mobile detector system to its surroundings using panoramic video

Mobile radiation detector systems are important tools for detecting radiological and nuclear sources outside of regulatory control, but due to their mobility, they are subject to complex and varying backgrounds in most realistic operational scenarios. Recent work has found correlations between non-radiological contextual information and gamma-ray spectral features that can be used to decrease false alarm rates, however a more complete understanding of background source terms has been elusive. A measurement campaign developed a full radiological characterization of a controlled facility that roughly corresponded to two city blocks. As part of the campaign, the Radiological Multi-sensor Analysis Platform (RadMAP) collected extensive multi-sensor data. In this work, RadMAP’s panoramic video data were used to visually identify several different materials and quantify the detector response to each material. A linear model was fit between the material responses and radiological features, and the results demonstrate reasonable agreement with ground truth flux measurements for each material. This paper will describe the data collection, processing, and analysis of the gamma-ray and video data from RadMAP. The paper will conclude with perspectives on the applicability of such a method to less controlled environments both with respect to achieving better understanding the sources of variability of background radiation in urban environments and whether such methods could be leveraged in operational scenarios.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Microwave-assisted C–H oxidation of methylpyridylheteroarenes via a Kornblum-Type reaction

Expansion of the operational capacity of soft-Lewis basic complexant scaffolds towards improved physical properties for the chemoselective sequestration of minor actinides from the electronically similar lanthanides necessitates rapid access to synthons for efficient complexant construction for downstream employment in separations assays. Pursuant to the aforementioned, we were interested in exploring the potential utility of advanced, unsymmetric heteroarene constructs for separations which required access to pyridyl carbaldehydes. Limited commercial availability of synthetic precursors inspired our effort to define a chemoselective, microwave assisted, Kornblum-type reaction via C–H functionalization. This efficient reaction sequence uses I 2 as a mild oxidant without acidic or basic additives, in concert with DMSO as the solvent and putative oxygen source to afford a diverse array of heteroaryl products devoid of competitive remote methyl group oxidation, or degradation of the heteroaryl N atom. Finally, method development, substrate scope, and a preliminary mechanistic hypothesis supported by Density Functional Theory are presented herein.

1,2,4-triazine↗
DOE OSTI2018

Equilibria and Rate Phenomena from Atomistic to Mesoscale: Simulation Studies of Magnetite

Batteries are complex devices composed of multiple components that operate far from equilibrium and may operate under extreme stress and varying loads. Research of isolated battery components are valuable to the fundamental understanding of the physical processes occurring within each constituent element. When the components are integrated into a full device and operated under realistic conditions, it can be difficult to decouple the physical processes that occur across multiple interfaces and multiple length scales. Thus, the physical processes studied in isolated components may change in a full battery setup or may be irrelevant to performance. Simulation studies on many length scales play a key role in the analysis of experiments and in the elucidation of the relevant physical processes impacting performance. In this Account, we aim to highlight the use of modeling on multiple length scales to identify rate limiting phenomena in lithium-ion batteries. To illustrate the utility of modeling, we examine lithium-ion batteries with nanostructured magnetite, Fe 3 O 4 , as the positive electrode active material against a solid Li 0 negative electrode. Due to continuous operation away from equilibrium, batteries exhibit highly nonideal behavior, and a model that aims to reproduce behavior under realistic operating conditions must be able to capture the physics occurring on the length scales relevant to the performance of the system. It is our experience that limiting behavior in lithium-ion batteries can be observed on the atomic scale and up through the electrode scale and thus, predictive models must be capable of integrating and communicating physics across multiple length scales. Magnetite is studied as an electrode material for lithium-ion batteries, but it is found to suffer from slow solid-state transport of lithium, slow reaction kinetics, and poor cycling. Magnetite (Fe 3 O 4 ) is a material capable of undergoing multiple electron transfers (MET), and can accept up to eight lithium per formula unit (Li 8 Fe 3 O 4 ). Magnetite, (Fe 8a 3+ )[Fe 3+ Fe 2+ ] 16d O 4,32e 2– , has a close-packed inverse spinel structure and undergoes intercalation, structural rearrangement, and conversion reactions upon full lithiation. To overcome solid-state transport resistances, magnetite can be nanostructured to decrease Li + diffusion lengths, and this has been shown to increase capacity. Additionally, unique architectures incorporating both carbon and Fe 3 O 4 have shown to alleviate transport and cycling issues in the material. Here, we solely address traditional composite electrodes, in which Fe 3 O 4 is synthesized as nanoparticles and combined with additives to fabricate the electrode. In the case of nanoparticulate magnetite, it has been found that the electrode fabrication process results in the formation of micrometer-sized agglomerates of the Fe 3 O 4 nanoparticles, introducing a secondary structural motif. The agglomerates may form in one or more fabrication processes, and their elimination may not be straightforward or warranted. Here, we highlight the impact of these secondary formations on the performance of the Fe 3 O 4 lithium-ion battery. We illustrate how simulations can be used to design experiments, prioritize research efforts, and predict performance.

