Non-additive Mixture Research Articles

Exploring anisotropic pressure and spatial correlations in strongly confined hard-disk fluids: Exact results.

This study examines the transverse and longitudinal properties of hard disks confined in narrow channels. Employing an exact mapping of the system onto a one-dimensional polydisperse, nonadditive mixture of hard rods with equal chemical potentials, we compute various thermodynamic properties, including the transverse and longitudinal equationsof state, along with their behaviors at both low and high densities. Structural properties are analyzed using the two-body correlation function and the radial distribution function, tailored for the highly anisotropic geometry of this system. The results are corroborated by computer simulations.

Inverse design of crystals and quasicrystals in a non-additive binary mixture of hard disks.

The development of new materials typically involves a process of trial and error, guided by insights from past experimental and theoretical findings. The inverse design approach for soft-matter systems has the potential to optimize specific physical parameters, such as particle interactions, particle shape, or composition and packing fraction. This optimization aims to facilitate the spontaneous formation of specific target structures through self-assembly. In this study, we expand upon a recently introduced inverse design protocol for monodisperse systems to identify the required conditions and interactions for assembling crystal and quasicrystal phases within a binary mixture of two distinct species. This method utilizes an evolution algorithm to identify the optimal state point and interaction parameters, enabling the self-assembly of the desired structure. In addition, we employ a convolutional neural network (CNN) that classifies different phases based on their diffraction patterns, serving as a fitness function for the desired structure. Using our protocol, we successfully inverse design two-dimensional crystalline structures, including a hexagonal lattice and a dodecagonal quasicrystal, within a non-additive binary mixture of hard disks. Finally, we introduce a symmetry-based order parameter that leverages the encoded symmetry within the diffraction pattern. This order parameter circumvents the need for training a CNN and is used as a fitness function to inverse design an octagonal quasicrystal.

Arrested coarsening and large density fluctuations in driven particle mixtures in two dimensions

Using molecular dynamics simulations, we study a driven, nonadditive binary mixture of spherical particles confined to move in two dimensions and immersed in an explicit solvent consisting of point particles with purely repulsive interactions. We show that, without a drive, the mixture of spherical particles phase separates and coarsens with kinetics consistent with an Ising-like conserved dynamics. Conversely, when the drive is applied, the coarsening is arrested and the system develops large density fluctuations. We show that the drive creates domains of a characteristic size which decreases with an increasing force. Furthermore, we find that these domains are anisotropic and can be oriented either parallel or perpendicular to the drive direction. Finally, we connect our findings to existing theories of strongly-driven systems, pointing out the importance of introducing the explicit solvent particles to break the Galilean invariance of the system.

Non-additive mixture effects of benzo[a]pyrene and pesticides in vitro and in vivo: Role of AhR signaling

Polycyclic aromatic hydrocarbons (PAHs) and pesticides are two major groups of environmental contaminants which humans are simultaneously exposed to. However, potential mixture interactions of these groups of chemicals are not well-studied. In this study, the effects of binary mixtures of the PAH benzo[a]pyrene (B[a]P) and the commonly used pesticides chlorpyrifos, paraquat and tebuconazole on human liver HepG2 cells were investigated. The results showed that binary mixtures of B[a]P and paraquat or tebuconazole mainly caused additive effects on cell viability and cytochrome P4501a1 (CYP1A1) expression compared to single compound exposures. In contrast, the binary mixture with chlorpyrifos interacted antagonistically on cell viability and ROS production, whereas synergistic effects were observed for induction of CYP1A1 expression. B[a]P and chlorpyrifos also inhibited the activity of recombinant human CYP1A1 enzyme. To verify the synergistic in vitro results, zebrafish (Danio rerio) embryos were exposed to binary mixtures of B[a]P and chlorpyrifos. The mixtures caused synergistic induction of CYP1A expression, as well as synergistic developmental toxicity on multiple endpoints including non-inflated swim bladder, yolk-sac and pericardial edema, and spinal deformation. The effects were reduced upon morpholino-mediated knockdown of the aryl hydrocarbon receptor (AhR), indicating an AhR-dependence of the synergistic toxicity. Altogether, these data suggest that the combination of AhR activation and CYP1A1 inhibition is responsible for the underlying non-additive interaction between B[a]P and chlorpyrifos in vitro and in vivo.

