# AutoMOOSE: Use Case and Logical Views of Agentic Phase-Field Simulation Software

arXiv: https://arxiv.org/abs/2608.20571 · HTML: https://mlsanity.com/paper/2608.20571/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use.
- Builds on 4 of its 17 references that are in the map.
- First posted on arXiv 20 Aug 2026.

## Placed in

- LLM agents and tool use / [Medical and scientific domain agents](https://mlsanity.com/agents/medical-and-scientific-domain-agents/)

## Builds on (most cited first, 4 of 4)

- [ChemCrow: Augmenting large-language models with chemistry tools](https://mlsanity.com/paper/2304.05376/) (2023)
- [Parsl: Pervasive Parallel Programming in Python](https://mlsanity.com/paper/1905.02158/) (2019)
- [AiiDA: Automated Interactive Infrastructure and Database for Computational Science](https://mlsanity.com/paper/1504.01163/) (2015)
- [AutoMOOSE: An Agentic AI for Autonomous Phase-Field Simulation](https://mlsanity.com/paper/2603.20986/) (2026)

## Abstract (arXiv)

AutoMOOSE is an agentic software framework that converts a natural-language request into an executed, screened, and interpreted MOOSE phase-field simulation. Here, we deploy AutoMOOSE as a agentic software, complementing our prior work which focused on development of the agentic tool. We describe our software framework and architecture through Use Case and logical views of the 1+5 architectural-views model, covering its user roles, component structure, six-agent pipeline, physics plugin layer, Model Context Protocol interface, and screening/falsification/recovery loop. Our architecture separates physical falsification from automatic repair, so corrected simulations remain inspectable and must be re-admitted before acceptance. We focus on software design, extensibility, interoperability, and reuse of the AutoMoose framework for broad utilization in multiphysics materials design problems.