Harvesting Energy from Changes in Relative Humidity Using Nanoscale Water Capillary Bridges.

We show that nanoscale water capillary bridges (WCB) formed between patchy surfaces can extract energy from the environment when subjected to changes in relative humidity (RH). Our results are based on molecular dynamics simulations combined with a modified version of the Laplace-Kelvin equation, which is validated using the nanoscale WCB. The calculated energy density harvested by the nanoscale WCB is relevant, ≈1700 kJ/m3, and is comparable to the energy densities harvested using available water-responsive materials that expand and contract due to changes in RH.

Generic maximum-valence model for fluid polyamorphism.

Recently, a maximal-valence model has been proposed to model a liquid-liquid phase transition induced by polymerization in sulfur. In this paper we present a simple generic model to describe liquid polyamorphism in single-component fluids using a maximum-valence approach for any arbitrary coordination number. The model contains three types of interactions: (i) atoms attract each other by van der Waals forces that generate a liquid-gas transition at low pressures, (ii) atoms may form covalent bonds that induce association, and (iii) additional repulsive forces between atoms with maximal valence and atoms with any valence. This additional repulsion generates liquid-liquid phase separation and the region of the negative heat expansion coefficient (density anomaly) on a P-T phase diagram. We show the existence of liquid-liquid phase transitions for dimerization, polymerization, gelation, and network formation for corresponding coordination numbers z=1,2,...,6 and discuss the limits of this generic model for producing fluid polyamorphism.

Interfacial Properties of Fluids Exhibiting Liquid Polyamorphism and Water-Like Anomalies.

It has been hypothesized that liquid polyamorphism, the existence of multiple amorphous states in a single-component substance, may be caused by molecular or supramolecular interconversion. A simple microscopic model [Caupin and Anisimov, Phys. Rev. Lett. 2021, 127, 185701] introduces interconversion in a compressible binary lattice to generate various thermodynamic scenarios for fluids that exhibit liquid polyamorphism and/or water-like anomalies. Using this model, we demonstrate the dramatic effects of interconversion on the interfacial properties. In particular, we find that the liquid-vapor surface tension exhibits either an inflection point or two extrema in its temperature dependence. Correspondingly, we observe anomalous behavior of the interfacial thickness and a significant shift in the location of the concentration profile with respect to the location of the density profile.

Formation of dissipative structures in microscopic models of mixtures with species interconversion.

The separation of substances into different phases is ubiquitous in nature and important scientifically and technologically. This phenomenon may become drastically different if the species involved, whether molecules or supramolecular assemblies, interconvert. In the presence of an external force large enough to overcome energetic differences between the interconvertible species (forced interconversion), the two alternative species will be present in equal amounts, and the striking phenomenon of steady-state, restricted phase separation into mesoscales is observed. Such microphase separation is one of the simplest examples of dissipative structures in condensed matter. In this work, we investigate the formation of such mesoscale steady-state structures through Monte Carlo and molecular dynamics simulations of three physically distinct microscopic models of binary mixtures that exhibit both equilibrium (natural) interconversion and a nonequilibrium source of forced interconversion. We show that this source can be introduced through an internal imbalance of intermolecular forces or an external flux of energy that promotes molecular interconversion, possible manifestations of which could include the internal nonequilibrium environment of living cells or a flux of photons. The main trends and observations from the simulations are well captured by a nonequilibrium thermodynamic theory of phase transitions affected by interconversion. We show how a nonequilibrium bicontinuous microemulsion or a spatially modulated state may be generated depending on the interplay between diffusion, natural interconversion, and forced interconversion.

Cascading traffic jamming in a two-dimensional Motter and Lai model.

We study the cascading traffic jamming on a two-dimensional random geometric graph using the Motter and Lai model. The traffic jam is caused by a localized attack incapacitating a circular region or a line of a certain size, as well as a dispersed attack on an equal number of randomly selected nodes. We investigate if there is a critical size of the attack above which the network becomes completely jammed due to cascading jamming, and how this critical size depends on the average degree 〈k〉 of the graph, on the number of nodes N in the system, and the tolerance parameter α of the Motter and Lai model.

Modeling fluid polyamorphism through a maximum-valence approach.

