Themed collection Synthesis 4.0: Towards an Internet of Chemistry

Guest Editors Richard Bourne, King Kuok (Mimi) Hii and Brandon Reizman introduce this themed collection on progress towards data-driven synthesis and an ‘internet of chemistry’.

This manuscript highlights the unavoidable connection between manual and self-optimized flow synthesis protocols for multistep flow synthesis and its scale-up.

With renewed interest and significant progress in computer-assisted synthetic planning, it is essential to codify the logic that should be followed when translating organic synthetic knowledge into reaction rules understandable to the machine.

The advent of transition-metal catalysis (and likewise, bio-catalysis, photoredox-catalysis and organo-catalysis, etc.) promises to greatly increase access to diverse chemical matter in medicinal chemistry, but new catalytic reactions often fail to deliver product in applied synthesis.

The Internet of Things (IoT), Industry 4.0, and the digitalization of business processes offer new opportunities and business models for the process industry, including education and training.

Self-optimising chemical systems have experienced a growing momentum in recent years. Herein, we review algorithms used for the self-optimisation of chemical reactions in an accessible way for the general chemist.

This article highlights recent progress in continuous flow self-optimizing platforms.

A definitive screening design (DSD) combined with reaction profiling was conducted using a flow reactor, in a short time frame, for the accurate estimation of kinetic parameters.

Application of an automated profiling system with online HPLC uncovers an induction period in a cross-coupling and facilitates catalyst optimization.

The generation and use of acyl ketenes under continuous flow reaction conditions is reported. Several reaction classes of these reactive intermediates have been studied. Under zero headspace conditions, a ketone exchange process is possible between volatile ketones. The process can be readily scaled to deliver gram quantities of product.

A flexible and cost-effective methodology to develop compact flow devices with heat exchange ability is presented here.

The integration of high-performance liquid chromatography-evaporative light scattering detection with robotic sampling allows for the acquisition of reliable and data-rich solubility and crystallization profiles of minimally- or non-UV active compounds in an automated manner.

Multidisciplinary collaboration enables the rapid and efficient design and selection of an improved manufacturing route to a new potential medicine for the treatment of asthma.

We report an automated device for the efficient microscale separation of immiscible liquids.

The use of multidimensional dynamic flow experiments for reaction profiling and generation of an empirical surface response model for a Knoevenagel condensation reaction is described.

Rapid estimation of kinetic parameters with high precision is facilitated by automation combined with online Model-Based Design of Experiments.

Rapid knowledge building of chemical processes with highly automated DoE (HAD) and statistical analyses and modeling.

Application of high-speed DESI-MS analysis for the identification of optimal reaction conditions through high-throughput experimentation screening.

The coupling of a modular microreactor platform, real-time inline analysis by IR and NMR, and online UPLC, leads to efficient optimization of a multistep organolithium transformation to a given product without the need for human intervention.

A popular electronic module and the associated Internet-of-Things tools provide chemists with more control over long-term experimental procedures and enhance lab work safety.

A continuous flow synthesis of PyOX ligands has been developed using an autonomous self-optimizing flow reactor.

A conceptual framework for incorporating machine learned ligand prediction into predictive route comparisons, to enable greener chemistry outcomes.