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DOE OSTI2023

Dissipation of Mixed-Phase Arctic Clouds and Its Relationship to Aerosol Properties - Final Technical Report

The overarching objective of this project was to further our understanding of low-level Arctic cloud behavior in ultra-low aerosol concentration environments. To this end, we used a combination of modeling and analysis of DOE ARM datasets to understand the frequency of aerosol-limited cloud dissipation events, to understand the microphysical processes that lead to aerosol-limited dissipation, and to understand how above-cloud aerosol particles can work to maintain low-level clouds that exist in boundary layers with ultra-low aerosol concentrations. We found that aerosol-limited dissipation is unlikely to occur at the DOE long-term observation facilities at North Slope Alaska and Oliktok Point but possibly does occur at higher latitudes in the Arctic. At these higher latitudes, aerosol concentrations are frequently observed to be higher, often substantially higher, than in the boundary layer. These reservoirs can be sufficient to maintain low-level clouds. When they are insufficient, clouds appear to dissipate due to a depletion of liquid water through precipitation that is reinforced by a shutdown of the dynamical processes that support these clouds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Characterizing Hydrogen Storage Potential in U.S. Underground Gas Storage Facilities

Abstract Underground hydrogen storage is a long‐duration energy storage option for a low‐carbon economy. Although research into the technical feasibility of underground hydrogen storage is ongoing, existing underground gas storage (UGS) facilities are appealing candidates for the technology because of their ability to store and deliver natural gas. We estimate that UGS facilities in the United States (U.S.) can store 327 TWh (9.8 MMT) of pure hydrogen. A complete transition to hydrogen storage would reduce the collective working‐gas energy of UGS facilities by ∼75%; however, most (73.2%) UGS facilities could maintain current energy demand using a 20% hydrogen‐natural gas blend. U.S. UGS facilities can buffer 23.9%–44.6% of the high and low hydrogen demand projected for 2050, respectively, which exceeds the current percentage of natural gas demand buffered by storage. Thus, transitioning UGS infrastructure to hydrogen could substantially reduce the number of new hydrogen storage facilities needed to support a hydrogen economy.

08 HYDROGEN↗

DOE OSTI2023

Financial Analysis of the 2022 Macroinvertebrate Production Flow Experiment at Glen Canyon Dam

This report was prepared by Argonne National Laboratory (Argonne) in support of a financial analysis of the Glen Canyon Dam (GCD) flow experiment that was intended to support downstream macroinvertebrate production that are a primary food supply for fishes in the Colorado River. Also known as “bug flow” experiments, these experimental water releases were conducted on the weekends and holidays from the beginnings of May 2022 through the end of August 2022. This analysis was funded by and prepared for the Colorado River Storage Project (CRSP) Office of the U.S. Department of Energy’s Western Area Power Administration (WAPA). CRSP markets electricity produced by hydroelectric facilities collectively known as the Salt Lake City Area Integrated Projects including dams equipped for power generation on the Colorado, Green, Gunnison, and Rio Grande Rivers and on Plateau Creek in the states of Arizona, Colorado, New Mexico, Utah, and Wyoming. Staff members in Argonne’s Energy Systems and Infrastructure Analysis Division prepared this technical memorandum with assistance from WAPA’s CRSP and Energy Marketing and Management Offices (EMMO).

13 HYDRO ENERGY↗

DOE OSTI2023

Assessment of Cloud-Based Applications Enabling a Scalable Risk-Informed Predictive Maintenance Strategy Across the Nuclear Fleet

The current light water reactor fleet uses time-based or failure-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging technologies in terms of artificial intelligence (AI) and cloud computing to enable a cost-effective, predictive maintenance strategy. This report examines the feasibility of cloud computing for the nuclear industry’s needs in terms of the cloud’s computing capabilities, feasibility, and regulatory concerns. The technical viability of cloud computing was analyzed using one year worth of data from a boiling water reactor’s safety relief valve. Models were hosted on a local desktop, Idaho National Laboratory’s high-performance computer, and Microsoft Azure. Data was loaded, processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was used to determined that cloud computing has adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, there is a benefit as the plant no longer needs manage their own servers, software, cybersecurity, and IT support staff. Many of these features can be offloaded on to the cloud provider. A comprehensive analysis was completed that showed the current annual cost of operating is more expensive than using cloud computing resources. Lastly, the regulatory framework does not explicitly address AI or autonomous control. Currently, the NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than new regulations to address the use of AI and ML. But since many of the AI applications are focused on non-safety related applications, such as balance-of-plant components, they will likely have little or no regulatory restrictions or necessary approvals. Demonstrating how AI can improve maintenance and operation of these non-safety related systems seems like the likely path forward for implementing AI and cloud computing resources inside nuclear power plants (NPPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

