78 citations · 279 across the 12 of their papers we have counts for
13 papers
Extending Shannon's Ionic Radii Database Using Machine Learning
Ahmer A. B. Baloch, Saad M. Alqahtani, Faisal Mumtaz +3
In computational material design, ionic radius is one of the most important physical parameters used to predict material properties. Motivated by the progress in computational mate…
Direct Scheme Calculation of the Kinetic Energy Functional Derivative Using Machine Learning
H. Saidaoui, S. Kais, S. Rashkeev +1
We report a direct scheme calculation of kinetic energy functional derivative using Machine Learning. Support Vector Regression and Kernel Ridge Regression techniques were independ…
An Efficient Descriptor Model for Designing Materials for Solar Cells
Fahhad H Alharbi, Sergey N Rashkeev, Fedwa El-Mellouhi +3
An efficient descriptor model for fast screening of potential materials for solar cell applications is presented. It works for both excitonic and non-excitonic solar cells material…
Hydrogen Bonding: A Mechanism for Tuning Electronic and Optical Properties of Hybrid Organic-Inorganic Frameworks
Fedwa El-Mellouhi, El Tayeb Bentria, Asma Marzouk +3
Here we demonstrate that significant progress in this area may be achieved by introducing structural elements that form hydrogen bonds with environment. Considering several example…
Enhancing Intrinsic Stability of Hybrid Perovskite Solar Cell by Strong, yet Balanced, Electronic Coupling
Fedwa El-Mellouhi, El Tayeb Bentria, Sergey N Rashkeev +2
In the past few years, the meteoric development of hybrid organic--inorganic perovskite solar cells (PSC) astonished the community. The efficiency has already reached the level nee…
Domain Walls Conductivity in Hybrid Organometallic Perovskites: The Key of CH3NH3PbI3 Solar Cell High Performance
Sergey N. Rashkeev, Fedwa El-Mellouhi, Sabre Kais +1
The past several years has witnessed a surge of interest in organometallic trihalide perovskites, which are at the heart of the new generation of solid-state solar cells. Here, we…