Interfacial Layer Breaker: A Violation of Stokes' Law in High-Speed Atomic Force Microscope Flows.

Structured water near surfaces is important in nonclassical crystallization, biomineralization, and restructuring of cellular membranes. In addition to equilibrium structures, studied by atomic force microscopy (AFM), high-speed AFM (H-S AFM) can now detect piconewton forces in microseconds. With increasing speeds and decreasing tip diameters, there is a danger that continuum water models will not hold, and molecular dynamic (MD) simulations would be needed for accurate predictions. MD simulations, however, can only evolve over tens of nanoseconds due to memory and computational efficiency/speed limitations, so new methods are needed to bridge the gap. Here, we report a hybrid, multiscale simulation method, which can bridge the size and time scale gaps to existing experiments. Structured water is studied between a moving silica AFM colloidal tip and a cleaved mica surface. The computational domain includes 1,472,766 atoms. To mimic the effect of long-range hydrodynamic forces occurring in water, when moving the AFM tip at speeds from 5 × 10-7 to 30 m/s, a hybrid multiscale method with local atomistic resolution is used, which serves as an effective open-domain boundary condition. The multiscale simulation is thus equivalent to using a macroscopically large computational domain with equilibrium boundary conditions. Quantification of the drag force shows the breaking of continuum behavior. Nonmonotonic dependence on both the tip speed and distance from the surface implies breaking of the hydration layer around the moving tip at time scales smaller than water cluster formation and strong water compressibility effects at the highest speeds.

A hybrid molecular dynamics/fluctuating hydrodynamics method for modelling liquids at multiple scales in space and time.

A new 3D implementation of a hybrid model based on the analogy with two-phase hydrodynamics has been developed for the simulation of liquids at microscale. The idea of the method is to smoothly combine the atomistic description in the molecular dynamics zone with the Landau-Lifshitz fluctuating hydrodynamics representation in the rest of the system in the framework of macroscopic conservation laws through the use of a single "zoom-in" user-defined function s that has the meaning of a partial concentration in the two-phase analogy model. In comparison with our previous works, the implementation has been extended to full 3D simulations for a range of atomistic models in GROMACS from argon to water in equilibrium conditions with a constant or a spatially variable function s. Preliminary results of simulating the diffusion of a small peptide in water are also reported.

The nut-and-bolt motion of a bacteriophage sliding along a bacterial flagellum: a complete hydrodynamics model.

The 'nut-and-bolt' mechanism of a bacteriophage-bacteria flagellum translocation motion is modelled by numerically integrating the 3D Stokes equations using a Finite-Element Method (FEM). Following the works by Katsamba and Lauga (Phys Rev Fluids 4(1): 013101, 2019), two mechanical models of the flagellum-phage complex are considered. In the first model, the phage fiber wraps around the smooth flagellum surface separated by some distance. In the second model, the phage fiber is partly immersed in the flagellum volume via a helical groove imprinted in the flagellum and replicating the fiber shape. In both cases, the results of the Stokes solution for the translocation speed are compared with the Resistive Force Theory (RFT) solutions (obtained in Katsamba and Lauga Phys Rev Fluids 4(1): 013101, 2019) and the asymptotic theory in a limiting case. The previous RFT solutions of the same mechanical models of the flagellum-phage complex showed opposite trends for how the phage translocation speed depends on the phage tail length. The current work uses complete hydrodynamics solutions, which are free from the RFT assumptions to understand the divergence of the two mechanical models of the same biological system. A parametric investigation is performed by changing pertinent geometrical parameters of the flagellum-phage complex and computing the resulting phage translocation speed. The FEM solutions are compared with the RFT results using insights provided from the velocity field visualisation in the fluid domain.

A physics-based machine learning technique rapidly reconstructs the wall-shear stress and pressure fields in coronary arteries.

With the global rise of cardiovascular disease including atherosclerosis, there is a high demand for accurate diagnostic tools that can be used during a short consultation. In view of pathology, abnormal blood flow patterns have been demonstrated to be strong predictors of atherosclerotic lesion incidence, location, progression, and rupture. Prediction of patient-specific blood flow patterns can hence enable fast clinical diagnosis. However, the current state of art for the technique is by employing 3D-imaging-based Computational Fluid Dynamics (CFD). The high computational cost renders these methods impractical. In this work, we present a novel method to expedite the reconstruction of 3D pressure and shear stress fields using a combination of a reduced-order CFD modelling technique together with non-linear regression tools from the Machine Learning (ML) paradigm. Specifically, we develop a proof-of-concept automated pipeline that uses randomised perturbations of an atherosclerotic pig coronary artery to produce a large dataset of unique mesh geometries with variable blood flow. A total of 1,407 geometries were generated from seven reference arteries and were used to simulate blood flow using the CFD solver Abaqus. This CFD dataset was then post-processed using the mesh-domain common-base Proper Orthogonal Decomposition (cPOD) method to obtain Eigen functions and principal coefficients, the latter of which is a product of the individual mesh flow solutions with the POD Eigenvectors. Being a data-reduction method, the POD enables the data to be represented using only the ten most significant modes, which captures cumulatively greater than 95% of variance of flow features due to mesh variations. Next, the node coordinate data of the meshes were embedded in a two-dimensional coordinate system using the t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm. The reduced dataset for t-SNE coordinates and corresponding vector of POD coefficients were then used to train a Random Forest Regressor (RFR) model. The same methodology was applied to both the volumetric pressure solution and the wall shear stress. The predicted pattern of blood pressure, and shear stress in unseen arterial geometries were compared with the ground truth CFD solutions on "unseen" meshes. The new method was able to reliably reproduce the 3D coronary artery haemodynamics in less than 10 s.

