Optimization-based process synthesis applied to hydrogen production via ammonia decomposition

• Grant number: 25/26852-0
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: March 01, 2026
• End date: February 28, 2027
• Field of knowledge: Engineering - Chemical Engineering - Chemical Process Industries
• Principal Investigator: Rita Maria de Brito Alves
• Grantee: Leonardo Antonio Cáceres Avilez
• Supervisor: Alexander William Dowling
• Host Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Institution abroad: University of Notre Dame, United States
• Associated to the scholarship: 24/08858-9 - Ammonia decomposition for hydrogen production: Modeling, simulation, and process optimization, BP.DR

Abstract

Replacing fossil-based energy sources with clean and renewable technologies remains one of the major challenges faced by the scientific community, with hydrogen emerging as a carbon-free energy carrier with high energy density. However, its transport and storage represent key challenges for enabling this energy transition. In this context, ammonia has been recognized as a promising alternative for hydrogen transport and storage in liquid form. The feasibility of this strategy largely depends on the efficiency of the ammonia decomposition and subsequent hydrogen separation. Although several conceptual designs for ammonia-to-hydrogen processes have been reported, systematic studies identifying the optimal process configuration through rigorous technology selection are still lacking. The optimal design of the ammonia decomposition and subsequent hydrogen purification can be addressed through optimization-based process synthesis, which is more robust than traditional sequential approaches as it identifies complex interactions among process units. In this project, a multi-objective superstructure optimization will be formulated as a mixed-integer nonlinear programming (MINLP) problem, integrating different ammonia decomposition reactor technologies and hydrogen purification methods. The multi-objective optimization will consider techno-economic and environmental performance criteria. Deterministic optimization will be complemented by stochastic programming to evaluate the influence of exogenous uncertainties such as market prices, hydrogen demand, and utilities prices. The results of this work are expected to support the design of industrial ammonia decomposition processes, which may also provide a foundation for the optimum design of other chemical processes. (AU)