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DOE OSTI2022

Pit Stability Predictions of Additively Manufactured SS316 Surfaces Using Finite Element Analysis

Stainless steels are susceptible to localized forms of corrosion attack, such as pitting. The size and lifetime of a nucleated pit can vary, depending on a critical potential or current density criterion, which determines if the pit repassivates or continues growing. This work uses finite element method (FEM) modeling to compare the critical pit radii predicted by thermodynamic and kinetic repassivation criteria. Experimental electrochemical boundary conditions are used to capture the active pit kinetics. Geometric and environmental parameters, such as the pit shape and size (analogous to additively manufactured lack-of-fusion pores), solution concentration, and water layer thickness were considered to assess their impact on the pit repassivation criterion. The critical pit radius (the transition point from stable growth to repassivation) predicted for a hemispherical pit was larger when using the repassivation potential (E rp ) criteria, as opposed to the current density criteria (pit stability product). Including both the pit stability product and E rp into its calculations, the analytical maximum pit model predicted a critical radius two times more conservative than the FEA approach, under the conditions studied herein. The complex pits representing lack-of-fusion pores were shown to have minimal impact on the critical radius in atmospheric conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Aerosol Chemical Speciation Monitor (ACSM) Composition-Dependent Collection Efficiency (CDCE) Value-Added Product Report

Aerosol particles influence the Earth’s radiation balance directly by absorbing and scattering light and indirectly by influencing cloud formation, properties, and lifetimes. Measurements of aerosol particle optical properties, mass loading, size distributions, microphysical properties, cloud formation properties, and chemical composition are important for understanding the aerosol life cycle and for validating earth system models that predict these quantities. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Aerosol Observing System (AOS) is a highly instrumented platform that measures many of these aerosol properties in situ. The Aerodyne aerosol chemical speciation monitor (ACSM) is a baseline instrument deployed in the AOS. The ACSM provides a quantitative measurement of aerosol particle chemical composition for non-refractory (operationally defined as components that evaporate on the 600ºC vaporizer) aerosol components in real time. Standard output is the mass concentration of particulate organics, nitrate, sulfate, chloride, and ammonium. One well-known limitation to the accuracy of the ACSM data is in evaluating the fraction of the ambient aerosol particles that are detected by the instrument. This quantity is referred to as the collection efficiency (CE) and is often less than unity. This is attributed to particles rebounding after impaction onto the heated vaporizer rather than being trapped, volatilized rapidly, and detected. Other factors, such as divergence of the aerosol particle beam, may also impact CE, but the particle rebound effect is the dominant factor. Scientists will sometimes assume CE = 0.5 (i.e., one half of sampled particles are detected) for ambient particles collected during field missions. However, parameterizations have been developed that express CE as a function of the measured chemical composition, referred to as the composition-dependent collection efficiency (CDCE). The physical explanation for a CDCE, supported by laboratory studies, is that rebound from the vaporizer is a function of the particle phase, with liquid-like particles “sticking” to the vaporizer and solid-like or crystalline particles “bouncing” from the vaporizer. Thus, particles with compositions are liquids-like under the measurement conditions (e.g., certain organics, acidic particles, particles enriched in nitrate) have CE close to unity while crystalline or solid particles (e.g., deliquesced ammonium sulfate) have lower CE. This value-added product (VAP) implements the procedure described by Middlebrook et al. (2012) to correct the ACSM data for the composition-dependent collection efficiency. Applying this parameterization improves the accuracy of the ACSM data and brings them into better agreement with other co-located aerosol measurements.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Scanning Mobility Particle Sizer (SMPS)-Aerodynamic Particle Sizer (APS) Merged Size Distribution (mergedsmpsaps) Value-Added Product Report

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Dynamic Evolution of Mass and Physical Properties of Atmospheric Organic Aerosol under Solar Irradiance

