About

Jacopo Buongiorno is a Battelle Energy Alliance Professor in Nuclear Science and Engineering and a Professor of Mechanical Engineering at the Massachusetts Institute of Technology. He serves as the Director of the Center for Advanced Nuclear Energy Systems at MIT. His role involves leading research and educational initiatives in nuclear science and engineering, with a focus on advanced nuclear energy systems. His work contributes to the development and understanding of nuclear energy technologies, supporting innovation and safety in the field.

Research topics

• Physics
• Engineering
• Classical mechanics
• Mechanics
• Waste management
• Electrical engineering
• Architectural engineering
• Thermodynamics
• Environmental economics
• Nuclear physics
• Nuclear engineering
• Environmental science
• Construction engineering
• Business
• Civil engineering
• Economics
• Optics

Selected publications

• Prismatic and Pebble-Bed Micro-HTGRs in Continuous-Recycle Nuclear Fuel Cycles

  Nuclear Science and Engineering · 2026-02-09

  article
  PublisherDOI

• Contributors

  Elsevier eBooks · 2026-01-01

  book-chapterOpen access
  PublisherDOI

• Moving beyond high costs: A case study of hydrogen production with nuclear microreactors

  Elsevier eBooks · 2026-01-01 · 1 citations

  book-chapterSenior author
  PublisherDOI

• Physics-Informed Neural Networks for the safety analysis of nuclear reactors

  Progress in Nuclear Energy · 2025-03-17 · 10 citations

  articleOpen access

  This work explores the development of surrogate models for estimating the evolution of quantities of interest during nuclear reactor accident scenarios. Physics-Informed Neural Networks (PINNs) offer a promising surrogate modelling approach because they allow integrating laws of physics and domain knowledge into traditional Neural Network (NN) surrogates. Specifically, the proposed solution incorporates an additional term in the PINN loss function to enforce physics-based constraints in correspondence of allocation points, which are randomly sampled points whose corresponding target output is not known. As a result, accuracy of the estimation of the quantities of interest and their adherence to the laws of physics are improved. Applications to a synthetic case study and to the response of a nuclear microreactor system during a Loss of Heat Sink scenario confirm that the developed surrogate model based on PINN with allocation points improves the estimation accuracy with respect to other state-of-the-art methods. • A surrogate model is developed for the safety assessment of nuclear microreactors. • Allocation points are introduced for Physics-Informed Neural Network training. • Quantities of interest are estimated during accident scenarios. • The model provides accurate, consistent with physics and trustworthy predictions.

  PublisherDOI

• Bottom-up levelized cost estimation of low-enriched and low-pressure nuclear batteries

  Nuclear Engineering and Design · 2025-04-08 · 1 citations

  article
  PublisherDOI

• Bottom-Up Levelized Cost Estimation of Low-Enriched and Low-Pressure Nuclear Batteries

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Preliminary Investigation of Gamma Radiation on the Chemical and Physical Characteristics of an Organic Coolant

  Nuclear Technology · 2025-12-05

  articleSenior author

  Organic-cooled reactor concepts offer potential advantages over traditional light water reactors, including operation at elevated temperatures and reduced pressures. However, radiation-induced degradation of organic coolants remains a critical concern requiring thorough investigation. This study examines the effects of gamma irradiation (1-MGy dose) on Dowtherm A (27% biphenyl, 73% diphenyl ether) under varying atmospheric conditions (ambient air versus argon) and temperatures (room temperature versus 250°C). Chemical characterization using Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy (UV-Vis), and gas chromatography-mass spectrometry revealed the formation of higher molecular weight byproducts, including terphenyls and quaterphenyls, along with notable biphenyl degradation. Physical property measurements using differential scanning calorimetry, rheometry, and thermal conductivity analysis demonstrated significant changes in the thermophysical properties, including decreased heat capacity and viscosity, with increased thermal conductivity observed under argon irradiation conditions. Pronounced photodarkening occurred in all the irradiated samples, with atmospheric conditions significantly influencing degradation pathways. UV-Vis analysis indicated that oxygen presence during irradiation suppresses certain chromophoric species formation. These findings provide crucial insights into radiation-induced degradation mechanisms and their impact on coolant performance, informing future organic coolant system design and optimization strategies for advanced reactor applications.

