Call For Papers
Smart Chemical Engineering
AI-Enabled Catalytic Engineering: From Catalyst Design to Process Optimization
Smart Chemical Engineering (SCE) is announcing a Call for Papers for the topic “AI-Enabled Catalytic Engineering: From Catalyst Design to Process Optimization”. Catalysis plays an important role in energy conversion, advanced materials manufacturing, and health-related applications, while also presenting major challenges associated with complex reaction networks, multiscale process coupling, and precise regulation. Recent advances in artificial intelligence (AI), particularly in high-dimensional data mining, complex relationship modeling, and optimization-driven decision-making, are reshaping catalyst design, mechanistic understanding, and process optimization. In this context, Smart Chemical Engineering (SCE) is pleased to announce a Call for Papers and invites submissions of high-quality contributions that highlight methodological advances and emerging applications of AI in catalytic engineering. We welcome original research articles, reviews, and perspective papers addressing theoretical developments, methodological innovation, and practical applications of AI in catalyst design, mechanistic analysis, and related process engineering. Topics of interest include, but are not limited to: AI-driven catalyst design, screening, and optimization AI-assisted mechanistic understanding and analysis of complex catalytic reaction networks AI-driven research in computational catalysis Integration of multimodal characterization and AI for catalytic spectral analysis and mechanistic studies AI-driven multi-objective optimization, process regulation, and engineering applications of catalytic systems Keywords: Artificial Intelligence, Catalytic Engineering, Catalyst Design, Mechanistic Analysis, Process Regulation Academic Editors Prof. Yuanhui Ji Affiliation: School of Chemistry and Chemical Engineering, Southeast University Prof. Jiahua Zhu Affiliation: College of Chemical Engineering, Nanjing Tech University Prof. Xiaonan Wang Affiliation: Department of Chemical Engineering, Tsinghua University Submission Details: Submission Deadline: 30 November 2026 Office Contact: sce@sciltp.com Instruction for Authors: https://www.sciltp.com/journals/sce/instructionForAuthors Submission Link: https://sciflux.org/authors/submissions/add-submissions?journalCode=1909189275485560833
Smart Chemical Engineering
Deadline: 30 Nov 2026Artificial Intelligence for Chemical Product Engineering: From Process Regulation to Product Customization
Smart Chemical Engineering (SCE) is announcing a Call for Papers for the topic “Artificial Intelligence for Chemical Product Engineering: From Process Regulation to Product Customization” . Chemical engineering has evolved from traditional chemical process engineering toward a new era that integrates process and product engineering, with the goal of precisely customizing chemical products. Artificial intelligence (AI) is deeply permeating all aspects of chemical engineering, with applications extending beyond individual unit operations (e.g., separation and reaction) to integrated processes/systems, thereby advancing optimization and regulation of processes and the targeted customization of high-performance products. Smart Chemical Engineering (SCE) hereby announces this Call for Papers, to reflect the deep integration trend between AI and chemical engineering, as well as to highlight AI’s pivotal role in driving the shift from process-oriented to product-oriented in chemical engineering. We sincerely invite scholars worldwide to contribute pioneering findings that showcase frontier advances in AI-empowered chemical product engineering. We welcome original research articles, reviews and perspectives that explore the applications and breakthroughs of machine learning and other artificial intelligence technologies in the innovation development of chemical product engineering. Topics of interest include, but are not limited to: Correlation Mechanism of "Process Conditions-Product Structure-Performance" in AI-based Chemical Product Engineering AI-driven Multi-Objective Process Optimization, Regulation, and System Integration Focusing on Product Structure and Performance AI-assisted Multi-dimensional Regulation Mechanism and Action Principle for Chemical Products Core Theories, Key Methods and Innovations Algorithms of Artificial Intelligence for Chemical Product Engineering Keywords: artificial intelligence; machine learning; chemical product engineering; chemical process engineering; fundamental mechanism Academic Editors: Prof. Zheng-Hong Luo（Shanghai Jiaotong University/ Ningxia University） Dr. Jiantao Li（Ningxia University） Dr. Jie Jin（Shanghai Jiaotong University） Submission Deadline: 30 June 2026 Office Contact: sce@sciltp.com Submission Link: https://sciflux.org/authors/submissions
Smart Chemical Engineering
Deadline: 30 Jun 2026
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