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<p>This study presents a comprehensive evaluation of carotenoid mixtures derived from various dye-producing microorganisms for application in dye-sensitized solar cells (DSSCs). Raw microbial biomasses were analyzed using rapid, non-destructive portable Raman spectroscopy, and spectral differences were interpreted through Principal Component Analysis (PCA), enabling the discrimination of four distinct classes of compounds not immediately evident from spectroscopy alone. To validate this pre-screening approach, DSSCs were fabricated using extracted pigments, and their photoelectrochemical properties were assessed by I–V and EIS measurements. The best-performing devices were associated with a specific Raman-PCA cluster, confirming a consistent correlation between spectral grouping and photovoltaic trends. Notably, this methodology represents a transferable and scalable screening platform that can be applied to microorganisms with diverse chemical structures, enabling the rapid and sustainable selection of promising pigment sources for green solar energy applications.</p> Graphical abstract <p></p>

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Rapid identification of natural dyes derived from microbial biomass through portable Raman spectroscopy coupled with multivariate analysis for DSSC application

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月9日

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  • Donatella Spadaro,
  • Dario Giuffrida,
  • Alessia Tropea,
  • Ilaria Citro,
  • Giuseppe Calogero,
  • Stefano Trocino,
  • Cassamo U. Mussagy,
  • Rosa C. Ponterio,
  • Luigi Mondello

摘要

This study presents a comprehensive evaluation of carotenoid mixtures derived from various dye-producing microorganisms for application in dye-sensitized solar cells (DSSCs). Raw microbial biomasses were analyzed using rapid, non-destructive portable Raman spectroscopy, and spectral differences were interpreted through Principal Component Analysis (PCA), enabling the discrimination of four distinct classes of compounds not immediately evident from spectroscopy alone. To validate this pre-screening approach, DSSCs were fabricated using extracted pigments, and their photoelectrochemical properties were assessed by I–V and EIS measurements. The best-performing devices were associated with a specific Raman-PCA cluster, confirming a consistent correlation between spectral grouping and photovoltaic trends. Notably, this methodology represents a transferable and scalable screening platform that can be applied to microorganisms with diverse chemical structures, enabling the rapid and sustainable selection of promising pigment sources for green solar energy applications.

Graphical abstract