Carbon Capture and Storage (CCS) field is growing rapidly as a means to mitigate the accumulation of greenhouse gas emissions. However, the geomechanical stability of CCS systems, particularly related to bearing capacity, remains a critical challenge that requires accurate prediction models. In this research paper, we investigate the efficacy of employing an Autoregressive Deep Neural Network (ARDNN) algorithm to predict the geomechanical bearing capacity in CCS systems through shear wave velocity prediction as an index for bearing capacity evaluation of deep rock formations. The model utilizes a dataset consisting of 23,000 data points to train and test the ARDNN algorithm. Its scalability, use of deep learning techniques, automatic feature extraction, adaptability to changes in data, and versatility in various prediction tasks make it an attractive option for accurate predictions. The results demonstrate exceptional performance, as evidenced by an R-squared value of 0.9906 and a mean squared error of 0.0438 for the test data compared to the measured data. This research has significant practical implications for effectively predicting geomechanical stability in CCS systems, thus mitigating potential risks associated with their operation.

In this study, choline chloride/urea was used as a green deep eutectic solvent in the three-component reaction of hydrazine/phenylhydrazine, malononitrile, and aromatic aldehydes for synthesizing pyrazole derivatives, and in the four-component reaction of methyl/ethyl acetoacetate, hydrazine/phenylhydrazine, malononitrile, and aromatic aldehydes for synthesizing pyrano[2,3-c]pyrazole derivatives. Elemental analysis, ¹H, and ¹³C NMR spectroscopy were used to confirm the structure of the synthesized pyrazole and pyrano[2,3-c] pyrazole derivatives. The antimicrobial effects of the synthesized pyrazole and pyrano[2,3-c] pyrazole derivatives were investigated. In antimicrobial tests, instructions from clinical and laboratory standards institutes were used. Antimicrobial study was done on pathogenic gram-positive and gram-negative species, and specialized aquatic strains and fungal species. Using choline chloride/urea, novel pyrazole derivatives and pyrano[2,3-c]pyrazole derivatives were synthesized, and other derivatives were synthesized with higher efficiency in less time than some previously reported methods. MIC (minimum inhibitory concentration) and MBC (minimum bactericidal concentration) obtained for derivatives were higher than some antibiotic drugs. Synthesis and reports of new derivatives of pyrazole and pyrano[2,3-c]pyrazole, and investigation and reports of their antimicrobial properties on gram-positive, gram-negative, and specialized aquatic and fungal species are among the novel and important findings of this study.