About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Additive Manufacturing and Innovative Feedstock Processing for Multifunctional Materials
|
| Presentation Title |
AI-Augmented Direct Ink Writing of Heirarchical Meta-Foams for Multifunctional Applications |
| Author(s) |
Dhanush Patil, Kenan Song |
| On-Site Speaker (Planned) |
Dhanush Patil |
| Abstract Scope |
We present an additive manufacturing platform integrating direct ink writing (DIW) with multi-agent AI frameworks to transcend lattice-based limitations in hierarchical porous structures. By synergizing innovative feedstock processing using static mixers to regulate reaction kinetics via flow rates with AI-driven computational design, we achieve simultaneous control over stochastic micro-porosity and programmable macro-architectures. This approach decouples structural innovation from traditional porous media constraints, enabling rapid discovery of self-similar fractal meta-structures that distribute thermal/mechanical stresses across scales. The feedstock processing enables real-time pore size/porosity tuning during deposition, while AI reduces design cycles by >10x through generative modeling of natural/synthetic structures. Resulting meta-foams exhibit multifunctionality, 92% elastic recovery for impact-resistant conformal liners (e.g., helmet padding) and ultralow thermal conductivity (0.067 W·m⁻¹·K⁻¹) for thermo-therapeutic devices. This scalable, waste-minimized process bridges computational design and advanced manufacturing, establishing a new paradigm for lightweight, multifunctional materials in aerospace, automotive, and personalized healthcare. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Polymers, Other |