eFlow-Hydrogenation: Practical and Scalable Single-Pass Electrochemical Reduction Platform for Unsaturated Bonds

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Authors: Sagar Arepally, Thomas Wirth, Tribani Boruah, Rebecca L. Melen
Cited by: 0

Abstract

We report a flow electrochemical platform which is capable of reducing alkenes, alkynes, α,β-unsaturated carbonyls, ketones, and aldehydes using solvents and electrolytes as benign hydrogen sources. The system operates under mild conditions with simple current control and a fixed reactor design, enabling seamless translation from discovery to multigram scale without reoptimization. Gram-scale reactions proceed with short residence times of about 1 min, 59 examples with up to 96% yield are reported. The platform also enables two-step flow electrochemical hydrogenation by connecting undivided microreactors in series, allowing selective and sequential reduction of different functional groups within a continuous single flow process. A key engineering innovation is a three-electrode, dual-sided cathode architecture that enables efficient single-pass electroreduction and supports high throughput operation. With 16 parallel reactors a 100 g electrochemical reduction with >98% conversion and 96% isolated yield was achieved, delivering 19.1 g/h productivity under safe and hydrogen-free conditions.In this project, all data were generated using a continuous‑flow electrochemical setup, with full documentation of flow‑cell specifications, standard operating procedures, and analytical methods including NMR and HRMS. The data files (1H, 13C, 19F) are arranged according to the compound numbers used in the Manuscript and the Supporting Information. All NMR data were processed by MestReNova software, and HRMS data were provided in .pdf file.

Fields of Study & Subjects

Innovative Microfluidic and Catalytic Techniques Innovation Radical Photochemical Reactions Asymmetric Hydrogenation and Catalysis

Publication details

Journal / source
ORCA Online Research @Cardiff (Cardiff University)
Publication date
11 March 2026
Language
EN
Document type
Dataset