Jungmok Oh, Junho Lee, Jisu Park, Namgi Jeon, Gyoung S. Na, Hyunju Chang, Joonsuk Huh, Hyun Woo Kim* and Yongju Yun*,
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引用次数: 0
Abstract
Recent advances in data-driven approaches using the machine learning (ML) method have enabled the discovery of high-performance materials. This paper presents a hybrid framework that combines ML models with a metaheuristic optimization algorithm, to explore improved heterogeneous catalysts for propane dehydrogenation (PDH). The framework proposes multiple PDH catalysts, utilizing our laboratory-scale database. A unique five-component catalyst, 2.4Ga 2.2Pt 1.7B 1.3Zr/Al2O3, exhibits superior performance, achieving a propylene yield of 58% at 600 °C. This work highlights the excellent predictive capability of the framework and offers a new data-driven approach for developing high-performance materials for heterogeneous catalysis.
期刊介绍：
ACS Materials Letters is a journal that publishes high-quality and urgent papers at the forefront of fundamental and applied research in the field of materials science. It aims to bridge the gap between materials and other disciplines such as chemistry, engineering, and biology. The journal encourages multidisciplinary and innovative research that addresses global challenges. Papers submitted to ACS Materials Letters should clearly demonstrate the need for rapid disclosure of key results. The journal is interested in various areas including the design, synthesis, characterization, and evaluation of emerging materials, understanding the relationships between structure, property, and performance, as well as developing materials for applications in energy, environment, biomedical, electronics, and catalysis. The journal has a 2-year impact factor of 11.4 and is dedicated to publishing transformative materials research with fast processing times. The editors and staff of ACS Materials Letters actively participate in major scientific conferences and engage closely with readers and authors. The journal also maintains an active presence on social media to provide authors with greater visibility.
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