Search Results (44)

As a contactless physical field, a steady magnetic field (SMF) is capable of acting on substances, which leads to changes in physical and/or chemical properties and to further influencing thermodynamic and kinetic behaviors at macroscopic, mesoscopic, and microscopic scales. The application of the SMF to material science has evolved into an important interdisciplinary field—the Electromagnetic Processing of Materials (EPM). Therein, the implementation of the SMF for the solidification of metals and alloys has been increasingly given attention. The SMF was found to regulate nucleation, crystal growth, the distribution of solutes and structure morphology during alloy solidification via various magnetic effects, such as magnetic damping, the thermoelectric magnetic effect, magnetic orientation and magnetically controlled diffusion. In this review, we briefly summarize the main SMF effects and review recent progress in magnetic field-assisted solidification processing, including nucleation, dendritic growth, solute segregation and interfacial phenomena. Finally, future perspectives regarding controlling alloys’ solidification using an SMF are discussed. Full article

The self-assembly mechanisms of various complex biological structures, including viral capsids and carboxysomes, have been theoretically studied through numerous kinetic models. However, most of these models focus on the equilibrium aspects of a simplified kinetic description in terms of a single reaction coordinate, typically the number of proteins in a growing aggregate, which is often insufficient to describe the size and shape of the resulting structure. In this article, we use mesoscopic non-equilibrium thermodynamics (MNET) to derive the equations governing the non-equilibrium kinetics of viral capsid formation. The resulting kinetic equation is a Fokker–Planck equation, which considers viral capsid self-assembly as a diffusive process in the space of the relevant reaction coordinates. We discuss in detail the case of the self-assembly of a spherical (icosahedral) capsid with a fixed radius, which corresponds to a single degree of freedom, and indicate how to extend this approach to the self-assembly of spherical capsids that exhibit radial fluctuations, as well as to tubular structures and systems with higher degrees of freedom. Finally, we indicate how these equations can be solved in terms of the equivalent Langevin equations and be used to determine the rate of formation and size distribution of closed capsids, opening the door to the better understanding and control of the self- assembly process. Full article

Heat engines transform thermal energy into useful work, operating in a cyclic manner. For centuries, they have played a key role in industrial and technological development. Historically, only gases and liquids have been used as working substances, but the technical advances achieved in recent decades allow for expanding the experimental possibilities and designing engines operating with a single particle. In this case, the system of interest cannot be addressed at a macroscopic level and their study is framed in the field of stochastic thermodynamics. In the present work, we study mesoscopic heat engines built with a Brownian particle submitted to harmonic confinement and immersed in a fluid acting as a thermal bath. We design a Stirling-like heat engine, composed of two isothermal and two isochoric branches, by controlling both the stiffness of the harmonic trap and the temperature of the bath. Specifically, we focus on the irreversible, non-quasi-static case—whose finite duration enables the engine to deliver a non-zero output power. This is a crucial aspect, which enables the optimisation of the thermodynamic cycle by maximising the delivered power—thereby addressing a key goal at the practical level. The optimal driving protocols are obtained by using both variational calculus and optimal control theory tools. Furthermore, we numerically explore the dependence of the maximum output power and the corresponding efficiency on the system parameters. Full article

In previous work, we investigated thermodynamic processes in systems at the mesoscopic level where traditional thermodynamic descriptions (macroscopic or microscopic) may not be fully adequate. The key result is that entropy in such systems does not change continuously, as in macroscopic systems, but rather in discrete steps characterized by the quantization constant $\beta$. This quantization reflects the underlying discrete nature of the collision process in low-dimensional systems and the essential role played by thermodynamic fluctuations at this scale. Thermodynamic variables conjugate to the forces, along with Glansdorff–Prigogine’s dissipative variable can be discretized, enabling a mesoscopic-scale formulation of canonical commutation rules (CCRs). In this framework, measurements correspond to determining the eigenvalues of operators associated with key thermodynamic quantities. This work investigates the quantization parameter $\beta$ in the CCRs using a nano-gas model analyzed through classical statistical physics. Our findings suggest that $\beta$ is not an unknown fundamental constant. Instead, it emerges as the minimum achievable value derived from optimizing the uncertainty relation within the framework of our model. The expression for $\beta$ is determined in terms of the ratio $\chi$, which provides a dimensionless number that reflects the relative scales of volume and mass between entities at the Bohr (atomic level) and the molecular scales. This latter parameter quantifies the relative influence of quantum effects versus classical dynamics in a given scattering process. Full article

