Manawwer Alam Source Confirmed

OverviewAI-generated summary

Manawwer Alam's research investigates the application of computational methods, including artificial neural networks and density functional theory (DFT), to predict material properties and behaviors. His work explores areas such as the surface tension of deep eutectic solvents, CO2 capture capabilities of these solvents, and the potential of perovskite hydride materials for hydrogen storage. Alam has also studied the photocatalytic performance of hybrid nanocomposites, the corrosion inhibition of copper by amino acids, and the effects of nanoparticles on epoxy coatings. Furthermore, his research includes investigating the adsorption of heavy metals from aqueous solutions, such as Cr(III) from Algerian kaolinite clay.

With a substantial publication record, Alam has authored 315 publications and garnered over 7,000 citations, reflected in his h-index of 43. He is recognized as a highly cited researcher. His recent work demonstrates a continued engagement with advanced computational techniques and materials science, with publications spanning topics from theoretical predictions of novel materials to experimental investigations of environmental remediation and material performance.

Metrics

• h-index: 43
• Publications: 315
• Citations: 7,088