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DOE OSTI2026

Spectral characterization and performance of SPT-SLIM on-chip filterbank spectrometers

The South Pole Telescope Shirokoff Line Intensity Mapper (SPT-SLIM) experiment is a pathfinder for demonstrating the use of on-chip spectrometers for millimeter (mm) Line Intensity Mapping (LIM). We present spectral bandpass measurements of the SPT-SLIM spectrometer channels made on site using a Fourier Transform Spectrometer during the first deployment of SPT-SLIM in the 2024-2025 Austral summer season. We note the effect of FTS systematics on measurements of on-chip filterbank spectrometer resolutions and demonstrate a technique for measuring the narrow band passes of the SPT-SLIM filterbanks that improves beyond the intrinsic resolution of a Fourier Transform Spectrometer.

Benson, C. S. [Cardiff U.]↗

DOE OSTI2020

Electrostatic control of photoisomerization pathways in proteins

Rotation around a specific bond after photoexcitation is central to vision and emerging opportunities in optogenetics, super-resolution microscopy, and photoactive molecular devices. Competing roles for steric and electrostatic effects that govern bond-specific photoisomerization have been widely discussed, the latter originating from chromophore charge transfer upon excitation. We systematically altered the electrostatic properties of the green fluorescent protein chromophore in a photoswitchable variant, Dronpa2, using amber suppression to introduce electron-donating and electron-withdrawing groups to the phenolate ring. Through analysis of the absorption (color), fluorescence quantum yield, and energy barriers to ground- and excited-state isomerization, we evaluate the contributions of sterics and electrostatics quantitatively and demonstrate how electrostatic effects bias the pathway of chromophore photoisomerization, leading to a generalized framework to guide protein design.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Two-dimensional phase cartography for high-harmonic spectroscopy

Extremely nonlinear spectroscopy based on high-order-harmonic generation has become a powerful investigation method for attosecond dynamics in gas and solid targets. In particular, the phase of harmonic emission was shown to carry profound insight into atomic and molecular structure and dynamics. However, current techniques offer phase measurements only along specific directions, thus providing partial characterization. Here we report on a new approach combining optical and quantum interferometers measuring along two dimensions the intensity and phase of harmonic emission from aligned molecules in the exact same experimental conditions. This two-dimensional cartography technique measures the phase with no arbitrary offset and no uncertainty on its sign. Measurements along different dimensions can be combined in two ways: either a single mapping or a redundant mapping allowing high-precision phase recovery using a Shack–Hartmann-like algorithm. We demonstrate both methods in a nitrogen test case, which allows disentangling structural and dynamical effects. Two-dimensional phase cartography paves the way to high-resolution high-harmonic spectroscopy for applications such as quantum orbital tomography and attosecond charge migration in molecules.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Measuring Electron Diffusion and Constraining the Neutral Current $\pi^0$ Background for Single-Photon Events in MicroBooNE

Liquid Argon Time Projection Chambers (LArTPCs) are a rising technology in the field of experimental neutrino physics. LArTPCs use ionization electrons and scintillation light to reconstruct neutrino interactions with exceptional calorimetric and position resolution capabilities. Here, I present two analyses conducted in the MicroBooNE LArTPC at Fermilab: a measurement of the longitudinal electron diffusion coefficient, $D_L$, in the MicroBooNE detector and a constraint of the systematic uncertainty on MicroBooNE's single-photon analysis due to the dominant neutral current (NC) \piz{} background. Longitudinal electron diffusion modifies the spatial and timing resolution of the detector, and measuring it will help correct for these effects. Furthermore, current measurements of $D_L$ in liquid argon are sparse and in tension with one another, making the MicroBooNE measurement especially valuable. We report a measurement of $3.74^{+0.28}_{-0.29}$ cm$^2$/s. MicroBooNE is searchin g for si ngle-photon events as a potential explanation for the MiniBooNE low-energy excess (LEE) of electron neutrino-like events, which has been interpreted as evidence for low-mass sterile neutrinos. However, this search is overwhelmed by a large NC \piz{} background. By performing a sideband selection of NC \piz{} events, we apply a data-driven rate constraint to the single-photon analysis to reduce the systematic uncertainties. At present, this constraint improves the single-photon analysis' median sensitivity to the LEE-like signal from 0.9$\sigma$ to $1.5\sigma$. This sensitivity is expected to improve significantly as more data become available. Both of these measurements will not only benefit MicroBooNE, but also inform future LArTPC experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Strategic Energy Management Program Persistence and Cost Effectiveness An Analysis of the SEM Program Landscape

