Showing papers by "University of South Carolina published in 2018"

The Complete Light-curve Sample of Spectroscopically Confirmed SNe Ia from Pan-STARRS1 and Cosmological Constraints from the Combined Pantheon Sample

Abstract: Author(s): Scolnic, DM; Jones, DO; Rest, A; Pan, YC; Chornock, R; Foley, RJ; Huber, ME; Kessler, R; Narayan, G; Riess, AG; Rodney, S; Berger, E; Brout, DJ; Challis, PJ; Drout, M; Finkbeiner, D; Lunnan, R; Kirshner, RP; Sanders, NE; Schlafly, E; Smartt, S; Stubbs, CW; Tonry, J; Wood-Vasey, WM; Foley, M; Hand, J; Johnson, E; Burgett, WS; Chambers, KC; Draper, PW; Hodapp, KW; Kaiser, N; Kudritzki, RP; Magnier, EA; Metcalfe, N; Bresolin, F; Gall, E; Kotak, R; McCrum, M; Smith, KW | Abstract: We present optical light curves, redshifts, and classifications for 365 spectroscopically confirmed Type Ia supernovae (SNe Ia) discovered by the Pan-STARRS1 (PS1) Medium Deep Survey. We detail improvements to the PS1 SN photometry, astrometry, and calibration that reduce the systematic uncertainties in the PS1 SN Ia distances. We combine the subset of 279 PS1 SNe Ia (0.03 l z l 0.68) with useful distance estimates of SNe Ia from the Sloan Digital Sky Survey (SDSS), SNLS, and various low-z and Hubble Space Telescope samples to form the largest combined sample of SNe Ia, consisting of a total of 1048 SNe Ia in the range of 0.01 l z l 2.3, which we call the Pantheon Sample. When combining Planck 2015 cosmic microwave background (CMB) measurements with the Pantheon SN sample, we find Wm = 0.307 ± 0.012 and w = -1.026 ± 0.041 for the wCDM model. When the SN and CMB constraints are combined with constraints from BAO and local H0 measurements, the analysis yields the most precise measurement of dark energy to date: w0 = -1.007 ± 0.089 and wa = -0.222 ± 0.407 for the w0waCDM model. Tension with a cosmological constant previously seen in an analysis of PS1 and low-z SNe has diminished after an increase of 2× in the statistics of the PS1 sample, improved calibration and photometry, and stricter light-curve quality cuts. We find that the systematic uncertainties in our measurements of dark energy are almost as large as the statistical uncertainties, primarily due to limitations of modeling the low-redshift sample. This must be addressed for future progress in using SNe Ia to measure dark energy.

Best Practices for Developing and Validating Scales for Health, Social, and Behavioral Research: A Primer.

Abstract: Scale development and validation are critical to much of the work in the health, social, and behavioral sciences. However, the constellation of techniques required for scale development and evaluation can be onerous, jargon-filled, unfamiliar, and resource-intensive. Further, it is often not a part of graduate training. Therefore, our goal was to concisely review the process of scale development in as straightforward a manner as possible, both to facilitate the development of new, valid, and reliable scales, and to help improve existing ones. To do this, we have created a primer for best practices for scale development in measuring complex phenomena. This is not a systematic review, but rather the amalgamation of technical literature and lessons learned from our experiences spent creating or adapting a number of scales over the past several decades. We identified three phases that span nine steps. In the first phase, items are generated and the validity of their content is assessed. In the second phase, the scale is constructed. Steps in scale construction include pre-testing the questions, administering the survey, reducing the number of items, and understanding how many factors the scale captures. In the third phase, scale evaluation, the number of dimensions is tested, reliability is tested, and validity is assessed. We have also added examples of best practices to each step. In sum, this primer will equip both scientists and practitioners to understand the ontology and methodology of scale development and validation, thereby facilitating the advancement of our understanding of a range of health, social, and behavioral outcomes.

