The study investigates the competition between mononuclear and binuclear copper sites in various zeolite topologies, focusing on CHA, MOR, BEA, AFX, and FER zeolites. Using interatomic potentials, quantum chemical calculations, and Monte Carlo simulations, the researchers develop predictive models to understand the speciation and nuclearity of Cu cations under different conditions. The models rationalize experimental observations, including differences in nuclearity populations, structural variations, and methanol yields per Cu. Key findings include: 1. **Topological and Al-Siting Influences**: The topology of the zeolite and the distribution of aluminum sites (Al-siting) significantly affect the population of binuclear Cu sites. MOR zeolites, with their biased Al-siting, have a higher population of binuclear Cu sites compared to CHA and BEA zeolites. 2. **Temperature Effects**: The temperature dependence of Cu speciation is explored, showing that the transition from monomeric to dimeric Cu species occurs at higher temperatures in MOR than in CHA. 3. **Nonrandom Al Distributions**: The impact of nonrandom aluminum distributions on Cu speciation is examined, revealing that biased Al distributions can significantly alter the population of dimeric Cu sites. 4. **Geometric Features of Z2Cu2O Dimers**: The geometric features of Z2Cu2O dimers, such as Cu–O–Cu angles and Cu–Cu distances, are analyzed, providing insights into their role in catalytic activity. 5. **Correlation with Methanol Yields**: The predicted total dimer fractions are correlated with experimentally reported methanol yields, suggesting that the equilibrium population of higher nuclearity Cu species influences the maximum achievable methanol yields. 6. **Classification of Zeolite Topologies**: A machine learning model is used to classify zeolite topologies based on their preference for mononuclear or binuclear Cu sites, identifying zeolites with strong preferences for either type of Cu site. The study highlights the importance of zeolite topology and Al-siting in determining the nuclearity of Cu sites, which is crucial for understanding and optimizing the catalytic performance of metal-exchanged zeolites in various applications, such as automotive emissions control and partial methane oxidation.The study investigates the competition between mononuclear and binuclear copper sites in various zeolite topologies, focusing on CHA, MOR, BEA, AFX, and FER zeolites. Using interatomic potentials, quantum chemical calculations, and Monte Carlo simulations, the researchers develop predictive models to understand the speciation and nuclearity of Cu cations under different conditions. The models rationalize experimental observations, including differences in nuclearity populations, structural variations, and methanol yields per Cu. Key findings include: 1. **Topological and Al-Siting Influences**: The topology of the zeolite and the distribution of aluminum sites (Al-siting) significantly affect the population of binuclear Cu sites. MOR zeolites, with their biased Al-siting, have a higher population of binuclear Cu sites compared to CHA and BEA zeolites. 2. **Temperature Effects**: The temperature dependence of Cu speciation is explored, showing that the transition from monomeric to dimeric Cu species occurs at higher temperatures in MOR than in CHA. 3. **Nonrandom Al Distributions**: The impact of nonrandom aluminum distributions on Cu speciation is examined, revealing that biased Al distributions can significantly alter the population of dimeric Cu sites. 4. **Geometric Features of Z2Cu2O Dimers**: The geometric features of Z2Cu2O dimers, such as Cu–O–Cu angles and Cu–Cu distances, are analyzed, providing insights into their role in catalytic activity. 5. **Correlation with Methanol Yields**: The predicted total dimer fractions are correlated with experimentally reported methanol yields, suggesting that the equilibrium population of higher nuclearity Cu species influences the maximum achievable methanol yields. 6. **Classification of Zeolite Topologies**: A machine learning model is used to classify zeolite topologies based on their preference for mononuclear or binuclear Cu sites, identifying zeolites with strong preferences for either type of Cu site. The study highlights the importance of zeolite topology and Al-siting in determining the nuclearity of Cu sites, which is crucial for understanding and optimizing the catalytic performance of metal-exchanged zeolites in various applications, such as automotive emissions control and partial methane oxidation.