NA-22 Quarterly Report: IST for Extended Deterrence (Q4FY24)

Department of Energy (DOE) scientists have long enjoyed technical collaboration with Japanese colleagues – valuing their technical and scientific prowess in materials science and engineering, large-scale, scientific computing, and many other areas. In particular, NNSA’s laboratories are attractive partners for this effort because they have a heritage of performing high quality, basic research; they work with an awareness of the dual use nature of emerging science and technology; and, importantly, they work with deep national security sensibilities through engagement with NNSA and other national security mission responsibilities. Other DOE laboratories with significant national security bona fides are also significant collaborators. In FY23 a Trilateral Leaders Summit was convened at Camp David. The DOE was given responsibility for “Trilateral National Laboratories Cooperation: The United States, Japan, and the ROK will drive new trilateral cooperation between the U.S. Department of Energy’s National Laboratories and counterpart laboratories—supported by a budget of at least $6 million—to advance knowledge, strengthen scientific collaboration, and spearhead innovation in support of the three countries’ shared interests. Scientists and innovators from the three countries will advance collaborative projects on priority critical and emerging technology areas; potential areas of cooperation include advanced computing, artificial intelligence, materials research, and climate and earthquake modeling among other technology areas.”

36 MATERIALS SCIENCE↗

DOE OSTI2021

Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Solarize Fairbanks BRITE: Facilitating Efficient, Resilient Homes in Cold Climates

Solarize Fairbanks began an annual Solarize campaign in the Interior Alaska city in 2020, located in IECC climate zone 8, with a goal to increase the number of solar PV panels in the community. The campaign provides peer support, education, bulk purchase discounts, and simplified installation of solar PV technologies for homes, businesses, and nonprofits. In 2021, the campaign began offering energy audits to building and homeowners with a bulk discount; however, building owners were responsible for pursuing next steps on their own. In 2022, a diverse team of local, state, and federal partners formed a team to create a process to further facilitate energy efficiency improvements alongside solar PV technology. The resulting project, Solarize Fairbanks - Building Resilience for the Interior (BRITE) aims to build out an efficiency component over 3 years. If implemented, it will be the first efficiency add-on to a solarize campaign in Alaska. In year one, the team conducted energy audits of four nonprofits located in the cold climate of Interior Alaska and is providing technical assistance and fundraising for the nonprofits to pursue the recommended retrofits. These audits provided insights on the types of retrofits that could be expected to increase efficiency, comfort, and resiliency of buildings, including LED lighting retrofits, increased envelope insulation, improved building controls, and air source heat pump technology. A pre- and post-retrofit analysis will provide further insight on the energy savings and other benefits of the retrofits. It will also inform the offerings in the following years of the BRITE add-on to Solarize campaigns. In this presentation, program implementers will review the past campaigns of Solarize Fairbanks, summarize the energy efficiency and resiliency analyses of the nonprofit buildings, cover future plans for Solarize Fairbanks BRITE, and provide recommendations for other communities pursuing similar programs.

Alaska↗

DOE OSTI2025

Techno-economic assessment of residential PV system tariff policies in Jordan

This study assesses the economic and technical performance of four energy policy scenarios for Jordan's residential photovoltaic (PV) systems: net metering, net billing, zero-export with battery storage, and sell-all-buy-all. With the recent introduction of time-of-use (TOU) tariffs and policies addressing the “duck curve” effect, the research focuses on optimizing PV system sizing across different regulatory frameworks. A detailed techno-economic analysis evaluates these scenarios based on energy production, cost savings, payback periods, and energy self-sufficiency. The findings indicate that net metering and net billing offer the highest cost savings and the shortest payback periods (∼3 years). While the zero-export strategy with battery storage enhances energy self-sufficiency by up to 70%, it requires a higher upfront investment. The sell-all-buy-all scenario supports larger system sizes, achieving a low levelized cost of electricity (0.0696 USD/kWh) and a net present value of 619 USD. Additionally, the study identifies a critical feed-in tariff threshold of 0.055 USD/kWh, at which net billing becomes as financially attractive as net metering. Here, these insights offer valuable recommendations for policymakers to optimize net billing rates and TOU tariffs, promoting the expansion of Jordan's renewable energy sector.

