Data and code related to the manuscript "Towards a predictive understanding of direct ink writing of graphene-based inks"

In the work related to this dataset, we demonstrated the feasibility of high-resolution direct ink writing of platelet-based inks on the example of graphene nanoplatelets. We developed a workflow for the combined optimization of ink rheology and printing process parameters to gain a predictive understanding of filament quality and morphology. Design of experiments was used to design the data collection and analysis steps, with most of the study performed in the form of several Central Composite Designs (CCDs). This dataset includes the experimental data obtained with a rheometer, grind gauge, 3D profilometer and multimeter and the corresponding processing scripts (Python and Matlab) and processed data. This dataset also includes python scripts for the statistical analysis of the Central Composite Designs. It also includes G-code files with the printer commands to reproduce our print designs and print settings.

本数据集相关研究以石墨烯纳米片（graphene nanoplatelets）为示例，验证了片基油墨（platelet-based inks）的高分辨率直接墨水书写（direct ink writing）可行性。我们构建了一套用于油墨流变学与打印工艺参数联合优化的工作流程，以实现对丝材质量与形貌的预测性认知。研究采用实验设计（Design of Experiments）规划数据采集与分析步骤，绝大多数研究环节通过若干中心复合设计（Central Composite Designs, CCDs）完成。本数据集包含通过流变仪、刮板细度计、三维形貌仪与万用表获取的实验数据，配套的处理脚本（Python与Matlab语言）以及处理后的数据。此外，本数据集还包含用于中心复合设计统计分析的Python脚本。同时，数据集还包含带有打印机指令的G代码（G-code）文件，可用于复现本研究的打印设计方案与打印参数设置。