Statistical Framework for Multiresponse Analyses: Comparative Assessment of Surface Activation Strategies for 3D-Printed Carbon Black/Polylactic Acid Electrodes toward Electrochemical (Bio)Sensing Applications.

Additive manufacturing using conductive polymeric filaments offers a powerful strategy for fabricating electrochemical (bio)-sensors. However, the insulating polymer matrix often limits electron transfer, demanding surface activation to expose conductive fillers and enhance electrochemical performance. Even electrodes made from bespoke filaments may demand activation. While some reagent-free treatments may require automation or careful process control to minimize operator-dependent variability, and biological treatments may involve longer processing times, chemical and electrochemical activations have provided promising results. Yet, the absence of standardized, statistically validated protocols can lead to unnecessarily complex or costly procedures, as optimal treatments are often selected based on isolated electrochemical metrics rather than on a comprehensive statistical assessment. To address this gap, the present work introduces a statistical framework for multiresponse comparison, applicable to any experimental system requiring simultaneous evaluation of multiple variables, and demonstrates its use through a case study on 3D-printed carbon black/polylactic acid (CB/PLA) electrodes fabricated via fused deposition modeling (FDM). Electrodes subjected to chemical, electrochemical, and combined activations were evaluated using the [Fe-(CN)