aldenv

A collection of environments for autonomous materias synthesis and process optimization using atomic layer deposition and area selective deposition.

Motivation

Integrating ML algorithms and AI agents based on LLMs with experimental tools requires extensive testing to ensure that the models can perform when deployed for research tasks.

One approach to derisk this development is to use virtual tools that provide realistic simulations of both the processes and tool interfaces. These virtual tools can also be used to generate benchmarks that can be used to evaluate models and agents and identify shortcomings of existing models.

This is the approach that we have followed in two recent works, one that demonstrates the integration of LLM-based agents with an experimental atomic layer deposition (ALD) tool, and another that explores the performance of reasoning large language models in ALD process optimization:

• Design and performance of AI agents interfacing with an atomic layer deposition tool

• Performance of AI agents based on reasoning language models on ALD process optimization tasks

It also incorporates the code used in prior works focused more on conventional ML algorithms.

Documentation

Full documentation is available at https://aldsim.github.io/aldenv/.

Funding acknowledgement

The work conducive to aldenv was funded as part of Argonne National Laboratory's Laboratory Directed Research and Development microelectronics portfolio.

Copyright and license

Copyright© 2026, UChicago Argonne, LLC

aldenv is distributed under the terms of BSD License.

Argonne Patent & Intellectual Property File Number: SF-26-055