Journal of Material Science and Technology Research

Articles

Vol. 13 (2026)

An AI-Driven Roadmap for the Development of Alkali Metal-Modified BiFeO3 Multiferroics

DOI:
https://doi.org/10.31875/2410-4701.2026.13.08
Submitted
September 19, 2026
Published
2026-10-07

Abstract

Bismuth ferrite (BiFeO3) is one of the most promising single-phase multiferroic materials because it coexists with ferroelectric and antiferromagnetic ordering at room temperature. Nevertheless, it has intrinsic limitations for practical applications, including high leakage current, poor magnetization due to cycloidal spin structures, and phase instability. This review is a detailed discussion of the basic physics behind BiFeO3, its crystal structure, the origin of ferroelectricity, magnetic ordering, as well as the magnetoelectric coupling mechanism. The alkali metal (Li, Na, K, Rb, Cs) substitution is of particular interest, as it has been found to be a useful approach to design structural distortion, defect chemistry, polarization behavior, and magnetic interactions. In addition, the shortcomings of traditional experimental methods in the optimization of dopant content and processing are mentioned. To address these problems, new artificial intelligence (AI) and machine learning (ML) methods are pointed out as effective means to speed up the exploration of materials, forecast structure-property correlations, and design high-performance multiferroics. Lastly, a roadmap for the systematic creation of alkali metal-modified BiFeO3 systems is suggested, which offers perspectives on the subsequent generation of versatile materials and applications in devices.

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