Double transition-metal MXenes: Classification, properties, machine learning, artificial intelligence, and energy storage applications

Iftikhar Hussain; Uzair Sajjad; Onkar Jaywant Kewate; Umay Amara; Faiza Bibi; Abdul Hanan; Darshna Potphode; Muhammad Ahmad; Muhammad Sufyan Javed; P. Rosaiah; Sajjad Hussain; Karim Khan; Zeeshan Ajmal; S. Punniyakoti; Saleh S. Alarfaji; Jee-Hyun Kang; Wail Al Zoubi; Sumanta Sahoo; Kaili Zhang

doi:10.1016/j.mtphys.2024.101382

Double transition-metal MXenes: Classification, properties, machine learning, artificial intelligence, and energy storage applications

Iftikhar Hussain^*, Uzair Sajjad^*, Onkar Jaywant Kewate, Umay Amara, Faiza Bibi, Abdul Hanan, Darshna Potphode, Muhammad Ahmad, Muhammad Sufyan Javed, P. Rosaiah, Sajjad Hussain, Karim Khan, Zeeshan Ajmal, S. Punniyakoti, Saleh S. Alarfaji, Jee-Hyun Kang, Wail Al Zoubi^*, Sumanta Sahoo^*, Kaili Zhang^*

^*Corresponding author for this work

Department of Mechanical Engineering

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

48 Citations (Scopus)

Abstract

Continuous research efforts have yielded significant advancements in MXenes, particularly with the discovery of ordered double transition metal (DTM) MXenes. These DTM MXenes have expanded the MXene family by incorporating two different transition metals at the metal sites. In this review, the classification, properties, and energy storage applications of DTM MXenes have been thoroughly discussed. Additionally, the utilization of machine learning (ML) and artificial intelligence (AI) in theoretical modeling has also been studied to understand the development of DTM MXenes. Moreover, critical research directions have been outlined to pave the way for achieving high-performance DTM MXenes, not only for energy storage applications but also for broader and diverse applications in different fields. © 2024

Original language	English
Article number	101382
Number of pages	21
Journal	Materials Today Physics
Volume	42
Online published	24 Feb 2024
DOIs	https://doi.org/10.1016/j.mtphys.2024.101382
Publication status	Published - 6 Mar 2024

Funding

This work was supported by the Hong Kong Research Grants Council (project number CityU 11218420). This research was also supported by National Research Foundation (NRF) of South Korea (2022R1A2C1004392). The authors express their appreciation to the Deanship of Scientific Research at King Khalid University, Saudi Arabia, for supporting this work through research group program under grant number RGP. 2/445/44.

Research Keywords

Artificial intelligence
DTM MXenes
Energy storage
Machine learning
MXenes
Properties

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10.1016/j.mtphys.2024.101382

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Hussain, I., Sajjad, U., Kewate, O. J., Amara, U., Bibi, F., Hanan, A., Potphode, D., Ahmad, M., Javed, M. S., Rosaiah, P., Hussain, S., Khan, K., Ajmal, Z., Punniyakoti, S., Alarfaji, S. S., Kang, J.-H., Al Zoubi, W., Sahoo, S., & Zhang, K. (2024). Double transition-metal MXenes: Classification, properties, machine learning, artificial intelligence, and energy storage applications. Materials Today Physics, 42, Article 101382. https://doi.org/10.1016/j.mtphys.2024.101382

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Hussain, I, Sajjad, U, Kewate, OJ, Amara, U, Bibi, F, Hanan, A, Potphode, D, Ahmad, M, Javed, MS, Rosaiah, P, Hussain, S, Khan, K, Ajmal, Z, Punniyakoti, S, Alarfaji, SS, Kang, J-H, Al Zoubi, W, Sahoo, S & Zhang, K 2024, 'Double transition-metal MXenes: Classification, properties, machine learning, artificial intelligence, and energy storage applications', Materials Today Physics, vol. 42, 101382. https://doi.org/10.1016/j.mtphys.2024.101382

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AU - Hussain, Iftikhar

AU - Sajjad, Uzair

AU - Kewate, Onkar Jaywant

AU - Amara, Umay

AU - Bibi, Faiza

AU - Hanan, Abdul

AU - Potphode, Darshna

AU - Ahmad, Muhammad

AU - Javed, Muhammad Sufyan

AU - Rosaiah, P.

AU - Hussain, Sajjad

AU - Khan, Karim

AU - Ajmal, Zeeshan

AU - Punniyakoti, S.

AU - Alarfaji, Saleh S.

AU - Kang, Jee-Hyun

AU - Al Zoubi, Wail

AU - Sahoo, Sumanta

AU - Zhang, Kaili

PY - 2024/3/6

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AB - Continuous research efforts have yielded significant advancements in MXenes, particularly with the discovery of ordered double transition metal (DTM) MXenes. These DTM MXenes have expanded the MXene family by incorporating two different transition metals at the metal sites. In this review, the classification, properties, and energy storage applications of DTM MXenes have been thoroughly discussed. Additionally, the utilization of machine learning (ML) and artificial intelligence (AI) in theoretical modeling has also been studied to understand the development of DTM MXenes. Moreover, critical research directions have been outlined to pave the way for achieving high-performance DTM MXenes, not only for energy storage applications but also for broader and diverse applications in different fields. © 2024

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ER -

Double transition-metal MXenes: Classification, properties, machine learning, artificial intelligence, and energy storage applications

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GRF: Fabrication, Energetic and Combustion Properties of Energetic Microchip Based on In Situ Synthesized Energetic Coordination Polymer and Aluminum

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Double transition-metal MXenes: Classification, properties, machine learning, artificial intelligence, and energy storage applications

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GRF: Fabrication, Energetic and Combustion Properties of Energetic Microchip Based on In Situ Synthesized Energetic Coordination Polymer and Aluminum

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