Research & Development World

  • R&D World Home
  • Topics
    • Aerospace
    • Automotive
    • Biotech
    • Careers
    • Chemistry
    • Environment
    • Energy
    • Life Science
    • Material Science
    • R&D Management
    • Physics
  • Technology
    • 3D Printing
    • A.I./Robotics
    • Software
    • Battery Technology
    • Controlled Environments
      • Cleanrooms
      • Graphene
      • Lasers
      • Regulations/Standards
      • Sensors
    • Imaging
    • Nanotechnology
    • Scientific Computing
      • Big Data
      • HPC/Supercomputing
      • Informatics
      • Security
    • Semiconductors
  • R&D Market Pulse
  • R&D 100
    • 2025 R&D 100 Award Winners
    • 2025 Professional Award Winners
    • 2025 Special Recognition Winners
    • R&D 100 Awards Event
    • R&D 100 Submissions
    • Winner Archive
  • Resources
    • Research Reports
    • Digital Issues
    • Educational Assets
    • Subscribe
    • Video
    • Webinars
    • Content submission guidelines for R&D World
  • Global Funding Forecast
  • Top Labs
  • Advertise
  • SUBSCRIBE

Roblonski platform automates photochemistry with 1,000-fold reduction in reagent use

By Julia Rock-Torcivia | April 24, 2026

Researchers from North Carolina State University have developed a compact, automated robotic platform for foundational photochemical assays. They call the system Roblonski, after A. Jablonski, who created the Jablonski diagram. They published their findings in ACS Central Science.  

(A) Schematic illustration of the developed robo-fluidic platform (Roblonski) and (B) the general workflows implemented in this work. Credit: ACS Central Science

Reliable photochemical and photophysical characterization is essential for understanding and optimizing photocatalytic processes. However, traditional spectroscopic methods are time-, cost-, material- and labor-intensive. 

Automating three foundational photochemical assays

Roblonski automated three foundational photochemical assays with high precision, reproducibility and accuracy, the researchers report. The researchers used Ru(bpy)3(PF6)2 as a model photosensitizer and photocatalyst to test the system. The machine-generated results matched manual experimental measurements and literature benchmarks. 

Roblonski reduced sample consumption 20-fold by solution volume and 1,000-fold by reagent moles. It also accelerated data collection fourfold 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,” the researchers claim in their paper. 

Roblonski automated Stern-Volmer (SV) analysis, Beer-Lambert (BL) studies and Photoluminescence Quantum Yield (PLQY). 

A hybrid robo-fluidic architecture 

The system is built around a Gilson GX-241 robotic liquid handler and an Ocean Optics QE-Pro photodiode array spectrometer. A custom flow cell is integrated directly into the liquid handler’s tubing, minimizing wasted sample and speeding up transport. Roblonski is controlled through Python to automatically perform liquid transfers, mixing, spectroscopic measurements and cleaning. The system is just 0.27 cubic meters, small enough to fit inside a standard laboratory glovebox. 

The team used Roblonski to perform SV analyses with 11 different quenchers, completing in 25 hours what would take two weeks to complete manually. 

The system uses both a broadband UV-vis deuterium-halogen source, for absorption and BL studies, and a narrow-band UV LED, for excitation in photoluminescence and SV analysis. 

Roblonski operates on two main modes: serial dilution and sample series. In the serial dilution mode, used for BL and PLQY studies, the robot starts with a stock solution and performs automated dilutions to generate a multi-point calibration curve. In the sample series mode, for SV analysis, the robot prepares a series of vials with a constant catalyst concentration but varying amounts of quencher molecule to observe how the light emission is suppressed. 

Roblonski features closed-loop decision-making. If the initial measurement shows that the sample is too concentrated, the system automatically calculates the necessary dilution factor and restarts the assay without human intervention. For SV studies, the system performs a real-time linear regression and automatically prepares and measures additional replicates if the R2 falls below a user-defined threshold. 

“Looking forward, Roblonski’s solvent compatibility and adaptability position it for quantitative studies in photochemical kinetics, photochromism, photochemical upconversion and dynamic photoluminescence measurements,” the paper notes. “Similarly, Roblonski’s flexibility makes it amenable for the spectroscopic evaluation of both soft and hard, organic and inorganic materials, semiconductor nanocrystals, metal–organic frameworks and other valuable photonic materials platforms.”

Related Articles Read More >

SpaceX is now worth nearly as much as 41 aerospace peers combined. Its revenue is another story
Q&A: Owkin’s five-year Sanofi deal bets on ‘purpose-built’ AI agents
Is Karpathy’s viral LLM wiki helpful? My opinion after one month of experimenting with one.
Leica, Indica Labs and Lunit team up as AI biomarker scoring moves toward clinical scale
rd newsletter
EXPAND YOUR KNOWLEDGE AND STAY CONNECTED
Get the latest info on technologies, trends, and strategies in Research & Development.

R&D World Digital Issues

Fall 2025 issue

Browse the most current issue of R&D World and back issues in an easy to use high quality format. Clip, share and download with the leading R&D magazine today.

R&D 100 Awards
Research & Development World
  • Subscribe to R&D World Magazine
  • Sign up for R&D World’s newsletter
  • Contact Us
  • About Us
  • Drug Discovery & Development
  • Pharmaceutical Processing
  • Global Funding Forecast

Copyright © 2026 WTWH Media LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media
Privacy Policy | Advertising | About Us

Search R&D World

  • R&D World Home
  • Topics
    • Aerospace
    • Automotive
    • Biotech
    • Careers
    • Chemistry
    • Environment
    • Energy
    • Life Science
    • Material Science
    • R&D Management
    • Physics
  • Technology
    • 3D Printing
    • A.I./Robotics
    • Software
    • Battery Technology
    • Controlled Environments
      • Cleanrooms
      • Graphene
      • Lasers
      • Regulations/Standards
      • Sensors
    • Imaging
    • Nanotechnology
    • Scientific Computing
      • Big Data
      • HPC/Supercomputing
      • Informatics
      • Security
    • Semiconductors
  • R&D Market Pulse
  • R&D 100
    • 2025 R&D 100 Award Winners
    • 2025 Professional Award Winners
    • 2025 Special Recognition Winners
    • R&D 100 Awards Event
    • R&D 100 Submissions
    • Winner Archive
  • Resources
    • Research Reports
    • Digital Issues
    • Educational Assets
    • Subscribe
    • Video
    • Webinars
    • Content submission guidelines for R&D World
  • Global Funding Forecast
  • Top Labs
  • Advertise
  • SUBSCRIBE