US Department Of Energy Research Articles

Regional-scale fault-to-structure earthquake simulations with the EQSIM framework: Workflow maturation and computational performance on GPU-accelerated exascale platforms

Continuous advancements in scientific and engineering understanding of earthquake phenomena, combined with the associated development of representative physics-based models, is providing a foundation for high-performance, fault-to-structure earthquake simulations. However, regional-scale applications of high-performance models have been challenged by the computational requirements at the resolutions required for engineering risk assessments. The EarthQuake SIMulation (EQSIM) framework, a software application development under the US Department of Energy (DOE) Exascale Computing Project, is focused on overcoming the existing computational barriers and enabling routine regional-scale simulations at resolutions relevant to a breadth of engineered systems. This multidisciplinary software development—drawing upon expertise in geophysics, engineering, applied math and computer science—is preparing the advanced computational workflow necessary to fully exploit the DOE’s exaflop computer platforms coming online in the 2023 to 2024 timeframe. Achievement of the computational performance required for high-resolution regional models containing upward of hundreds of billions to trillions of model grid points requires numerical efficiency in every phase of a regional simulation. This includes run time start-up and regional model generation, effective distribution of the computational workload across thousands of computer nodes, efficient coupling of regional geophysics and local engineering models, and application-tailored highly efficient transfer, storage, and interrogation of very large volumes of simulation data. This article summarizes the most recent advancements and refinements incorporated in the workflow design for the EQSIM integrated fault-to-structure framework, which are based on extensive numerical testing across multiple graphics processing unit (GPU)-accelerated platforms, and demonstrates the computational performance achieved on the world’s first exaflop computer platform through representative regional-scale earthquake simulations for the San Francisco Bay Area in California, USA.

Effects of Gas-Diffusion Layers and Water Management on the Carbon Corrosion of a Catalyst Layer in Proton-Exchange Membrane Fuel Cells

Carbon corrosion in a catalyst layer (CL) deteriorates the performance and durability of proton-exchange membrane fuel cells (PEMFCs), which are closely related to water management within these cells. This study investigates the characteristics of water behavior of two gas diffusion layers (GDLs) and compares their influence on degrees of degradation in the CL. First, the properties of the GDLs, including their thickness, pore size distribution, gas permeability, electrical resistance, contact angle, and polytetrafluoroethylene (PTFE) content, are evaluated. The dynamic behavior of liquid water is observed using a visualization cell and synchrotron X-ray imaging. Second, a modified accelerated stress test (AST), which includes a water generation reaction within the catalyst support protocol of the US Department of Energy (DOE), is performed. For assessing the degradation, we utilize polarization curves, electrochemical impedance spectroscopy, cyclic voltammetry, scanning electron microscopy, and field emission transmission electron microscopy. The results reveal that, even though GDL B contains a higher hydrophobic content than GDL A, it exhibits lower water discharge, indicating a reduced performance at high relative humidity (RH) levels. This is attributed to a low capillary pressure gradient, which is influenced not only by PTFE but also by the overall pore structure (i.e., porosity and pore size). Consequently, a high capillary pressure gradient can enhance water discharge and thereby mitigate carbon corrosion and Pt agglomeration in the CL. In addition, the application of the modified AST induces carbon corrosion with fewer cycles than that achieved using the DOE carbon support protocol.

Algae to HEFA: Economics and potential deployment in the United States

AbstractTo reach the goals set by the US Department of Energy's Sustainable Aviation Fuel (SAF) Grand Challenge, currently available feedstocks may be insufficient. Giving priority to developing, prototyping and reducing the cost of algal feedstock before investing and lining up locations is important. As the production of algal feedstocks advances, a simplified conversion approach using more mature technologies can help reduce the investment risk for algae‐based fuels. Reducing process complexity to the steps described here [namely, conversion of lipids to HEFA (hydroprocessed esters and fatty acids) fuels and relegating the remainder of the biomass to anaerobic digestion or food/feed production] enables the near‐term production of algal SAF but presents challenging economics depending on achievable cultivation costs and compositional quality. However, these economics can be improved by present‐day policy incentives. With these incentives, the modeled algae‐to‐HEFA pathway could reach a minimum fuel selling price as low as $4.7 per gasoline gallon equivalent depending on the carbon intensity reduction that can be achieved compared with petroleum. Uncertainty about algal feedstock production maturity in the current state of technology and the future will play a large role in determining the economic feasibility of building algae‐to‐HEFA facilities. For example, if immaturity increases the feedstock price by even 10%, SAF production in 2050 is about 58% of the production which could have been achieved with mature feedstock. Additionally, growth in this conversion pathway can be notably boosted through the inclusion of subsidies, and also through higher‐value coproducts or higher lipid yields beyond the scope of the process considered here.

