Thermal Characterization of Heat Transfer Fluids for Data Center Cooling

A Multi-Property Approach to Figure of Merit Analysis Special Guest Speakers: Bret Timme, Electrical Engineer at Soltex, specializing in liquid cooling for data center applications Wasif Altaf, Industrial Rheology Lab, specializing in physical property characterization of fluids In this collaborative webinar, Bret Trim of Soltex and Wasif Altaf of Industrial Rheology Lab join C-Therm to deliver a rigorous, multi-disciplinary examination of heat transfer fluid characterization for data center liquid cooling, from individual property measurements to an integrated Figure of Merit (FOM) framework for fluid selection and benchmarking. From Individual Properties to a Figure of Merit Effective fluid selection demands more than a single number. This session frames thermal conductivity and specific heat capacity, characterized by C-Therm, alongside density, viscosity, and coefficient of thermal expansion (CTE), measured by Industrial Rheology Lab, as a unified property dataset. Attendees will learn how these properties combine to define a fluid's Figure of Merit: a quantitative, physics-grounded index that enables direct, apples-to-apples comparison of candidate fluids under real operating conditions. The session will examine how each property contributes to FOM and how measurement methodology and uncertainty propagate through to fluid ranking decisions. Thermal Property Characterization: Thermal Conductivity and Specific Heat Capacity C-Therm will present the methods and results for thermal conductivity and specific heat capacity measurement across the candidate fluid set, including measurement approach, temperature dependence, and how these properties interact with system-level performance parameters such as heat transfer coefficient and thermal resistance. Attendees will develop a clear understanding of what these measurements mean physically, how they are obtained with confidence, and what thresholds matter in the context of single-phase and two-phase cooling architectures. Physical Property Characterization: Density, Viscosity, and CTE Wasif Altaf from Industrial Rheology Lab will present the complementary physical property dataset, density, dynamic and kinematic viscosity, and coefficient of thermal expansion, for the same fluid candidates. This section will address measurement methodology, temperature and shear dependencies relevant to cooling system design, and how these properties interact with pumping power, flow regime, and mechanical system constraints. Real-World Context: Soltex Fluid Selection and Deployment Bret Trim will ground the multi-property analysis in Soltex's field experience with liquid-cooled data center deployments. Drawing on real-world fluid selection decisions, Bret will illustrate how the FOM framework applies in practice, which properties drove decisions, how candidate fluids ranked under real operating conditions, and what the deployment outcomes revealed about the predictive value of the characterization approach. Engineering Takeaways The session closes with a practical framework for materials and thermal engineers: how to structure a multi-property fluid evaluation program, how to weight FOM components for specific application architectures, and how to integrate characterization data into a defensible selection methodology. Attendees will leave with both a deeper understanding of fluid physics and a structured approach to data-driven fluid qualification. Keywords: thermal conductivity, specific heat capacity, heat transfer fluids, liquid cooling, data center cooling, Figure of Merit, FOM, fluid characterization, multi-property measurement, dielectric fluids, immersion cooling, cold plate cooling, single-phase cooling, two-phase cooling, polyalphaolefin, synthetic fluids, thermal resistance, viscosity, density, coefficient of thermal expansion, CTE, heat transfer coefficient, pumping power, fluid benchmarking, thermal management, fluid chemistry, cooling system optimization, power density, high-performance computing, HPC cooling, AI data centers, fluid selection, materials engineering, Soltex, Industrial Rheology Lab, fluid rheology, thermophysical properties, property database, fluid ranking