Computational Materials Design of Functionally Graded Structures for Enhanced Cooling of Plasma Facing Components via Additive Manufacturing

Nuclear fusion has the potential to provide an abundant supply of clean, low-cost energy. Localized stresses induced by the large difference in coefficient of expansion between the shielding material (tungsten) and cooling structure material (steel or Cu) during thermal cycling associated with normal operation can lead to cracking at the joint interface, potentially resulting in failure of the plasma facing component. Under this SBIR/STTR program, QuesTek Innovations LLC, a leader in the field of Integrated Computational Materials Engineering, partners with Texas A&M University (TAMU) to design and fabricate a functionally graded material, joining PFCs and underlying coolant-contacting parts (e.g., steel, Cu) via advanced additive manufacturing techniques for enhanced cooling and improved lifetime of the PFCs. During the Phase I program, novel compositional gradients between steel and pure W were computationally designed and validated via additive manufacturing prototyping. TAMU’s novel machine learning-enhanced computational methodology was used to design compositional gradients between steel and tungsten in a composition space. Two compositional gradients were designed. They significantly reduce the phase fraction of deleterious phases at any temperature when compared to the linear gradient. The designed paths also satisfy constraints on printability metrics like solidification cracking and hot cracking susceptibility. In parallel, extensive experimental work was performed through the Phase I to develop additive manufacturing process parameters and build small proof-of-concept coupons. By the end of the program, partial gradients were successfully printed. Initial characterization of the gradients confirmed the good build quality (no major porosity observed nor large deleterious second phase) and compositional accuracy. In Phase II, The functionally graded additive manufacturing technology demonstrated in Phase I will be further optimized and developed in Phase II, in tandem with additional improvement and expansion of the computational gradient planning tool. On top of the approaches used in Phase I, the team proposes additional approaches in Phase II to significantly enhance the gradient design and fabrication framework. They include: 1) expand and optimize the AM process of gradient fabrication; 2) expand the gradient design methodology; and 3) make fundamental improvements to the algorithms. By synergizing the complementary experimental and computational efforts, the team will aim to offer a comprehensive solution to address the challenges in additive manufacturing of functionally graded materials and enable enhanced cooling of plasma facing components. Our proposed research to design and develop novel functionally graded PFCs with enhanced cooling can directly boost the success of U.S. and international Fusion Energy Sciences programs. The research can help enhance scientific state-of-the-art in fusion community and improve the US technical leadership. QuesTek’s product out of the program will contain a design toolkit that will allow for users, including researchers, scientists, engineers and others, to design additive manufacturing printing plans for functionally graded materials, with a focus on path planning for material gradients. QuesTek’s developed technology will include inherent attributes that support the underlying systems-based approach of materials design and optimization. Furthermore, a product that may be developed under the scope of this program is a unique composition and/or AM processing specification for a novel functionally graded material.