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Catalysts, artificially or naturally generated, are often considered to be important factors in numerous chemical processes. Although each catalyst can act under its own characteristics, the efficiency of chemical interactions can be enhanced by a balanced combination of different catalysts. On the other hand, many game-theoretical results have been widely applied to seek the optimal or balanced state for efficiency regulation, resource control, portfolio allocation, and behavior simulation in modern academic literature. Based on game-theoretical approaches under actual chemical and biochemical environments, this article aims to analyze, construct, simulate, and derive the most efficient optimal or balanced combinations for a group of catalysts with different conditions and actions. In this article, a power index is proposed by simultaneously focusing on the factors and its active levels. In order to analyze the accuracy and rationality of this power index, we adopt usual axioms to offer some characterizations. In conjunction with the constructed game-theoretical results that are related to chemical and biochemical environments, this article further analyzes, verifies, and demonstrates the validity, accuracy, feasibility, plausibility, and applicability of the combination of catalysts with different conditions and actions.

Sustainable Combination Mechanism for Catalysts: A Game-Theoretical Approach