Fully automated and high-fidelity robotic platform enabling accelerated discovery of nanocatalysts

The discovery of heterogeneous catalysts increasingly relies on high-throughput experimentation and high-fidelity data. Here, we report a fully automated robotic platform that integrates two synchronized collaborative robotic arms, automated liquid handling, and time-resolved UV-Vis kinetic analysis for the rapid, reproducible, and data-rich evaluation of nanocatalysts. Unlike existing high-throughput systems, which often compromise data quality, our platform combines parallel reaction execution with real-time processing of time-resolved measurements and automated performance ranking, thereby delivering both speed and precision. Using the catalytic reduction of 4-nitrophenol as a benchmark, we screened 24 Pd-based catalysts including 22 metal-added Pd/AC variants, and completed 96 measurements in 16 h 40 min achieving an average throughput of ∼10 min per sample. The system achieved high reproducibility, with relative standard deviations of approximately 2%, and detected subtle kinetic differences such as the enhanced activity of catalysts containing Fe, Cu, Zn, and Sn. Correlating experimental performance with density functional theory (DFT)-derived descriptors revealed structure-activity relationships and highlighted nanoscale effects not captured by bulk calculations.

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Publication Details

Journal
Chemical Science
Published
2025-12-30
DOI
https://doi.org/10.1039/d5sc06192j
Primary Topic
Micro and Nano Robotics
Type
article
Field-Weighted Citation Impact
0.00

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article

Fully automated and high-fidelity robotic platform enabling accelerated discovery of nanocatalysts

Sanha Jang, Ji Chan Park, Jin Gyu Lee, Kanghoon Yim et al.
Chemical Science
Micro and Nano Robotics
article

Fully automated and high-fidelity robotic platform enabling accelerated discovery of nanocatalysts

Sanha Jang, Ji Chan Park, Jin Gyu Lee, Kanghoon Yim, Jung-Il Yang, Kyung Hee Oh, Shin Wook Kang
article en

Abstract

The discovery of heterogeneous catalysts increasingly relies on high-throughput experimentation and high-fidelity data. Here, we report a fully automated robotic platform that integrates two synchronized collaborative robotic arms, automated liquid handling, and time-resolved UV-Vis kinetic analysis for the rapid, reproducible, and data-rich evaluation of nanocatalysts. Unlike existing high-throughput systems, which often compromise data quality, our platform combines parallel reaction execution with real-time processing of time-resolved measurements and automated performance ranking, thereby delivering both speed and precision. Using the catalytic reduction of 4-nitrophenol as a benchmark, we screened 24 Pd-based catalysts including 22 metal-added Pd/AC variants, and completed 96 measurements in 16 h 40 min achieving an average throughput of ∼10 min per sample. The system achieved high reproducibility, with relative standard deviations of approximately 2%, and detected subtle kinetic differences such as the enhanced activity of catalysts containing Fe, Cu, Zn, and Sn. Correlating experimental performance with density functional theory (DFT)-derived descriptors revealed structure-activity relationships and highlighted nanoscale effects not captured by bulk calculations.

Chemical ScienceVol. 17(9)
Korea Institute of Energy Research (KR), Korea University of Science and Technology (KR)
Ministry of Trade, Industry and Energy, Korea Institute of Energy Research, Korea Evaluation Institute of Industrial Technology
Openalex Percentile: Top 29%
Micro and Nano Robotics
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Fully automated and high-fidelity robotic platform enabling accelerated discovery of nanocatalysts — Sanha Jang, Ji Chan Park, et al. · Chemical Science (2025) | TGRS Research Map | TGRS