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        <datestamp>2026-09-25T16:37:39Z</datestamp>
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        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Statistical Framework
for Multiresponse Analyses:
Comparative Assessment of Surface Activation Strategies for 3D-Printed
Carbon Black/Polylactic Acid Electrodes toward Electrochemical (Bio)Sensing
Applications</dc:title>
          <dc:creator>Leonan dos Santos Rodrigues (25111015)</dc:creator>
          <dc:creator>Guilherme Sales da Rocha (25111018)</dc:creator>
          <dc:creator>Franccesca Fornasier (8430291)</dc:creator>
          <dc:creator>Andresa Viana Ramos (25111021)</dc:creator>
          <dc:creator>Elton Jorge da
Rocha Rodrigues (25111024)</dc:creator>
          <dc:creator>José Carlos
Costa da Silva Pinto (21773114)</dc:creator>
          <dc:creator>João Victor Nicolini (25111027)</dc:creator>
          <dc:creator>Helen Conceição Ferraz (23673461)</dc:creator>
          <dc:subject>Biochemistry</dc:subject>
          <dc:subject>Space Science</dc:subject>
          <dc:subject>Medicine</dc:subject>
          <dc:subject>Pharmacology</dc:subject>
          <dc:subject>Biotechnology</dc:subject>
          <dc:subject>Environmental Sciences not elsewhere classified</dc:subject>
          <dc:subject>Chemical Sciences not elsewhere classified</dc:subject>
          <dc:subject>Sociology</dc:subject>
          <dc:subject>Biological Sciences not elsewhere classified</dc:subject>
          <dc:subject>surface activation strategies</dc:subject>
          <dc:subject>statistically validated protocols</dc:subject>
          <dc:subject>provided promising results</dc:subject>
          <dc:subject>often selected based</dc:subject>
          <dc:subject>including filament development</dc:subject>
          <dc:subject>expose conductive fillers</dc:subject>
          <dc:subject>effective activation route</dc:subject>
          <dc:subject>demanding surface activation</dc:subject>
          <dc:subject>careful process control</dc:subject>
          <dc:subject>adjusted score (&lt;</dc:subject>
          <dc:subject>printed carbon black</dc:subject>
          <dc:subject>present work introduces</dc:subject>
          <dc:subject>cn )&lt; sub</dc:subject>
          <dc:subject>alkaline treatments proved</dc:subject>
          <dc:subject>1 mol l</dc:subject>
          <dc:subject>even electrodes made</dc:subject>
          <dc:subject>peak current ratio</dc:subject>
          <dc:subject>anodic peak current</dc:subject>
          <dc:subject>subsequent electrochemical activation</dc:subject>
          <dc:subject>enhance electrochemical performance</dc:subject>
          <dc:subject>versatile statistical framework</dc:subject>
          <dc:subject>comprehensive statistical assessment</dc:subject>
          <dc:subject>0 mol l</dc:subject>
          <dc:subject>printed electrodes</dc:subject>
          <dc:subject>statistical framework</dc:subject>
          <dc:subject>work provides</dc:subject>
          <dc:subject>optimal treatments</dc:subject>
          <dc:subject>l &lt;/</dc:subject>
          <dc:subject>&gt;&lt; sub</dc:subject>
          <dc:subject>electrodes subjected</dc:subject>
          <dc:subject>comparative assessment</dc:subject>
          <dc:subject>aging assessment</dc:subject>
          <dc:subject>peak separation</dc:subject>
          <dc:subject>fabricating electrochemical</dc:subject>
          <dc:subject>electrochemical activations</dc:subject>
          <dc:subject>unnecessarily complex</dc:subject>
          <dc:subject>simultaneous evaluation</dc:subject>
          <dc:subject>redox probe</dc:subject>
          <dc:subject>powerful strategy</dc:subject>
          <dc:subject>polylactic acid</dc:subject>
          <dc:subject>objective comparison</dc:subject>
          <dc:subject>nanomaterial integration</dc:subject>
          <dc:subject>multiresponse comparison</dc:subject>
          <dc:subject>multiresponse approach</dc:subject>
          <dc:subject>multiresponse analyses</dc:subject>
          <dc:subject>multiple variables</dc:subject>
          <dc:description>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)&lt;sub&gt;6&lt;/sub&gt;]&lt;sup&gt;3–/4–&lt;/sup&gt; redox probe. A multiresponse approach was employed, using a weighted
performance function (&lt;i&gt;L&lt;/i&gt;) to aggregate normalized
electrochemical variables (anodic peak current, peak current ratio,
peak-to-peak separation, and charge transfer resistance). This function
was further converted into a risk-adjusted score (&lt;i&gt;L&lt;/i&gt;&lt;sub&gt;99%&lt;/sub&gt;), penalizing variability and enabling robust statistical
analysis. Alkaline treatments proved the most effective activation
route. The best condition combined 3.0 mol L&lt;sup&gt;–1&lt;/sup&gt; NaOH
for 30 min with subsequent electrochemical activation in 0.1 mol L&lt;sup&gt;–1&lt;/sup&gt; NaOH, although the simpler chemical treatment alone
offered similar performance, making it more practical for future optimization.
Beyond identifying effective activation protocols for 3D-printed electrodes,
this work provides a versatile statistical framework for multiresponse
analyses that can serve as a practical guide for the objective comparison
and optimization of diverse systems, including filament development,
aging assessment, nanomaterial integration, bioreceptor immobilization,
and any application involving the simultaneous evaluation of multiple
variables.</dc:description>
          <dc:date>2026-09-25T00:00:00Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Dataset</dc:type>
          <dc:identifier>10.1021/acsomega.6c05769.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/dataset/Statistical_Framework_for_Multiresponse_Analyses_Comparative_Assessment_of_Surface_Activation_Strategies_for_3D-Printed_Carbon_Black_Polylactic_Acid_Electrodes_toward_Electrochemical_Bio_Sensing_Applications/33997510</dc:relation>
          <dc:rights>CC BY-NC 4.0</dc:rights>
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