[The selection and design of new, sustainable refrigerant mixtures require both high accuracy and fast, efficient calculations. Traditional Helmholtz‑Equation‑of‑State (HEOS) models provide reliable data, but they face two major limitations:
The project will overcome these issues by:
Main objectives
By combining machine‑learning surrogates, advanced molecular simulations, and robust optimization, we will create an efficient, reliable platform for developing climate‑friendly refrigerant mixtures.
In the second funding phase of the SPP, mixtures of long‑chain alkanes are highlighted as promising working fluids. The goal remains to model relevant mixtures while systematically accounting for uncertainties—now not only for equilibrium properties but also for transport properties such as viscosities, which are described using Residual‑Entropy‑Scaling (RES). Uncertainties in the RES parameters and in the residual entropy are quantified with advanced, generalized Bayesian inference methods. Because experimental data are insufficient for development and validation, we supplement them with molecular simulations. The force‑field parametrization is performed simultaneously on the basis of both equilibrium and transport data. To use the viscosity values obtained from the simulations as a reliable reference, we are testing novel approaches for reducing their statistical uncertainty.
Most heating, ventilation, air-conditioning and refrigeration (HVAC&R) applications today employ hydrofluorocarbons (HFC) as working fluids. Though these compounds are potent green house gases as they exhibit a high global warming potential (GWP). Following the Kyoto Protocol to limit the emission of greenhouse gas, phase-out regulations for HFCs with high GWP became effective, which necessitates the adoption of alternative refrigerants. Refrigerant manufacturers have responded to this with the introduction of unsaturated fluorinated or chlorinated compounds as alternative working fluids, i.e hydrofluoroolefins (HFO) and hydrochlorofluoroolefins (HCFO).
The exploration of the performance of new working fluids in potential technical applications requires a detailed knowledge of their thermophysical properties over a wide range of state points. As the commercialization of this new class of working fluids is in its early stage, experimental data on the thermophysical properties on newly introduced HFO or HCFO compounds are rare. This is especially true for mixtures, i.e. potential refrigerant blends.
We have therefore developed a transferable force field for HFO and HCFO compounds to enable reliable predictions of the properties of these components and their mixtures by molecular simulations. We are thereby closely cooperating with experimental and modelling research groups worldwide such as Ryo Akasaka (Kyushu Sangyo University, Japan) , Eric Lemmon (NIST, USA) or Eric May (University of Western Australia).
The simulation results are applied worldwide, for instance for the development of highly accurate empirical equations of state (EOS) for these compounds, or of mixing models to describe refrigerant blends.The simulation results are also used in the simulation program REFPROP from the NIST, which is widely used in the refrigeration industry. In our group, we are employing the simulation data to parameterize the PC(P)-SAFT EOS to also allow for the modelling of these new refrigerants and blends by a physically based molecular equation of state.
Refrigerant-Lubricant Interactions
The aim of a newly funded project is a detailed understanding of the molecular mechanism of refrigerant-lubricants interactions, which is of fundament importance and high topicality for the development of efficient HVAC&R systems. For the first time, a systematic analysis of the fundamental interaction mechanisms between different current refrigerants and varying lubricants structures will be performed by molecular simulations.
Based on the simulation results a detailed analysis on the relation of molecular interactions and structures in mixture and the resulting properties such as solubility and viscosity will be performed to identify the relevant molecular interaction pattern in refrigerant-lubricant pairs. The results of the project will provide the scientific basis for the development of future refrigerant-lubricant pairs for sustainable HVAC&R systems.