Atomically dispersed manganese catalysts for oxygen reduction in proton-exchange membrane fuel cells

Abstract: Platinum group metal (PGM)-free catalysts that are also iron free are highly desirable for the oxygen reduction reaction (ORR) in proton-exchange membrane fuel cells, as they avoid possible Fenton reactions. Here we report an efficient ORR catalyst that consists of atomically dispersed nitrogen-coordinated single Mn sites on partially graphitic carbon (Mn-N-C). Evidence for the embedding of the atomically dispersed MnN4 moieties within the carbon surface-exposed basal planes was established by X-ray absorption spectroscopy and their dispersion was confirmed by aberration-corrected electron microscopy with atomic resolution. The Mn-N-C catalyst exhibited a half-wave potential of 0.80 V versus the reversible hydrogen electrode, approaching that of Fe-N-C catalysts, along with significantly enhanced stability in acidic media. The encouraging performance of the Mn-N-C catalyst as a PGM-free cathode was demonstrated in fuel cell tests. First-principles calculations further support the MnN4 sites as the origin of the ORR activity via a 4e− pathway in acidic media. Platinum group metal- and iron-free catalysts are highly desirable for the oxygen reduction reaction in proton-exchange membrane fuel cells. Now, Wu and co-workers show a carbon catalyst with atomically dispersed single Mn sites as an efficient catalyst with enhanced stability in acidic media.

Ultrawide-Bandgap Semiconductors: Research Opportunities and Challenges

Abstract: J. Y. Tsao,* S. Chowdhury, M. A. Hollis,* D. Jena, N. M. Johnson, K. A. Jones, R. J. Kaplar,* S. Rajan, C. G. Van de Walle, E. Bellotti, C. L. Chua, R. Collazo, M. E. Coltrin, J. A. Cooper, K. R. Evans, S. Graham, T. A. Grotjohn, E. R. Heller, M. Higashiwaki, M. S. Islam, P. W. Juodawlkis, M. A. Khan, A. D. Koehler, J. H. Leach, U. K. Mishra, R. J. Nemanich, R. C. N. Pilawa-Podgurski, J. B. Shealy, Z. Sitar, M. J. Tadjer, A. F. Witulski, M. Wraback, and J. A. Simmons

Avelumab, an anti-PD-L1 antibody, in patients with locally advanced or metastatic breast cancer: a phase 1b JAVELIN Solid Tumor study.

Abstract: Agents targeting programmed death receptor 1 (PD-1) or its ligand (PD-L1) have shown antitumor activity in the treatment of metastatic breast cancer (MBC). The aim of this study was to assess the activity of avelumab, a PD-L1 inhibitor, in patients with MBC. In a phase 1 trial (JAVELIN Solid Tumor; NCT01772004), patients with MBC refractory to or progressing after standard-of-care therapy received avelumab intravenously 10 mg/kg every 2 weeks. Tumors were assessed every 6 weeks by RECIST v1.1. Adverse events (AEs) were graded by NCI-CTCAE v4.0. Membrane PD-L1 expression was assessed by immunohistochemistry (Dako PD-L1 IHC 73-10 pharmDx). A total of 168 patients with MBC, including 58 patients with triple-negative breast cancer (TNBC), were treated with avelumab for 2–50 weeks and followed for 6–15 months. Patients were heavily pretreated with a median of three prior therapies for metastatic or locally advanced disease. Grade ≥ 3 treatment-related AEs occurred in 13.7% of patients, including two treatment-related deaths. The confirmed objective response rate (ORR) was 3.0% overall (one complete response and four partial responses) and 5.2% in patients with TNBC. A trend toward a higher ORR was seen in patients with PD-L1+ versus PD-L1− tumor-associated immune cells in the overall population (16.7% vs. 1.6%) and in the TNBC subgroup (22.2% vs. 2.6%). Avelumab showed an acceptable safety profile and clinical activity in a subset of patients with MBC. PD-L1 expression in tumor-associated immune cells may be associated with a higher probability of clinical response to avelumab in MBC.

Photochemistry and photophysics of MOFs: steps towards MOF-based sensing enhancements.

Abstract: In this review, we highlight how recent advances achieved in the fields of photochemistry and photophysics of metal–organic frameworks (MOFs) could be applied towards the engineering of next generation MOF-based sensing devices. In addition to high surface area and structural tunability, which are crucial for efficient sensor development, progress in the field of MOF-based sensors could rely on the combination of MOF light-harvesting ability, understanding energy transfer processes within a framework, and application of MOF-based photocatalysis towards sensing enhancement. All photophysical concepts could be integrated within one material to improve efficiency and selectivity of sensing devices. Thus, the focus of this review is shifted towards a “beyond the pores” approach, which could foreshadow new guidelines for sensor engineering.