Organic aerosol (OA) particles constitute a substantial fraction of sub-micron particulate mass in the atmosphere and play a critical role in climate system. OA undergoes dynamic aging processes in the atmosphere, with photolytic aging induced by ultraviolet solar irradiance being an important yet poorly characterized mechanism. Knowledge gaps persist regarding the role of volatility transformations during photolytic aging on the OA mass decay kinetics and the evolution of climate-relevant properties, such as hygroscopicity, hindering the model evaluation of OA spatiotemporal distributions and atmospheric budgets. In this study, we conduct isothermal photolytic aging experiments on both laboratory-generated secondary organic aerosols and ambient-collected particles from urban Atlanta, utilizing a high-sensitivity Quartz Crystal Microbalance. Our results reveal that photolytic aging reduces 40–66% of the low-volatility OA mass with lifetimes ranging from 8 to 200 hours under solar irradiance, and 44–92% of the photolytic mass loss is through slow evaporation of semi- or intermediate-volatile products, kinetically limited by their volatility. We observe up to ±50% changes in OA hygroscopicity with the transformation of fresh OA to photo-recalcitrant low-volatility products, associated with changes in oxygen-to-carbon ratio and molecular weight. A kinetic model incorporating photolytic volatility transformation provides a cohesive explanation for the observed photolysis-induced changes in mass, volatility, and hygroscopicity. Our results can help constrain model representation of the dynamic evolutions of mass and climate-relevant properties during photolytic aging processes of the ambient OA, improving our understanding of OA atmospheric behavior and climate impact.

Bai, Bin↗

DOE OSTI2021

Search for exotic decays of the Higgs boson into long-lived particles in pp collisions at $\sqrt{s}$ = 13 TeV using displaced vertices in the ATLAS inner detector

A novel search for exotic decays of the Higgs boson into pairs of long-lived neutral particles, each decaying into a bottom quark pair, is performed using 139 fb -1 of $\sqrt{s}$ = 13 TeV proton-proton collision data collected with the ATLAS detector at the LHC. Events consistent with the production of a Higgs boson in association with a leptonically decaying Z boson are analysed. Long-lived particle (LLP) decays are reconstructed from inner-detector tracks as displaced vertices with high mass and track multiplicity relative to Standard Model processes. The analysis selection requires the presence of at least two displaced vertices, effectively suppressing Standard Model backgrounds. The residual background contribution is estimated using a data-driven technique. No excess over Standard Model predictions is observed, and upper limits are set on the branching ratio of the Higgs boson to LLPs. Branching ratios above 10% are excluded at 95% confidence level for LLP mean proper lifetimes cτ as small as 4 mm and as large as 100 mm. For LLP masses below 40 GeV, these results represent the most stringent constraint in this lifetime regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Electron shelving of a superconducting artificial atom

Interfacing long-lived qubits with propagating photons is a fundamental challenge in quantum technology. Cavity and circuit quantum electrodynamics (cQED) architectures rely on an off-resonant cavity, which blocks the qubit emission and enables a quantum non-demolition (QND) dispersive readout. However, no such buffer mode is necessary for controlling a large class of three-level systems that combine a metastable qubit transition with a bright cycling transition, using the electron shelving effect. Here we demonstrate shelving of a circuit atom, fluxonium, placed inside a microwave waveguide. With no cavity modes in the setup, the qubit coherence time exceeds 50 μs, and the cycling transition’s radiative lifetime is under 100 ns. By detecting a homodyne fluorescence signal from the cycling transition, we implement a QND readout of the qubit and account for readout errors using a minimal optical pumping model. Our result establishes a resource-efficient (cavityless) alternative to cQED for controlling superconducting qubits.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Early-Stage Radiation Safety Analysis for the Spallation Neutron Source Second Target Station Bunker Operations

