Tentative Program

This track focuses on the latest developments in nanomaterials specifically designed for catalytic applications. Researchers are invited to present their findings on the synthesis, characterization, and performance of these innovative materials.

This session explores the integration of machine learning techniques, including supervised and unsupervised learning, in chemical engineering processes. Contributions should highlight predictive modeling and data-driven methodologies for process optimization.

This track emphasizes the design principles and performance evaluation of nanoscale catalysts in various chemical reactions. Participants are encouraged to share insights on reaction engineering and the impact of nanoscale features on catalytic efficiency.

This session addresses the challenges of feature extraction and anomaly detection in complex catalytic systems. Researchers will discuss novel techniques and case studies that enhance system monitoring and model evaluation.

This track focuses on the automation of workflows in chemical engineering, emphasizing the role of smart materials and nanotechnology. Presentations should cover innovative approaches to streamline processes and improve efficiency.

This session invites contributions that utilize simulation and analytics to understand the behavior of nanomaterials in catalytic applications. Emphasis will be placed on computational methods and their practical implications in chemical engineering.