Roblonski: A Material-Efficient Robo-Fluidic Toolbox for Rapid Photochemical Characterization

Abstract Reliable photochemical and photophysical characterization is essential for understanding and optimizing photocatalytic processes; however, traditional, manual spectroscopic methods for determining bimolecular photoreaction quenching constants, molar extinction coefficients, and photoluminescence quantum yields (PLQYs) are time-, cost-, material-, and labor-intensive and generate considerable chemical waste. Herein, we report Roblonski, a compact, material-efficient microfluidic robotic platform that automates these three foundational photochemical assays with high precision, reproducibility, and accuracy. Using Ru­(bpy)3(PF6)2 as a model photosensitizer and photocatalyst, we performed Stern–Volmer analyses with 11 excited state electron and triplet energy transfer quenchers, Beer–Lambert studies of five compounds spanning 3 orders of magnitude in their molar extinction coefficients across multiple solvents, and relative PLQY determinations for fluorophores/luminophores with PLQYs ranging over 3 orders of magnitude in efficiency. The machine-generated results matched manual experimental measurements and literature benchmarks across diverse spectral features, solvent environments, and signal intensity regimes. Roblonski reduces sample consumption (20-fold by solution volume, 1000-fold by reagent moles) and accelerates data collection (4-fold) compared to traditional, manual approaches. By integrating these photochemically relevant assays into a single, compact automated platform, Roblonski has the potential to lower experimental barriers, enable data-rich evaluation of photocatalysts and substrates, and augment autonomous photochemical discovery and characterization.