Dependency of active pressure and equation of state on stiffness of wall

Autonomous motion and motility are hallmarks of active matter. Active agents, such as biological cells and synthetic colloidal particles, consume internal energy or extract energy from the environment to generate self-propulsion and locomotion. These systems are persistently out of equilibrium due to continuous energy consumption. It is known that pressure is not always a state function for generic active matter. Torque interaction between active constituents and confinement renders the pressure of the system a boundary-dependent property. The mechanical pressure of anisotropic active particles depends on their microscopic interactions with a solid wall. Using self-propelled dumbbells confined by solid walls as a model system, we perform numerical simulations to explore how variations in the wall stiffness influence the mechanical pressure of dry active matter. In contrast to previous findings, we find that mechanical pressure can be independent of the interaction of anisotropic active particles with walls, even in the presence of intrinsic torque interaction. Particularly, the dependency of pressure on the wall stiffness vanishes when the stiffness is above a critical level. In such a limit, the dynamics of dumbbells near the walls are randomized due to the large torque experienced by the dumbbells, leading to the recovery of pressure as a state variable of density.

Entropy and Entropic Forces to Model Biological Fluids

Living cells are complex systems characterized by fluids crowded by hundreds of different elements, including, in particular, a high density of polymers. They are an excellent and challenging laboratory to study exotic emerging physical phenomena, where entropic forces emerge from the organization processes of many-body interactions. The competition between microscopic and entropic forces may generate complex behaviors, such as phase transitions, which living cells may use to accomplish their functions. In the era of big data, where biological information abounds, but general principles and precise understanding of the microscopic interactions is scarce, entropy methods may offer significant information. In this work, we developed a model where a complex thermodynamic equilibrium resulted from the competition between an effective electrostatic short-range interaction and the entropic forces emerging in a fluid crowded by different sized polymers. The target audience for this article are interdisciplinary researchers in complex systems, particularly in thermodynamics and biophysics modeling.

Structure of benzothiadiazine at zwitterionic phospholipid cell membranes

The use of drugs derived from benzothiadiazine, which is a bicyclic heterocyclic benzene derivative, has become a widespread treatment for diseases such as hypertension (treated with diuretics such as bendroflumethiazide or chlorothiazide), low blood sugar (treated with non-diuretic diazoxide) or the human immunodeficiency virus, among others. In this work we have investigated the interactions of benzothiadiazine with the basic components of cell membranes and solvents such as phospholipids, cholesterol, ions and water. The analysis of the mutual microscopic interactions is of central importance to elucidate the local structure of benzothiadiazine as well as the mechanisms responsible for the access of benzothiadiazine to the interior of the cell. We have performed molecular dynamics simulations of benzothiadiazine embedded in three different model zwitterionic bilayer membranes made by dimyristoilphosphatidylcholine, dioleoylphosphatidylcholine, 1,2- dioleoyl-sn-glycero-3-phosphoserine and cholesterol inside aqueous sodium-chloride solution in order to systematically examine microscopic interactions of benzothiadiazine with the cell membrane at liquid-crystalline phase conditions. From data obtained through radial distribution functions, hydrogen-bonding lengths and potentials of mean force based on reversible work calculations, we have observed that benzothiadiazine has a strong affinity to stay at the cell membrane interface although it can be fully solvated by water in short periods of time. Furthermore, benzothiadiazine is able to bind lipids and cholesterol chains by means of single and double hydrogen-bonds of different characteristic lengths.

Entropy and Entropic Forces to Model Biological Fluids

Living cells are complex systems that may be characterized by fluids crowded by hundreds of different elements in particular by a high density of polymers; they are an excellent and challenging laboratory to study exotic emerging physical phenomena where entropic forces emerge from organization processes of many-body interactions. The competition between microscopic and entropic forces may generate complex behaviors like phase transitions that living cells may use to accomplish their functions. In the era of the big data, when biological information abounds but general principles and precise understanding of the microscopic interactions scarce, the entropy methods may offer significant information. In this work we develop a model where the thermodynamic equilibrium results from the competition between an effective electrostatic shortrange interaction and the entropic forces emerging in a fluid crowded by different size polymers. The target audience for this article are interdisciplinary researchers in complex systems, particularly in thermodynamics and biophysics modeling.