Battery storage↗

DOE OSTI2025

Poplar: a phylogenomics pipeline

Motivation Generating phylogenomic trees from the genomic data is essential in understanding biological systems. Each step of this complex process has received extensive attention and has been significantly streamlined over the years. Given the public availability of data, obtaining genomes for a wide selection of species is straightforward. However, analyzing that data to generate a phylogenomic tree is a multistep process with legitimate scientific and technical challenges, often requiring a significant input from a domain-area scientist. Results We present Poplar, a new, streamlined computational pipeline, to address the computational logistical issues that arise when constructing the phylogenomic trees. It provides a framework that runs state-of-the-art software for essential steps in the phylogenomic pipeline, beginning from a genome with or without an annotation, and resulting in a species tree. Running Poplar requires no external databases. In the execution, it enables parallelism for execution for clusters and cloud computing. The trees generated by Poplar match closely with state-of-the-art published trees. The usage and performance of Poplar is far simpler and quicker than manually running a phylogenomic pipeline. Availability and implementation Freely available on GitHub at https://github.com/sandialabs/poplar. Implemented using Python and supported on Linux.

Koning, Elizabeth [Sandia National Laboratories (S↗

DOE OSTI2023

Assessing Low-Temperature Geothermal Play Types: Relevant Data and Play Fairway Analysis Methods

This data catalog contains information on low temperature geothermal play types. The U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) supports the Geothermal Heating and Cooling Geospatial Datasets and Analysis project, conducted by the National Renewable Energy Laboratory (NREL). This project is part of a broader effort to demonstrate the multifaceted value of integrating geothermal power and geothermal heating and cooling technologies into national decarbonization strategies and community energy plans. There is a need to establish baseline low-temperature geothermal resource data sets and evaluate methods for deploying these technologies. This project aims to reduce exploration risk of low temperature geothermal systems by collecting baseline datasets that can be used for Play Fairway Analysis methodologies. This data catalog contains links to publicly available datasets from different sources that can be relevant for the low temperature geothermal systems. This submission contains data catalogs for Alaska, Hawaii, and the Conterminous United States, as well as a technical report on the methods used to classify and asses the geothermal play types.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Grid Optimization Competition Challenge 3 Problem Formulation

This report contains the problem formulation for the Grid Optimization (GO) Competition Challenge 3. The Grid Optimization Competition is run by a team of researchers from a number of organizations, including the sponsor Advanced Research Projects Agency - Energy (ARPA-E), lead organization Pacific Northwest National Laboratory (PNNL), and technical contributors from Los Alamos National Laboratory (LANL), National Renewable Energy Laboratory (NREL), Texas A&M University (TAMU), Georgia Institute of Technology (GT), University of Wisconsin (UW), and others. The GO Competition poses challenge problems in the field of power grid management, invites entrants to develop solvers for these problems, invokes the solvers on a set of problem instances using common hardware, ranks the solvers according to their performance, and awards prizes according to the rankings. The overall goal of the GO Competition is to spur innovative research on high impact and computationally challenging problems in power grid management from initial development through commercial deployment. Complete information about the GO Competition can be found online at [2]. The webpage covers previous Challenges, rules, timeline, registration information, data formats, scoring methods, computational platform information, information on supported solvers and languages, sponsor information, frequently asked questions, administrator contact information, publicly available problem instances, computer code for reading and evaluating problem and solution data, a sandbox for testing solvers, and a solver submission interface, results, and publications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

BRAVE_EBC-TMT.1.0

Exhaled breath condensate (EBC) represents a low-cost and non-invasive means of examining respiratory health. EBC has been used to discover and validate exhaled volatile and non-volatile biomarkers of disease related to the respiratory system distress such as asthma, COPD, lung cancer, and secondary infections. One newly emerging utilization of EBC, is proteomics analysis, which can provide an unbiased snapshot into ongoing biological processes in the airway. Fully characterizing the biological landscape of EBC collections is challenging though, due to sample variability, and low detection sensitivity. EBC is primarily composed of condensed water, causing technical challenges with detecting key macromolecules from the dilute sample matrix; therefore, high sensitivity techniques are required to unlock the full capability of EBC as a method for non-invasive biomarker detection. To overcome some of these technical challenges for proteomic analyses, we applied our recently developed microscale proteomic techniques and developed a novel TMT based approach which enabled reliable, relative quantification with significantly improved detection of low abundance peptides/proteins across multiple healthy volunteer EBC samples. Our EBC collection design includes longitudinal EBC collections from five individual healthy volunteers on three separate days of the week with triplicate, back-to-back donations each day. Here, we report a total of 235 quantifiable proteins corresponding to 1,877 non-redundant peptides for evaluating sample collection reproducibility and establishing a healthy (human host) baseline EBC biomarker proteome studies. This work will pave the way for further investigations of EBC protein expression profiles and showcase the value of using non-invasive collection method techniques for clinically relevant biomarker discovery. This research was supported by the LDRD Biomedical Resilience And Readiness in AdVerse Operating Environments (BRAVE) Project (73748), and was conducted at Pacific Northwest National Laboratory (PNNL) in Richland, WA. PNNL is a multiprogram national laboratory operated by Battelle for the Department of Energy (DOE) under Contract DE-AC05-76RLO 1830.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Development of Integrated Safety and Security Models for Comprehensive Reliability and Resiliency Evaluation

