Artificial Intelligence-Guided Science of Molten Salts: Chemistry, Structure, and Properties Across the Periodic Table

Date: December 5, 2025; Time: 2:30 PM Location: PWEB 175

Abstract: A central challenge to deploying molten salt nuclear technologies lies in our ability to accurately characterize, predict, and monitor the chemistry of molten salts throughout the fuel cycle. In synthesis, the properties of molten salts can be tailored for specific combination of properties. During operation, fuel salt composition evolves continuously with generation of numerous fission products, which produces significant changes in the thermophysical and thermochemical properties. In reprocessing, impurities must be separated from reusable fuel. Each of these steps requires the study of an enormous array of chemical and thermodynamic conditions. Here, current experimental and computational approaches are not sufficiently accurate and expeditious for assessing these design spaces. As such, it is unlikely that we will achieve the robust chemical understanding required for commercial deployment under conventional research paradigms employed in the study of molten salts. This talk will discuss our latest advances in applying artificial intelligence (AI) to overcome these challenges for studying the chemistry-structure-property relationships in molten salt, which include 1) machine learning (ML)-assisted atomistic simulation for speed and accuracy, 2) chemistry-informed ML for learning the thermal properties of molten salts across the periodic table and generative AI for targeted-property design, and 3) machine learning-enhanced characterization and online monitoring with spectroscopic methods. We will show how state-of-the-art methods have been applied for uncovering structure-property of molten salts with unprecedented speed and resolution and discuss future opportunities for improvement in each of these areas.

Biographical Sketch: Stephen Lam is the Director of Nuclear Engineering, and Assistant Professor of Chemical Engineering at the University of Massachusetts Lowell. His research focuses on combining artificial intelligence and materials simulation to inform experiments for the purpose of understanding chemical structure, reactions and property relationships in advanced energy materials. Stephen obtained a PhD in nuclear engineering in 2020 from the MIT, and BS in Chemical Engineering in 2013 from the University of British Columbia. He was the recipient of the U.S. Department of Energy Early Career Award, and U.S. Nuclear Regulatory Commission’s Distinguished Faculty Advancement Award in 2024. His work includes computational material screening with high-throughput simulation, development of machine learning-based interatomic potentials for predicting properties and understanding microscale phenomena, application of artificial intelligence for unraveling hidden structure-property relationships, and machine learning-assisted spectroscopies for enhancing structural characterization and monitoring techniques. His work has been published in over 30 peer-reviewed articles (including JACS Au, Nature Machine Intelligence, npj Computational Materials, Chemical Science) in areas of machine learning, molten salt chemistry, tritium interactions with materials, carbon materials, and high-temperature ceramics.

Creating Thermal Solutions for Ultrawide Bandgap Electronics

Date: November 7, 2025; Time: 2:30 PM Location: PWEB 175

Abstract: Wide bandgap semiconductors made from GaN and AlGaN alloys have promise for future rf electronics and power switches.  One of the key issues that arises in developing future electronics from these materials is the desire for high-power operation, which will place more demands on managing the heat dissipation from these devices.  This is especially true when using ternary nitride alloys since they possess an intrinsically low thermal conductivity.  This requires careful design of the device architecture and layout to yield effective heat dissipation pathways for wide bandgap semiconductor systems.

In this talk, we will present results on the integration of high thermal conductivity materials with wide bandgap semiconductors as a viable pathway to improve heat dissipation.  We will discuss the important role that interfaces play in enabling the integration of materials such CVD diamond, AlN, and SiC while supporting enhanced heat dissipation. We will present results on the use of new interlayers to reduce the thermal boundary conductance between diamond and nitride semiconductors.  We will also discuss early results on the development of AlN as a semiconductor with promise for future power device applications.  Overall, we will demonstrate the role of modeling in helping to advance the design of thermal solutions for these architectures. Finally, we will discuss the improvements in measurement techniques that allow for the characterization of complex interfaces being developed for advanced nitride rf and power electronics.

Biographical Sketch: Dr. Samuel Graham is the Nariman Farvardin Professor and Dean of Engineering at the University of Maryland.  Prior to joining the University of Maryland, he was a professor and chair of the Woodruff School of Mechanical Engineering at the Georgia Institute of Technology. He holds a joint appointment with the National Renewable Energy Laboratory, serves on the Emerging Technologies Technical Advisory Committee for the U.S. Department of Commerce, the Department of Navy S&T Board, and the Advisory Committee for the Engineering Directorate of NSF.  His research expertise is in the thermal characterization and reliability of wide bandgap semiconductor technologies and the packaging of organic and flexible electronics.

