Artificial intelligence (AI) is a rapidly evolving field with the potential to transform nearly every area of science, as highlighted by the 2024 Nobel prizes in physics and chemistry. This includes advancements in chemical synthesis and computational library optimization, where AI and machine learning (ML) can enhance efficiency and drive data-based decision-making. However, these innovations are often constrained by the need for extensive human intervention, which can be both time-consuming and labour-intensive. Electrochemical synthesis provides an economical and sustainable approach to chemical transformations, in which electrons are used directly to promote chemical bond formation rather than chemical reagents. To apply it effectively requires advanced automation of synthesis processes and precisely optimized reaction steps.

To overcome these limitations, Laudadio and co-workers used a slug-based automated electrochemical flow platform, where small slugs of reaction mixture are separated from each other by a cushion of gas. This creates a two phase (liquid–gas) system. The small slug size minimizes material consumption while enhancing reagent mixing, and ensuring reproducible data collection from small volumes. The low-volume electrochemical microreactor enables rapid reactions with improved mass transfer, supporting an efficient single-pass flow configuration. The workflow is fully automated through user-friendly Python-based software, streamlining tasks from reaction preparation to sample collection — reducing human intervention and accelerating data generation with enhanced precision and reproducibility. This setup was successfully used to synthesize a 44-member compound library through electrochemical C–N cross-coupling reactions between aryl bromides and amines.