1 citations · 3 across the 5 of their papers we have counts for
5 papers
NANOGPT: A Query-Driven Large Language Model Retrieval-Augmented Generation System for Nanotechnology Research
Achuth Chandrasekhar, Omid Barati Farimani, Olabode T. Ajenifujah +2
This paper presents the development and application of a Large Language Model Retrieval-Augmented Generation (LLM-RAG) system tailored for nanotechnology research. The system lever…
Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning
Olabode T. Ajenifujah, Amir Barati Farimani
Additive manufacturing (AM) is a rapidly evolving technology that has attracted applications across a wide range of fields due to its ability to fabricate complex geometries. Howev…
AMGPT: a Large Language Model for Contextual Querying in Additive Manufacturing
Achuth Chandrasekhar, Jonathan Chan, Francis Ogoke +2
Generalized large language models (LLMs) such as GPT-4 may not provide specific answers to queries formulated by materials science researchers. These models may produce a high-leve…
Integrating Multi-Physics Simulations and Machine Learning to Define the Spatter Mechanism and Process Window in Laser Powder Bed Fusion
Olabode T. Ajenifujah, Francis Ogoke, Florian Wirth +2
Laser powder bed fusion (LPBF) has shown promise for wide range of applications due to its ability to fabricate freeform geometries and generate a controlled microstructure. Howeve…
Inexpensive High Fidelity Melt Pool Models in Additive Manufacturing Using Generative Deep Diffusion
Francis Ogoke, Quanliang Liu, Olabode Ajenifujah +5
Defects in laser powder bed fusion (L-PBF) parts often result from the meso-scale dynamics of the molten alloy near the laser, known as the melt pool. For instance, the melt pool c…