Predicting Sintering Window of Binder Jet Additively Manufactured Parts Using a Coupled Data Analytics and CALPHAD Approach

Journal Article · 24 October 2023 · Integrating Materials and Manufacturing Innovation

DOI: https://doi.org/10.1007/s40192-023-00313-7 · OSTI ID:2204597

Kannan, Rangasayee  ^[1]; Nandwana, Peeyush  ^[1]

---

1. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Batch-to-batch variation in powder compositions for binder jet additive manufacturing (BJAM) can significantly deter defining an “ideal” sintering window for a given alloy. One way to overcome the problem is by running sintering experiments at various temperatures for each batch of the powder. However, such an approach increases the time required to achieve large-scale production of parts. The predictive capabilities of computational thermodynamic tools like CALPHAD can be leveraged to overcome the challenge, especially for binder jet additive manufacturing, since the process occurs under near-equilibrium conditions. However, calculating the sintering window using CALPHAD can be computationally expensive, considering many possible feedstock compositions within “specification”. Here, we generate high throughput CALPHAD data for nickel-based superalloys to develop machine learning models to predict the sintering window rapidly. The predictive capability of the models has been validated using published results on BJAM of Inconel 718 and 625. Further, validated models are lightweight and can be deployed in an industrial setting to get sintering window in an accelerated manner.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Manufacturing Demonstration Facility (MDF)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Advanced Materials & Manufacturing Technologies Office (AMMTO); USDOE Office of Fossil Energy and Carbon Management (FECM)
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 2204597
• Journal Information: Integrating Materials and Manufacturing Innovation, Journal Name: Integrating Materials and Manufacturing Innovation Vol. 12; ISSN 2193-9764
• Publisher: SpringerCopyright Statement
• Country of Publication: United States
• Language: English