The Second Target Station project at Oak Ridge National Laboratory will develop a cold neutron source to meet growing experimental needs. This paper describes calculations of the residual dose rates associated with the monolith shield plug and the beamline bunker, two key conventional operations and radiation safety features. While neutron production is active, the instrument hall outside the bunker must be generally accessible with dose rates of less than 0.25 mrem/h. When neutron production is halted, the bunker must be accessible for hands-on maintenance operations. Further, these two requirements form the cause for the assessments reported herein of residual dose rates caused by the monolith shield plug and residual dose rates in the bunker. The monolith shield plug was shown to not produce significant dose rates inside the bunker after a 20-year lifetime, and the residual dose rates inside the bunker for the case of an operating beamline were shown to reasonably allow for hands-on maintenance. These calculations are based on preliminary design models of the relevant systems. Additionally, an example showing the significance of considering neutron supermirror physics in transport calculations that track nuclide production and destruction rates to produce gamma sources for residual dose rate calculations is included. The example shows that if neutron supermirror physics is not considered, dose rate fields may be significantly underpredicted.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2026

Proposal to search for long-lived neutral particles in CERN service shafts

Long-lived particles are predicted by many extensions of the Standard Model and have been gaining interest in recent years. In this paper the original proposal is presented for AN Underground Belayed In-Shaft (ANUBIS) detector that substantially extends the sensitivity to particle lifetimes by instrumenting the existing service shafts above the ATLAS or CMS experiments with tracking stations. For scenarios with electrically neutral long-lived particles with 𝑚 ≳ 1~GeV produced at the electroweak scale and above, the lifetime reach is increased by 2-3 orders of magnitude compared to currently operating and approved future experiments at the LHC. Here, the original ANUBIS detector design proposal is outlined along with the projected costs.

ANUBIS↗

DOE OSTI2022

Commercial, industrial, and institutional discount rate estimation for efficiency standards analysis: Sector-level data 1998–2021

Underlying each of the Department of Energy’s (DOE’s) federal appliance and equipment energy conservation standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). DOE determines economic justification based on whether the benefits exceed the burdens, considering a variety of factors, including the economic impact of the standard on consumers of the product and the savings in lifetime operating cost compared to any increase in price or maintenance expenses (42 U.S.C. 6295(o)(2)(B)). As part of this determination, DOE conducts a Life-Cycle Cost (LCC) analysis, which models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample in order to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels. Thus, the commercial discount rate value(s) used to calculate the present value of energy cost savings within the LCC model implicitly plays a role in estimating the economic impact of potential standard levels. This report provides an in-depth discussion of the commercial discount rate estimation process. It is an update to previous reports on estimating commercial discount rates from firm-level financial data (Fujita, 2016). Major topics covered in this report include: Discount rate estimation methods and rationale; -Data sources used and data limitations; -Discount rate distributions for use in standards analysis; -Discount rate estimation methods and distributions specific to the small business subgroup analysis. Going forward, this report will be updated as data allow and analyses necessitate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Commercial, industrial, and institutional discount rate estimation for efficiency standards analysis: Sector-level data 1998–2022

Underlying each of the U.S. Department of Energy’s (DOE’s) federal appliance and equipment energy conservation standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). DOE determines economic justification based on whether the benefits exceed the burdens, considering a variety of factors, including the economic impact of the standard on consumers of the product and the savings in lifetime operating cost compared to any increase in price or maintenance expenses (42 U.S.C. 6295(o)(2)(B)). As part of this determination, DOE conducts a life-cycle cost (LCC) analysis, which models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels. Thus, the commercial discount rate value(s) used to calculate the present value of energy cost savings within the LCC model implicitly plays a role in estimating the economic impact of potential standard levels. This report provides an in-depth discussion of the commercial discount rate estimation process. It is an update to previous reports on estimating commercial discount rates from firm-level and sector-level financial data (e.g., Fujita, 2021, 2016). Major topics covered in this report include the following: -Discount rate estimation methods and rationale -Data sources used and data limitations -Discount rate distributions for use in standards analysis -Discount rate estimation methods and distributions specific to the small business subgroup analysis A version of this analysis was most recently released in 2022. Going forward, this report will be updated as data allow and analyses necessitate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Commercial, industrial, and institutional discount rate estimation for efficiency standards analysis: Sector-level data 1998–2023