Picturing the Gap Between the Performance and US-DOE's Hydrogen Storage Target: A Data-Driven Model for MgH2 Dehydrogenation.

Developing solid-state hydrogen storage materials requires a comprehensive understanding of the dehydrogenation chemistry of a solid-state hydride. Transition state search and kinetics calculations are essential to understanding and designing high-performance solid-state hydrogen storage materials by filling in the knowledge gap that current experimentscannot measure. However, the ab initio analysis of these processes is expensive and time-consuming. Searching for descriptors to accurately predict the energy barrier is urgently needed, to accelerate the prediction of hydrogen storage material properties and identify the opportunities and challenges. Herein, we develop a data-driven model to describe and predict the dehydrogenation barriers of a typical solid-state hydrogen storage material, MgH2, based on the combination of the crystal Hamilton population orbital of Mg-H bond and the distance between atomic hydrogen.All the parameters in this model can be directly calculated with significantly less computational cost than conventional transition state search, so that the dehydrogenation performance of hydrogen storage materials can be predicted efficiently. Finally, we found that this model leads to excellent agreement with typical experimental measurements reported to date and provides clear design guidelines on how to propel the performance of MgH2 closer to the target set by the United States Department of Energy (US-DOE).

Picturing the Gap Between the Performance and US‐DOE’s Hydrogen Storage Target: A Data‐Driven Model for MgH2 Dehydrogenation

Developing solid‐state hydrogen storage materials requires a comprehensive understanding of the dehydrogenation chemistry of a solid‐state hydride. Transition state search and kinetics calculations are essential to understanding and designing high‐performance solid‐state hydrogen storage materials by filling in the knowledge gap that current experiments cannot measure. However, the ab initio analysis of these processes is expensive and time‐consuming. Searching for descriptors to accurately predict the energy barrier is urgently needed, to accelerate the prediction of hydrogen storage material properties and identify the opportunities and challenges. Herein, we develop a data‐driven model to describe and predict the dehydrogenation barriers of a typical solid‐state hydrogen storage material, MgH2, based on the combination of the crystal Hamilton population orbital of Mg‐H bond and the distance between atomic hydrogen. All the parameters in this model can be directly calculated with significantly less computational cost than conventional transition state search, so that the dehydrogenation performance of hydrogen storage materials can be predicted efficiently. Finally, we found that this model leads to excellent agreement with typical experimental measurements reported to date and provides clear design guidelines on how to propel the performance of MgH2 closer to the target set by the United States Department of Energy (US‐DOE).

Review of solar-enabled desalination and implications for zero-liquid-discharge applications

Abstract Production of fresh water from desalination of the abundant saline water on the planet is increasingly considered as a climate change adoption measure. Yet, there are challenges associated with the cost and environmental impact of desalination. Effective integration of solar energy generation and freshwater production can address both issues. This review article highlights recent key advances in such integration achieved in a joint-research university-national laboratory partnership under the auspices of the United States Department of Energy (DOE) and parallel efforts world-wide.
First, an overview of current and emerging desalination technologies and associated pretreatment and brine management technologies that together can result in zero-liquid-discharge (ZLD) systems is presented and their technological readiness levels are evaluated. Then advanced modeling techniques and new software platforms that enable optimization of solar-desalination applications with the dual objective of cost and environmental impact minimization are discussed. 