The security of the electric grid and supporting energy systems is crucial to national security. One of the complexities in analyzing the security of energy systems is the safety consequences that may result from accidents. For energy systems, the goal is to ensure that they operate as intended and that any consequences are mitigated or prevented. The integration of safety and security is paramount to protecting these systems from attacks and ensuring that large consequences are prevented. This report describes an integrated safety and security methodology to evaluate cybersecurity events that can lead to large consequences. This novel approach first describes how Systems-Theoretic Process Analysis (STPA) provides a digital causal analysis for Bayesian Networks (BNs). The use of STPA causal analysis provides a systematic approach to constructing BNs that adequately model cyber scenarios that result in consequences. When combined with the technical principles described in Risk-Informed Management of Enterprise Systems (RIMES), a comprehensive risk-informed cybersecurity analysis results that allows decision-makers to prioritize systems that most impact risk.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

RaDIATE Collaboration Thermal shock studies

As next-generation accelerator target facilities (High Energy Physics, Spallation Sources, ... ) become increasingly more powerful and intense, high power target systems face key technical challenges, such as radiation damage and thermal shock. Those ultimately degrade the performance and lifetime of targets and have been identified as the leading cross-cutting challenges of high-power target facilities. In order to operate reliable beam-intercepting devices in the framework of energy and intensity increase for next generation accelerators, the RaDIATE Collaboration (Radiation Damage In Accelerator Target Environment), established in 2012 and managed by Fermilab, brings together existing expertise in nuclear material and accelerator targets from 20 international institutions, including CERN, to execute a coordinated strategy for high power targetry R&D. In this context, several thermal shock studies were performed at CERN's HiRadMat (High-Radiation to Materials) facility, that took a key step towards improving our knowledge on target damage tolerance. The first experiment HRMT-24, supported by EURCARD2 and completed in 2015, successfully validated the Johnson-Cook strength model developed at SwRI on beryllium S200FH (used for beam window material), providing a better confidence in simulating the thermal shock response of current and future S200FH beryllium components. HRMT-43, supported by ARIES and completed in 2018, tested various materials (Be, C, SiC, Si, Ti and ceramic nanofiber). It was a first and unique test which included pre-irradiated specimens from high energy proton beam irradiation to identify thermal shock response differences between non-irradiated and previously irradiated materials. Real-time measurement of dynamic thermomechanical response of graphite helped to benchmark numerical simulations.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Economic Analysis of a Novel Thermal Energy Storage System Using Solid Particles for Grid Electricity Storage: Preprint

As renewable power generation becomes the mainstream new-built energy source, energy storage will become an indispensable need to complement the uncertainty of renewable resources to firm the power supply. When phasing out fossil-fuel power plants to meet the carbon neutral utility target in the midcentury around the world, large capacity of energy storage will be needed to provide reliable grid power. The integration of renewable power and storage to support future carbon-free utility has several significant and positive impacts including expanding the renewable generation into the grid, improving the peak-load response, and balancing the electricity supply and demand. Long-duration energy storage (10–100 hours duration) can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system has promising cost and performance for the future growing energy storage needs. This paper introduces the system and components required for the particle TES to be technically and economically competitive. A technoeconomic analysis based on preliminary component designs and performance shows that the particle TES integrated with an efficient air-Brayton combined cycle power system can provide power for several days by low-cost, high-performance storage cycles. It addresses grid storage needs by enabling large-scale grid integration of intermittent renewables like wind and solar, thereby increasing their grid value. The design specifications and cost estimations of major components in a commercial scale system are presented in this paper. The cost model provides insights for further development and cost comparison with competing technologies.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2024

Assessment of Cloud-based Applications for Enabling a Scalable Riskinformed Predictive Maintenance Strategy