A monolayer consisting of two types of particles, with energetically favored alternating stripes of the two components, is studied by Monte Carlo simulations and within a mesoscopic theory. We consider a triangular lattice model and assume short-range attraction and long-range repulsion between particles of the same kind, as well as short-range repulsion and long-range attraction for the cross-interaction. The structural evolution of the model upon increasing temperature is studied for equal chemical potentials of the two species. We determine the structure factor, the chemical potential–density isotherms, the specific heat, and the compressibility, and show how these thermodynamic functions are associated with the spontaneous formation of stripes with varying degrees of order. Full article

We pursue to illustrate the capabilities of the Dual Model of Liquids (DML) showing that it may explain crossed effects notable in Non-Equilibrium Thermodynamics (NET). The aim of the paper is to demonstrate that the DML may correctly model the thermodiffusion, in particular getting formal expressions for positive and negative Soret coefficient, and another “unexpected” mechano-thermal effect recently discovered in liquids submitted to shear strain, for which the first-ever theoretical interpretation is provided. Both applications of the DML are supported by the comparison with experimental data. The phenomenology of liquids, either pure or mixtures, submitted to external force fields is characterized by coupled effects, for instance mechano-thermal and thermo-mechanical effects, depending on whether the application of a mechanical force field generates a coupled thermal effect in the liquid sample or vice-versa. Although these phenomena have been studied since their discoveries, dating back to the XIX century, no firm theoretical interpretation exists yet. Very recently the mesoscopic model of liquids DML has been proposed and its validity and applicability demonstrated in several cases. According to DML, liquids are arranged on a mesoscopic scale by means of aggregates of molecules, or liquid particles. These structures share the liquid world with a population of lattice particles, i.e., elastic waves that interact with the liquid particles by means of an inertial force, allowing the mutual exchange of energy and momentum between the two populations. The hit particle relaxes the acquired energy and momentum due to the interaction, giving them back to the system a step forward and a time-lapse later, alike in a tunnel effect. Full article

The spontaneous formation of self-sorted columnar structures of electron-donating and accepting π-conjugated molecules is attractive for photoconducting and photovoltaic properties. However, the simple mixing of donor–acceptor discotic molecules usually results in the formation of mixed-stacked or alternating-stacked columns. As a new strategy for overcoming this problem, here, we report the “side-chain labeling” approach using binary discotic systems and realize the preferential formation of such self-sorted columnar structures in a thermodynamically stable phase. The demonstrated key strategy involves the use of hydrophobic and hydrophilic side chains. The prepared blend is composed of liquid crystalline phthalocyanine with branched alkyl chains (H₂Pc) and perylenediimide (PDI) carrying alkyl chains at one side and triethyleneglycol (TEG) chains at the other side (PDI_C12/TEG). To avoid the thermodynamically unfavorable contact among hydrophobic and hydrophilic chains, PDI_C12/TEG self-assembles to stack up on top of each other and H₂Pc as well, forming a homo-stacked pair of columns (self-sort). Importantly, H₂Pc and PDI_C12/TEG in the blend are macroscopically miscible and uniform, and mesoscopically segregated. The columnar liquid crystalline microdomains of H₂Pc and PDI_C12/TEG are homeotropically aligned in a glass sandwiched cell. The “labeling” strategy demonstrated here is potentially applicable to any binary discotic system and enables the preferential formation of self-sorted columnar structures. Full article

Ion-flow-stimulated roughening transition is a phenomenon that may prove useful in the hierarchical structuring of nanostructures. In this work, we have investigated theoretically and experimentally the surface texturing of single-crystal and multi-crystalline silicon wafers irradiated using ion-beam flows. In contrast to previous studies, ions had relatively low energies, whereas flow densities were high enough to induce a quasi-liquid state in the upper silicon layers. The resulting surface modifications reduced the wafer light reflectance to values characteristic of black silicon, widely used in solar energetics. Features of nanostructures on different faces of silicon single crystals were studied numerically based on the mesoscopic Monte Carlo model. We established that the formation of nano-pyramids, ridges, and twisting dune-like structures is due to the stimulated roughening transition effect. The aforementioned variety of modified surface morphologies arises due to the fact that the effects of stimulated surface diffusion of atoms and re-deposition of free atoms on the wafer surface from the near-surface region are manifested to different degrees on different Si faces. It is these two factors that determine the selection of the allowable “trajectories” (evolution paths) of the thermodynamic system along which its Helmholtz free energy, F, decreases, concomitant with an increase in the surface area of the wafer and the corresponding changes in its internal energy,$U$ ($dU>0$), and entropy,$S$ ($dS>0$), so that $dF=dU – TdS<0$, where $T$ is the absolute temperature. The basic theoretical concepts developed were confirmed in experimental studies, the results of which showed that our method could produce, abundantly, black silicon wafers in an environmentally friendly manner compared to traditional chemical etching. Full article