Underlying each of the U.S. Department of Energy’s (DOE’s) federal appliance and equipment energy conservation standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). DOE determines economic justification based on whether the benefits exceed the burdens, considering a variety of factors, including the economic impact of the standard on consumers of the product and the savings in lifetime operating cost compared to any increase in price or maintenance expenses (42 U.S.C. 6295(o)(2)(B)). As part of this determination, DOE conducts a life-cycle cost (LCC) analysis, which models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels. Thus, the commercial discount rate value(s) used to calculate the present value of energy cost savings within the LCC model implicitly plays a role in estimating the economic impact of potential standard levels. This report provides an in-depth discussion of the commercial discount rate estimation process relying on the Capital Asset Pricing Model (CAPM) to estimate a business’ cost of equity, and by adding a risk adjustment factor to the risk-free rate associated with long-term U.S. Treasury bonds to estimate their cost of debt. It is an update to previous reports on estimating commercial discount rates from firm-level and sector-level financial data (e.g., Fujita, 2021, 2016). Major topics covered in this report include the following: • Discount rate estimation methods and rationale • Data sources used and data limitations • Discount rate distributions for use in standards analysis • Discount rate estimation methods and distributions specific to the small business subgroup analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Regulating Gas Transport in Molecularly Engineered Polymer Membranes (Final Technical Report)

Energy-efficient separation processes are essential for a wide range of applications ranging from clean fuels (e.g., hydrogen purification) and petroleum refining (e.g., natural gas processing) to water purification and carbon capture. Membrane-mediated separations have shown tremendous promise in providing high productivity and high separation efficiency at significantly lower energy consumption, e.g., up to 90% less energy cost than traditional thermally driven processes such as distillation. Polymeric membranes–the dominant separation membrane materials–have yet to reach their full potential due to their limitations in long-term durability (e.g., productivity loss over the period of their lifetime due to physical aging) or insufficient stability under harsh conditions (e.g., high temperature, chemically complex feeds). This research seeks to establish a new paradigm in polymer membrane material design by harnessing crosslinked model networks with well-defined yet finely tailorable microstructure to facilitate fast and selective gas transport and simultaneously enhance membrane stability. Unlike traditional randomly crosslinked polymers, which suffer from structural inconsistencies and consequently suboptimal gas separation performance, crosslinked model network membranes prepared via a precisely controlled end-linking process enables the creation of previously unattainable microstructure tunability, which, in turn, results in versatile crosslinked membranes with high separation performance that meet the needs of various challenging gas separations. Using model network framework as a fundamental tool by applying this concept in diverse polymer categories, this work has led to the development of various innovative crosslinked membrane structures such as unimodal, bimodal and clustered model networks. These advanced crosslinked polymer membranes not only demonstrate exceptional gas separation performance that significantly outperform existing randomly crosslinked membranes, but also possess excellent long-term durability and robust stability under complex operating conditions. From a fundamental perspective, results from this research provide critical mechanistic insights into gas separation in crosslinked polymer membranes, addressing key knowledge gaps and opening new avenues for membrane design to meet various separation needs. The new membrane materials produced from this research enable the use of polymeric membranes for high temperature gas separations, offering substantial energy and cost savings by eliminating the need for repeated cooling-heating cycles in industrial processes.

02 PETROLEUM↗

DOE OSTI2025

Storage-Induced Collapse of Lignin Macromolecular Structure and Its Impacts on the Biorefinery

