Vol 14 Issue 1 April 2026-September 2026

Abstract: The global transition toward renewable energy has placed unprecedented pressure on the photovoltaic (PV) community to discover new solar absorber materials that are efficient, stable, non-toxic and scalable. Traditional Edisonian screening and even Density Functional Theory (DFT) high-throughput calculations remain computationally expensive, often requiring 10⁴–10⁶ CPU-hours to survey modest chemical spaces. This paper presents a Master's-level review and technical analysis of how machine learning (ML) models trained on established DFT databases—including the Materials Project, OQMD, AFLOW and JARVIS-DFT—are transforming the discovery pipeline for next-generation solar cell materials. We focus on two properties central to PV performance: the electronic bandgap (E_g) and thermodynamic/structural stability expressed through the formation energy (E_form) and energy above the convex hull (E_hull). Random Forest, Gradient Boosted Regression, Kernel Ridge Regression, and Graph Neural Networks such as CGCNN and MEGNet are compared with respect to mean absolute error, training cost and transferability. On benchmark datasets, modern GNNs achieve bandgap MAEs of 0.28–0.32 eV and formation energy MAEs below 30 meV/atom, enabling the screening of more than 10⁵ candidate structures in minutes. Applications to halide perovskites, chalcogenides and vehicle-integrated PV (VIPV) are highlighted, along with current limitations involving dataset bias, interpretability and experimental validation loops.

Keywords:  Bandgap prediction, Crystal structure stability, Density Functional Theory, Machine learning, Materials discovery, Photovoltaics, Solar cells.

Title: Accelerating Solar Cell Material Discovery Using Machine Learning Models Trained on DFT Databases for Bandgap Prediction and Crystal Structure Stability

Author: Eng. Nawaf F DH Almutairi, Eng. Ali Mejbel Aljadei

International Journal of Mathematics and Physical Sciences Research  

ISSN 2348-5736 (Online)

Vol. 14, Issue 1, April 2026 - September 2026

Page No: 11-18

Research Publish Journals

Website: www.researchpublish.com

Published Date: 21-April-2026

Abstract: In order to formulate atomic physics, which first formulates the theory of hydrogen, we must find the true units of the quantities of physics (kg, volts, etc.), and then proceed to describe the structure and forms of the atom. I have published many papers on atomic physics, but here, which is noticeable, it respects views such as Bohr's and is based on experiments such as electrolysis, the mass spectrograph, of the Millikan experiment, and Thompson. Since the units are corrected, it follows that the experimental results need to be corrected.

Of course, knowledge is used from the papers I published in the journal Mathematics, where I prove that the acceleration of gravity is half of what has been accepted. At the same time, I demonstrated centripetal velocity, but also centripetal acceleration, which differs by one constant, from the acceptable one.

We are led to the fact that matter is infinitely divisible, a principle of Anaxagoras. We are led to formulate the nature of electric charge, the essence of matter and the nature of gravitons. Thus lies the experiment of detecting the gravitons of the earth and the experiment devised to confirm them.

Keywords: formulate atomic physics, hydrogen, Artificial Gravity and Antigravity.

Title: ATOMIC PHYSICS UNDER EXPERIMENTS AND ARTIFICIAL GRAVITY AND ANTIGRAVITY

Author: ALEKOS CHARALAMBOPOULOS

International Journal of Mathematics and Physical Sciences Research  

ISSN 2348-5736 (Online)

Vol. 14, Issue 1, April 2026 - September 2026

Page No: 1-10

Research Publish Journals

Website: www.researchpublish.com

Published Date: 08-April-2026