From Nanochannels to Oscillating Heat Pipes: Understanding and Engineering Liquid-Vapor Interfaces for Passive Thermal Management
Event details
| Date | 30.09.2026 |
| Hour | 11:00 › 12:00 |
| Speaker | Prof. Shalabh C. Maroo, Syracuse University |
| Location | |
| Category | Conferences - Seminars |
| Event Language | English |
Abstract
Thermal management of high-power electronics increasingly hinges on how we understand and engineer liquid-vapor interfaces, from the molecular scale to the device scale. This talk presents an experimental and computational body of work spanning three connected threads. First, I will show how the disjoining pressure of water, a near-surface molecular interaction, can be quantified from wicking experiments in silicon-dioxide nanochannels, reaching pressures as high as ~1.5 MPa. Implemented in continuum CFD, this relation predicts bubble nucleation temperatures that match independent experiments, bridging nanoscale physics and continuum simulation. Second, I will describe a route to durable, regenerative superhydrophobic surfaces built on porous-nanochannel geometry, which sustain a stable air plastron that survives high-speed water jets, saltwater, chemicals, freeze-thaw cycling, and month-long submersion. Third, I will turn to oscillating heat pipes (OHPs) as passive two-phase cooling devices, using a glass adiabatic section to isolate the working fluid's true contribution, measuring equivalent thermal conductivities for multiple working fluids, and introducing predictive criteria for OHP operational failure. Finally, I will present a machine-learning (ML) framework that links flow visualization directly to OHP thermal transport. These ML models detect liquid slugs and vapor plugs across 84,000 frames at 90-96% accuracy, and, together with slug-population frequency analysis, produce two thermal-conductivity correlations that collapse distinct working fluids onto a single trend. These tools advance the long-sought but still-unrealized goal of predictive OHP design, a capability increasingly important for managing AI and data-center thermal loads.
About the speaker
Shalabh C. Maroo is a Professor in the Department of Mechanical and Aerospace Engineering at Syracuse University, where he directs the Multiscale Research and Engineering Laboratory. His group works at the intersection of multiscale transport phenomena, thermal management, energy conversion, and water desalination, and using the fundamentals of nanoscience to build efficient macroscale systems, with support from the DoD, NSF, DOE and industry. Before joining Syracuse in 2011, he earned his B.Tech. from IIT Bombay, his M.S. and Ph.D. from University of Florida, and was a postdoctoral associate at MIT. He is the recipient of the NSF CAREER award, and his group’s recent research has appeared in broad-ranging journals such as Nano Letters, Chemical Engineering Journal, ACS Applied Materials & Interfaces, Journal of Colloid and Interface Science, Cell Reports Physical Science, and Applied Thermal Engineering.
Thermal management of high-power electronics increasingly hinges on how we understand and engineer liquid-vapor interfaces, from the molecular scale to the device scale. This talk presents an experimental and computational body of work spanning three connected threads. First, I will show how the disjoining pressure of water, a near-surface molecular interaction, can be quantified from wicking experiments in silicon-dioxide nanochannels, reaching pressures as high as ~1.5 MPa. Implemented in continuum CFD, this relation predicts bubble nucleation temperatures that match independent experiments, bridging nanoscale physics and continuum simulation. Second, I will describe a route to durable, regenerative superhydrophobic surfaces built on porous-nanochannel geometry, which sustain a stable air plastron that survives high-speed water jets, saltwater, chemicals, freeze-thaw cycling, and month-long submersion. Third, I will turn to oscillating heat pipes (OHPs) as passive two-phase cooling devices, using a glass adiabatic section to isolate the working fluid's true contribution, measuring equivalent thermal conductivities for multiple working fluids, and introducing predictive criteria for OHP operational failure. Finally, I will present a machine-learning (ML) framework that links flow visualization directly to OHP thermal transport. These ML models detect liquid slugs and vapor plugs across 84,000 frames at 90-96% accuracy, and, together with slug-population frequency analysis, produce two thermal-conductivity correlations that collapse distinct working fluids onto a single trend. These tools advance the long-sought but still-unrealized goal of predictive OHP design, a capability increasingly important for managing AI and data-center thermal loads.
About the speaker
Shalabh C. Maroo is a Professor in the Department of Mechanical and Aerospace Engineering at Syracuse University, where he directs the Multiscale Research and Engineering Laboratory. His group works at the intersection of multiscale transport phenomena, thermal management, energy conversion, and water desalination, and using the fundamentals of nanoscience to build efficient macroscale systems, with support from the DoD, NSF, DOE and industry. Before joining Syracuse in 2011, he earned his B.Tech. from IIT Bombay, his M.S. and Ph.D. from University of Florida, and was a postdoctoral associate at MIT. He is the recipient of the NSF CAREER award, and his group’s recent research has appeared in broad-ranging journals such as Nano Letters, Chemical Engineering Journal, ACS Applied Materials & Interfaces, Journal of Colloid and Interface Science, Cell Reports Physical Science, and Applied Thermal Engineering.
Practical information
- General public
- Free