Photovoltaic performance of MOF-derived transition metal doped titania-based photoanodes for DSSCs.

The enduring effort toward stabilizing and improving the efficiency of dye-sensitized solar cells (DSSCs) has stirred the solar research community to follow innovative approaches. Current research centered on electrode materials design, which improves photoanodes' light-harvesting efficiency (LHE). Metal-Organic Frameworks (MOFs) are a new family of materials that can be used as competent materials due to their desirable qualities, including high porosity, flexible synthesis methodology, high thermal and chemical stability, and good light-harvesting capabilities. MOF-derived porous photoanodes can effectively adsorb dye molecules and improve LHE, resulting in high power conversion efficiency (PCE). Doping is a prospective methodology to tune the bandgap and broaden spectral absorption. Hence, a novel and cost-effective synthesis of high surface area transition metal (TM) doped TiO2 nanocrystals (NCs) via the metal-organic framework route for DSSCs is reported here. Among the TM dopants (i.e., Mn, Fe, Ni), a remarkable PCE of 7.03% was obtained for nickel-doped samples with increased Jsc (14.66 mA/cm2) due to the bandgap narrowing and porous morphology of TiO2. The findings were further confirmed using electrochemical impedance spectroscopy (EIS) and dye-desorption experiments. The present study expedites a promising way to enhance the LHE for many innovative optoelectronic devices.

Coronavirus COVID-19 outbreak and control: Effect of temperature, relative humidity, and lockdown implementation.

Meteorological parameters are important factors that have an influence on infectious diseases. The present study aimed to explore the correlation between the spread of COVID-19, temperature, and relative humidity. The effect of human-imposed control parameters in the form of lockdown on the dissipation of COVID-19 was also analysed. Data were collected on the three study variables - temperature, relative humidity, and lockdown period - from nine of the most infected cities worldwide as well as information on changes in the number of COVID-19 patients from the beginning to a specific point in the lockdown period. A generalised regression model was applied to explore the effect of temperature and relative humidity on the change in daily new cases of COVID-19. The regression analysis did not find any significant correlation between temperature, humidity, and change in number of COVID-19 cases. Analysis of the cities with wide-ranging temperature variations showed a negative correlation of COVID-19 transmission (P=0.079) with temperature, but a relatively non-significant correlation with relative humidity (P=0.198). The number of total deaths was also higher in low-temperature countries compared with high-temperature countries. The specific growth rate in COVID-19 cases was decreased by more than 66% after implementation of a lockdown. This growth rate was exponentially decreased over time through the proper implementation of lockdown. Analysis of the real-case scenario and application of predictive models showed that for New York, Lombardy, and Madrid more than 120 days of strict lockdown was required for complete control of the transmission of COVID-19.