An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1

Abstract. The interaction between clouds and radiation is a key process within the climate system, and assessing the impacts of that interaction provides valuable insights into both the present-day climate and future projections. Many modeling experiments have been designed over the years to probe the impact of the cloud radiative effect (CRE) on the climate, including those that seek to disrupt the mean CRE effect and those that only disrupt the covariance of the CRE with the circulation. Seven such experimental designs have been added to the Energy Exascale Earth System Model version 1 (E3SMv1) of the US Department of Energy. These experiments include both the first and second iterations of the Clouds On/Off Klimate Intercomparison Experiment (COOKIE) experimental design, as well as the cloud-locking method. This paper documents the code changes necessary to implement such experiments and also provides detailed instructions for how to run them. Analyses across experiment types provide valuable insights and confirm the findings of prior studies, including the role of cloud radiative heating toward intensifying the monsoon, intensifying rain rates, and poleward expansion of the general circulation owing to cloud feedbacks.

Feeling the strain: Enhancing the thermodynamics characteristics of magnesium nickel hydride Mg2NiH4 for hydrogen storage applications through strain engineering

This work is based on density functional theory (DFT) and studies the structural, electronic, thermodynamic properties and dehydrogenation kinetics of the hydride Mg2NiH4 under different uniaxial and biaxial strain applied to Mg2Ni or Mg2NiH4. structural properties are first studied based on generalized gradient (GGA) and local density (LDA). Thermodynamic and electronic properties and dehydrogenation kinetics are then studied using the GGA method based on the Perdew-Burke-Ernzerhor (PPE) approximation. The results obtained show that uniaxial/biaxial tensile and compressive strains are capable of inducing structural deformation by increasing the value of the strain step on both Mg2Ni and Mg2NiH4, and that these strains applied to Mg2NiH4 are capable of reducing the stability of the system more than strains applied to Mg2Ni, due to the contribution of strain energy. More specifically, it lowers the enthalpy of formation to −40 kJ/mol.H2 under compressive strain ε = −7.5% or biaxial tensile strain ε = +7.8%, which corresponds exactly to the ideal value suggested by the US Department of Energy (DOE) for materials suitable for hydrogen storage. And the decomposition temperature fell within the fuel cell operating range (PEM) of 289–393 K. On the other hand, under uniaxial and biaxial strains, the activation energy of hydrogen atom diffusion in Mg2NiH4 varied between 0.40 eV and 0.22 eV, resulting in a remarkable improvement in dehydrogenation properties. Analysis of the total (TDOS) and partial (PDOS) density curves shows that the Mg2NiH4 system has a metallic characteristic, and that this characteristic is maintained by increasing the strain pitch, with a variation in the energy width of the valence band.

Ultralow-Loading Ruthenium-Iridium Fuel Cell Catalysts Dispersed on Zn-N Species-Doped Carbon.

Developing low-loading platinum-group-metal (PGM) catalysts is one of the key challenges in commercializing anion-exchange-membrane-fuel-cells (AEMFCs), especially for hydrogen oxidation reaction (HOR). Here, ruthenium-iridium nanoparticles being deposited on a Zn-N species-doped carbon carrier (Ru6Ir/Zn-N-C) are synthesized and used as an anodic catalyst for AEMFCs. Ru6Ir/Zn-N-C shows extremely high mass activity (5.87AmgPGM -1) and exchange current density (0.92mAcm-2), which is 15.1 and 3.9 times that of commercial Pt/C, respectively. Based on the Ru6Ir/Zn-N-C AEMFCs achieve a peak power density of 1.50Wcm-2, surpassing the state-of-the-art commercial PtRu catalysts and the power ratio of the normalized loading is 14.01WmgPGM anode -1 or 5.89W mgPGM -1 after decreasing the anode loading (87.49µgcm-2) or the total PGM loading (0.111mgcm-2), satisfying the US Department of Energy's PGM loading target. Moreover, the solvent and solute isotope separation method is used for the first time to reveal the kinetic process of HOR, which shows the reaction is influenced by the adsorption of H2O and OH-. The improvement of the hydrogen bond network connectivity of the electric double layer by adjusting the interfacial H2O structure together with the optimized HBE and OHBE is proposed to be responsible for the high HOR activity of Ru6Ir/Zn-N-C.