This study examines the relationship between strategic energy management (SEM) programs and their persistence and cost effectiveness, with analysis based on interview data from 24 SEM program administrators, SEM program evaluations, and other reports. The 80 interview questions focused on the topics of program design, energy savings, energy savings persistence, cost effectiveness, and customer SEM persistence. The generosity of interview respondents provided a wealth of data, resulting in a report of sufficient length to warrant inclusion of this brief guide of the report structure. The major sections are listed below with brief descriptions. Individual sections of this report are mainly stand-alone and do not require reading of other sections. As a result, there is some duplication between sections, but with differing levels of detail. Executive Summary: Presents three key conclusions of this work with a short description of potential actions to advance the understanding of each key finding. Brief Observations: Lists a large number of bulleted observations resulting from this research, arranged by the five major topic areas included in the interviews. Analysis details are provided in the Analysis of Interview Results section. Foundations for this Research: Provides an overview of SEM, SEM frameworks, SEM programs, the topics of persistence and cost effectiveness, and the focus of this research. Methodology: Details the approach and strategy of this research, providing background information relevant to the formulation of interview questions and the identification of which SEM programs to interview. Observations from Compiled Evaluations and Other Reports: Reports observations from the collection and analysis of program evaluations, annual reports, utility planning documents, and SEM-related white papers. This section, presented in bullet form, highlights challenges in data collection and ultimately a comparison of program practices as they pertain to persistence and cost effectiveness. Analysis of Interview Results: Presents detailed analysis of responses from SEM program administrators, arranged by the five major categories examined: program design, energy savings, energy savings persistence, cost effectiveness, and customer SEM persistence. Interview questions are generally grouped together into subsections when it makes sense to examine them together. SEM Programs Challenge Traditional Cost-Effectiveness Metrics: Details an analysis based on five key factors showing that applying traditional cost-effectiveness metrics to SEM programs is not straightforward. This invites the opportunity to consider whether traditional cost-effectiveness metrics are applicable to SEM programs, either individually or at large. Resolution of Research Hypotheses: Tabulates a set of hypotheses that were developed to address the fundamental nature of the research at hand. Analysis of responses to multiple questions informs an understanding of each hypothesis and can be used to better understand the SEM program environment at large.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Aerosol impacts on isolated deep convection: findings from TRACER

This study focuses on quantifying the conditional relationship between aerosol and convective precipitation properties of isolated deep convective clouds (DCCs) in the Houston–Galveston region, after adjusting for confounding effects. We leverage comprehensive ground-based observations from the TRacking Aerosol Convection interactions ExpeRiment (TRACER) to estimate aerosol effects on convective echo top height (ETH), intensity, and area separately. Our results show that greater aerosol number concentrations generally have a limited impact on these convective properties, showing relationships consistent with the possibility of both invigoration and suppression effects. Under certain conditions, where ultrafine particles are abundant, aerosols exhibit a positive effect on ETH, increasing it by about 1 km. However, it is inevitable to consider measurement uncertainties and the limitations of temporal and spatial resolution in the data, as these factors can further contribute to uncertainties in our estimates. In DCCs associated with sea breezes, the estimated aerosol effects on DCCs are found to be more pronounced. However, this heightened effect could be attributed to the exclusion of key confounders such as boundary layer updrafts in the analysis.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

