COVID-19 impact on wind and solar energy sector and cost of energy prediction based on machine learning.

This study examines the impact of the COVID-19 pandemic on renewable energy sectors across seven countries through techno-economic analysis and machine learning (ML). In China, the renewable fraction decreased in grid-connected systems due to 14.6 % higher diesel fuel prices. They reduced grid electricity prices, with Cost of Energy (COE) reductions driven by a 2.8 % inflation decrease and a 3 % discount rate cut. The increase in renewable energy adoption in the USA during the pandemic was driven by decreased initial and operational costs of renewable components, a significant rise in diesel fuel prices, and government policy changes, despite a reduction in renewable energy sell-back prices and rising capital and annual costs due to expanded renewable capacity. Canada noted a shift to standalone systems with 50 % lower PV sell-back prices, 2 % lower WT prices, and a 48 % fuel cost rise, reducing COE except in grid/WT scenarios. Germany managed rising electricity and fuel costs, decreasing COE despite inflation. India expanded standalone HRESs driven by a sevenfold PV capacity increase, lowering COE. Japan saw stable COE with minimal variation. Iran faced economic challenges with a 104 % inflation increase, impacting COE despite a grid-connected COE decrease. Machine learning forecasts suggest that COVID-19 may cause an increase in COE in China and India due to pandemic effects.

Magnetically purification/immobilization of poly histidine-tagged proteins by PEGylated magnetic graphene oxide nanocomposites.

Carbon-based nanomaterials have many applications in biomedicine due to their unique mechanical, chemical, and biological properties. Among them, graphene has received special attention due to its very high specific surface area, high flexibility, and chemical stability. In this study, graphene oxide was first functionalized with amine groups (GO-NH2) and then Fe3O4 nanoparticles were deposited on it using the hydrothermal method. In addition, polyethylene glycol (PEG) was attached to the magnetic graphene nanoparticles to increase their stability and solubility. Finally, PEGylated magnetic graphene nanocomposites were functionalized with nickel-nitrilotriacetic acid (NTA-Ni+2) to bind to the poly-histidine tag in recombinant proteins. The resulting nanocomposites (MG-PEG-NTA-Ni+2) were then used for magnetic immobilization and purification of recombinant ß-NGF as a protein with his-tag sequence. Binding and purification were confirmed by FTIR and SDS-PAGE techniques, respectively. Importantly, differentiation of the PC12 cell line into neurons demonstrated that the purified ß-NGF was fully functional. Our results suggest that MG-PEG-NTA-Ni+2 nanocomposites may be a suitable alternative to commercial resins for rapid and specific protein immobilization and purification.