Matteo Bucci

Matteo Bucci is the Esther and Harold E. Edgerton Associate Professor of Nuclear Science and Engineering at MIT. His research group studies two-phase heat transfer mechanisms in nuclear reactors and space systems, develops high-resolution non-intrusive diagnostics and surface engineering techniques to enhance two-phase heat transfer, and creates machine learning tools to accelerate data analysis and conduct autonomous heat transfer experiments. He has won several awards for his research and teaching, including the Ruth and Joel Spira Award for Excellence in Teaching (2020), ANS/PAI Outstanding Faculty Award (2018 and 2023), the UIT-Fluent Award (2006), the European Nuclear Education Network Award (2010), and the 2012 ANS Thermal-Hydraulics Division Award. Matteo is the founding editor and deputy Editor-in-Chief of AI Thermal Fluids. He also serves as Editor of Applied Thermal Engineering, is the founder and coordinator of the NSF Thermal Transport Café and works as a consultant for the nuclear industry. Matteo is also co-founder of Ferveret, a startup developing advanced cooling technologies for data center cooling.

• Italian Union of Thermal-Fluid Dynamics – Fluent Best MSc Thesis Award, 2006
• 2010 ENEN Prize for best European PhD research in Nuclear Engineering, 2010
• 2012 ANS THD Best Paper Award, ANS Thermal Hydraulics Division, 2012
• 2016 CFD4NRS Conference Best Poster Award, 2016
• Best Paper Award, 17th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, 2017
• American Nuclear Society MIT Chapter – PAI Outstanding Faculty Award, 2018
• MIT School of Engineering Ruth and Joel Spira Award for Excellence in Teaching, 2020
• DOE Distinguished Early Career Award for Nuclear Energy, 2022
• Best Paper Award, 20th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, 2023
• American Nuclear Society MIT Chapter – PAI Outstanding Faculty Award, 2023

Development of Experimental Diagnostics and Machine Learning Algorithms

We develop advanced diagnostics and data-processing algorithms to investigate the physics of two-phase heat transfer. While our work encompasses a range of techniques, our primary focus is on non-intrusive optical diagnostics, e.g., infrared (IR) thermography and phase detection. This includes the development of novel materials and coatings, the characterization of their thermophysical and optical properties, and the creation of custom post-processing algorithms tailored to high-resolution datasets.  In parallel, we integrate machine learning techniques into our post-processing pipeline to enhance the speed, accuracy, and robustness of data analysis. These algorithms are used to identify patterns in complex, high-dimensional datasets, extract relevant physical features, and enable real-time or automated interpretation of experimental results. By combining domain knowledge with data-driven models, we accelerate insight generation and enable predictive capabilities in diagnostics development.

Experimental Investigation of Boiling Heat Transfer in Extreme Environments

We design and conduct experiments to advance the fundamental understanding of boiling heat transfer across a wide range of operating conditions, including those relevant to nuclear reactor safety and cryogenic space propulsion. Our experimental platforms are engineered to operate under extreme conditions—ranging from high-pressure, high-temperature environments representative of pressurized water reactors, to the low-temperature regimes of cryogenic fluids used in rocket propulsion and energy storage systems. These experiments are tailored to capture the complex, transient, and multiscale nature of boiling phenomena. By leveraging advanced diagnostics and rigorous experimental design, we generate high-fidelity datasets that inform the development of mechanistic and predictive models. These models aim to accurately capture the key physics of boiling heat transfer and provide a foundation for the design and optimization of high-performance thermal systems in both nuclear and aerospace applications.

Boiling of Cryogenic Fluids in Micro-Gravity Conditions

We investigate the boiling behavior of cryogenic fluids with direct relevance to space propulsion. Our research focuses on understanding the fundamental heat transfer mechanisms and interfacial dynamics governing cryogenic boiling. To capture the transient and microscale phenomena involved, we employ high-resolution, non-intrusive phase-detection diagnostics. These experiments are conducted both in normal gravity and in microgravity environments to isolate and quantify the role of buoyancy in vapor-liquid interactions. For microgravity studies, we utilize parabolic flight campaigns, enabling short-duration zero-gravity conditions to examine boiling behavior in the absence of gravitationally driven convection.

Surface Engineering for Enhanced Boiling Heat Transfer

We investigate the influence of surface properties on boiling and quenching heat transfer. This includes the study of Accident Tolerant Fuel (ATF) coatings applied to nuclear fuel claddings and their impact on nucleation dynamics and critical heat flux (CHF) under reactor-relevant conditions. We also explore advanced surface engineering strategies aimed at enhancing CHF and quenching phenomena for nuclear reactor and space propulsion applications through controlled modification of surface thermophysical properties, wettability, roughness, and micro- and nano-structuring.