In this study, we applied text mining to the problem of synthesis methodology optimisation, exploring to what extent the previously accumulated collective knowledge of a particular nanomaterial can accelerate the development of reliable and scalable synthesis protocols. As the first step toward this objective, in this study, we posed three research questions: first, is it possible to use text mining tools to provide deep insight into a single synthetic target, rather than a comprehensive overview of a family of materials? Second, is it possible to standardise the synthesis details extracted as a means of performing like-for-like comparison between different studies? Finally, is it possible to use this analysis to suggest optimal synthesis conditions, thereby accelerating methodology development?