EPCAPE-PT-LANL Measurements: Proton Transfer Reaction Mass Spectrometer

Coastal cities offer a unique environment for studying aerosol-cloud interactions and the effects of urban emissions on cloud properties. As part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), the Partitioning Thrust by Los Alamos National Laboratory (EPCAPE-PT-LANL) was conducted. Our campaign focused on measuring the optical and chemical properties of aerosols and their interactions within marine stratocumulus clouds in La Jolla, California. EPCAPE-PT-LANL enhances the primary goals of EPCAPE through innovative observations of vapor-phase transitions between aerosols and cloud droplets, the impact of black carbon on aerosol-cloud dynamics, and the effects of cloud processing on aerosol optical properties. Instrument: IONICON High-Resolution PTR-TOF-MS - Trace VOC Analyzer. Concentrations were calculated based on theoretical reaction rates of each species with H3O+. Details of the calculation are found in the PTR-MS Ionicon Manual. Data Notes: It is a high-resolution PTR-TOF-MS we have sub-selected relevant species. Contact us if you want additional data products from this instrument. Header: - CalculatedAcetonitrile[ppbv]: The concentration of acetonitrile expressed in parts per billion by volume (ppbv). - CalculatedAcetaldehyde[ppbv]: The concentration of acetaldehyde expressed in parts per billion by volume (ppbv). - CalculatedAcetone[ppbv]: The concentration of acetone expressed in parts per billion by volume (ppbv). - CalculatedAceticAcid[ppbv]: The concentration of acetic acid expressed in parts per billion by volume (ppbv). - CalculatedIsoprene[ppbv]: The concentration of isoprene expressed in parts per billion by volume (ppbv). - CalculatedMVK[ppbv]: The concentration of methyl vinyl ketone (MVK) and methacrolein (MACR) expressed in parts per billion by volume (ppbv). - CalculatedMEK[ppbv]: The concentration of methyl ethyl ketone (MEK) expressed in parts per billion by volume (ppbv). - CalculatedBenzene[ppbv]: The concentration of benzene expressed in parts per billion by volume (ppbv). - CalculatedToluene[ppbv]: The concentration of toluene expressed in parts per billion by volume (ppbv).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Hydrologic response of artificially drained agricultural watersheds: insights from high-resolution integrated surface/subsurface simulations

Artificial drainage systems comprising subsurface networks of perforated pipes (tile drains) and engineered surface ditches are widely used to remove excess water from poorly drained agricultural regions. Artificial drainage lowers the water table by design but also has inadvertent effects on the watershed-scale hydrologic response with important implications for flood risk and nutrient exports. We investigated the effects of tile drains on watershed-scale hydrologic response in the Portage River, OH, Watershed using a high-resolution physically based integrated surface/subsurface hydrology model with recently developed capabilities to represent artificial drainage. Tile drains were found to enhance streamflow during times of low flow, generally consistent with previous studies. Streamflow flashiness was found to have a non-monotonic dependence on tile spacing with a minimum at intermediate spacings (∼50 m). Flashiness and the event hydrographs for small tile spacing were similar to the situation with no tiles, but flow paths from farm to stream were very different for those two end member cases, emphasizing the limitations of the stream hydrograph in characterizing hydrologic response. For typical tile spacings, peak flow can either be enhanced or attenuated by the presence of tiles, depending on the size of the event and the antecedent meteorological conditions. Tiles enhance peak flow when the event is below a threshold of ∼25 mm or when events arrive in dry conditions. Peak flow is reduced by tiles when events are large and arrive in conditions that are not overly dry. The dependence on event size and antecedent conditions is explained by differences in available storage and flow paths to the streams. These results provide additional insights into how tile drainage modulates event-scale hydrologic response, an important control on flood generation mechanisms and nutrient exports.

agricultural watershed↗

DOE OSTI2021

Distributed Fiber Sensors With High Spatial Resolution in Extreme Radiation Environments in Nuclear Reactor Cores

This paper is a comprehensive experimental report on the neutron radiation effects of distributed optical fiber sensors with enhanced Rayleigh scattering profiles in an in-pile environment. Femtosecond laser direct writing was used to inscribe Type-II modifications in standard telecom fibers and radiation-hardened fibers with fluorine-doped cores. Rayleigh backscattering signals were enhanced for continuous 1.5 m. In-pile lead-out sensors tests were carried out at the MIT Research Reactor for two months, which was operated at a nominal power of 5.7 MW with fast neutron (>0.1 MeV) flux of 1.29 × 1014 n/cm2/s and an in-core temperature of up to 560°C. Using the Optical Frequency Domain Reflectometry technique, the backscattering profiles of fiber sensors were interrogated with a 3-cm spatial resolution to monitor the temperature profile of the reactor. Results show that laser inscribed Type-II modifications in the form of nanogratings are highly stable against extreme temperature and ionizing radiation. Both standard telecom fibers and radiation-hardened fibers with laser-enhanced Rayleigh profiles can continuously perform distributed temperature measurements over the entire duration of the in-pile testing. Temperature coefficients of sensors and spectral shift quality were studied as functions of total radiation fluence. To the best of our knowledge, we present for the first time, the temperature profile of an operating nuclear reactor core with 3-cm spatial resolution, enabled by distributed fiber sensors with laser-enhanced Rayleigh scattering profiles. The high spatial resolution measurements can provide valuable data for the design and validation of digital twin and virtual reality of nuclear energy systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Determination of effective attenuation length of slow electrons in polymer films