Mg-decorated CN monolayer with enhanced hydrogen storage

Current hydrogen storage confronts safety and high energy cost challenges. Solid-state hydrogen storage provides an efficient pathway with lower cost and pressure conditions. Here, we perform density functional theory (DFT) calculations measuring the hydrogen storage properties of Mg-decorated CN monolayer. 8Mg@CN structure is confirmed based on energetic and geometric criteria and it can absorb up to 40 H2 molecules, achieving a high gravimetric density of 8.92 wt% over the US Department of Energy (DOE) target. The polarized H2 molecules are proven to be physiosorbed on Mg atoms to guarantee desorption. The electronic properties are studied to illustrate the electrostatic attractions between the H2 molecules and the Mg-decorated CN monolayer. Moreover, the desorption temperatures and adsorption pressures are calculated to illustrate the reversibility of hydrogen storage applications on 8Mg@CN. These results indicate 8Mg@CN could be a promising candidate for hydrogen storage with potentially reversible application.

Efficient bubble/precipitate traffic enables stable seawater reduction electrocatalysis at industrial-level current densities

Seawater electroreduction is attractive for future H2 production and intermittent energy storage, which has been hindered by aggressive Mg2+/Ca2+ precipitation at cathodes and consequent poor stability. Here we present a vital microscopic bubble/precipitate traffic system (MBPTS) by constructing honeycomb-type 3D cathodes for robust anti-precipitation seawater reduction (SR), which massively/uniformly release small-sized H2 bubbles to almost every corner of the cathode to repel Mg2+/Ca2+ precipitates without a break. Noticeably, the optimal cathode with built-in MBPTS not only enables state-of-the-art alkaline SR performance (1000-h stable operation at –1 A cm−2) but also is highly specialized in catalytically splitting natural seawater into H2 with the greatest anti-precipitation ability. Low precipitation amounts after prolonged tests under large current densities reflect genuine efficacy by our MBPTS. Additionally, a flow-type electrolyzer based on our optimal cathode stably functions at industrially-relevant 500 mA cm−2 for 150 h in natural seawater while unwaveringly sustaining near-100% H2 Faradic efficiency. Note that the estimated price (~1.8 US$/kgH2) is even cheaper than the US Department of Energy’s goal price (2 US$/kgH2).

Electrospun catalyst layers using short-side-chain ionomer for low platinum and high performance PEMFCs

Proton exchange membrane fuel cells (PEMFCs) should further reduce the platinum consumption to lower their manufacturing costs and life-cycle carbon emissions. However, the performance of the catalyst layers with low-Pt loading needs to be improved. Short-side-chain (SSC) ionomers have been proven to enhance the catalytic activity of conventional catalyst layers. In this work, the SSC ionomer was applied to the electrospun catalyst layer, and achieved a remarkable improvement in the performance. With the use of commercially available catalyst, the membrane electrode assemblies (MEAs) prepared in this work exhibited a low total-Pt-consumption of 0.064 g kW−1 (stoichiometric ratios of 1.5/2.5 for H2/air, 80°C, 100 kPa) and achieved the 2025 target proposed by the US Department of Energy. Separating activation, ohmic, and concentration overpotentials, the performance enhancement of the electrospun catalyst layer mainly came from the decrease of ohmic overpotential and concentration overpotential. The electrospun ionomer membrane without catalyst was used as a research model to explore the proton transport properties inside the electrospun catalyst layer. The results showed that in the range of PEMFC operating temperature, the proton conductivity of the electrospun catalyst layer could be higher, but meanwhile the proton-conduction activation energy was also elevated. Compared with the conventional catalyst layer, the electrospun catalyst layer showed obviously better performance before and after accelerated stress test, thus verifying the practicality of the electrospun catalyst layers. This work provided a reference for the development of low platinum and high performance catalyst layers.