Nanomaterials in the environment: behavior, fate, bioavailability, and effects—an updated review

Abstract: The present review covers developments in studies of nanomaterials (NMs) in the environment since our much cited review in 2008. We discuss novel insights into fate and behavior, metrology, transformations, bioavailability, toxicity mechanisms, and environmental impacts, with a focus on terrestrial and aquatic systems. Overall, the findings were that: 1) despite substantial developments, critical gaps remain, in large part due to the lack of analytical, modeling, and field capabilities, and also due to the breadth and complexity of the area; 2) a key knowledge gap is the lack of data on environmental concentrations and dosimetry generally; 3) substantial evidence shows that there are nanospecific effects (different from the effects of both ions and larger particles) on the environment in terms of fate, bioavailability, and toxicity, but this is not consistent for all NMs, species, and relevant processes; 4) a paradigm is emerging that NMs are less toxic than equivalent dissolved materials but more toxic than the corresponding bulk materials; and 5) translation of incompletely understood science into regulation and policy continues to be challenging. There is a developing consensus that NMs may pose a relatively low environmental risk, but because of uncertainty and lack of data in many areas, definitive conclusions cannot be drawn. In addition, this emerging consensus will likely change rapidly with qualitative changes in the technology and increased future discharges. Environ Toxicol Chem 2018;37:2029-2063. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments

Abstract: With more than a hundred elements in the periodic table, a large number of potential new materials exist to address the technological and societal challenges we face today; however, without some guidance, searching through this vast combinatorial space is frustratingly slow and expensive, especially for materials strongly influenced by processing. We train a machine learning (ML) model on previously reported observations, parameters from physiochemical theories, and make it synthesis method–dependent to guide high-throughput (HiTp) experiments to find a new system of metallic glasses in the Co-V-Zr ternary. Experimental observations are in good agreement with the predictions of the model, but there are quantitative discrepancies in the precise compositions predicted. We use these discrepancies to retrain the ML model. The refined model has significantly improved accuracy not only for the Co-V-Zr system but also across all other available validation data. We then use the refined model to guide the discovery of metallic glasses in two additional previously unreported ternaries. Although our approach of iterative use of ML and HiTp experiments has guided us to rapid discovery of three new glass-forming systems, it has also provided us with a quantitatively accurate, synthesis method–sensitive predictor for metallic glasses that improves performance with use and thus promises to greatly accelerate discovery of many new metallic glasses. We believe that this discovery paradigm is applicable to a wider range of materials and should prove equally powerful for other materials and properties that are synthesis path–dependent and that current physiochemical theories find challenging to predict.

Integrating human behaviour dynamics into flood disaster risk assessment

Abstract: The behaviour of individuals, businesses, and government entities before, during, and immediately after a disaster can dramatically affect the impact and recovery time. However, existing risk-assessment methods rarely include this critical factor. In this Perspective, we show why this is a concern, and demonstrate that although initial efforts have inevitably represented human behaviour in limited terms, innovations in flood-risk assessment that integrate societal behaviour and behavioural adaptation dynamics into such quantifications may lead to more accurate characterization of risks and improved assessment of the effectiveness of risk-management strategies and investments. Such multidisciplinary approaches can inform flood-risk management policy development.

First Results from CUORE: A Search for Lepton Number Violation via 0νββ Decay of ^{130}Te.

Abstract: The CUORE experiment, a ton-scale cryogenic bolometer array, recently began operation at the Laboratori Nazionali del Gran Sasso in Italy. The array represents a significant advancement in this technology, and in this work we apply it for the first time to a high-sensitivity search for a lepton-number-violating process: ^{130}Te neutrinoless double-beta decay. Examining a total TeO_{2} exposure of 86.3 kg yr, characterized by an effective energy resolution of (7.7±0.5) keV FWHM and a background in the region of interest of (0.014±0.002) counts/(keV kg yr), we find no evidence for neutrinoless double-beta decay. Including systematic uncertainties, we place a lower limit on the decay half-life of T_{1/2}^{0ν}(^{130}Te)>1.3×10^{25} yr (90% C.L.); the median statistical sensitivity of this search is 7.0×10^{24} yr. Combining this result with those of two earlier experiments, Cuoricino and CUORE-0, we find T_{1/2}^{0ν}(^{130}Te)>1.5×10^{25} yr (90% C.L.), which is the most stringent limit to date on this decay. Interpreting this result as a limit on the effective Majorana neutrino mass, we find m_{ββ}<(110-520) meV, where the range reflects the nuclear matrix element estimates employed.

