StFX Scholar (St. Francis Xavier University)
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Plasmonic photocatalysis for sustainable phenol production
No full textPhenols are widely used across medicinal and pharmaceutical chemistry as antioxidants, anti-allergic and anti-cancer agents, to name a few. Previous methods for synthesising phenols, such as hydrolysis of arene diazonium salts and Hock’s process, involve harsh reaction conditions and highly reactive chemicals in activating the aryl halide precursor, which is unfavorable from an environmental perspective. One alternative over these more traditional routes is using lightactivated pathways, or photocatalysis, to afford a more efficient and selective process. Phenylboronic acids (PBA) as possible phenol precursors are considered advantageous compared to more traditional diazonium and peroxide reagents given their improved environmental compatibility and diminished hazards compared with traditional methods. Work by Pitre and colleagues has illustrated efficient oxidative hydroxylation of PBA to phenol using a methylene blue dye sensitizer activated by visible light for 7 hours.¹ Copper nanoparticles supported on triazine covalent organic polymers have also shown success in converting PBA to phenol in as little as 10 min.² In these examples, materials were used to respond to lower energy blue light, but issues remain regarding lengthy time requirements (for reaction or catalyst preparation) or limited recyclability of the catalysts. The proposed research will build on this prior, established work of synthesizing phenols from PBA using blue light, but will aim to optimize the reaction/catalyst preparation time, as well as catalyst recyclability using cuprous oxide (Cu₂O) nanoparticle doped metal oxides as photocatalysts. Here, Cu₂O will respond to blue light, and the use of this solid photocatalyst may improve recyclability and, therefore, decreased chemical waste associated with this process
Regional Climate under SSP245 and SSP585
No full textAtlantic Canada and Nova Scotia currently do not have established regional climate models, which presents a gap in localized climate projections. We use the Weather Research and Forecasting model for a regional climate simulation. We seek to establish a robust repository of future climate projections for the region, that include the influence of northern ice coverage from the Labrador Sea and Ungava Bay, and sea surface temperatures. The simulation is bounded by a Bias-Corrected ensemble of 18 CMIP6 General Circulation Models that offer better quality boundaries conditions than the individual CMIP6 models in terms of the climatological mean, interannual variance and extreme events. The simulation extends from a historical period from 1980 to 2014 and two future scenarios (SSP245 and SSP585) from 2015 to 2100. The finest resolution at 3 km by 3 km cover an area of approximately 561 kilometers by 462 kilometers around the province of Nova Scotia, Canada. The temporal resolution in WRF is set at 180 seconds, with boundary conditions updated every 6 hours, yielding output at a 6-hour time step for all WRF variables. To validate the historical simulation, we use reanalysis data from ECMWF and observations from Environment and Climate Change Canada (ECCC). The evaluation includes both spatial and temporal analyses, as well as the assessment of distributions, to ensure the model accurately represents climate patterns across regions, time scales, and value ranges. We identified differences across regions, resolutions, and extreme values. There is no clear increasing in precipitation trend in Nova Scotia domain. However, extreme events show a significant rise in both frequency and intensity. Also, WRF projects that Atlantic Canada is warming faster overall. These findings provide valuable insights into the model performance and variability, and highlight areas for potential refinement for our projections scenarios. Analyses of the future (2015-2100) simulations are focused on estimating future precipitation (convective permitting), and surface air temperature (T2) extreme events
