High‐Throughput Analysis of Materials for Chemical Looping Processes

Abstract

Chemical looping is a promising approach for improving the energy efficiency of many industrial chemical processes. However, a major limitation of modern chemical looping technologies is the lack of suitable active materials to mediate the involved subreactions. Identification of suitable materials has been historically limited by the scarcity of high-temperature (> 600 °C) thermochemical data to evaluate candidate materials. An accurate thermodynamic approach is demonstrated here to rapidly identify active materials which is applicable to a wide variety of chemical looping chemistries. Application of this analysis to chemical looping combustion correctly classifies 17/17 experimentally studied redox materials by their viability and identifies over 1,300 promising yet previously unstudied active materials. This approach is further demonstrated by analyzing redox pairs for mediating a novel chemical looping process for producing pure SO2 from raw sulfur and air which could provide a more efficient and lower emission route to sulfuric acid. 12 promising redox materials for this process are identified, two of which are supported by previous experimental studies of their individual oxidation and reduction reactions. This approach provides the necessary foundation for connecting process design with high-throughput materials discovery to accelerate the innovation and development of a wide-range of chemical looping technologies.

Computationally Accelerated Discovery and Experimental Demonstration of Gd0.5La0.5Co0.5Fe0.5O3 for Solar Thermochemical Hydrogen Production

“…With the vast composition space of inorganic materials, preliminary computational materials screening has become an important tool for accelerating materials discovery. Computational methods were previously applied to materials screening for the solid-state hydrogen storage reaction and chemical looping process (Clary et al, 2020;Singstock et al, 2020). For STCH, ternary (ABO 3 ) and quaternary (AA'BO 3 ) perovskites were explored to computationally evaluate their oxygen vacancy formation energies, electronic properties, and thermodynamic stabilities, with several promising candidate materials predicted based on these results (Emery et al, 2016;Sai Gautam et al, 2020).…”

Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS) – a state-of-the-art review

“…Figure 7 Workflow of developing a machine-learning model for oxygen carriers in chemical-looping processes 17 Singstock et al 150 proposed a statistical ML descriptor-based method to predict the reaction free energies and classify the thermodynamically viable active materials for chemical-looping processes, and the authors applied it to evaluate materials for a novel chemical looping process for pure SO 2 production. This approach is envisioned to link the process design with highthroughput material discovery to promote the development of a wide range of chemical-looping technologies 150 .…”

“…Figure 7 Workflow of developing a machine-learning model for oxygen carriers in chemical-looping processes 17 Singstock et al 150 proposed a statistical ML descriptor-based method to predict the reaction free energies and classify the thermodynamically viable active materials for chemical-looping processes, and the authors applied it to evaluate materials for a novel chemical looping process for pure SO 2 production. This approach is envisioned to link the process design with highthroughput material discovery to promote the development of a wide range of chemical-looping technologies 150 . Wilson and Sahinidis 151 proposed a mixed-integer nonlinear programming (MNLP) formulation to estimate and identify kinetic rate parameters from a postulated superset of reactions, and they validated that this approach can automatically generate accurate kinetic models from dynamic CLC process.…”

Upcycling the carbon emissions from the steel industry into chemicals using three metal oxide loops

“…As for the optimisation of metal oxides, the use of computational screening of materials could facilitate the search for the ideal metal oxides combination for the proposed technology. 20,21,[97][98][99] A demonstration of this process on a pilot scale at optimum conditions would help bring it closer to practical implementation and provide data for further determining its technical and economic viability for large scale efficient utilisation of CO 2 .…”