Nowadays, with the rocketing of computational power, advanced numerical tools, and parallel computing, multi-scale simulations are becoming applied more and more to complex multi-physics industrial processes. One of the several challenging processes to be numerically modelled is gas phase nanoparticle synthesis. In an applied industrial scenario, the possibility to correctly estimate the geometric properties of the mesoscopic entities population (e.g., their size distribution) and to more precisely control the results is a crucial step to improve the quality and efficiency of the production. The “NanoDOME” project (2015–2018) aims to be an efficient and functional computational service to be applied in such processes. NanoDOME has also been refactored and upscaled during the H2020 Project “SimDOME”. To prove its reliability, we present here an integrated study between experimental data and NanoDOME’s predictions. The main goal is to finely investigate the effect of a reactor’s thermodynamic conditions on the thermophysical history of mesoscopic entities along the computational domain. To achieve this goal, the production of silver nanoparticles has been assessed for five cases with different experimental operative conditions of the reactor. The time evolution and final size distribution of nanoparticles have been simulated with NanoDOME by exploiting the method of moments and population balance model. The validation is performed by comparing NanoDOME’s calculations with the experimental data. Full article

This review points out that three of the essential features of natural selection—competition for a finite resource, variation, and transmission of memory—occur in an extremely simple, thermalized molecular population, one of colliding “billiard balls” subject to an anisotropy, a directional flux of energetic molecules. The emergence of scaling behavior, scale invariance, in such systems is considered in the context of the emergence of complexity driven by Gibbs free energy, the origins of life, and known chemistries in planetary and astrophysical conditions. It is suggested that the thermodynamic formalism of statistical multifractality offers a parallel between the microscopic and macroscopic views of non-equilibrium systems and their evolution, different from, empirically determinable, and therefore complementing traditional definitions of entropy and its production in living systems. Further, the approach supports the existence of a bridge between microscopic and macroscopic scales, the missing mesoscopic scale. It is argued that natural selection consequently operates on all scales—whether or not life results will depend on both the initial and the evolving boundary conditions. That life alters the boundary conditions ensures nonlinearity and scale invariance. Evolution by natural selection will have taken place in Earth’s fluid envelope; both air and water display scale invariance and are far from chemical equilibrium, a complex condition driven by the Gibbs free energy arising from the entropy difference between the incoming solar beam and the outgoing infrared radiation to the cold sink of space acting on the initial conditions within evolving boundary conditions. Symmetry breaking’s role in the atmospheric state is discussed, particularly in regard to aerosol fission in the context of airborne bacteria and viruses in both current and prebiotic times. Over 4.4 billion years, the factors operating to support natural selection will have evolved along with the entire system from relative simplicity to the current complexity. Full article

Amyloid fibrils may adopt different morphologies depending on the solution conditions and the protein sequence. Here, we show that two chemically identical but morphologically distinct α-synuclein fibrils can form under identical conditions. This was observed by nuclear magnetic resonance (NMR), circular dichroism (CD), and fluorescence spectroscopy, as well as by cryo-transmission electron microscopy (cryo-TEM). The results show different surface properties of the two morphologies, A and B. NMR measurements show that monomers interact differently with the different fibril surfaces. Only a small part of the N-terminus of the monomer interacts with the fibril surface of morphology A, compared to a larger part of the monomer for morphology B. Differences in ThT binding seen by fluorescence titrations, and mesoscopic structures seen by cryo-TEM, support the conclusion of the two morphologies having different surface properties. Fibrils of morphology B were found to have lower solubility than A. This indicates that fibrils of morphology B are thermodynamically more stable, implying a chemical potential of fibrils of morphology B that is lower than that of morphology A. Consequently, at prolonged incubation time, fibrils of morphology B remained B, while an initially monomorphic sample of morphology A gradually transformed to B. Full article

