Household mixed plastic waste derived adsorbents for CO2 capture: A feasibility study.

The feasibility of producing activated carbon (AC) from real Household Mixed Plastic Waste (HMPW) comprising of LDPE, HDPE, PP, PS, and PET for carbon capture via direct carbonisation followed by microwave-assisted or conventional thermally assisted chemical activation was investigated. A microwave-assisted activation procedure was adopted to assess the impact on the CO2 capture capacity of the resulting AC using both a lower temperature (400 °C vs. 700 °C) and a shorter duration (5 vs. 120 mins) than that required for conventional activation. The results obtained showed that the AC yield was 71 and 78% for the conventional and microwave-assisted samples, respectively. Microwave activation consumed five-fold less energy (0.19 kWh) than the conventional activation (0.98 kWh). Thermal stability results indicated total weight loss of 10.0 and 8.3 wt%, respectively, for conventional and microwave-activated samples over the temperature range of 25-1000 °C, with ACs from both activation routes displaying a type 1 nitrogen isotherm. The dynamic CO2 uptake capacity at 1 bar and 25 °C was 1.53 mmol/g, with maximum equilibrium uptake ranging between 1.32 and 2.39 mmol/g at temperatures (0-50 °C) and 1 bar for the conventionally activated AC. The analogous microwave-activated sample showed a higher dynamic CO2 uptake of 1.62 mmol/g and equilibrium uptake in the range 1.58-2.88 mmol/g under equivalent conditions. The results therefore indicate that microwave activation results in enhanced carbon capture potential. To the best of our knowledge, this is the first-time microwave heating has been employed to convert household mixed plastic wastes directly into ACs for carbon capture applications. This report therefore demonstrates that the management of mixed plastics could lead to the development of a circular economy through the conversion of waste into value-added materials.

A hybrid computational framework for intelligent inter-continent SARS-CoV-2 sub-strains characterization and prediction.

Whereas accelerated attention beclouded early stages of the coronavirus spread, knowledge of actual pathogenicity and origin of possible sub-strains remained unclear. By harvesting the Global initiative on Sharing All Influenza Data (GISAID) database ( https://www.gisaid.org/ ), between December 2019 and January 15, 2021, a total of 8864 human SARS-CoV-2 complete genome sequences processed by gender, across 6 continents (88 countries) of the world, Antarctica exempt, were analyzed. We hypothesized that data speak for itself and can discern true and explainable patterns of the disease. Identical genome diversity and pattern correlates analysis performed using a hybrid of biotechnology and machine learning methods corroborate the emergence of inter- and intra- SARS-CoV-2 sub-strains transmission and sustain an increase in sub-strains within the various continents, with nucleotide mutations dynamically varying between individuals in close association with the virus as it adapts to its host/environment. Interestingly, some viral sub-strain patterns progressively transformed into new sub-strain clusters indicating varying amino acid, and strong nucleotide association derived from same lineage. A novel cognitive approach to knowledge mining helped the discovery of transmission routes and seamless contact tracing protocol. Our classification results were better than state-of-the-art methods, indicating a more robust system for predicting emerging or new viral sub-strain(s). The results therefore offer explanations for the growing concerns about the virus and its next wave(s). A future direction of this work is a defuzzification of confusable pattern clusters for precise intra-country SARS-CoV-2 sub-strains analytics.