We suggest a simple model to describe polyamorphism in single-component fluids using a maximum-valence approach. The model contains three types of interactions: (i) Atoms attract each other by van der Waals forces that generate a liquid-gas transition at low pressures, (ii) atoms may form covalent bonds that induce association, and (iii) atoms with maximal valence attract or repel each other stronger than other atoms, thus generating liquid-liquid separation. As an example, we qualitatively compare this model with the behavior of liquid sulfur and show that condition (iii) generates a liquid-liquid phase transition in addition to the liquid-gas phase transition.

Efficient network immunization under limited knowledge.

Targeted immunization of centralized nodes in large-scale networks has attracted significant attention. However, in real-world scenarios, knowledge and observations of the network may be limited, thereby precluding a full assessment of the optimal nodes to immunize (or quarantine) in order to avoid epidemic spreading such as that of the current coronavirus disease (COVID-19) epidemic. Here, we study a novel immunization strategy where only n nodes are observed at a time and the most central among these n nodes is immunized. This process can globally immunize a network. We find that even for small n (≈10) there is significant improvement in the immunization (quarantine), which is very close to the levels of immunization with full knowledge. We develop an analytical framework for our method and determine the critical percolation threshold p c and the size of the giant component P ∞ for networks with arbitrary degree distributions P(k). In the limit of n → ∞ we recover prior work on targeted immunization, whereas for n = 1 we recover the known case of random immunization. Between these two extremes, we observe that, as n increases, p c increases quickly towards its optimal value under targeted immunization with complete information. In particular, we find a new general scaling relationship between |p c (∞) - p c (n)| and n as |p c (∞) - p c (n)| ∼ n -1exp(-αn). For scale-free (SF) networks, where P(k) ∼ k -γ, 2 < γ < 3, we find that p c has a transition from zero to nonzero when n increases from n = 1 to O(log N) (where N is the size of the network). Thus, for SF networks, having knowledge of ≈log N nodes and immunizing the most optimal among them can dramatically reduce epidemic spreading. We also demonstrate our limited knowledge immunization strategy on several real-world networks and confirm that in these real networks, p c increases significantly even for small n.

Phase amplification in spinodal decomposition of immiscible fluids with interconversion of species.

A fluid composed of two molecular species may undergo phase segregation via spinodal decomposition. However, if the two molecular species can interconvert, e.g., change their chirality, then a phenomenon of phase amplification, which has not been studied so far to our best knowledge, emerges. As a result, eventually, one phase will completely eliminate the other one. We model this phenomenon on an Ising system which relaxes to equilibrium through a hybrid of Kawasaki-diffusion and Glauber-interconversion dynamics. By introducing a probability of Glauber-interconversion dynamics, we show that the particle conservation law is broken, thus resulting in phase amplification. We characterize the speed of phase amplification through scaling laws based on the probability of Glauber dynamics, system size, and distance to the critical temperature of demixing.

Distribution of blackouts in the power grid and the Motter and Lai model.

Carreras, Dobson, and colleagues have studied empirical data on the sizes of the blackouts in real grids and modeled them with computer simulations using the direct current approximation. They have found that the resulting blackout sizes are distributed as a power law and suggested that this is because the grids are driven to the self-organized critical state. In contrast, more recent studies found that the distribution of cascades is bimodal resulting in either a very small blackout or a very large blackout, engulfing a finite fraction of the system. Here we reconcile the two approaches and investigate how the distribution of the blackouts changes with model parameters, including the tolerance criteria and the dynamic rules of failure of the overloaded lines during the cascade. In addition, we study the same problem for the Motter and Lai model and find similar results, suggesting that the physical laws of flow on the network are not as important as network topology, overload conditions, and dynamic rules of failure.

Market instability and the size-variance relationship.

We show that some key features of the behavior of mutual funds is accounted for by a stochastic model of proportional growth. We find that the negative dependence of the variance of funds' growth rates on size is well described by an approximate power law. We discover that during periods of crisis the volatility of the largest funds' growth rates increases with respect to mid-sized funds. Our result reveals that a lower and flatter slope provides relevant information on the structure of the system. We find that growth rates volatility poorly depends on the size of the funds, thus questioning the benefits of diversification achieved by larger funds. Our findings show that the slope of the size-variance relationship can be used as a synthetic indicator to monitor the intensity of instabilities and systemic risk in financial markets.

Diffusion interactions between crossing fibers of the brain.