Biomolecular condensation and phase separation are increasingly understood to play crucial roles in cellular compartmentalization and spatiotemporal regulation of cell machinery implicated in function and pathology. A key aspect of current research is to gain insight into the underlying physical mechanisms of these processes. Accordingly, concepts of soft matter and polymer physics, the thermodynamics of mixing, and material science have been utilized for understanding condensation mechanisms of multivalent macromolecules resulting in viscoelastic mesoscopic supramolecular assemblies. Here, we focus on two topological concepts that have recently been providing key mechanistic understanding in the field. First, we will discuss how percolation provides a network-topology-related framework that offers an interesting paradigm to understand the complex networking of dense ‘connected’ condensate structures and, therefore, their phase behavior. Second, we will discuss the idea of entanglement as another topological concept that has deep roots in polymer physics and important implications for biomolecular condensates. We will first review some historical developments and fundamentals of these concepts, then we will discuss current advancements and recent examples. Our discussion ends with a few open questions and the challenges to address them, hinting at unveiling fresh possibilities for the modification of existing knowledge as well as the development of new concepts relevant to condensate science. Full article

This commentary tackles the subtle at-the-edge problem of passing locally by a mesoscopic matter-aggregating system from a classical stochastic to a quantum stochastic description. A d-dimensional entropy-productive aggregation of the matter is taken as the starting point. Then, a dimensional reduction towards a one-dimensional quantum-wire type matter-aggregation system is proposed, resulting in postponing surface-tension conditions for the effectively d = 1-dimensional quantum-wire type or nanorod-like cluster/polycrystal, which is qualitatively consistent with a physical-metallurgical (high-temperature) Louat’s grain growth model. A certain recuperative interplay based on maneuvering between subtle temperature rises applied to the system under study while maintaining its quantum character (the so-called Nelson’s quantum-stochastic procedure) within the limits of a vanishing Planck’s constant, involved in the diffusivity measure of the aggregation, is discussed. Certain applications towards the formation of d = 1-dimensional semiconductors and other nanostructures (possibly using soft materials or (bio)polymeric materials such as nanofibers) are envisioned. As a special example, one may propose a nanotechnological process which is termed the Van der Waals heteroepitaxy. The process itself contains the main quantum vs. classical crossover due to the involvement of weak repulsion (quantum) vs. attraction (treated classically) interactions, which are represented by a Lennard-Jones-type potential. Full article

The application of fractional calculus in the field of kinetic theory begins with questions raised by Bernoulli, Clausius, and Maxwell about the motion of molecules in gases and liquids. Causality, locality, and determinism underly the early work, which led to the development of statistical mechanics by Boltzmann, Gibbs, Enskog, and Chapman. However, memory and nonlocality influence the future course of molecular interactions (e.g., persistence of velocity and inelastic collisions); hence, modifications to the thermodynamic equations of state, the non-equilibrium transport equations, and the dynamics of phase transitions are needed to explain experimental measurements. In these situations, the inclusion of space- and time-fractional derivatives within the context of the continuous time random walk (CTRW) model of diffusion encodes particle jumps and trapping. Thus, we anticipate using fractional calculus to extend the classical equations of diffusion. The solutions obtained illuminate the structure and dynamics of the materials (gases and liquids) at the molecular, mesoscopic, and macroscopic time/length scales. The development of these models requires building connections between kinetic theory, physical chemistry, and applied mathematics. In this paper, we focus on the kinetic theory of gases and liquids, with particular emphasis on descriptions of phase transitions, inter-phase mixing, and the transport of mass, momentum, and energy. As an example, we combine the pressure–temperature phase diagrams of simple molecules with the corresponding anomalous diffusion phase diagram of fractional calculus. The overlap suggests links between sub- and super-diffusion and molecular motion in the liquid and the vapor phases. Full article

The question of how energy resources can be efficiently used is likewise of fundamental and technological interest. In this opinion, we give a brief overview on developments of harvesting solar energy across different length scales and address some strategies to tackle economic and ecological challenges, in particular with a view to sustainability and toward a circular economy. On the mesoscopic scale, the emergence of thermodynamic laws in open quantum systems is of central importance and how they can be employed for efficient quantum thermal machines and batteries. The broad tunability of band gaps in quantum dot systems makes them attractive for hybrid photovoltaic devices. Complementary, machine learning-aided band gap engineering and the high-throughput screening of novel materials assist with improving absorption characteristics. On the device scale, hybrid concepts of optical control via metasurfaces enable a multitude of functionalities such as a directed re-emission of embedded photoluminescent materials or field enhancement effects from nanostructures. Advanced techniques in computational nanophotonics concern a topology optimization of nanostructured layers together with multiobjective optimization toward specific light management tasks. On the industrial level, modern manufacturers explore 3D printing and flexible solar cell platforms obtained from roll-to-roll technologies. The remote control of solar parks through applications via the Internet of Things opens up new strategies to expand to difficult terrain where human interaction is only required to a limited extent. Full article