The Impact of a Reported Penicillin Allergy on Surgical Site Infection Risk

Abstract: Background A reported penicillin allergy may compromise receipt of recommended antibiotic prophylaxis intended to prevent surgical site infections (SSIs). Most patients with a reported penicillin allergy are not allergic. We determined the impact of a reported penicillin allergy on the development of SSIs. Methods In this retrospective cohort study of Massachusetts General Hospital hip arthroplasty, knee arthroplasty, hysterectomy, colon surgery, and coronary artery bypass grafting patients from 2010 to 2014, we compared patients with and without a reported penicillin allergy. The primary outcome was an SSI, as defined by the Centers for Disease Control and Prevention's National Healthcare Safety Network. The secondary outcome was perioperative antibiotic use. Results Of 8385 patients who underwent 9004 procedures, 922 (11%) reported a penicillin allergy, and 241 (2.7%) had an SSI. In multivariable logistic regression, patients reporting a penicillin allergy had increased odds (adjusted odds ratio, 1.51; 95% confidence interval, 1.02-2.22) of SSI. Penicillin allergy reporters were administered less cefazolin (12% vs 92%; P < .001) and more clindamycin (49% vs 3%; P < .001), vancomycin (35% vs 3%; P < .001), and gentamicin (24% vs 3%; P < .001) compared with those without a reported penicillin allergy. The increased SSI risk was entirely mediated by the patients' receipt of an alternative perioperative antibiotic; between 112 and 124 patients with reported penicillin allergy would need allergy evaluation to prevent 1 SSI. Conclusions Patients with a reported penicillin allergy had a 50% increased odds of SSI, attributable to the receipt of second-line perioperative antibiotics. Clarification of penicillin allergies as part of routine preoperative care may decrease SSI risk.

Ordered Pt3Co Intermetallic Nanoparticles Derived from Metal-Organic Frameworks for Oxygen Reduction.

Abstract: Highly ordered Pt alloy structures are proven effective to improve their catalytic activity and stability for the oxygen reduction reaction (ORR) for proton exchange membrane fuel cells. Here, we report a new approach to preparing ordered Pt3Co intermetallic nanoparticles through a facile thermal treatment of Pt nanoparticles supported on Co-doped metal–organic-framework (MOF)-derived carbon. In particular, the atomically dispersed Co sites, which are originally embedded into MOF-derived carbon, diffuse into Pt nanocrystals and form ordered Pt3Co structures. It is very crucial for the formation of the ordered Pt3Co to carefully control the doping content of Co into the MOFs and the heating temperatures for Co diffusion. The optimal Pt3Co nanoparticle catalyst has achieved significantly enhanced activity and stability, exhibiting a half-wave potential up to 0.92 V vs reversible hydrogen electrode (RHE) and only losing 12 mV after 30 000 potential cycling between 0.6 and 1.0 V. The highly ordered intermetal...

Physico-chemical characteristics of evaporating respiratory fluid droplets

Abstract: The detailed physico-chemical characteristics of respiratory droplets in ambient air, where they are subject to evaporation, are poorly understood. Changes in the concentration and phase of major components in a droplet-salt (NaCl), protein (mucin) and surfactant (dipalmitoylphosphatidylcholine)-may affect the viability of any pathogens contained within it and thus may affect the efficiency of transmission of infectious disease by droplets and aerosols. The objective of this study is to investigate the effect of relative humidity (RH) on the physico-chemical characteristics of evaporating droplets of model respiratory fluids. We labelled these components in model respiratory fluids and observed evaporating droplets suspended on a superhydrophobic surface using optical and fluorescence microscopy. When exposed to continuously decreasing RH, droplets of different model respiratory fluids assumed different morphologies. Loss of water induced phase separation as well as indication of a decrease in pH. The presence of surfactant inhibited the rapid rehydration of the non-volatile components. An enveloped virus, ϕ6, that has been proposed as a surrogate for influenza virus appeared to be homogeneously distributed throughout the dried droplet. We hypothesize that the increasing acidity and salinity in evaporating respiratory droplets may affect the structure of the virus, although at low enough RH, crystallization of the droplet components may eliminate their harmful effects.

