The impact of increasing Zr dopant concentration in Ruddlesden Popper perovskite to enhance Resistive Random-Access Memory performance: Using the DFT method
As Resistive Random- Access memory (RRAM) emerges as a promising solution for high-performance memory application, this study applies density functional theory (DFT) to analyze the structural, electronic, and optical properties of pure and Zr-doped Mg<sub>3</sub>Hf<sub>2</sub>O<sub>7</sub> at various doping concentrations (0, 0.25, 0.50, 0.75, and 1.0). The electronic analysis reveals that increasing Zr doping reduces the bandgap, thereby enhancing the conductivity of the composites. These findings highlight their potential for resistive switching memory applications. Iso-surface charge density plots revealed that the substitutional replacement of all Hf atoms by Zr atoms significantly increased the number of conducting channels, which enhanced the material's overall conductivity and increased the efficiency of non-volatile memory. Optical analysis showed that Mg<sub>3</sub>Zr<sub>2</sub>O<sub>7</sub> composite has significant conductivity and absorption over a wide range of photon energies and low reflectivity. In particular, Mg<sub>3</sub>Zr<sub>2</sub>O<sub>7</sub> exhibited the least formation energy and highest conductivity, suggesting it is the most stable composite. Mechanical properties confirm all studied materials' stability, anisotropic nature, and ductility. The analysis indicates that Mg<sub>3</sub>Zr<sub>2</sub>O<sub>7</sub> holds strong potential for Resistive Random- Access memory applications.
Authors
- Fayyaz Hussain (ORCID: https://orcid.org/0000-0002-9490-9631)
- Ammar M. Tighezza (ORCID: https://orcid.org/0000-0003-1675-8783)
- R.M. Arif Khalil (ORCID: https://orcid.org/0000-0002-1035-1598)
- Muhammad Fahad Ehsan (ORCID: https://orcid.org/0000-0002-8353-3560)
- Umbreen Rasheed
- Muhammad Imran (ORCID: https://orcid.org/0000-0003-4072-4997)
- Aqsa Arooj
Institutions
- Bahauddin Zakariya University (PK)
- Northeastern University (US)
- Daegu Gyeongbuk Institute of Science and Technology (KR)
- Government College University, Faisalabad (PK)
- King Saud University (SA)
Publication Details
- Journal
- Journal of Molecular Graphics and Modelling
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1016/j.jmgm.2025.109000
- Citations
- 2
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 1.46
Funders
- King Saud University