Microscopic Forces and Flows due to Temperature Gradients

Nano-scale fluid flow is unlike transport on the macro-scale. Pressure gradients typically dominate effects on a large scale while thermal gradients contribute negligibly to the motion of fluid. The situation entirely reverses on the nano-scale. At a microscopic level, flows induced by thermal gradients are caused by forces that act on atoms or molecules near an interface. These thermo-osmotic forces cannot, at present, be derived analytically or measured experimentally. Clearly, it would be useful to calculate these forces via molecular simulations, but direct approaches fail because in the steady-state, the average force per particle vanishes, as the thermo-osmotic force is balanced by a gradient in shear stress. In our journey to indirectly calculate the osmotic force, we met another unknown in the field of molecular theory at interfaces: the microscopic pressure tensor. The latter is an open problem since the microscopic pressure near an interface is not uniquely defined. Using local thermodynamics theories, we relate the thermo-osmotic force to the gradient of the microscopic pressure tensor. Yet, because the pressure is not uniquely defined, we arrive at multiple answers for the thermo-osmotic force, where at most one can be correct. To resolve the latter puzzle, we develop a direct, non-equilibrium simulation protocol to measure the thermo-osmotic force, whereby a thermal gradient is imposed and the osmotic force is measured by eliminating the shear force. Surprisingly, we find  that the osmotic force cannot be derived from the gradient of well-known microscopic pressure expressions. We, therefore, derive a thermodynamic expression that gets close. In this work, we report the first, direct calculation of the thermo-osmotic force while simultaneously showing that standard microscopic pressure expressions fail to predict pressure gradients.Raymond and Beverly Sackler Fund for the Physics of Medicin

Hamiltonian Transformation to Compute Thermo-osmotic Forces.

If a thermal gradient is applied along a fluid-solid interface, the fluid experiences a thermo-osmotic force. In the steady state, this force is balanced by the gradient of the shear stress. Surprisingly, there appears to be no unique microscopic expression that can be used for computing the magnitude of the thermo-osmotic force. Here we report how, by treating the mass M of the fluid particles as a tensor in the Hamiltonian, we can eliminate the balancing shear force in a nonequilibrium simulation and therefore compute the thermo-osmotic force at simple solid-fluid interfaces. We compare the nonequilibrium force measurement with estimates of the thermo-osmotic force based on computing gradients of the stress tensor. We find that the thermo-osmotic force as measured in our simulations cannot be derived from the most common microscopic definitions of the stress tensor

Dynamic clustering regulates activity of mechanosensitive membrane channels

Experiments have suggested that bacterial mechanosensitive channels separate into 2D clusters, the role of which is unclear. By developing a coarse-grained computer model we find that clustering promotes the channel closure, which is highly dependent on the channel concentration and membrane stress. This behaviour yields a tightly regulated gating system, whereby at high tensions channels gate individually, and at lower tensions the channels spontaneously aggregate and inactivate. We implement this positive feedback into the model for cell volume regulation, and find that the channel clustering protects the cell against excessive loss of cytoplasmic content

Pressure gradients fail to predict diffusio-osmosis.

We present numerical simulations of diffusio-osmotic flow, i.e. the fluid flow generated by a concentration gradient along a solid-fluid interface. In our study, we compare a number of distinct approaches that have been proposed for computing such flows and compare them with a reference calculation based on direct, non-equilibrium molecular dynamics simulations. As alternatives, we consider schemes that compute diffusio-osmotic flow from the gradient of the chemical potentials of the constituent species and from the gradient of the component of the pressure tensor parallel to the interface. We find that the approach based on treating chemical potential gradients as external forces acting on various species agrees with the direct simulations, thereby supporting the approach of Marbach et al (2017 J. Chem. Phys. 146 194701). In contrast, an approach based on computing the gradients of the microscopic pressure tensor does not reproduce the direct non-equilibrium results.European Union ( European Training Network NANOTRANS Grant 674979)

Microscopic Marangoni Flows Cannot Be Predicted on the Basis of Pressure Gradients.

A concentration gradient along a fluid-fluid interface can cause flow. On a microscopic level, this so-called Marangoni effect can be viewed as being caused by a gradient in the pressures acting on the fluid elements or as the chemical-potential gradients acting on the excess densities of different species at the interface. If the interface thickness can be ignored, all approaches should result in the same flow profile away from the interface. However, on a more microscopic scale, the different expressions result in different flow profiles, only one of which can be correct. Here we compare the results of direct nonequilibrium molecular dynamics simulations with the flows that are generated by pressure and chemical-potential gradients. We find that the approach based on the chemical-potential gradients agrees with the direct simulations, whereas the calculations based on the pressure gradients do not

Vibrational and structural signatures of the crossover between dense glassy and sparse gel-like attractive colloidal packings

We investigate the vibrational modes of quasi-two-dimensional disordered colloidal packings of hard colloidal spheres with short-range attractions as a function of packing fraction. Certain properties of the vibrational density of states (vDOS) are shown to correlate with the density and structure of the samples (i.e., in sparsely versus densely packed samples). Specifically, a crossover from dense glassy to sparse gel-like states is suggested by an excess of phonon modes at low frequency and by a variation in the slope of the vDOS with frequency at low frequency. This change in phonon mode distribution is demonstrated to arise largely from localized vibrations that involve individual and/or small clusters of particles with few local bonds. Conventional order parameters and void statistics did not exhibit obvious gel-glass signatures as a function of volume fraction. These mode behaviors and accompanying structural insights offer a potentially new set of indicators for identification of glass-gel transitions and for assignment of gel-like versus glass-like character to a disordered solid material

How the T cell signaling network processes information to discriminate between self and agonist ligands

© 2020 National Academy of Sciences. All rights reserved. T cells exhibit remarkable sensitivity and selectivity in detecting and responding to agonist peptides (p) bound to MHC molecules in a sea of self pMHC molecules. Despite much work, understanding of the underlying mechanisms of distinguishing such ligands remains incomplete. Here, we quantify T cell discriminatory capacity using channel capacity, a direct measure of the signaling network's ability to discriminate between antigen-presenting cells (APCs) displaying either self ligands or a mixture of self and agonist ligands. This metric shows how differences in information content between these two types of peptidomes are decoded by the topology and rates of kinetic proofreading signaling steps inside T cells. Using channel capacity, we constructed numerically substantiated hypotheses to explain the discriminatory role of a recently identified slow LAT Y132 phosphorylation step. Our results revealed that in addition to the number and kinetics of sequential signaling steps, a key determinant of discriminatory capability is spatial localization of a minimum number of these steps to the engaged TCR. Biochemical and imaging experiments support these findings. Our results also reveal the discriminatory role of early negative feedback and necessary amplification conferred by late positive feedback