Offshore low-level jet observations and model representation using lidar buoy data off the California coast

Abstract. Low-level jets (LLJs) occur under a variety of atmospheric conditions and influence the available wind resource for wind energy projects. In 2020, lidar-mounted buoys owned by the US Department of Energy (DOE) were deployed off the California coast in two wind energy lease areas administered by the Bureau of Ocean Energy Management: Humboldt and Morro Bay. The wind profile observations from the lidars and collocated near-surface meteorological stations (4–240 m) provide valuable year-long analyses of offshore LLJ characteristics at heights relevant to wind turbines. At Humboldt, LLJs were associated with flow reversals and north-northeasterly winds, directions that are more aligned with terrain influences than the predominant northerly flow. At Morro Bay, coastal LLJs were observed primarily during northerly flow as opposed to the predominant north-northwesterly flow. LLJs were observed more frequently in colder seasons within the lowest 250 m a.s.l. (above sea level), in contrast with the summertime occurrence of the higher-altitude California coastal jet influenced by the North Pacific High, which typically occurs at heights of 300–400 m. The lidar buoy observations also validate LLJ representation in atmospheric models that estimate potential energy yield of offshore wind farms. The European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) was unsuccessful at identifying all observed LLJs at both buoy locations within the lowest 200 m. An extension of the National Renewable Energy Laboratory (NREL) 20-year wind resource dataset for the Outer Continental Shelf off the coast of California (CA20-Ext) yielded marginally greater captures of observed LLJs using the Mellor–Yamada–Nakanishi–Niino (MYNN) planetary boundary layer (PBL) scheme than the 2023 National Offshore Wind dataset (NOW-23), which uses the Yonsei University (YSU) scheme. However, CA20-Ext also produced the most LLJ false alarms, which are instances when a model identified an LLJ but no LLJ was observed. CA20-Ext and NOW-23 exhibited a tendency to overestimate the duration of LLJ events and underestimate LLJ core heights.

Abstract 7432: Improving FAIRness of computational approaches for cancer: The computational resources for cancer research portal

Abstract The Computational Resources for Cancer Research website is a public portal supported by NCI that democratizes access to available computational resources for the cancer research community. In supporting an emerging FAIR (Findable, Accessible, Interoperable, Reusable) data science ecosystem inclusive of software, models and data, the goals of the portal are to serve cancer data scientists by increasing understanding, access, and adoption of computational resources for cancer research, and to foster new collaborative research projects. Initially populated with resources developed in NCI supported collaborations with the US Department of Energy, the portal is serving as a unified reference and resource for computational resources developed broadly by the cancer community. These collaborative projects include CANDLE (the Cancer Distributed Learning Environment), IMPROVE (Innovative Methods and data for PRedictive Oncology model Validation and Evaluation), ADMIRRAL (AI Driven Multi-scale Investigation of Ras-Raf Activation Lifecycle), MOSSAIC (Model Outcomes using Surveillance Data and Scalable AI for Cancer) and ATOM (Accelerating Therapeutics for Opportunities in Medicine). The resources include software, models, and datasets as well as descriptive use cases and references to tutorials associated with many of the described resources. The portal also integrates content from the Predictive Oncology Model and Data Clearinghouse (modac.cancer.gov) which can be accessed through REST APIs. Ongoing development of the portal is driven by community insights and contributions including input from an interdisciplinary advisory committee, working groups, early users, and preliminary feedback received at AACR 2023. The portal will also support community contributions of computational resources. In addition, the portal highlights computational approaches in emerging and challenging areas, such as digital twins for cancer. The portal will enable the cancer research community to learn about new computational research methods through use cases and educational material, access cancer related software, datasets, and AI models, engage with peers and cross-disciplinary researchers at different career levels through an interactive forum, explore emerging areas, such as computational imaging, community-based standards for data management, predictive radiation oncology, and digital twin technologies, learn about in industry and community events, conferences, and workshops, and create new collaborative research projects. The presentation will deliver insights into key resources offered through the Computational Resources for Cancer Research Portal, how the portal will help the cancer research community identify and adopt computational resources of interest, and how researchers can join and participate in this growing community. Citation Format: Eric Stahlberg, Lynn Borkon, Ruth Frost, Sara Jones, Amar Khalsa, Lauren Lewis, Emily Greenspan, Sunita Menon. Improving FAIRness of computational approaches for cancer: The computational resources for cancer research portal [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7432.

