To this end, we developed software to systematically analyse nanomaterials synthesis methods based on established text mining protocols. We extracted structured data to describe the details of each synthesis protocol, enabling large-scale statistical analysis of the synthesis parameter space and clustering of similar methods together to identify well-explored regions of the synthesis space. We believe that this progress represents the first step in creating a closed feedback loop for the automated optimisation of experimental nanomaterials synthesis, visualised in Figure . In this feedback loop text mined information can identify common limits to parameters as well as lowdimensional sub-regions of interest in the synthesis space. By using this information as initial conditions for iterative high-throughput experimentation, the search for synthesis protocols optimised against any target material quality metric can be greatly accelerated. As a case study to demonstrate the utility of this approach, we performed a quantitative metaanalysis of 1600 synthesis methods for the common MOF ZIF-8. Using this framework, we identified key aspects of the synthesis including the range of chemicals used as reagents, solvents, and ancillary modulators/pH modifiers. We extracted information about the quantity of each reagent used during the synthesis, enabling us to identify the distribution of synthesis scales, reagent ratios, and reaction mixture solids concentration, as well as reaction times and temperatures. Further insight was gathered by cross-referencing chemicals mentioned against the stage they were introduced into the synthesis protocol -for example identifying that ethanol is primarily used as a washing solvent rather than in the reaction medium. We demonstrated how the quantitative metaanalysis performed here can assist in systematic searches of the synthesis phase space by identifying both low-dimensional regions of interest and the distribution of synthesis parameters. As a result, we were able to reduce the number of hypothetical experiments required to optimise ZIF-8 significantly. Notably, while we considered MOF materials as a case study in this work, the methods developed here are general to any synthesis type. Particularly, we envisage they will be useful the systematising understanding of other emerging nanomaterial systems such as mesoporous (organo)silicas, covalent organic frameworks, and polymers of intrinsic microporosity.