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For targeted development of platinum group metal-free (PGM-free) catalysts for proton exchange membrane fuel cell applications, it is critically important to elucidate the catalytic moieties of Fe–N–C materials as they relate to the structure and morphology of the graphitic layers of carbon, the catalyst basic building blocks. In this Letter, X-ray diffraction analysis with a carbon-specific structure refinement algorithm was performed on 12 Fe–N–C catalysts. Samples with fewer graphitic layers exhibit increased kinetic performance in fuel cell testing. This trend is consistent with the dominant active species residing within the graphitic plane as opposed to at the edges. We also report the performance of an optimized catalyst based on structure–property predictions derived in a recently published report. This catalyst produces 0.44 mA cm–2 at 0.85 V and has a maximum power density of 490 mW cm–2 in 1 bar O2 (not iR corrected).

A platinum group metal-free (PGM-free) oxygen reduction reaction (ORR) catalyst engineered for stability has been synthesized using the sacrificial support method (SSM). This catalyst was comprehensively characterized by physiochemical analyses and tested for performance and durability in fuel cell membrane electrode assemblies (MEAs). This catalyst, belonging to the family of Fe-N-C materials, is easily scalable and can be manufactured in batches up to 200 g. The fuel cell durability tests were performed in a single cell configuration at realistic operating conditions of 0.65 V, 1.25 atm gauge air, and 90% RH for 100 hours. In-depth characterization of surface chemistry and morphology of the catalyst layer before and after durability tests were performed. The failure modes of the PGM-free electrodes were derived from structure-to-property correlations. It is

The role of the interaction between doped carbon-based materials and ionic conductors is essential in multiple technologies, from fuel cells and energy storage devices to conductive polymer composites. In this paper, we report how the surface chemistry of transition metal−nitrogen−carbon (MNC) electrocatalysts affects catalyst−ionomer interaction and the resulting structure of cathodes. The cathode structure resulting from these interactions is directly related to the performance in membrane electrode assembly (MEA) fuel cells. To advance the development of platinum group metal (PGM)free electrodes for the oxygen reduction reaction it is necessary to understand the structure of the catalyst layers with focus on chemistry and distribution of active sites and ionomer morphology. To assess catalyst interaction with an ionomer, X-ray photoelectron spectroscopy is applied to study the chemistry of catalyst layers while density functional theory (DFT) is used to calculate adsorption energies of the ionomer side chain on different nitrogen species. We report that a high surface concentration of hydrogenated nitrogen at the surface of MNC catalysts causes inefficient ionomer morphology, while an abundance of surface oxides promotes both an efficient distribution of active sites and an optimal ionomer−catalyst interface. The critical role of protonation of nitrogen within catalytic layers in inhibiting proton transport during fuel cell operation is also suggested. This is the first report of the effect the surface chemistry of MNC catalysts, in the presence of the ionomer, has on the structure and performance of MEA electrodes.

This work studies the morphology of platinum group metal-free (PGM-free) ironnitrogen-carbon (Fe-N-C) catalyst layers for the oxygen reduction reaction (ORR) and compares catalytic performance via polarization curves. Three different nitrogen-rich organic precursors are used to prepare the catalysts. Using scanning electron microscopy (SEM) and focused ion beam (FIB) tomography, the porosity, Euler number (pore connectivity), overall roughness, solid phase size and pore size are calculated for catalyst surfaces and volumes. Catalytic activity is determined using membrane electrode assembly (MEA) testing. It is found that the dominant factor in MEA performance is transport limitations. Through the 2D and 3D metrics it is concluded that pore connectivity has the biggest effect on transport performance.

Background: Effective mosquito control approaches incorporate both adult and larval stages. For the latter, physical, biological, and chemical control have been used with varying results. Successful control of larvae has been demonstrated using larvicides including insect growth regulators, e.g. the organophosphate temephos, as well as various entomopathogenic microbial species. However, a variety of health and environmental issues are associated with some of these. Laboratory trials of essential oils (EO) have established the larvicidal activity of these substances, but there are currently no commercially available EO-based larvicides. Here we report on the development of a new approach to mosquito larval control using a novel, yeast-based delivery system for EO. Methods: Food-grade orange oil (OO) was encapsulated into yeast cells following an established protocol. To prevent environmental contamination, a proprietary washing strategy was developed to remove excess EO that is adsorbed to the cell exterior during the encapsulation process. The OO-loaded yeast particles were then characterized for OO loading, and tested for efficacy against Aedes aegypti larvae. Results: The composition of encapsulated OO extracted from the yeast microparticles was demonstrated not to differ from that of un-encapsulated EO when analyzed by high performance liquid chromatography. After lyophilization, the oil in the larvicide comprised 26-30 percentage weight (wt%), and is consistent with the 60-65% reduction in weight observed after the drying process. Quantitative bioassays carried with Liverpool and Rockefeller Ae. aegypti strains in three different laboratories presented LD 50 of 5.1 (95% CI: 4.6-5.6) to 27.6 (95% CI: 26.4-28.8) mg/l, for L1 and L3/L4 mosquito larvae, respectively. LD 90 ranged between 18.9 (95% CI: 16.4-21.7) mg/l (L1 larvae) to 76.7 (95% CI: 69.7-84.3) mg/l (L3/L4 larvae). Conclusions: The larvicide based on OO encapsulated in yeast was shown to be highly active (LD 50 < 50 mg/l) against all larval stages of Ae. aegypti. These results demonstrate its potential for incorporation in an integrated approach to larval source management of Ae. aegypti. This novel approach can enable development of affordable control strategies that may have significant impact on global health.

The discrete wavelet transform (DWT) has found significant utility in process monitoring, filtering, and feature isolation of SEM, AFM, and optical images. Current use of the DWT for surface analysis assumes initial knowledge of the sizes of the features of interest in order to effectively isolate and analyze surface components. Current methods do not adequately address complex, heterogeneous surfaces in which features across multiple size ranges are of interest. Further, in situations where structure-to-property relationships are desired, the identification of features relevant for the function of the material is necessary. In this work, the DWT is examined as a tool for quantitative, length-scale specific surface metrology without prior knowledge of relevant features or length-scales. A new method is explored for determination of the best wavelet basis to minimize variation in roughness and skewness measurements with respect to change in position and orientation of surface features. It is observed that the size of the wavelet does not directly correlate with the size of features on the surface, and a method to measure the true length-scale specific roughness of the surface is presented. This method is applied to SEM and AFM images of non-precious metal catalysts, yielding new length-scale specific structure-to-property relationships for chemical speciation and fuel cell performance. The relationship between SEM and AFM length-scale specific roughness is also explored. Evidence is presented that roughness distributions of SEM images, as measured by the DWT, is representative of the true surface roughness distribution obtained from AFM.

Proper phosphorus precursor selection during synthesis could help produce better tin-pyrophosphate powder and composite membranes with improved fuel cell performance.