  Solar Thermochemical Hydrogen Production Using Redox Active Materials

Date: October 31, 2025; Time: 2:30 PM Location: PWEB 175

Abstract: Hydrogen is a valuable widely used chemical and an essential component in renewable fuels. Steam-methane reforming is currently used to produce low-cost “grey” hydrogen, that can be turned “blue” by capturing and storing CO2 at extra cost. “Green” hydrogen can be produced via electrolysis at much higher cost. Efforts are underway to advance photosynthesis.  Thermochemical methods, in which high temperature non-stoichiometric reduction of metal oxides is followed by lower temperature oxidation using steam, have the potential to reduce the cost and operate at high-capacity factor. The same technology can also reduce CO2 and produce syngas; an essential feedstock for SAF and efuels. This however requires innovations in redox materials, reactor design and system’s integration. I will introduce the technology and our recent advancements. Ceria is the gold standard because of its stability, but its reduction temperature is high and oxygen carrying capacity is low. Effort to develop alternatives, mostly pervoskites, are underway. Significant reduction-oxidation temperature swing makes it necessary to recover most of the sensible heat. We have designed systems employing multiple reactors that circulate between the two stages to maximize regenerative heat recovery. Generating deep vacuum for reduction, a costly endeavor, can be accomplished by staged oxygen evacuation and novel thermochemical or electrochemical pumping technologies. System level analysis shows that: separation energy should be minimized using, e.g., membrane systems; and waste heat recovery on the exothermic oxidation side should be used to produce electricity to power auxiliary components. To enable continuous operations with optimally sized units, specially designed indirectly heated reactors should operate while communicating with thermal energy storage units. A novel system invented at MIT integrates these ideas and is currently undergoing derisking and validation.

Biographical Sketch: Ahmed F. Ghoniem is the Ronald C. Crane Professor of Mechanical Engineering, Director of the Center for Energy and Propulsion Research and the Reacting Gas Dynamics Laboratory. He received his B.Sc. and M.Sc. degree from Cairo University, and Ph.D. at the University of California, Berkeley. His research covers computational engineering, turbulence and combustion, multiphase flow, clean energy technologies with focus on oxy-combustion for CO2 capture, renewable energy, biofuel and solar fuel production. He supervised more than 120 graduate students and post-doctoral students; published more than 500 articles in leading journals and conferences; and consulted for the aerospace, automotive and energy industry. He is fellow of the ASME, the APS, and the Combustion Institute. He received several awards including the ASME James Harry Potter Award in Thermodynamics, the AIAA Propellant and Combustion Award, the KAUST Investigator Award, the “Committed to Caring Professor” at MIT and the Combustion Institute Bernard Lewis Gold Medal.

Cryogenic Fluid Management Technologies at Creare

Date: October 3, 2025; Time: 2:30 PM Location: PWEB 175

Abstract: Creare LLC is a small business of 190 employees in Hanover, New Hampshire.  The company has been in operation since 1961 focusing on research and development of highly engineered technologies and products.  Creare has a broad technology portfolio but a consistent business area since inception has been thermal and fluid management systems.  During the last 4 decades, we have worked on space-borne cryocoolers and cryogenic fluid/thermal management to support NASA’s space science and exploration initiatives.  More recently, we have worked on cryogenic cooling systems for detectors in proliferated space architectures for earth science and missile defense.  In today’s presentation, Dr. Zagarola will provide an overview of Creare’s work on cryocoolers and cryogenic fluid management devices, and the associated technical challenges with making these devices for space.

Biographical Sketch: Dr. Zagarola is a Principal Engineer and Partner at Creare LLC.  Since joining Creare in 1995, he has focused his efforts on the development of cryocoolers, advanced space-flight thermal management hardware, and cryocooler control electronics. He currently leads Creare’s cryocooler business area. During his tenure, he has provided programmatic and technical leadership to many cryocooler development activities including turbo-Brayton and J-T cryocoolers, the development of turbo-Brayton technologies such as advanced recuperators and gas bearing turbomachines, and development of cryocooler drive electronics.  He was chairman of the 20th International Cryocooler Conference (ICC), served on the boards of the ICC and Cryogenic Society of America, and was a technical editor for several volumes of Advances in Cryogenic Engineering. In 2024, he received the ICC Exceptional Service Award for his long-time contributions to the ICC and the cryogenic community.  Mark has authored or coauthored over 80 papers documenting his work in the field of cryogenics.

Dr. Zagarola received his B.S.M.E degree from Rutgers University and his M.S.M.E and Ph.D. degrees from Princeton University.  While at Princeton University, Dr. Zagarola designed, planned, and implemented a unique, 28 ton, pipe flow facility that provided accurate data at Reynolds number over one order of magnitude larger than previous experiments. Data that he acquired and theories that he proposed provided new insights into the scaling of wall-bounded shear flows.