PURPOSE: Recent observations of several preferred orientations of diffusion in deep white matter may indicate either (a) that axons in different directions are independently bundled in thick sheets and function noninteractively, or more interestingly, (b) that the axons are closely interwoven and would exhibit branching and sharp turns. This study aims to investigate whether the dependence of dMRI Q-ball signal on the interpulse time Δ can decode the smaller-than-voxel-size brain structure, in particular, to distinguish scenarios (a) and (b). METHODS: High-resolution Q-ball images of a healthy brain taken with b=8000  s/mm2 for 3 different values of Δ were analyzed. The exchange of water molecules between crossing fibers was characterized by the fourth Fourier coefficient f4(Δ) of the signal profile in the plane of crossing. To interpret the empirical results, a model consisting of differently oriented parallel sheets of cylinders was developed. Diffusion of water molecules inside and outside cylinders was simulated by the Monte Carlo method. RESULTS: Simulations predict that f4(Δ) , agreeing with the empirical results, must increase with Δ for large b-values, but may peak at a typical Δ that depends on the thickness of the cylinder sheets for intermediate b-values. Thus, the thickness of axon layers in voxels with 2 predominant orientations can be detected from empirical f4(Δ) taken at smaller b-values. CONCLUSION: Based on the simulation results, recommendations are made on how to design a dMRI experiment with optimal b-value and range of Δ in order to measure the thickness of axon sheets in the white matter, hence to distinguish (a) and (b).

Systemic stress test model for shared portfolio networks.

We propose a dynamic model for systemic risk using a bipartite network of banks and assets in which the weight of links and node attributes vary over time. Using market data and bank asset holdings, we are able to estimate a single parameter as an indicator of the stability of the financial system. We apply the model to the European sovereign debt crisis and observe that the results closely match real-world events (e.g., the high risk of Greek sovereign bonds and the distress of Greek banks). Our model could become complementary to existing stress tests, incorporating the contribution of interconnectivity of the banks to systemic risk in time-dependent networks. Additionally, we propose an institutional systemic importance ranking, BankRank, for the financial institutions analyzed in this study to assess the contribution of individual banks to the overall systemic risk.

Reversible bootstrap percolation: Fake news and fact checking.

Bootstrap percolation has been used to describe opinion formation in society and other social and natural phenomena. The formal equation of the bootstrap percolation may have more than one solution, corresponding to several stable fixed points of the corresponding iteration process. We construct a reversible bootstrap percolation process, which converges to these extra solutions displaying a hysteresis typical of discontinuous phase transitions. This process provides a reasonable model for fake news spreading and the effectiveness of fact checking. We show that sometimes it is not sufficient to discard all the sources of fake news in order to reverse the belief of a population that formed under the influence of these sources.

Energy Stored in Nanoscale Water Capillary Bridges between Patchy Surfaces.

We perform molecular dynamics (MD) simulations of a water capillary bridge (WCB) expanding between two identical chemically heterogeneous surfaces. The model surfaces, based on the structure of silica, are hydrophobic and are decorated by a hydrophilic (hydroxylated silica) patch that is in contact with the WCB. Our MD simulations results, including the WCB profile and forces induced on the walls, are in agreement with capillarity theory even at the smallest wall separations studied, h = 2.5-3 nm. Remarkably, the energy stored in the WCB can be relatively large, with an energy density that is comparable to that harvested by water-responsive materials used in actuators and nanogenerators.

Faster calculation of the percolation correlation length on spatial networks.

The divergence of the correlation length ξ at criticality is an important phenomenon of percolation in two-dimensional systems. Substantial speed-ups to the calculation of the percolation threshold and component distribution have been achieved by utilizing disjoint sets, but existing algorithms of this sort cannot measure the correlation length. Here we utilize the parallel axis theorem to track the correlation length as nodes are added to the system, allowing us to utilize disjoint sets to measure ξ for the entire percolation process with arbitrary precision in a single sweep. This algorithm enables direct measurement of the correlation length in lattices as well as spatial network topologies and provides an important tool for understanding critical phenomena in spatial systems.

Insights into bootstrap percolation: Its equivalence with k-core percolation and the giant component.

