Simple implementation examples of agent AI on free energy calculation and phase-field simulation

With the development of an environment that equips large language models with tools, chat-type artificial intelligence (AI) is currently shifting to agent-type AI. Although building an agent AI with complex behavior is an important issue, a method for easily implementing simple agent AI is also useful in materials research. The objectives of this study are to demonstrate the usefulness of simple agent AI codes and to distribute them as supplemental materials. The key points are summarized as follows. (1) Using Gibbs energy calculations as an example, we demonstrated a simple method for constructing agent AI, including explanation and distribution of the Python code. (2) We applied this method to a scratch code development of phase-field simulation, and the template Python code was also distributed. (3) Using the simple agent AI technique, we were able to easily verify that the Jarzynski equality is applicable for the diffusion behavior in diffusion couple, which provides a new approach for directly evaluating free energy change from diffusion flux information. Using Gibbs energy calculations and diffusion simulations as examples, we demonstrated the implementation method and usefulness of simple agent AI, where sample python codes are distributed as supplemental materials.