Lignin plays a vital role in the economics of biorefineries, serving as a source of process energy and a feedstock for sustainable fuels and chemical production. While understanding lignin’s chemical composition is crucial, emerging evidence suggests that a more comprehensive understanding of its macromolecular structure is critical to explaining its complex behavior in the biorefinery. This study investigated the partial collapse of the lignin network in corn stover feedstock after harvest and storage as a result of the microbial digestion of hemicellulose. Fluorescence microscopy was used to detect the collapse of lignin in terms of lignin’s inter-molecular interaction and the re-orientation of lignin’s chromophores, by the changes in lignin’s fluorescence lifetime, anisotropy, and the number of effective emitters. With minimal sample perturbation, our in-situ microscopic results revealed lignin's coil-globule transition phenomena, which was only previously predicted by molecular dynamics modeling extracted lignin in solvent. This collapse of lignin macromolecular structure was confirmed by results from NMR, IR, Raman, and powder X-ray diffraction. We also investigated the impact of this storage-induced collapse on the downstream biorefinery processes. Our study revealed that the two major approaches for lignin valorization in the lignin-first biorefinery model, namely monomer extraction and milled wood lignin extraction, were negatively impacted by the lignin collapse. As changes during storage are a source of feedstock variability, our study highlights the importance of understanding the effect of feedstock handling on biorefinery operations and economics.

09 BIOMASS FUELS↗

DOE OSTI2020

Pair plasma instability in homogeneous magnetic guide fields

Pair plasmas, collections of both matter and antimatter particles of equal mass, represent a paradigm for the study of basic plasma science, and many open questions exist regarding these unique systems. They are found in many astrophysical settings, such as gamma-ray bursts, and have recently also been produced in carefully designed laboratory experiments. A central research topic in plasma physics is instability; however, unlike their more common ion–electron siblings, pair plasmas are generally thought to be stable to cross field pressure gradients in homogeneous magnetic fields. It is shown here by means of kinetic full-f simulations that, when a pressure gradient is first established, the Gradient-driven Drift Coupling mode is destabilized and becomes turbulent. Force balance is eventually achieved by a combination of flattened pressure profiles due to turbulent transport and establishment of a magnetic field gradient, saturating the growth. During the unstable phase, key physics can be captured by a δf gyrokinetic description, where it is shown analytically and numerically that parallel particle motion results in a coupling of all electromagnetic field components. A fluid model derived therefrom accurately predicts linear eigenmodes and is used to resolve global profile effects. For laser-based electron–positron plasma experiments, prompt instability is predicted with growth times much shorter than plasma lifetimes. Similarly, growth rates are calculated for the planned APEX experiment as well as gamma-ray burst scenarios, suggesting that the instability may contribute to the early evolution of these systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Limits on non-relativistic matter during Big-bang nucleosynthesis

Big-bang nucleosynthesis (BBN) probes the cosmic mass-energy density at temperatures ~10 MeV to ~100 keV. Here, we consider the effect of a cosmic matter-like species that is non-relativistic and pressureless during BBN. Such a component must decay; doing so during BBN can alter the baryon-to-photon ratio, η, and the effective number of neutrino species. We use light element abundances and the cosmic microwave background (CMB) constraints on η and N ν to place constraints on such a matter component. We find that electromagnetic decays heat the photons relative to neutrinos, and thus dilute the effective number of relativistic species to N eff < 3 for the case of three Standard Model neutrino species. Intriguingly, likelihood results based on Planck CMB data alone find N ν = 2.800 ± 0.294, and when combined with standard BBN and the observations of D and 4 He give N ν = 2.898 ± 0.141. While both results are consistent with the Standard Model, we find that a nonzero abundance of electromagnetically decaying matter gives a better fit to these results. Our best-fit results are for a matter species that decays entirely electromagnetically with a lifetime τ X = 0.89 sec and pre-decay density that is a fraction ξ = (ρ X /ρ rad |10 MeV = 0.0026 of the radiation energy density at 10 MeV; similarly good fits are found over a range where ξτ X 1/2 is constant. On the other hand, decaying matter often spoils the BBN+CMB concordance, and we present limits in the (τ X ,ξ) plane for both electromagnetic and invisible decays. For dark (invisible) decays, standard BBN (i.e. ξ = 0) supplies the best fit. We end with a brief discussion of the impact of future measurements including CMB-S4.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Efficient Loads Surrogates for Waked Turbines in an Array

