Data-driven discovery of novel metal organic frameworks with superior ammonia adsorption capacity

• Published in: Materials today advances Vol. 23; p. 100510
• Main Authors: Kim, Sanghyun, Lee, Joo-Hyoung
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2024; Elsevier
• Subjects: Ammonia capture; Grand canonical Monte Carlo; Machine learning; Metal organic framework; Metal organic framework; Ammonia capture; Grand canonical Monte Carlo; Machine learning

Ammonia (NH3) has been a subject of great interest due to its important roles in diverse technological applications. However, high toxicity and corrosiveness of NH3 has made it an important task to develop an efficient carrier to safely capture NH3 with high capacity. Here, we employ a machine learn...