In this work, we propose a generic and simple definition of a line separating gas-like and liquid-like fluid behaviors from the standpoint of shear viscosity. This definition is valid even for fluids such as the hard sphere and the inverse power law that exhibit a unique fluid phase. We argue that this line is defined by the location of the minimum of the macroscopically scaled viscosity when plotted as a function of the excess entropy, which differs from the popular Widom lines. For hard sphere, Lennard-Jones, and inverse-power-law fluids, such a line is located at an excess entropy approximately equal to −2/3 times Boltzmann’s constant and corresponds to points in the thermodynamic phase diagram for which the kinetic contribution to viscosity is approximately half of the total viscosity. For flexible Lennard-Jones chains, the excess entropy at the minimum is a linear function of the chain length. This definition opens a straightforward route to classify the dynamical behavior of fluids from a single thermodynamic quantity obtainable from high-accuracy thermodynamic models.

In this work, the thermodynamic scaling framework has been used to emphasize the limitations of fully flexible coarse grained molecular models to yield shear viscosity of real liquids. In particular, extensive molecular dynamics simulations have confirmed that, while being reasonable to describe the viscosity of short normal alkanes, the fully flexible Lennard-Jones and Mie chains force fields are inadequate to capture the density dependence of shear viscosity of medium to long alkanes. In addition, it is shown that such a weakness in terms of coarse grained molecular models can be readily quantified by using the thermodynamic scaling framework. As a simple alternative to these force fields, it is demonstrated that the insertion of a variable intramolecular rigidity in the Lennard-Jones chains model exhibits promising results to model medium to long chain-like real fluids from both thermodynamic and viscosity points of view.

Integrating microbial activity into underground hydrogen storage models is crucial for simulating long-term reservoir behavior. In this work, we present a coupled framework that incorporates bio-geochemical reactions and compositional flow models within the Matlab Reservoir Simulation Toolbox (MRST). Microbial growth and decay are modeled using a double Monod formulation, with populations influenced by hydrogen and carbon dioxide availability. First, a refined Equation of State (EoS) is employed to accurately capture hydrogen dissolution, thereby improving phase behavior and modeling of microbial activity. The model is then discretized using a cell-centered finite-volume method with implicit Euler time discretization. A fully coupled fully implicit strategy is considered. Our implementation builds upon MRST's compositional module by incorporating the Søreide-Whitson EoS, microbial reaction kinetics, and specific effects such as bio-clogging and molecular diffusion. Through a series of 1D, 2D and 3D simulations, we analyze the effects of microbial-induced bio-geochemical transformations on underground hydrogen storage in porous media.These results highlight that accounting for bio-geochemical effects can substantially impact hydrogen loss, purity, and overall storage performance.