SAV Operations on a Bus Line Corridor: Travel Demand, Service Frequency, and Vehicle Size

Before shared automated vehicles (SAVs) can be widely adopted, they are anticipated to be implemented commercially in confined regions or fixed routes where the benefits of automation can be realized. SAVs have the potential to operate in a traditional transit corridor, replacing conventional transit vehicles, and have frequent interactions with riders and other vehicles sharing the same right of way. This paper microsimulates SAVs’ operation on a 6.5-mile corridor to understand how vehicle size and attributes of such SAV-based transit affect traffic, transit riders, and system costs. The SUMO (Simulation of Urban MObility) platform is employed to model microscopic interactions among SAVs, transit passengers, and other traffic. Results show that the use of smaller, but more frequent, SAVs leads to reduced passenger waiting times but increased vehicle travel times. More frequent services of smaller SAVs do not, in general, significantly affect general traffic due to shorter dwell times. Overall, using smaller SAVs instead of the large 40-seat SAVs can reduce system costs by up to 4% while also reducing passenger waiting times, under various demand levels and passenger loading factors. However, the use of 5-seat SAVs does not always have the lowest system costs.

Graph neural networks for an accurate and interpretable prediction of the properties of polycrystalline materials

Various machine learning models have been used to predict the properties of polycrystalline materials, but none of them directly consider the physical interactions among neighboring grains despite such microscopic interactions critically determining macroscopic material properties. Here, we develop a graph neural network (GNN) model for obtaining an embedding of polycrystalline microstructure which incorporates not only the physical features of individual grains but also their interactions. The embedding is then linked to the target property using a feed-forward neural network. Using the magnetostriction of polycrystalline Tb0.3Dy0.7Fe2 alloys as an example, we show that a single GNN model with fixed network architecture and hyperparameters allows for a low prediction error of ~10% over a group of remarkably different microstructures as well as quantifying the importance of each feature in each grain of a microstructure to its magnetostriction. Such a microstructure-graph-based GNN model, therefore, enables an accurate and interpretable prediction of the properties of polycrystalline materials.

Viscoelastic Networks: Forming Cells and Tissues

Spatiotemporal changes in viscoelasticity are a key component of the morphogenesis of living systems. Experimental and theoretical findings suggest that cellular- and tissue-scale viscoelasticity can be understood as a collective property emerging from macromolecular and cellular interactions, respectively. Linking the changes in the structural or material properties of cells and tissues, such as material phase transitions, to the microscopic interactions of their constituents, is still a challenge both at the experimental and theoretical level. In this review, we summarize work on the viscoelastic nature of cytoskeletal, extracellular and cellular networks. We then conceptualize viscoelasticity as a network theory problem and discuss its applications in several biological contexts. We propose that the statistical mechanics of networks can be used in the future as a powerful framework to uncover quantitatively the biomechanical basis of viscoelasticity across scales.

Internal OH− induced cascade quenching of upconversion luminescence in NaYF4:Yb/Er nanocrystals

Internal hydroxyl impurity is known as one of the main detrimental factors affecting the upconversion (UC) efficiency of upconversion luminescence (UCL) nanomaterials. Different from surface/ligand-related emission quenching which can be effectively diminished by, e.g., core/shell structure, internal hydroxyl is easy to be introduced in synthesis but difficult to be quantified and controlled. Therefore, it becomes an obstacle to fully understand the relevant UC mechanism and improve UC efficiency of nanomaterials. Here we report a progress in quantifying and large-range adjustment of the internal hydroxyl impurity in NaYF4 nanocrystals. By combining the spectroscopy study and model simulation, we have quantitatively unraveled the microscopic interactions underlying UCL quenching between internal hydroxyl and the sensitizers and activators, respectively. Furthermore, the internal hydroxyl-involved UC dynamical process is interpreted with a vivid concept of “Survivor effect,” i.e., the shorter the migration path of an excited state, the larger the possibility of its surviving from hydroxyl-induced quenching. Apart from the consistent experimental results, this concept can be further evidenced by Monte Carlo simulation, which monitors the variation of energy migration step distribution before and after the hydroxyl introduction. The new quantitative insights shall promote the construction of highly efficient UC materials.