Phase transformation mechanisms, microstructural characteristics and mechanical performances of an additively manufactured Ti-6Al-4V alloy under dual-stage heat treatment

Understanding phase transformation behaviors and microstructural evolutions during optimized post-heat treatments is essential for tuning the mechanical performances of additively manufactured titanium alloys. In this work, distinctive dual-stage heat treatments were proposed for improving the microstructure and properties of the laser powder bed fusion processed Ti-6Al-4V alloy. The effects of the heat treatments on phase transformation behaviors, microstructural characteristics, mechanical and tribological properties of the alloy were investigated systematically. The dual-stage heat treatments combined with salt bath quenching proved to be an effective approach for obtaining fine lamellar α/β microstructures through the introduction of martensitic and massive phase transformations, as well as achieving optimized strength and ductility. The grain boundary populations of the alloy were strongly influenced by the phase transformation behaviors. Moreover, high-density dislocations were introduced during the dual-stage heat treatments, and the <a> type dislocations were dominant. The nonadditive strengthening mixture rule between obstacles and dislocations was substantiated in this alloy. Different wear mechanisms were found in the dual-stage heat-treated alloys depending on their microstructural characteristics. Furthermore, the underlying mechanisms of phase transformation, strengthening and toughening are also discussed.

Importance of feature construction in machine learning for phase transitions.

Machine learning is an important tool in the study of the phase behavior from molecular simulations. In this work, we use un-supervised machine learning methods to study the phase behavior of two off-lattice models, a binary Lennard-Jones (LJ) mixture and the Widom-Rowlinson (WR) non-additive hard-sphere mixture. The majority of previous work has focused on lattice models, such as the 2D Ising model, where the values of the spins are used as the feature vector that is input into the machine learning algorithm, with considerable success. For these two off-lattice models, we find that the choice of the feature vector is crucial to the ability of the algorithm to predict a phase transition, and this depends on the particular model system being studied. We consider two feature vectors, one where the elements are distances of the particles of a given species from a probe (distance-based feature) and one where the elements are +1 if there is an excess of particles of the same species within a cut-off distance and -1 otherwise (affinity-based feature). We use principal component analysis and t-distributed stochastic neighbor embedding to investigate the phase behavior at a critical composition. We find that the choice of the feature vector is the key to the success of the unsupervised machine learning algorithm in predicting the phase behavior, and the sophistication of the machine learning algorithm is of secondary importance. In the case of the LJ mixture, both feature vectors are adequate to accurately predict the critical point, but in the case of the WR mixture, the affinity-based feature vector provides accurate estimates of the critical point, but the distance-based feature vector does not provide a clear signature of the phase transition. The study suggests that physical insight into the choice of input features is an important aspect for implementing machine learning methods.

Determinism of nonadditive litter mixture effect on decomposition: Role of the moisture content of litters.

The mechanisms behind the plant litter mixture effect on decomposition are still difficult to disentangle. To tackle this issue, we used a model that specifically addresses the role of the litter moisture content. Our model predicts that when two litters interact in terms of water flow, the difference of evaporation rate between two litters can trigger a nonadditive mixture effect on decomposition. Water flows from the wettest to the driest litter, changing the reaction rates without changing the overall litter water content. The reaction rate of the litter receiving the water increases relatively more than the decrease in the reaction rate of the litter supplying the water, leading to a synergistic effect. Such water flow can keep the microbial biomass of both litter in a water content domain suitable to maintain decomposition activity. When applied to experimental data (Sphagnum rubellum and Molinia caerulea litters), the model is able to assess whether any nonadditive effect originates from water content variation alone or whether other factors have to be taken into account.