Slow electrons (with energy below 10 eV) play an important role in nature and technology. For instance, they are believed to initiate solubility change in extreme ultraviolet resists. Depending on their mobility, such secondary electrons can lead to image blur and degradation of patterning resolution. Hence, it is important to characterize the transport of slow electrons by measuring parameters such as the effective attenuation length (EAL). In this work, we present a technique that allows for prompt characterization of EAL in polymer films. In this experiment, slow electrons are generated in a substrate upon absorption of x-ray photons. The attenuation of electron flux by a polymer film is measured as a function of film thickness, allowing for the determination of EAL for slow electrons. We illustrate this method with poly(hydroxy styrene) and poly(methyl metacrylate) films. Furthermore, we propose an improvement for this technique that would enable the measurement of EAL as a function of electron kinetic energy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Enhancing Short-Range Weather Forecasts through Temporal Variation Encoding: A Multiperiod Embedding Approach

Machine learning (ML) techniques have emerged as promising approaches to improve regional weather forecast accuracy and reliability through data-driven methods. We propose a novel ML-based weather forecasting model, the Multiperiod Embed Net (MPENet). A key distinguishing feature of MPENet is its explicit utilization of the inherent cyclic nature in weather dynamics, unlike the autoregressive strategies commonly used in other ML weather forecasting approaches. Critical cyclic structures are identified via Fourier analyses of dynamic time series. Cyclicity in the convolutional representation is achieved by transforming one-dimensional time series of meteorological variables into two-dimensional tensors based on identified periods. This approach enables the model to leverage intrinsic weather patterns, enhancing regional forecast performance. To demonstrate the effectiveness of MPENet, we conduct a comparative analysis with Nvidia’s FourCastNet. Both models are trained on High-Resolution Rapid Refresh (HRRR) data from 2015 to 2022, over a 192 km × 192 km region in Tennessee. The comparisons are performed locally at two specific locations known to have different weather dynamics due to orographic effects: Crossville, on the relatively flat Cumberland Plateau with fewer topographic airflow disruptions, and Oak Ridge, in the ridge-and-valley region, where airflow is heavily influenced by surrounding valleys and mountains. Our results indicate that FourCastNet achieves strong accuracy at very short lead times, while MPENet maintains competitive skill and shows advantages in capturing temporal evolution over longer periods. Cross-correlation analyses of MPENet and FourCastNet predictions with the HRRR data suggest that encoding critical cyclicity into the network architecture leads to improvements in the forecasting skill.

Artificial intelligence↗

DOE OSTI2026

Learning genetic perturbation effects with variational causal inference

Advances in sequencing technologies have enhanced the understanding of gene regulation in cells. In particular, Perturb-seq has enabled high-resolution profiling of the transcriptomic response to genetic perturbations at the single-cell level. This understanding has implications in functional genomics and potentially for identifying therapeutic targets. Various computational models have been developed to predict perturbational effects. While deep learning models excel at interpolating observed perturbational data, they tend to overfit in the lack of enough data and may not generalize well to unseen perturbations. In contrast, mechanistic models, such as linear causal models based on gene regulatory networks, hold greater potential for extrapolation, as they encapsulate regulatory information that can predict responses to unseen perturbations. However, their application has been limited to small studies due to overly simplistic assumptions, making them less effective in handling noisy, large-scale single-cell data. We propose a hybrid approach that combines a mechanistic causal model with variational deep learning, termed Single Cell Causal Variational Autoencoder (SCCVAE). The mechanistic model employs a learned regulatory network to represent perturbational changes as shift interventions that propagate through the learned network. SCCVAE integrates this mechanistic causal model into a variational autoencoder, generating rich, comprehensive transcriptomic responses. Our results indicate that SCCVAE exhibits superior performance over current state-of-the-art baselines for extrapolating to predict unseen perturbational responses. Additionally, for the observed perturbations, the latent space learned by SCCVAE allows for the identification of functional perturbation modules and simulation of single-gene knockdown experiments of varying penetrance, presenting a robust tool for interpreting and interpolating perturbational responses at the single-cell level.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Optical Photometric Indicators of Galaxy Cluster Relaxation