K-core and bootstrap percolation are widely studied models that have been used to represent and understand diverse deactivation and activation processes in natural and social systems. Since these models are considerably similar, it has been suggested in recent years that they could be complementary. In this manuscript we provide a rigorous analysis that shows that for any degree and threshold distributions heterogeneous bootstrap percolation can be mapped into heterogeneous k-core percolation and vice versa, if the functionality thresholds in both processes satisfy a complementary relation. Another interesting problem in bootstrap and k-core percolation is the fraction of nodes belonging to their giant connected components P_{∞b} and P_{∞c}, respectively. We solve this problem analytically for arbitrary randomly connected graphs and arbitrary threshold distributions, and we show that P_{∞b} and P_{∞c} are not complementary. Our theoretical results coincide with computer simulations in the limit of very large graphs. In bootstrap percolation, we show that when using the branching theory to compute the size of the giant component, we must consider two different types of links, which are related to distinct spanning branches of active nodes.

Communities and regularities in the behavior of investment fund managers.

We analyze a large microlevel dataset on the full daily portfolio holdings and exposures of 22 complex investment funds to shed light on the behavior of professional investment fund managers. We introduce a set of quantitative attributes that capture essential distinctive features of manager allocation strategies and behaviors. These characteristics include turnover, attitude toward hedging, portfolio concentration, and reaction to external events, such as changes in market conditions and flows of funds. We find the existence and stability of three main investment attitude profiles: conservative, reactive, and proactive. The conservative profile shows low turnover and resilience against external shocks; the reactive one is more prone to respond to market condition changes; and members of the proactive profile frequently adjust their portfolio allocations, but their behavior is less affected by market conditions. We find that exogenous shocks temporarily alter this configuration, but communities return to their original state once these external shocks have been absorbed and their effects vanish.

Network overload due to massive attacks.

We study the cascading failure of networks due to overload, using the betweenness centrality of a node as the measure of its load following the Motter and Lai model. We study the fraction of survived nodes at the end of the cascade p_{f} as a function of the strength of the initial attack, measured by the fraction of nodes p that survive the initial attack for different values of tolerance α in random regular and Erdös-Renyi graphs. We find the existence of a first-order phase-transition line p_{t}(α) on a p-α plane, such that if pp_{t}, p_{f} is large and the giant component of the network is still present. Exactly at p_{t}, the function p_{f}(p) undergoes a first-order discontinuity. We find that the line p_{t}(α) ends at a critical point (p_{c},α_{c}), in which the cascading failures are replaced by a second-order percolation transition. We find analytically the average betweenness of nodes with different degrees before and after the initial attack, we investigate their roles in the cascading failures, and we find a lower bound for p_{t}(α). We also study the difference between localized and random attacks.

On Economic Complexity and the Fitness of Nations.

Complex economic systems can often be described by a network, with nodes representing economic entities and edges their interdependencies, while network centrality is often a good indicator of importance. Recent publications have implemented a nonlinear iterative Fitness-Complexity (FC) algorithm to measure centrality in a bipartite trade network, which aims to represent the 'Fitness' of national economies as well as the 'Complexity' of the products being traded. In this paper, we discuss this methodological approach and conclude that further work is needed to identify stable and reliable measures of fitness and complexity. We provide theoretical and numerical evidence for the intrinsic instability in the nonlinear definition of the FC algorithm. We perform an in-depth evaluation of the algorithm's rankings in two real world networks at the country level: the global trade network, and the patent network in different technological domains. In both networks, we find evidence of the instabilities predicted theoretically, and show that 'complex' products or patents tend often to be those that countries rarely produce, rather than those that are intrinsically more difficult to produce.

Interdependent lattice networks in high dimensions.

We study the mutual percolation of two interdependent lattice networks ranging from two to seven dimensions, denoted as D. We impose that the length (measured as chemical distance) of interdependency links connecting nodes in the two lattices be less than or equal to a certain value, r. For each value of D and r, we find the mutual percolation threshold, p_{c}[D,r], below which the system completely collapses through a cascade of failures following an initial destruction of a fraction (1-p) of the nodes in one of the lattices. We find that for each dimension, D<6, there is a value of r=r_{I}>1 such that for r≥r_{I} the cascading failures occur as a discontinuous first-order transition, while for rr_{I}, and for r>r_{max} the vulnerability starts to decrease as r→∞. However, the decrease becomes less significant as D increases, and p_{c}[D,r_{max}]-p_{c}[D,∞] decreases exponentially with D. We also investigate the dependence of p_{c}[D,r] on the system size as well as how the nature of the transition changes as the number of lattice sites, N→∞.