Benchmarking of Molecular Dynamics Force Fields for Solid-Liquid and Solid-Solid Phase Transitions in Alkanes.

Accurate prediction of alkane phase transitions involving solids is needed to prevent catastrophic pipeline blockages, improve lubrication formulations, smart insulation, and energy storage, as well as bring fundamental understanding to processes such as artificial morphogenesis. However, simulation of these transitions is challenging and therefore often omitted in force field development. Here, we perform a series of benchmarks on seven representative molecular dynamics models (TraPPE, PYS, CHARMM36, L-OPLS, COMPASS, Williams, and the newly optimized Williams 7B), comparing with experimental data for liquid properties, liquid-solid, and solid-solid phase transitions of two prototypical alkanes, n-pentadecane (C15) and n-hexadecane (C16). We find that existing models overestimate the melting points by up to 34 K, with PYS and Williams 7B yielding the most accurate results deviating only 2 and 3 K from the experiment. We specially design order parameters to identify crystal-rotator phase transitions in alkanes. United-atom models could only produce a rotator phase with complete rotational disorder, whereas all-atom models using a 12-6 Lennard-Jones potential show no rotator phase even when superheated above the melting point. In contrast, Williams (Buckingham potential) and COMPASS (9-6 Lennard-Jones) reproduce the crystal-to-rotator phase transition, with the optimized Williams 7B model having the most accurate crystal-rotator transition temperature of C15.

Disordered protein-graphene oxide co-assembly and supramolecular biofabrication of functional fluidic devices.

Supramolecular chemistry offers an exciting opportunity to assemble materials with molecular precision. However, there remains an unmet need to turn molecular self-assembly into functional materials and devices. Harnessing the inherent properties of both disordered proteins and graphene oxide (GO), we report a disordered protein-GO co-assembling system that through a diffusion-reaction process and disorder-to-order transitions generates hierarchically organized materials that exhibit high stability and access to non-equilibrium on demand. We use experimental approaches and molecular dynamics simulations to describe the underlying molecular mechanism of formation and establish key rules for its design and regulation. Through rapid prototyping techniques, we demonstrate the system's capacity to be controlled with spatio-temporal precision into well-defined capillary-like fluidic microstructures with a high level of biocompatibility and, importantly, the capacity to withstand flow. Our study presents an innovative approach to transform rational supramolecular design into functional engineering with potential widespread use in microfluidic systems and organ-on-a-chip platforms.

Visualising and controlling the flow in biomolecular systems at and between multiple scales: from atoms to hydrodynamics at different locations in time and space.

A novel framework for modelling biomolecular systems at multiple scales in space and time simultaneously is described. The atomistic molecular dynamics representation is smoothly connected with a statistical continuum hydrodynamics description. The system behaves correctly at the limits of pure molecular dynamics (hydrodynamics) and at the intermediate regimes when the atoms move partly as atomistic particles, and at the same time follow the hydrodynamic flows. The corresponding contributions are controlled by a parameter, which is defined as an arbitrary function of space and time, thus, allowing an effective separation of the atomistic 'core' and continuum 'environment'. To fill the scale gap between the atomistic and the continuum representations our special purpose computer for molecular dynamics, MDGRAPE-4, as well as GPU-based computing were used for developing the framework. These hardware developments also include interactive molecular dynamics simulations that allow intervention of the modelling through force-feedback devices.

Concurrent multiscale modelling of atomistic and hydrodynamic processes in liquids.

Fluctuations of liquids at the scales where the hydrodynamic and atomistic descriptions overlap are considered. The importance of these fluctuations for atomistic motions is discussed and examples of their accurate modelling with a multi-space-time-scale fluctuating hydrodynamics scheme are provided. To resolve microscopic details of liquid systems, including biomolecular solutions, together with macroscopic fluctuations in space-time, a novel hybrid atomistic-fluctuating hydrodynamics approach is introduced. For a smooth transition between the atomistic and continuum representations, an analogy with two-phase hydrodynamics is used that leads to a strict preservation of macroscopic mass and momentum conservation laws. Examples of numerical implementation of the new hybrid approach for the multiscale simulation of liquid argon in equilibrium conditions are provided.

Water-Peptide Dynamics during Conformational Transitions.

Transitions between metastable conformations of a dipeptide are investigated using classical molecular dynamics simulation with explicit water molecules. The distribution of the surrounding water at different moments before the transitions and the dynamical correlations of water with the peptide's configurational motions indicate that the water molecules represent an integral part of the molecular system during the conformational changes, in contrast with the metastable periods when water and peptide dynamics are essentially decoupled.