Home /Research /Metal-organic frameworks: Role of artificial intelligence and machine learning algorithms for efficient discovery, design, synthesis and prediction of CO2 capture capacity - A state of art review

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Metal-organic frameworks: Role of artificial intelligence and machine learning algorithms for efficient discovery, design, synthesis and prediction of CO2 capture capacity - A state of art review

Aayzaz Ahmed, Mirza Aamish Hassan Khan, George Uwadiegwu Alaneme, Tariq Ali, Muhammad Zeeshan Qureshi, Ayed Eid Alluqmani, Ali Ajwad

Year: 2026
Citations: 9

Keywords

ScalabilityStability (learning theory)Support vector machineFeature (linguistics)Key (lock)State (computer science)

Metal-organic frameworks: Role of artificial intelligence and machine learning algorithms for efficient discovery, design, synthesis and prediction of CO2 capture capacity - A state of art review

Keywords

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