ArticleReaction chemistry & engineering2016
Suzuki-Miyaura cross-coupling optimization enabled by automated feedback.
Article in Reaction chemistry & engineering, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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The trial behind it
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Who cites it
43 citing papers in PubMed.
- Chemputer and chemputation-A universal chemical compound synthesis machine.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- The Impact of Continuous Flow Technology and Collaboration between Academia and Industry.JACS Au · 2026Review
- Review
- Homogeneous catalysis in continuous flow integrating photocatalysis, electrocatalysis, and automation technologies.Communications chemistry · 2025Review
- Synthesis of new nicotintaldehyde derivatives via Pd(0) catalyzed suzuki coupling with structural characterization and co-combined computational-experimental evaluation against oral pathogens.Scientific reports · 2025Article
- Applying Active Learning toward Building a Generalizable Model for Ni-Photoredox Cross-Electrophile Coupling of Aryl and Alkyl Bromides.Journal of the American Chemical Society · 2025Article
- Automating life science labs at the single-cell level through precise ultrasonic liquid sample ejection: PULSE.Microsystems & nanoengineering · 2024Article
- Self-Driving Laboratories for Chemistry and Materials Science.Chemical reviews · 2024Review
- Simultaneous reaction- and analytical model building using dynamic flow experiments to accelerate process development.Chemical science · 2024Article
- Multi-Variable Multi-Metric Optimization of Self-Assembled Photocatalytic COJournal of the American Chemical Society · 2024Article
- A green, facile, and practical preparation of capsaicin derivatives with thiourea structure.Scientific reports · 2024Article
- Machine learning-guided strategies for reaction conditions design and optimization.Beilstein journal of organic chemistry · 2024Review
- A deep learning framework for accurate reaction prediction and its application on high-throughput experimentation data.Journal of cheminformatics · 2023Article
- Recent Progress on One-Pot Multisubstrate Screening.Organic process research & development · 2023Review
- Accelerated Chemical Reaction Optimization Using Multi-Task Learning.ACS central science · 2023Article
- On the use of real-world datasets for reaction yield prediction.Chemical science · 2023Article
- A field guide to flow chemistry for synthetic organic chemists.Chemical science · 2023Review
- Digitizing chemical discovery with a Bayesian explorer for interpreting reactivity data.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- A Brief Introduction to Chemical Reaction Optimization.Chemical reviews · 2023Review
- Quid Pro Flow.Journal of the American Chemical Society · 2023Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
An automated, droplet-flow microfluidic system explores and optimizes Pd-catalyzed Suzuki-Miyaura cross-coupling reactions. A smart optimal DoE-based algorithm is implemented to increase the turnover number and yield of the catalytic system considering both discrete variables-palladacycle and ligand-and continuous variables-temperature, time, and loading-simultaneously. The use of feedback allows for experiments to be run with catalysts and under conditions more likely to produce an optimum; consequently complex reaction optimizations are completed within 96 experiments. Response surfaces predicting reaction performance near the optima are generated and validated. From the screening results, shared attributes of successful precatalysts are identified, leading to improved understanding of the influence of ligand selection upon transmetalation and oxidative addition in the reaction mechanism. Dialkylbiarylphosphine, trialkylphosphine, and bidentate ligands are assessed.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.