Island Loss for Learning Discriminative Features in Facial Expression Recognition

Abstract: Over the past few years, Convolutional Neural Networks (CNNs) have shown promise on facial expression recognition. However, the performance degrades dramatically under real-world settings due to variations introduced by subtle facial appearance changes, head pose variations, illumination changes, and occlusions. In this paper, a novel island loss is proposed to enhance the discriminative power of deeply learned features. Specifically, the island loss is designed to reduce the intra-class variations while enlarging the inter-class differences simultaneously. Experimental results on four benchmark expression databases have demonstrated that the CNN with the proposed island loss (IL-CNN) outperforms the baseline CNN models with either traditional softmax loss or center loss and achieves comparable or better performance compared with the state-of-the-art methods for facial expression recognition.

Macromolecular-clustered facial amphiphilic antimicrobials.

Abstract: Bacterial infections and antibiotic resistance, particularly by Gram-negative pathogens, have become a global healthcare crisis. We report the design of a class of cationic antimicrobial polymers that cluster local facial amphiphilicity from repeating units to enhance interactions with bacterial membranes without requiring a globally conformational arrangement associated with highly unfavorable entropic loss. This concept of macromolecular architectures is demonstrated with a series of multicyclic natural product-based cationic polymers. We have shown that cholic acid derivatives with three charged head groups are more potent and selective than lithocholic and deoxycholic counterparts, particularly against Gram-negative bacteria. This is ascribed to the formation of true facial amphiphilicity with hydrophilic ion groups oriented on one face and hydrophobic multicyclic hydrocarbon structures on the opposite face. Such local facial amphiphilicity is clustered via a flexible macromolecular backbone in a concerted way when in contact with bacterial membranes.

2D matrix engineering for homogeneous quantum dot coupling in photovoltaic solids.

Abstract: Colloidal quantum dots (CQDs) are promising photovoltaic (PV) materials because of their widely tunable absorption spectrum controlled by nanocrystal size1,2. Their bandgap tunability allows not only the optimization of single-junction cells, but also the fabrication of multijunction cells that complement perovskites and silicon 3 . Advances in surface passivation2,4–7, combined with advances in device structures 8 , have contributed to certified power conversion efficiencies (PCEs) that rose to 11% in 2016 9 . Further gains in performance are available if the thickness of the devices can be increased to maximize the light harvesting at a high fill factor (FF). However, at present the active layer thickness is limited to ~300 nm by the concomitant photocarrier diffusion length. To date, CQD devices thicker than this typically exhibit decreases in short-circuit current (JSC) and open-circuit voltage (VOC), as seen in previous reports3,9–11. Here, we report a matrix engineering strategy for CQD solids that significantly enhances the photocarrier diffusion length. We find that a hybrid inorganic–amine coordinating complex enables us to generate a high-quality two-dimensionally (2D) confined inorganic matrix that programmes internanoparticle spacing at the atomic scale. This strategy enables the reduction of structural and energetic disorder in the solid and concurrent improvements in the CQD packing density and uniformity. Consequently, planar devices with a nearly doubled active layer thicknesses (~600 nm) and record values of JSC (32 mA cm−2) are fabricated. The VOC improved as the current was increased. We demonstrate CQD solar cells with a certified record efficiency of 12%. A new matrix engineering strategy enables improvements of CQD solar cell efficiency via considerable enhancement of the photocarrier diffusion length.

Anatomy of aphasia revisited.

Abstract: In most cases, aphasia is caused by strokes involving the left hemisphere, with more extensive damage typically being associated with more severe aphasia. The classical model of aphasia commonly adhered to in the Western world is the Wernicke-Lichtheim model. The model has been in existence for over a century, and classification of aphasic symptomatology continues to rely on it. However, far more detailed models of speech and language localization in the brain have been formulated. In this regard, the dual stream model of cortical brain organization proposed by Hickok and Poeppel is particularly influential. Their model describes two processing routes, a dorsal stream and a ventral stream, that roughly support speech production and speech comprehension, respectively, in normal subjects. Despite the strong influence of the dual stream model in current neuropsychological research, there has been relatively limited focus on explaining aphasic symptoms in the context of this model. Given that the dual stream model represents a more nuanced picture of cortical speech and language organization, cortical damage that causes aphasic impairment should map clearly onto the dual processing streams. Here, we present a follow-up study to our previous work that used lesion data to reveal the anatomical boundaries of the dorsal and ventral streams supporting speech and language processing. Specifically, by emphasizing clinical measures, we examine the effect of cortical damage and disconnection involving the dorsal and ventral streams on aphasic impairment. The results reveal that measures of motor speech impairment mostly involve damage to the dorsal stream, whereas measures of impaired speech comprehension are more strongly associated with ventral stream involvement. Equally important, many clinical tests that target behaviours such as naming, speech repetition, or grammatical processing rely on interactions between the two streams. This latter finding explains why patients with seemingly disparate lesion locations often experience similar impairments on given subtests. Namely, these individuals' cortical damage, although dissimilar, affects a broad cortical network that plays a role in carrying out a given speech or language task. The current data suggest this is a more accurate characterization than ascribing specific lesion locations as responsible for specific language deficits.5705668782001awx363media15705668782001.