Glass design using machine learning property models with prediction uncertainties: Nuclear waste glass formulation

The United States Department of Energy is responsible for managing the legacy nuclear waste stored in underground tanks at the Hanford Site. The waste will be separately vitrified as low-activity waste and high-level waste fractions. Waste glass formulation algorithms have been traditionally developed using partial quadratic mixture property-composition models. Recently, machine learning (ML) techniques have been used to predict glass properties and discover new glass materials for nuclear waste vitrification, and these advancements can be utilized to improve waste glass composition design. In this proof-of-principle study, ML algorithms such as Gaussian process regression (GPR) were used to interpolate glass properties (e.g., viscosity, electrical conductivity, chemical durability). After selecting appropriate sets of GPR hyper-parameters for each property, an optimization program was developed to formulate glass compositions to maximize waste loading while simultaneously satisfying property constraints. The results of the ML-based waste loadings and glass compositions were compared to those obtained using the traditional methods. Comparing to the previous glass design framework, the ML-based optimization methods offer improved glass designs and a streamlined approach to generation of optimally designed data and near real-time updates.

A DFT study of structural, electronic, mechanical, optical, and hydrogen storage properties of quaternary hydride phase Li4BN3H10

In this paper, we investigated the structural, electronic, mechanical and optical properties of Li4BN3H10 using the ultra-soft pseudopotential method which is based on the density functional theory (DFT) with CASTEP code. The optimized lattice parameters of Li4BN3H10 correlate well with the theoretical calculations and experimental measurements that are currently available. Using elastic constants, the material's stability was verified. Based on the elastic constants, we discovered several mechanical features of the material. Between 0 and 20 eV, optical spectra calculations are made, taking into account the real and imaginary parts of the dielectric function ε(ω), reflectivity R(ω), index of refraction n(ω), coefficients of extinction k(ω) and absorption α(ω). The dielectric function is wide close to the middle ultraviolet (4.13–6.20 eV). The extinction coefficient of the Li4BN3H10 has the ability to worn for implements like Bragg's reflectors, optical and optoelectronic equipments. The optical parameters of Li4BN3H10 disclose that our working constructions have an elevated dielectric constant, with a greatest absorption in the visible range holding out over 1.49 × 105 cm−1 Li4BN3H10 is deemed to be an appropriate material for optoelectronic applications based on calculated optical results. The gravimetric hydrogen storage capacities of Li4BN3H10 compound is 11.06 wt %. These promising capacities exceed the 6.5 wt % target set by the US Department of Energy for 2025.

Effect of ion penetration on the aging of EPDM components used in caustic liquid transfer lines by microscopic analysis

The waste transfer lines at the United States Department of Energy's Hanford Site Tank Farm in Benton County, Washington, USA have flexible sections that are fabricated from ethylene propylene diene monomer (EPDM) hoses. The hoses are of a hose-in-hose design with an inner hose that carries the waste and an outer hose that acts as containment in the event of an inner hose failure. During waste transport, the inner hoses are exposed to several stressors including caustic solutions at high temperatures and high pressures. These hose-in-hose transfer lines (HIHTL) are exposed to several stressors including caustic solutions at high temperatures and high pressures during the waste transport. The aging behavior of the HIHTL inner hose were evaluated by exposure to solutions at 77 °C containing 6.25, 12.50, and 25.00% (v/v) sodium hydroxide (NaOH) for 12-months. After the exposure, the burst pressure of the HIHTL specimens were measured and compared to the unaged samples.The burst pressure of the HIHTL specimens exposed to the 6.25% NaOH solution exhibited the most significant deterioration and those exposed to 25.00% NaOH solution had the least deterioration. Examination of the inside surface of the HIHTL specimens with scanning electron microscopy showed that the surface deterioration for the specimens exposed to 6.25% NaOH solution were the most severe and the samples exposed to 25.00% NaOH solution had the least deterioration. Scanning Electron Microscope with Energy Dispersive Spectroscopy (SEM-EDS) analysis of the specimens showed that the specimen aged with the 6.25% NaOH solution had that greatest sodium ion penetration into the material with the sodium concentration being significantly higher than those seen with the other specimens. In addition, when the specimens aged with both the 12.50% and the 25.00% NaOH solutions were examined, a white crystalline coating was observed on the inside surfaces of the specimens which appears to have acted as a barrier that protected the EPDM material from attack by the NaOH solutions.

