For AuNR size determination, we investigated the dataset using a fixed synthesis protocol with the most reproduced set of precursors. This revealed a very weak trend (Fig. ), which may not be immediately exploitable. However, this general trend obtained from literature data is more robust against human factors and also encompasses a wider range of factor levels for each precursor, compared to existing OVAT studies. We also identified the challenges of this large data analysis by consolidating data from multiple sources in the literature. First is a bias in popularity. As shown in Table , most of the extracted recipes were nanorod synthesis, in which the majority of them used a precursor set from Nikoobakht and El-Sayed. The second challenge is the lack of negative data, i.e. synthesis with lower shape selectivity. As shown in Figure and Supplementary Figure , there are regions yet to be filled with data points for exploration or to confirm a low shape yield. Overall, we believe that expanding on the Design of Experiments (DoE) studies including Burrows et al., can pinpoint potential opportunities in extended exploration and exploitation within synthesis space. However, in the absence of controlled studies, this dataset can serve as a current map for known procedures.