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Updated: Mar 24, 2026

Using Cyclic Voltammetry, UV-Vis-NIR, and EPR Spectroelectrochemistry to Analyze Organic Compounds
Published on: October 18, 2018
Database utility for cyclovoltammetry knowledge (DUCK): unified platform for electrochemical data
Diego Garay-Ruiz1, Sergio Pablo-García2, Han Hao2
1Instituto de Micro y Nanotecnología, IMN-CNM, CSIC (CEI UAM+CSIC) Isaac Newton, 8 28760 Tres Cantos Madrid Spain marisol.martin@csic.es.
None:
Cyclic voltammetry (CV) is a valuable tool for electrochemistry, providing qualitative and quantitative information about redox processes occurring in solution. Despite its ubiquity, the lack of standardized reporting and sharing protocols, commonly adopted, significantly hinders data reusability and reproducibility. Here, we present DUCK (Database Utility for Cyclovoltammetry Knowledge), a comprehensive platform for organizing, analyzing and exploring CV data through ontology-based knowledge graphs. The system comprises three components: (1) CVOnto, a formal ontology for electrochemical CV measurement data, (2) DUCK-KG, an automated tool for the generation of knowledge graphs from experimental metadata, and (3) DUCK-Viz, an interactive web interface for visualization and analysis of CV data. We demonstrate applicability across two distinct domains: 130 CV experiments from electrodeposition studies in traditional laboratories, and 79 automated measurements from metal-ligand complexes in self-driving laboratories, performing Bayesian optimization workflows. The application to these two paradigms demonstrates DUCK's potential as a unified platform implementing FAIR data principles for the electrochemistry community.
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