Abstract The most dynamically relaxed clusters of galaxies play a special role in cosmological studies as well as astrophysical studies of the intracluster medium (ICM) and active galactic nucleus feedback. While high-spatial-resolution imaging of the morphology of the ICM has long been the gold standard for establishing a cluster’s dynamical state, such data are not available from current or planned surveys, and thus require separate, pointed follow-up observations. With optical and/or near-IR photometric imaging, and red-sequence cluster finding results from those data, expected to be ubiquitously available for clusters discovered in upcoming optical and millimeter-wavelength surveys, it is worth asking how effectively photometric data alone can identify relaxed cluster candidates, before investing in, e.g., high-resolution X-ray observations. Here we assess the ability of several simple photometric measurements, based on the redMaPPer cluster finder run on Sloan Digital Sky Survey data, to reproduce X-ray classifications of dynamical state for an X-ray selected sample of massive clusters. We find that two simple metrics contrasting the bright central galaxy (BCG) to other cluster members can identify a complete sample of relaxed clusters with a purity of ∼40% in our data set. Including minimal ICM information in the form of a center position increases the purity to ∼60%. However, all three metrics depend critically on correctly identifying the BCG, which is presently a challenge for optical red-sequence cluster finders.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

A High Resolution Simulation of a Single Shock-Accelerated Particle

We report particle drag models, which capture macroviscous and pressure effects, have been developed over the years for various flow regimes to enable cost effective simulations of particle-laden flows. The relatively recent derivation by Maxey and Riley has provided an exact equation of motion for spherical particles in a flow field based on the continuum assumption. Many models that have been simplified from these equations have provided reasonable approximations; however, the sensitivity of particle-laden flows to particle drag requires a very accurate model to simulate. To develop such a model, a two-dimensional axisymmetric Navier–Stokes direct numerical simulation of a single particle in a transient, shock-driven flow field was conducted using the hydrocode FLAG. FLAGs capability to run arbitrary Lagrangian-Eulerian hydrodynamics coupled with solid mechanic models makes it an ideal code to capture the physics of the flow field around and in the particle as it is shock-accelerated—a challenging regime to study. The goal of this work is twofold: to provide a validation for FLAGs Navier–Stokes and heat diffusion solutions and to provide a rationale for recent experimental particle drag measurements.

42 ENGINEERING↗

DOE OSTI2022

Radius measurement via super-resolution microscopy enables the development of a variable radii proximity labeling platform

The elucidation of protein interaction networks is critical to understanding fundamental biology as well as developing new therapeutics. Proximity labeling platforms (PLPs) are state-of-the-art technologies that enable the discovery and delineation of biomolecular networks through the identification of protein-protein interactions. These platforms work via catalytic generation of reactive probes at a biological region of interest; these probes then diffuse through solution and covalently “tag” proximal biomolecules. The physical distance that the probes diffuse determines the effective labeling radius of the PLP and is a critical parameter that influences the scale and resolution of interactome mapping. As such, by expanding the degrees of labeling resolution offered by PLPs, it is possible to better capture the various size scales of interactomes. At present, however, there is little quantitative understanding of the labeling radii of different PLPs. Here, we report the development of a superresolution microscopy-based assay for the direct quantification of PLP labeling radii. Using this assay, we provide direct extracellular measurements of the labeling radii of state-of-the-art antibody-targeted PLPs, including the peroxidase-based phenoxy radical platform (269 ± 41 nm) and the high-resolution iridium-catalyzed µMap technology (54 ± 12 nm). Last, we apply these insights to the development of a molecular diffusion-based approach to tuning PLP resolution and introduce a new aryl-azide-based µMap platform with an intermediate labeling radius (80 ± 28 nm).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Retinal microvascular and neuronal pathologies probed in vivo by adaptive optical two-photon fluorescence microscopy

