About this Abstract |
Meeting |
2025 TMS Annual Meeting & Exhibition
|
Symposium
|
Algorithms Development in Materials Science and Engineering
|
Presentation Title |
Optimizing Material Compositions Using an Ising Model-Based Annealing Method |
Author(s) |
Yoshishige Okuno, Suguru Sakaguchi |
On-Site Speaker (Planned) |
Yoshishige Okuno |
Abstract Scope |
We developed an information processing system that optimizes material compositions using an annealing method based on the Ising model. The system includes a computing device that executes annealing calculations and a material composition search device that converts the optimization function into an Ising model. Critical components of this system are the Input Unit, which accepts target values for physical properties; the Conversion Unit, which converts the optimization equation into the Ising model; the Optimization Unit, which calculates the optimal material composition that approximates the target values; and the Output Unit, which outputs the calculated optimal material composition. The equation includes a cost function that calculates the cost of compositions to prioritize low-cost materials and constraints to ensure the total ratio of materials sums to 100% and to favor compositions with fewer materials. We applied this system to search the mixture solvent to maximize the solubility and minimize the cost. |
Proceedings Inclusion? |
Planned: |
Keywords |
Machine Learning, Mechanical Properties, Modeling and Simulation |