Alcohol and Cancer: A Statement of the American Society of Clinical Oncology

Abstract: Alcohol drinking is an established risk factor for several malignancies, and it is a potentially modifiable risk factor for cancer. The Cancer Prevention Committee of the American Society of Clinical Oncology (ASCO) believes that a proactive stance by the Society to minimize excessive exposure to alcohol has important implications for cancer prevention. In addition, the role of alcohol drinking on outcomes in patients with cancer is in its formative stages, and ASCO can play a key role by generating a research agenda. Also, ASCO could provide needed leadership in the cancer community on this issue. In the issuance of this statement, ASCO joins a growing number of international organizations by establishing a platform to support effective public health strategies in this area. The goals of this statement are to:• Promote public education about the risks between alcohol abuse and certain types of cancer;• Support policy efforts to reduce the risk of cancer through evidence-based strategies that prevent exce...

Type Ia Supernova Distances at Redshift > 1.5 from the Hubble Space Telescope Multi-cycle Treasury Programs: The Early Expansion Rate

Abstract: We present an analysis of 15 Type Ia supernovae (SNe Ia) at redshift z 〉 1 (9 at 1.5 〈 z 〈 2.3) recently discovered in the CANDELS and CLASH Multi-Cycle Treasury programs using WFC3 on the Hubble Space Telescope. We combine these SNe Ia with a new compilation of ~1050 SNe Ia, jointly calibrated and corrected for simulated survey biases to produce accurate distance measurements. We present unbiased constraints on the expansion rate at six redshifts in the range 0.07 〈 z 〈 1.5 based only on this combined SN Ia sample. The added leverage of our new sample at z 〉 1.5 leads to a factor of ~3 improvement in the determination of the expansion rate at z = 1.5, reducing its uncertainty to ~20%, a measurement of H(z=1.5)/H_0 = 2.69_(-0.52)^(+0.86). We then demonstrate that these six derived expansion rate measurements alone provide a nearly identical characterization of dark energy as the full SN sample, making them an efficient compression of the SN Ia data. The new sample of SNe Ia at z 〉 1.5 usefully distinguishes between alternative cosmological models and unmodeled evolution of the SN Ia distance indicators, placing empirical limits on the latter. Finally, employing a realistic simulation of a potential Wide-Field Infrared Survey Telescope SN survey observing strategy, we forecast optimistic future constraints on the expansion rate from SNe Ia.

Examination of the Weighted Root Mean Square Residual: Evidence for Trustworthiness?

Abstract: This study examined the performance of the weighted root mean square residual (WRMR) through a simulation study using confirmatory factor analysis with ordinal data. Values and cut scores for the W...

Beyond catalysis and membranes: visualizing and solving the challenge of electrode water accumulation and flooding in AEMFCs

Abstract: A majority of anion exchange membrane fuel cells (AEMFCs) reported in the literature have been unable to achieve high current or power A recently proposed theory is that the achievable current is largely limited by poorly balanced water during cell operation In this work, we present convincing experimental results – coupling operando electrochemical measurements and neutron imaging – supporting this theory and allowing the amount and distribution of water, and its impact on AEMFC performance, to be quantified for the first time We also create new electrode compositions by systematically manipulating the ionomer and carbon content in the anode catalyst layer, which allowed us to alleviate the mass transport behavior limitations of H2/O2 AEMFCs and achieve a new record-setting peak power density of 19 W cm−2 – a step-change to existing literature Our efforts cast a new light on the design and optimization of AEMFCs – potentially changing the way that AEMFCs are constructed and operated