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Platinum group metal (PGM)-free oxygen reduction reaction (ORR) catalysts are of utmost importance for the rapid development of anion-exchange membrane fuel cell (AEMFC) technology. In this work, we demonstrate the improved ORR performance and stability of Co and Fe oxide-decorated/N-doped reduced graphene oxide (CoOx-Fe3O4/N-rGO) prepared via a hydrothermal method at the low temperature of 150 °C. The catalysts were characterized thoroughly using transmission electron microscopy, high-angle annular dark field-scanning electron microscopy, X-ray diffraction, N2 physisorption, Raman spectroscopy, and X-ray photoelectron spectroscopy to obtain information about morphology, elemental distribution, phases, porosity, defects, and surface elemental compositions. Significant ORR activity improvement (130 mV@-1.5 mA cm−2) was achieved with this catalyst compared to the pristine graphene oxide, and the ORR limiting current was even 12%@0.5 V higher than the commercial Pt/C. The enhanced ORR activity of CoOx-Fe3O4/N-rGO was attributed to the uniform dispersion of Co, Fe, and N on reduced graphene oxide (rGO) sheets. Furthermore, ORR accelerated stress tests revealed excellent durability, suggesting that this material could be a promising and durable catalyst. With a cathode layer of the CoOx-Fe3O4/N-rGO catalyst, we achieved a peak power density of 676 mW cm−2 in an operando H2-O2 AEMFC. To the best of our knowledge, this is the highest reported power density per cathode catalyst mass in a reported PGM-free cathode catalyst. Finally, we quantified the various cell polarization losses as a function of cathode catalyst loadings to obtain insights for future work with AEMFCs based on this catalyst. The improvement in the AEMFC performance using CoOx-Fe3O4/N-rGO as a cathode catalyst can be attributed to the synergistic effects of (i) the high turnover frequency of the transition metals (Co and Fe) for ORR and (ii) the enhancement provided by N doping to the metal distribution and stability. [ABSTRACT FROM AUTHOR]

Laser cleaning is a relatively new and promising industrial cleaning method. Despite its potential as an alternative to conventional de-rusting methods, very few studies have been done on rust removal. The current study is aimed at investigating experimentally the effect of various important laser parameters on properties of surface after laser processing. Rusted mild steel samples were irradiated with moving pulsed laser beam. Parameters like scan speed, number of passes, etc. were varied and the change in properties such as surface profile, roughness, hardness, etc. of the processed surface were observed along with depth of removal. The depth of removal was found to increase with an increase in laser power, and number of scans but decreased with an increase in scan speed. The surface got discoloured and deformed at lower speeds and higher powers. The surface roughness after processing hardly showed any variation with the initial roughness values before cleaning but depended on the scanning path of the laser. The microhardness values after laser processing varied with path traced by the laser beam which points to microstructure changes in the samples due to laser processing.

Crop coefficient ([K.sub.c]) based estimation of crop evapotranspiration ([ET.sub.c]) is one of the most commonly used methods for irrigation water management. The standardized FAO56 Penman-Monteith approach for estimating [ET.sub.c] from reference evapotranspiration and tabulated generalized [K.sub.c] values has been widely adopted worldwide to estimate [ET.sub.c]. In this study, we presented a modified approach toward estimating [K.sub.c] values from remotely sensed data. The surface energy balance algorithm for land model was used for estimating the spatial distribution of [ET.sub.c] for major agronomic crops during the 2005 growing season in southcentral Nebraska. The alfalfa-based reference evapotranspiration ([ET.sub.r]) was calculated using data from multiple automatic weather stations with geostatistical analysis. The [K.sub.c] values were estimated based on [ET.sub.c] and [ET.sub.r] (i.e., [K.sub.c]=[ET.sub.c]/[ET.sub.r]). A land use map was used for sampling and profiling the [K.sub.c] values from the satellite overpass for the major crops grown in southcentral Nebraska. Finally, a regression model was developed to establish the relationship between the normalized difference vegetation index (NDVI) and the [ET.sub.r]-based crop coefficients ([K.sub.cr]) for corn, soybeans, sorghum, and alfalfa. We found that the coefficients of variation (CV) for NDVI, as well as for [K.sub.c], of crops were lower during the midseason as compared to the early and late growing seasons. High CV values during the early growing season can be attributed to differences in planting dates between the fields, whereas high CVs during the late season can be attributed to differences in maturity dates of the crops, variety, and management practices. There was a good relationship between [K.sub.cr] and NDVI for all the crops except alfalfa. Validation of the developed model for irrigated corn showed very promising results. There was a good correlation between the NDVI-estimated [K.sub.cr] and the Bowen ratio energy balance system based [K.sub.cr] with a [R.sup.2] of 0.74 and a low root mean square difference of 0.21. This approach can be a very useful tool for a large (watershed or regional) scale estimation of evapotranspiration using the crop coefficient and reference evapotranspiration approach. DOI: 10.1061/(ASCE)IR.1943-4774.0000052 CE Database subject headings: Agriculture; Evapotranspiration; Irrigation; Water management; Remote Sensing.