Adjusting the Operational Potential Window as a Tool for Prolonging the Durability of Carbon-Supported Pt-Alloy Nanoparticles as Oxygen Reduction Reaction Electrocatalysts.

A current trend in the investigation of state-of-the-art Pt-alloys as proton exchange membrane fuel cell (PEMFC) electrocatalysts is to study their long-term stability as a bottleneck for their full commercialization. Although many parameters have been appropriately addressed, there are still certain issues that must be considered. Here, the stability of an experimental Pt-Co/C electrocatalyst is investigated by high-temperature accelerated degradation tests (HT-ADTs) in a high-temperature disk electrode (HT-DE) setup, allowing the imitation of close-to-real operational conditions in terms of temperature (60 °C). Although the US Department of Energy (DoE) protocol has been chosen as the basis of the study (30,000 trapezoidal wave cycling steps between 0.6 and 0.95 VRHE with a 3 s hold time at both the lower potential limit (LPL) and the upper potential limit (UPL)), this works demonstrates that limiting both the LPL and UPL (from 0.6-0.95 to 0.7-0.85 VRHE) can dramatically reduce the degradation rate of state-of-the-art Pt-alloy electrocatalysts. This has been additionally confirmed with the use of an electrochemical flow cell coupled to inductively coupled plasma mass spectrometry (EFC-ICP-MS), which enables real-time monitoring of the dissolution mechanisms of Pt and Co. In line with the HT-DE methodology observations, a dramatic decrease in the total dissolution of Pt and Co has once again been observed upon narrowing the potential window to 0.7-0.85 VRHE rather than 0.6-0.95 VRHE. Additionally, the effect of the potential hold time at both LPL and UPL on metal dissolution has also been investigated. The findings demonstrate that the dissolution rate of both metals is proportional to the hold time at UPL regardless of the applied potential window, whereas the hold time at the LPL does not appear to be as detrimental to the stability of metals.

Carbon Material-Reinforced Polymer Composites for Bipolar Plates in Polymer Electrolyte Membrane Fuel Cells.

Bipolar plates (BPs) are one of the most important components of polymer electrolyte membrane fuel cells (PEMFCs) because of their important role in gas and water management, electrical performance, and mechanical stability. Therefore, promising materials for use as BPs should meet several technical targets established by the United States Department of Energy (DOE). Thus far, in the literature, many materials have been reported for possible applications in BPs. Of these, polymer composites reinforced with carbon allotropes are one of the most prominent. Therefore, in this review article, we present the progress and critical analysis on the use of carbon material-reinforced polymer composites as BPs materials in PEMFCs. Based on this review, it is observed that numerous polymer composites reinforced with carbon allotropes have been produced in the literature, and most of the composites synthesized and characterized for their possible application in BPs meet the DOE requirements. However, these composites can still be improved before their use for BPs in PEMFCs.

A Parametric Study of the SASI Comparing General Relativistic and Nonrelativistic Treatments* * Notice: This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

We present numerical results from a parameter study of the standing accretion shock instability (SASI), investigating the impact of general relativity (GR) on the dynamics. Using GR hydrodynamics with GR gravity, and nonrelativistic (NR) hydrodynamics with Newtonian gravity, in an idealized model setting, we vary the initial radius of the shock, and by varying its mass and radius in concert, the proto-neutron star compactness. We investigate four compactnesses expected in a post-bounce core-collapse supernova (CCSN). We find that GR leads to a longer SASI oscillation period, with ratios between the GR and NR cases as large as 1.29 for the highest-compactness suite. We also find that GR leads to a slower SASI growth rate, with ratios between the GR and NR cases as low as 0.47 for the highest-compactness suite. We discuss implications of our results for CCSN simulations.