| About this Abstract |
| Meeting |
2025 TMS Annual Meeting & Exhibition
|
| Symposium
|
Innovations in Energy Materials: Unveiling Future Possibilities of Computational Modelling and Atomically Controlled Experiments
|
| Presentation Title |
Exploring Ultra-Stable Green Rust Compositions for Green Energy Catalysis |
| Author(s) |
Mohammad Hussein Naseef Al Assadi |
| On-Site Speaker (Planned) |
Mohammad Hussein Naseef Al Assadi |
| Abstract Scope |
Green rust is a mixed-valent iron mineral and structurally constitutes a family of layered double hydroxides in which the interlayer space is intercalated with molecules and radicals such as carbonate, sulfonate, lactate, and water. Green rust has excellent potential as a catalyst and catalyst support in green energy production. However, green rust often suffers instability compared to other iron oxides with higher oxidation states, limiting its applications. Here, using quenched molecular dynamics simulation based on ab initio techniques, we scan hundreds of possible green rust candidates (with various intercalants), searching for ultra-stable green rust compositions. The data produced here are also used as a training set for developing machine learning algorithms for identifying layered double hydroxides based on cobalt and nickel. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Computational Materials Science & Engineering, Machine Learning, Energy Conversion and Storage |