研究目的
To validate if model-supported development can be applied to the synthesis of new materials, specifically CuInS2/ZnS quantum dots, and to develop a model that predicts optical properties as a function of synthesis parameters.
研究成果
The neural network model can predict the optical properties of CIS and CIS/ZnS QDs with high accuracy, serving as a development tool for designing high-performance QDs. However, its reliability is limited to the tested parameter ranges.
研究不足
The model is reliable for prediction within the tested regions but cannot extrapolate outside of this range. A wider region of interest would require further experiments.
1：Experimental Design and Method Selection:
A neural network model was established to predict the optical properties of CIS/ZnS QDs based on synthesis parameters.
2：Sample Selection and Data Sources:
A set of 94 experimental results was used, with 80% for training and 20% for validation.
3：List of Experimental Equipment and Materials:
Not explicitly mentioned.
4：Experimental Procedures and Operational Workflow:
The model was trained on parameters such as reaction temperature, time of CIS core formation and ZnS shell growth, feed molar ratio of Cu/In and Zn/Cu, various starting precursors, and types of ligands.
5：Data Analysis Methods:
The model's accuracy was assessed by comparing predicted values with experimental data, using coefficients of determination R2.
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