  PublisherDOI

• Evaluation of Capital Costs for UO2-Fueled Microreactors

  2024-01-01

  articleSenior author
  PublisherDOI

• When Cities Go Nuclear: Exploring the Applications of Nuclear Batteries Toward Energy Transformation

  Urban Science · 2024-11-25 · 4 citations

  articleOpen accessSenior author

  Global society faces the pressing question of how to eliminate reliance on fossil fuels while meeting increasing energy demand. In comparison to solar and wind energy, nuclear power has been largely ignored in urban studies research. However, nuclear energy has recently regained attention through the emergence of Small Modular Reactors (SMRs), and as the stakes of decarbonization become increasingly essential. To evaluate situations in which SMRs bring value to urban energy mixes, this paper focuses on Nuclear Batteries (NBs), a specific class of SMRs, that can fit in standard shipping containers. First, we outline an evaluation framework for the use and application of NBs; second, we present use cases for NBs in real-world situations, from disaster relief to grid reinforcement; and third, we discuss the social challenges around this technology.

  PublisherOA PDFDOI

• Assessment of Technoeconomic Opportunities in Automation for Nuclear Microreactors

  Nuclear Science and Engineering · 2024-07-24 · 4 citations

  articleOpen accessSenior author

  Achieving full decarbonization of all economic sectors remains a challenge, especially in niche markets. For example, remote communities and industrial or mining activities detached from the main electric grid heavily rely on fossil fuels, similar to urban and industrial microgrids with combined heat and power needs. A combination of renewables and energy storage is often not suitable due to cost, reliability, intermittency, and large storage requirements. Small nuclear reactors with a flexible purpose could serve these applications. Microreactors (MR) are a class of reactors that are compact, factory manufactured, transportable, and self-regulating. Typically, they generate much less power than their large reactor counterparts. The main advantages of microreactors include the versatile nature of the energy produced, the reliability of supply, and freedom from having to transport and store large quantities of fuels on-site, coupled with the absence of dependence on an electrical grid. A strong business case is needed to move from the microreactor prototype to the commercialization phase. In fact, fossil fuels are still relatively inexpensive, and in the near term, carbon credits will be available to virtually compensate for emissions. For microreactors, one of the main costs in operation and maintenance (O&M) is their staffing levels. In this study, we investigate how to optimize the number (and thus the cost) of workers, moving from a traditional, fully manned, on-site personnel approach to an unmanned, remote personnel approach. We examine four different staffing models that can be implemented as the technology matures and evolves. We estimate the staffing needs of each model and build a business case to justify the substitution of on-site personnel with adequate technologies. To do so, we propose a cost model to quantify potential cost reductions from automating O&M activities. The model accounts for both the reduction in cost derived from the reduced number of full-time-equivalent (FTE) employees and the increase in cost derived from the need to buy new control hardware as needed. Applying the cost model that we created to different scenarios, an on-site O&M cost reduction exceeding 80% can be expected. Additionally, we found that it is more impactful to focus on automating routine O&M tasks rather than attempting to automate transient management (shutdowns, restarts, monitoring condition deviations). In fact, transients typically account for less than 1% of the total FTE time spent on the reactors.

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: International Nanofluid Properties Benchmark Exercise (INPBE)

  NSF · $38k · 2008–2010

Frequent coauthors

• Lin-Wen Hu

  Massachusetts Institute of Technology

  57 shared

• Thomas McKrell

  Massachusetts Institute of Technology

  51 shared

• Matteo Bucci

  21 shared

• N.E. Todreas

  21 shared

• Hyungdae Kim

  13 shared

• Bao Truong

  12 shared

• Bren Phillips

  11 shared

• Eric Forrest

  11 shared