Authors: Leroy Cronin, Sebastian Pagel, Abhishek Sharma
Affiliation: University of Glasgow

Chemputation reframes synthesis as the programmable execution of reaction code on a universally re-configurable hardware graph. Here we prove that a chemputer equipped with a finite, but extensible, set of reagents, catalysts and process conditions, together with a chempiler that maps reaction graphs onto hardware, is universal: it can generate any stable, isolable molecule in finite time and in analytically detectable quantity, provided real-time error correction keeps the per-step fidelity above the threshold set by the molecule's assembly index. The proof is constructed by casting the platform as a Chemical Synthesis Turing Machine (CSTM). The CSTM formalism supplies (i) an eight-tuple state definition that unifies reagents, process variables (including catalysts) and tape operations; (ii) the Universal Chemputation Principle; and (iii) a dynamic-error-correction routine ensuring fault tolerant execution. Linking this framework to assembly theory strengthens the definition of a molecule by demanding practical synthesizability and error correction becomes a prerequisite for universality. We validate the abstraction against >100 XDL programs executed on a modular chemputer rigs spanning single step to multi-step routes. Mapping each procedure onto CSTM shows that the cumulative number of unit operations grows linearly with synthetic depth. Together, these results elevate chemical synthesis to the status of a general computation: algorithms written in XDL are compiled to hardware, executed with closed-loop correction, and produce verifiable molecular outputs. By formalising chemistry in this way, the chemputer offers a path to shareable, executable chemical code, interoperable hardware ecosystems, and ultimately a searchable, provable atlas of chemical space.

The dataset provided in the data/ directory has been adapted from the following publication:

Science 2022, 377. DOI: 10.1126/science.abo0058

The notebooks/ directory contains Jupyter notebooks for demonstrating the usage of the codebase and reproducing figures.

• Figure6.py: Python script to generate Figure 6.
• ChemicalTuringMachine.nb: Mathematica notebook for the simulation of a chemical turing machine
• reaction_display.ipynb: Examples of visualizing chemical reactions and molecules using rxnframe.
• Figure7.ipynb: Code to generate subfigures of Figure 7.

This project uses uv for dependency management. To install the dependencies, run:

uv sync

Note: To run the Mathematica notebooks (.nb files), you will need a valid installation of Wolfram Mathematica.

If you use this code or data, please cite the following:

Chemputer and Chemputation -- A Universal Chemical Compound Synthesis Machine