Welcome To KFUPM Physics

Welcome to the Department of Physics at King Fahd University of Petroleum and Minerals. I invite you to explore our website where you can find information about our academic programs, courses, research activities, and faculty members. Physics has always been at the forefront of exploration. This is accomplished through cognitive enhancement by education transmitted through academic courses as well as carrying out research at the cutting-edge frontiers of human knowledge. The Physics department offer courses that are solidly based on the American system to meet international quality assurance requirements, which has placed the Department as a world-class regional center in a leading international institution. Our student body includes pure-physics students and double-major students, which reflects the interdisciplinary nature of our program. In addition, our research facilities span various fields of physics including condensed matter physics, lasers, materials research, magnetism and superconductivity, nuclear physics, and nonlinear and computational physics. Over the past five decades, our faculty members have conducted research using in-house facilities as well as collaborative research with national and international centers.

Mohammad Al-Kuhaili,
Professor & Chairman, Physics Department

Research and Academic Activity Statistics 2021 to 2025

Average Impact Factor Publications​

87

Patents

 9442

Cumulative Citation Count​

525

Publications

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Seminar

Next-Generation Memory Technology: ReRAM Fundamentals and a Low-Cost LaXO₃ Perovskite Thin-Film Application


Speaker:
Raghad Aljurays
Regular PhD Student

Date: Monday, November 16th, 2026
Time: 11:00 to 11:30 a.m.
Location: Bldg. 6/Room 125

Abstract:
Resistive Random-Access Memory (ReRAM) is a leading next-generation non-volatile memory based on resistance switching in a simple Metal–Insulator–Metal cell. This seminar first reviews ReRAM theory. It then presents an experimental application: LaXO₃ perovskite thin films (X = Fe, Mn, Cr, Ni) synthesized by low-cost sol–gel spin coating using a self-made spin coater. Films were characterized by XRD, FESEM, UV-Vis, and VSM, and Au/LaXO₃/FTO devices were fabricated and electrically tested. All devices showed bipolar resistive switching; LaFeO₃ performed best, with an ON/OFF ratio of ~7 × 10⁵, low operating voltages (0.7 V / −1 V), and stable endurance. The work demonstrates that simple spin coating can produce high-quality perovskite RRAM devices.


Neural Networks in Many-Body Physics: The Ising Model as an Example

Speaker:
Ahmed Alotaibi
Senior
Date: Monday, November 16th, 2026
Time: 11:30 a.m. to 12:00 p.m.
Location: Bldg. 6/Room 125

Abstract:
Machine learning offers new tools for addressing complex problems across many fields of science. In theoretical physics, the exponential growth of the many-body Hilbert space makes exact calculations challenging and motivates approximation methods. This seminar introduces how neural networks can represent many-body wavefunctions and approximate ground states through variational energy minimization. After outlining the basic neural-network machinery, we illustrate the approach using the quantum Ising model and discuss its advantages and limitations.
All faculty, researchers and students are invited to attend.


    Location and Time
  • 6/125

  • 16 Nov, 2026

  • 11:00 AM - 12:00 PM