Accurately and efficiently predicting wind turbine structural loading is a crucial step in wind farm design. Without considering structural loading, wind farm optimization could negatively impact turbine fatigue and ultimate loads, especially for waked and partially waked turbines, which could result in higher maintenance costs and reduced turbine lifetime. However, predicting turbine loads throughout an array is a costly step, as these quantities require time-accurate results across long time histories, which is often intractable for large array optimization. Therefore, surrogate models that link array spacing to load outputs are often used, but the surrogates are then unique to the inflow conditions and array configurations in the training library. This work develops surrogate models for many wind turbine load outputs based solely on rotor plane velocity measurements, with no required input about array configuration or freestream inflow parameters. Surrogate models were constructed for many turbine quantities of interest (QoI), considering mean, standard deviation, ultimate, and fatigue loads. In general, most QoI statistics were accurately captured, as measured by predicted vs. actual correlation coefficient, confirming the suitability of the approach. Temporal mean values of the QoI required only temporal mean measurements of the rotor plane inflow velocity. However, accurate prediction of temporal standard deviation, ultimate, and fatigue values of QoI also required temporal standard deviations of the rotor plane velocity field. Poor surrogate performance was observed when too many correlated inputs were used, such as multiple velocity components. If the fewest inflow parameters are used to construct the surrogates, the average correlation coefficient value for all output QoI statistics is 0.89. Surrogates for standard deviations and damage equivalent loads (DELs) of turbine QoIs generally had lower accuracy and tower-base and shaft load channels posed the most difficult to capture accurately. The results suggest that these surrogates could be easily paired with analytic wake models, which are frequently used for pre-construction wind farm array optimization, to account for turbine loading in addition to power production. By including the optimal inflow conditions, the surrogate accuracy can improve to an average correlation coefficient value for all output QoI statistics of 0.92. This work has established the ability to build accurate surrogates for mean, standard deviation, ultimate load, and DEL turbine QoI values based on the rotor plane inflow velocity, and identified which inflow conditions lead to greater surrogate accuracy.

17 WIND ENERGY↗

DOE OSTI2020

Neutron’s dark secret

The existing discrepancy between neutron lifetime measurements in bottle and beam experiments has been interpreted as a sign of the neutron decaying to dark particles. We summarize the current status of this proposal, including a discussion of particle physics models involving such a portal between the Standard Model and a baryonic dark sector. We also review further theoretical developments around this idea and elaborate on the prospects for verifying the neutron dark decay hypothesis in current and upcoming experiments.

Astronomy & Astrophysics↗

DOE OSTI2022

Electrolyzer Performance Loss from Accelerated Stress Tests and Corresponding Changes to Catalyst Layers and Interfaces

Stress tests are developed for proton exchange membrane electrolyzers that utilize low catalyst loading, elevated potential, and frequent cycling with square- and triangle-waves to accelerate anode catalyst layer degradation during intermittent operation. Kinetics drive performance losses (ohmic/transport secondary) and are accompanied by decreasing exchange current density, decreasing cyclic voltammetric capacitance, and increasing polarization resistance. Decreased kinetics are likely due to a combination of iridium (Ir) migration into electrochemically inaccessible locations in the anode or membrane, Ir particle growth (supported by X-ray scattering), changes in the extent of the Ir oxidation state (supported by X-ray absorption spectroscopy), and anode catalyst layer reordering. Decreasing catalyst/transport layer contact and catalyst/membrane interfacial tearing may add contact resistances and account for increasing ohmic losses. Performance losses for low and moderate catalyst loading, as well as from accelerated and model wind/solar cycling protocols, were likewise dominated by kinetics but vary in severity. Additionally, accelerated cycling (1 cycle per minute) appears to reasonably accelerate relevant loss mechanisms and can be used to project electrolyzer lifetime from anode deterioration. Ongoing accelerated stress test development and studies into performance loss mechanisms will continue to be critical as electrolysis shifts to intermittent power and low-cost applications.

30 DIRECT ENERGY CONVERSION↗