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A hybrid machine learning-genetic algorithm (ML-GA) model to predict optimal process parameters of nanoporous Cu for CO2 reduction

Materials ScienceProcess DesignChemical EngineeringNanoporous CuEngineeringSustainable Chemical ProductionEnergy EfficiencyEnergy ConversionCokingAi-based Process OptimizationOptimal Process ParametersChemistryCo2 Reduction