The current light-water reactor fleet uses time-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging artificial intelligence (AI) and cloud computing technologies to achieve a cost-effective, predictive-maintenance strategy. This paper presents discussion and results on the application of cloud computing in the nuclear industry. The technical viability of cloud computing was analyzed using data from a boiling-water reactor’s safety relief valve. The models were hosted on three different systems: a local personal computer, Idaho National Laboratory’s high-performance computer system, and Microsoft Azure. The data were loaded and processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was determined that cloud computing affords adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, the benefit is that the plants no longer need to manage their own servers, software, cybersecurity, and information technology support staff for in-house data analytics purpose. Many of these features can be offloaded to the cloud provider for a potential cost savings. Demonstrating how AI can improve the maintenance and operation of non-safety-related systems seems the likely path forward for implementing AI and cloud computing resources inside nuclear power plants.

azure↗

DOE OSTI2021

Economic Analysis of an Electric Thermal Energy Storage System Using Solid Particles for Grid Electricity Storage

As renewable power generation becomes the mainstream new-built energy source, energy storage will become an indispensable need to complement the uncertainty of renewable resources to firm the power supply. When phasing out fossil-fuel power plants to meet the carbon neutral utility target in the midcentury around the world, large capacity of energy storage will be needed to provide reliable grid power. The renewable power integration with storage can support future carbon-free utility and has several significant impacts including increasing the value of renewable generation to the grid, improving the peak-load response, and balancing the electricity supply and demand. Long-duration energy storage (10–100 hours duration) can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system has promising cost and performance for the future growing energy storage needs. This paper introduces the system and components required for the particle TES to be technically and economically competitive. A technoeconomic analysis based on preliminary component designs and performance shows that the particle TES integrated with an efficient air-Brayton combined cycle power system can provide power for several days by low-cost, high-performance storage cycles. It addresses grid storage needs by enabling large-scale grid integration of intermittent renewables like wind and solar, thereby increasing their grid value. The design specifications and cost estimations of major components in a commercial scale system are presented in this paper. The cost model provides insights for further development and cost comparison with competing technologies.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2021

Advanced PGM-free Cathode Engineering for High Power Density and Durability

Polymer electrolyte fuel cells (PEFCs) are among the most promising technologies for future electric vehicles by using clean H2 with much-improved energy conversion efficiency, longer range, and rapid refueling. However, due to a large amount of platinum group metal (PGM) catalyst used in their electrodes, their prohibitively high cost hinders broad commercialization of PEFCs for transportation. Therefore, there is a critical need to develop low-cost, high-performance PGM-free cathode catalysts that have the potential to dramatically transform the economics of PEFC commercialization by reducing catalyst costs by one to two orders of magnitude. However, before PGM-free cathodes become viable, several technical challenges associated with PGM-free cathodes must be addressed, including insufficient activity and stability of the catalysts, as well as severe water flooding and large transport losses in the electrodes. Overcoming those barriers and ultimately meeting the challenging automotive PEFC performance targets was the focus of this comprehensive research and development effort on new PGM-free cathodes. To this end, we assembled a team including leading researchers from universities and industry with different but complementary expertise and capabilities. The project combined three novel and promising approaches: Advanced metal-organic framework (MOF)-derived M-N-C catalysts with a high activity and impressive durability, Novel PGM-free specific cathode architectures and fabrication strategies capable of addressing the substantial flooding and transport resistances in thicker cathodes by introducing engineered hydrophobicity through additives and support layers, and Advanced electrode ionomers with high proton conductivity for low ohmic losses across the electrode and more uniform catalyst utilization. The implementation of these new materials and electrode designs was supported by a suite of advanced experimental and simulation tools that allows us to identify performance and durability bottlenecks, devise solutions, and establish rational material design and synthesis targets. These methods include advanced electrochemical characterization, high-resolution imaging, and multi-scale modeling. In addition, the project team leveraged a broad cross-section of the ElectroCat consortium’s national laboratory facilities and expertise in advancing these materials and design strategies. Finally, the industry partners on the project facilitated the evaluation of scaled-up synthesis and manufacturing in the United States. Over its four-year period, the project made significant year-over-year advances in PGM-free cathode performance and viability. A combination of high activity and highly durable catalysts were developed through novel catalyst synthesis strategies, which met several performance and durability targets. More specifically, a catalyst prepared from MOFs and Fe2O3 nanoparticles with ammonium chloride and chemical vapor deposition treatments yielded a significant advancement in PGM-free cathode durability. Several novel strategies for fabricating cathodes were demonstrated, including those designed to reduce flooding and thickness of the cells for significantly increased volumetric power density. An optimized cathode with high conductivity ionomer and tuned ink processing for hydrophobicity yielded high fuel cell performance with new levels power density and maximum current. The scientific studies and modeling assessment also provided an outlook for future efforts, including a focus on catalysts with an increased density of the highly stable active sites developed in this project.

08 HYDROGEN↗