Journal Article

Targeted Chemical Looping Materials Discovery by an Inverse Design

Natesakhawat, Sittichai, Ramazani, Ali, Popczun, Eric J., Duell, Brett A., Lekse, Jonathan W., Duan, Yuhua

2025

Overview

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. Taking the calculated Gibbs free energy of oxygen vacancy formation as inputs, an inverse high‐throughput machine learning workflow is developed to predict chemical formula of perovskite for chemical looping applications. Using this generic algorithm model, several new families of perovskites are identified as useful oxygen carrier materials. Particularly, a predicted new high‐performance oxygen carrier material, Sr0.89K0.11Fe0.80Zn0.20O3‐δ, is experimentally verified.

• Publisher: John Wiley & Sons, Inc,Wiley
• Subject: Carbon dioxide / Carbon sequestration / Carbonaceous materials / chemical looping with oxygen uncoupling / Datasets / Density functional theory / density functional theory calculations / doped-perovskite materials / Emissions / Energy / Fluidized bed combustion / genetic algorithm / Genetic algorithms / Gibbs free energy / high-throughput inverse design / Inverse design / Investigations / Machine learning / materials design / Materials science / Metals / Oxygen / oxygen carrier / Perovskites / Temperature / Workflow