Targeted Chemical Looping Materials Discovery by an Inverse Design

Targeted Chemical Looping Materials Discovery by an Inverse Design

Chemical looping with oxygen uncoupling (CLOU) materials is actively sought for combustion of carbonaceous materials to achieve complete conversion and capture of carbon dioxide. These materials may play a vital role in reducing atmospheric carbon via negative carbon output. However, there is no one...

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Bibliographic Details
Main Authors: Brett A. Duell, Ali Ramazani, Sittichai Natesakhawat, Eric J. Popczun, Jonathan W. Lekse, Yuhua Duan
Format: Article
Language:English
Published: Wiley 2025-04-01
Series:Advanced Intelligent Systems
Subjects:
chemical looping with oxygen uncoupling
density functional theory calculations
doped‐perovskite materials
genetic algorithm
high‐throughput inverse design
machine learning
Online Access:https://doi.org/10.1002/aisy.202401118
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Summary:Chemical looping with oxygen uncoupling (CLOU) materials is actively sought for combustion of carbonaceous materials to achieve complete conversion and capture of carbon dioxide. These materials may play a vital role in reducing atmospheric carbon via negative carbon output. However, there is no one‐size‐fits‐all approach as different operating conditions and feedstocks may require different CLOU materials. As a result, the exploration and discovery of high‐performance CLOU materials can be a slow process. To address this challenge, a high‐throughput inverse machine learning workflow that identifies optimum materials from perovskite oxides for a given set of targets is developed—temperature and Gibbs free energy of oxygen formation. The model is trained on high‐throughput density functional theory calculations of CLOU materials and inverts the materials design process using a genetic algorithm to produce realistic substituted SrFeO3‐δ compositions as output. Using the inverse model, it is able to identify several interesting new families of CLOU materials: Sr1‐xAxFe1‐yByO3‐δ (e.g., A = Ca or K; B = Mg, Bi, Mn, Ni, Co, Cu, or Zn). These materials have shown promising properties, and some of them even outperform the benchmark material in terms of oxygen release kinetics under relevant CLOU operating conditions.
ISSN:2640-4567

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