25 ENERGY STORAGE↗
DOE OSTI2022

Understanding Hydrogenation Chemistry at MgB 2 Reactive Edges from Ab Initio Molecular Dynamics

Solid-state hydrogen storage materials often operate via transient, multistep chemical reactions at complex interfaces that are difficult to capture. Here, we use direct ab initio molecular dynamics simulations at accelerated temperatures and hydrogen pressures to probe the hydrogenation chemistry of the candidate material MgB 2 without a priori assumption of reaction pathways. Focusing on highly reactive ($10\overline{1}0$) edge planes where initial hydrogen attack is likely to occur, we track mechanistic steps toward the formation of hydrogen-saturated BH 4 – units and key chemical intermediates, involving H 2 dissociation, generation of functionalities and molecular complexes containing BH 2 and BH 3 motifs, and B–B bond breaking. Further, the genesis of higher-order boron clustering is also observed. Different charge states and chemical environments at the B-rich and Mg-rich edge planes are found to produce different chemical pathways and preferred speciation, with implications for overall hydrogenation kinetics. The reaction processes rely on B–H bond polarization and fluctuations between ionic and covalent character, which are critically enabled by the presence of Mg 2+ cations in the nearby interphase region. Our results provide guidance for devising kinetic improvement strategies for MgB 2 -based hydrogen storage materials, while also providing a template for exploring chemical pathways in other solid-state energy storage reactions.

08 HYDROGEN↗
DOE OSTI2026

Stable Co-valorization of Carbon Dioxide and Methane via Dynamic Reconstruction of a Metal Oxide Solid Solution Catalyst

Dry reforming of methane (DRM) is a process that converts two greenhouse gases (methane and carbon dioxide) into syngas, a mixture of H 2 and CO, that can lead to a variety of value-added chemicals. Owing to its endothermic nature, high reaction temperatures up to 800 °C are typically required and the grand challenge lies in developing robust catalysts without sintering and coking-induced deactivation during the long-term on-stream operation. Towards this aim, herein, a robust complex oxide-supported NiCu alloy catalyst was generated in situ during DRM. By leveraging the configurational stability of a solid oxide solution precursor, tightly anchored NiCu bimetallic nanoparticles were in situ exsoluted and acted as the active sites in DRM. The as-afforded catalyst exhibited stable performance for DRM due to the ability to repel coke off the surface as the reaction proceeds. Kinetic experiments along with top surface characterization detail the reconstruction behavior of the solid oxide solution under DRM reaction conditions. In conclusion, the fundamental insights from this work provide guidance on generating resistant and flexible catalysts via in situ active sites formation from easily synthesized metal oxide solid solutions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Durability Research Is Pivotal for Perovskite Photovoltaics

Metal halide perovskite solar cells have shown promising power conversion efficiencies, but commercialization requires that decent durability is also demonstrated. Under normal operation, solar cells are subject to a complex combination of stressors, such as visible light, ultraviolet light, heat, humidity, mechanical stress and electric potential, which complicates the understanding of failure mechanisms. Existing stress tests do not act as a time machine. In new materials systems such as perovskite photovoltaics, the tests have no known relationship to field service. In this Perspective we recommend following a durability learning cycle that interleaves photovoltaic module engineering with field testing; accelerated testing; and preconditioning and performance engineering. We advocate for field testing to demonstrate real-world performance and identify field-relevant failure modes, and urge the community to develop accelerated and qualification tests that account for device metastability, variations in material composition and different/various processing methods. In conclusion, these practices are more difficult, but more important, than the simple pursuit of higher initial efficiencies.

14 SOLAR ENERGY↗