The retina, behind the transparent optics of the eye, is the only neural tissue whose physiology and pathology can be non-invasively probed by optical microscopy. The aberrations intrinsic to the mouse eye, however, prevent high-resolution investigation of retinal structure and function in vivo. Optimizing the design of a two-photon fluorescence microscope (2PFM) and sample preparation procedure, we found that adaptive optics (AO), by measuring and correcting ocular aberrations, is essential for resolving putative synaptic structures and achieving three-dimensional cellular resolution in the mouse retina in vivo. Applying AO-2PFM to longitudinal retinal imaging in transgenic models of retinal pathology, we characterized microvascular lesions with sub-capillary details in a proliferative vascular retinopathy model, and found Lidocaine to effectively suppress retinal ganglion cell hyperactivity in a retinal degeneration model. Tracking structural and functional changes at high-resolution longitudinally, AO-2PFM enables microscopic investigations of retinal pathology and pharmacology for disease diagnosis and treatment in vivo.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

sup3ruhi (Super Resolution for Renewable Resource Data and Urban Heat Islands) [SWR-25-05]

Urban heat is a growing concern, particularly in dense metropolitan areas where high temperatures increase the risk of heat-related illness and drive energy expenses for cooling. Estimating the effects of urban heat remains a challenge due to limitations in describing the built environment, computational constraints, and the need for high-resolution data. This software presents open-source, computationally efficient machine learning methods that enhance the accuracy of urban temperature estimates compared to historical reanalysis data. Models trained using this software have been applied to urban microclimates in Los Angeles and Seattle showing greater accuracy and less bias when compared to low-resolution reanalysis datasets like ERA5 and even when compared to high-resolution mesoscale numerical weather models like WRF with an urban canopy model. Initial findings highlight how machine learning can support urban heat resilience planning by enabling improved assessments of local heat islands, mitigation strategies, and their energy implications. This software is an extension of (sup3r). This software supports the following publication: Buster, Grant, et al. Tackling Extreme Urban Heat: A Machine Learning Approach to Assess the Impacts of Climate Change and the Efficacy of Climate Adaptation Strategies in Urban Microclimates. arXiv:2411.05952, arXiv, 8 Nov. 2024. arXiv.org, https://doi.org/10.48550/arXiv.2411.05952. And has related public data records available at: Buster, Grant, Cox, Jordan, Benton, Brandon, and King, Ryan. Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI). United States: N.p., 16 Oct, 2024. Web. https://data.openei.org/submissions/6220.

Buster, Grant [National Renewable Energy Laborator↗

DOE OSTI2020

Tailoring electrode microstructure via ink content to enable improved rated power performance for platinum cobalt/high surface area carbon based polymer electrolyte fuel cells

Improvements in polymer electrolyte fuel cell (PEFC) electrode performance have primarily focused on catalyst and ionomer developments, marginalizing the importance of catalyst ink formulation. In this study, the effect of ink formulation is examined across a series of cathodes comprised of PtCo supported on high surface area carbon (PtCo/ HSC ) and Nafion ionomer using an array of in situ electrochemical and ex situ characterization techniques. In contrast to prior work on Pt/Vu systems, ink water content had little effect on the electrochemically determined ionomer coverage for the PtCo/HSC electrocatalyst examined here. Characterization using nano-scale resolution X-ray computed tomography (nano-CT) demonstrated that water-rich ink formulations lead to a reduction in aggregate size (ionomer + PtCo/HSC), improving local O 2 transport. This understanding, combined with the use of a commercially-available electrocatalyst was used to produced state-of-the-art membrane electrode assemblies with Pt loadings of 0.03/0.08 mg Pt /cm 2 on the anode and cathode respectively, having; i) > 1 A/mg Pt (0.9 V iR-free , 150 kPa, 80 °C, 100% RH, H 2 /O 2 ), ii) 320 mA/cm 2 at 0.8 V, 150 kPa, 80 ° C, 100% RH, H 2 /Air), and iii) > 1 W/cm 2 elec at rated power (0.67 V, 250 kPa, 94 °C, 65% RH, H 2 /Air) or < 0.11 g Pt /kW rated .

25 ENERGY STORAGE↗