ColorLab: Visualizing Color from Absorbance Spectra

Spencer Yeager, Michael Anderson, Priscilla Babiak, Bryon Larson, Erin Ratcliff

Research output: Contribution to journalArticle


We present here the first public release of ColorLab, a Python-based program that can convert absorbance spectra into color images. It was designed for use with organic photovoltaic (OPV) materials and blends, which represent a myriad of colors based on molecular design and material blending that can exhibit persistent color or evolve over time via degradation or morphology changes. However, ColorLab is not limited to this application, and can generate color images from a single spectrum or an evolving color bar on a time axis from multiple time-stamped spectra. Using internationally defined illuminants, ColorLab can display colors that are representative of a variety of lighting situations, from indoor to outdoor. The development of this program aims to aid with the visualization of semitransparent materials and to connect researchers with designers, through conversion of spectra to color.
Original languageAmerican English
Number of pages11
StatePublished - 2022

NREL Publication Number

  • NREL/JA-5900-83164


  • absorbance
  • color
  • ColorLab
  • data visualization
  • degradation


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