Dr. Yakubu Wudil obtained his Ph.D. in physics from King Fahd University of Petroleum and Minerals, Saudi Arabia where he bagged his master’s degree with distinction. He obtained his bachelor’s degree in physics from Bayero University, Kano, where he won the vice chancellors prize for the overall best graduating student of the university at the 30th combined convocation of 2010/2011 and 2011/2012 sessions. He has won several local and international scholarships and research grants including the Federal government merit scholarship, KFUPM MSc and PhD scholarships, King Abdullah City for atomic and renewable energy grant 2019, University of Florida Ph.D. scholarship, Virginia Tech Ph.D. scholarship, Univ of Connecticut Ph.D. scholarship, and many others. He has published in several international journals of high repute.
He is a resourceful physics lecturer at the Federal University Dutse, Nigeria, with track-record of instructing students on the theories and applications of physics. He is passionate to inspire students to employ critical-thinking when approaching physics problems by relating issues to the physical world.
Dr. Wudil is a well-informed researcher with interests in the production of clean and sustainable energy based on the thermoelectric conversion of industrial waste-heat to electricity using nanostructured materials, development of cooling systems based on Peltier applications, photocatalytic water decontamination, oil-water separation, water splitting and pulsed laser deposition (PLD) of thin-film coatings for different applications such as gas sensing and dust-repellant surfaces. He also investigates the structural, electronic and magnetic properties of ferrites as well as thermoelectric properties of Heusler materials using the density functional theory (DFT) as enshrined in quantum espresso simulation package, followed by Postprocessing by solving the Boltzmann transport equations as encoded in BoltzTrap2. Furthermore, he employed the Gromacs simulation tool to study the miscibility of water and hydrocarbons for efficient separation of mixtures in petrochemical industries. Moreover, he uses robust machine learning techniques to solve different physical problems.