Time series based robust damage and fault diagnosis for engineering structures and systems under uncertainty

Date: September 26, 2025; Time: 2:30 PM Location: PWEB 175

Abstract: The problem of damage and fault diagnosis for structures and engineering systems operating under uncertainty is addressed via statistical time series based methods. A critical overview of the main principles, underlying assumptions, and available approaches is presented. The issue of robustness, arising from the need for counteracting the effects of uncertainty, including that due to varying Environmental and Operational Conditions (EOCs) and populations of similar structures and systems, is demonstrated. The main approaches for achieving robustness are presented, with emphasis on conceptual and practical simplicity, ease of use, operation with a low number of sensors and limited numbers of training signals, physical interpretability, and the achievement of high-performance even for early faults. The novel holistic Functional Model (FM) based method, within which the subproblems of damage/fault detection, precise localization, and level estimation may be seamlessly integrated, is then introduced and its various forms are discussed. Application case studies, pertaining to damage diagnosis for engineering structures and systems under uncertainty are presented, with diagnostic performance systematically assessed. The presentation concludes with remarks on the status of the technology and future perspectives.

Biographical Sketch: Spilios Fassois is Professor and Founding Director of the Stochastic Mechanical Systems and Automation (SMSA) Laboratory at the University of Patras, Greece. He previously served on the faculty of the University of Michigan – Ann Arbor. His research interests include stochastic mechanical and aeronautical systems, statistical time series methods, data-based modeling, diagnostics, Structural Health Monitoring, and Machine Learning with applications on structural, vehicular, aeronautical, and other engineering systems. He is the recipient of the 2023 `Evangelos Papanoutsos Excellence in Teaching Award’ at the University of Patras, the 1990 `Excellence in Teaching Award of the College of Engineering’ at the University of Michigan, and various other awards and distinctions. He is Editor-in-Chief for the Journal of Mechanical Systems and Signal Processing (MSSP), Board Member for additional international journals, and Scientific Committee member for numerous international conferences. He has given numerous Keynote and other invited presentations, has organized 5 Thematic Issues for esteemed international journals, and published over 320 articles in technical journals, conference proceedings, and encyclopedias, with his work being supported by industry and national/international funding agencies.

Hybrid-Electric Propulsion System For Commercial And Military Aircrafts

Date: September 19, 2025; Time: 2:30 PM Location: PWEB 175

Abstract: Decarbonizing long-haul air travel is essential to climate change mitigation but remains difficult because present alternatives to fossil fuels are constrained by energy density, mass, packaging, infrastructure, manufacturing readiness, and entrenched operating practices. Hybrid-electric propulsion offers a pragmatic near term pathway by pairing high-specific-energy liquid fuels with electric machines and power electronics to cut fuel burn and emissions while enabling novel engine airframe integration. Our discussions examines how the aerospace and defense start-up Marc-Antoni is developing a hybrid-electric propulsion system for single-aisle aircraft and evaluate its commercial viability across performance, weight, safety, certification, maintainability, and cost. The analysis focuses on core technologies, high efficiency generators and motors, propulsion system configurations, energy storage, and outlines a maturation roadmap. Our discussions also assesses defense applications. Confronted by growing threats from unmanned aerial systems and advanced missiles, the U.S. military is increasing its demand for non-kinetic, high-speed effects such as directed-energy weapons. These systems are limited by onboard power generation, power quality, and heat rejection. We will explore hybrid-electric architectures which could be adapted to combat aircrafts to provide higher continuous and pulsed electrical power with improved thermal margins, thereby enabling advanced electronic warfare and directed-energy capabilities.

Biographical Sketch: Ric Duncanson, a serial tech entrepreneur, is the founder of Marc-Antoni, an aerospace & defense start-up developing hybrid electric propulsion systems for civil and military aviation applications. Ric is an expert in technology transfer and the evaluation of intellectual property for commercialization, as evidenced by his acquisition of over 10 patents, ranging from lithium-ion cell components to a novel turbofan design. From 2017 to 2020, Ric was a member of the New York Institute of Technology (NYIT) Entrepreneurship and Technology Innovation Center (ETIC) program where he developed a robotic steering system for high-performance autonomous vehicles, as well as a four-motor full-torque vectoring all-wheel-drive system for high-performance electric race cars. Currently, Marc-Antoni is a member of the University of Connecticut (UConn) Technology Incubator Program (TIP), where the company is developing several research & development projects, including Titanium Niobium Oxide (TNO) lithium-ion cell, partially superconducting machines, and a superconducting turbofan. Although not a formally trained engineer or scientist, Ric considers himself an autodidact, having cultivated profound expertise in the engineering and scientific principles of the various subject matters associated with his innovations.