Moisture absorption and drying alter nonadditive litter flammability in a mixed conifer forest

Abstract Moisture content is a strong determinant of forest fuel flammability. However, little is known about the mechanisms by which species‐specific litter traits influence litter moisture absorption and retention. Characterizing how litter fuels retain moisture through time and how fuels from multiple species interact are key steps to adding taxon‐specific information to fire behaviour prediction. To fill these gaps in knowledge, we determined moisture absorption and retention characteristics of the litter from multiple tree species, investigated what litter traits influenced these processes and tested for nonadditive moisture dynamics and nonadditive flammability in multi‐species mixtures. The litter from eight tree species of a mixed conifer forest was saturated and allowed to dry to determine moisture absorption capacity and drying rates. Burn trials were performed in litter beds of single species and of mixtures to establish flammability response to the dry‐down process and to species interactions. Litter mixtures exhibited nonadditivity in flame spread rate and in fuel consumption. This nonadditivity became more positive with fuel drying. Moisture dynamics varied across species with higher specific leaf area being associated with higher maximum absorption and lower litter bulk density being associated with faster drying rates. We found that these differing moisture dynamics resulted in time since wetting having strongly differing effects on flammability across the major litter types typified by different tree taxa. Synthesis. This study is the first to examine ecologically relevant drying rates and their interaction with nonadditive mixture effects on flammability. We find that taxon specific patterns of moisture absorption and drying change flammability rankings under moist compared with dry fuels because traits that increase flame spread rate increase water absorption. Litter mixtures generally burn with fire behaviour more similar to that of the most flammable constituent species and this effect increases as fuels dry.

When does Wenzel's extension of Young's equation for the contact angle of droplets apply? A density functional study.

The contact angle of a liquid droplet on a surface under partial wetting conditions differs for a nanoscopically rough or periodically corrugated surface from its value for a perfectly flat surface. Wenzel's relation attributes this difference simply to the geometric magnification of the surface area (by a factor rw), but the validity of this idea is controversial. We elucidate this problem by model calculations for a sinusoidal corrugation of the form zwall(y) = Δ cos(2πy/λ), for a potential of short range σw acting from the wall on the fluid particles. When the vapor phase is an ideal gas, the change in the wall-vapor surface tension can be computed exactly, and corrections to Wenzel's equation are typically of the order σwΔ/λ2. For fixed rw and fixed σw, the approach to Wenzel's result with increasing λ may be nonmonotonic and this limit often is only reached for λ/σw > 30. For a non-additive binary mixture, density functional theory is used to work out the density profiles of both coexisting phases for planar and corrugated walls as well as the corresponding surface tensions. Again, deviations from Wenzel's results of similar magnitude as in the above ideal gas case are predicted. Finally, a crudely simplified description based on the interface Hamiltonian concept is used to interpret the corresponding simulation results along similar lines. Wenzel's approach is found to generally hold when λ/σw ≫ 1 and Δ/λ < 1 and under conditions avoiding proximity of wetting or filling transitions.

Choice of reference, influence of non-additivity, and present challenges in thermodynamic perturbation theory for mixtures.

This work revisits the fundamentals of thermodynamic perturbation theory for fluid mixtures. The choice of reference and governing assumptions can profoundly influence the accuracy of the perturbation theory. The statistical associating fluid theory for variable range interactions of the generic Mie form equation of state is used as a basis to evaluate three choices of hard-sphere reference fluids: single component, additive mixture, and non-additive mixture. Binary mixtures of Lennard-Jones fluids are investigated, where the ratios of σ (the distance where the potential is zero) and the ratios of ϵ (the well depth) are varied. By comparing with Monte Carlo simulations and results from the literature, we gauge the accuracy of different theories. A perturbation theory with a single-component reference gives inaccurate predictions when the σ-ratio differs significantly from unity but is otherwise applicable. Non-additivity becomes relevant in phase-equilibrium calculations for fluids with high ϵ-ratios or when the mixing rule of σ incorporates non-additivity through an adjustable parameter. This can be handled in three ways: by using a non-additive hard-sphere reference, by incorporating an extra term in the additive hard-sphere reference, or with a single-component reference when the σ-ratio is close to unity. For σ- and ϵ-ratios that differ significantly from unity, the perturbation theories overpredict the phase-equilibrium pressures regardless of reference. This is particularly pronounced in the vicinity of the critical region for mixtures with high ϵ-ratios. By comparing with Monte Carlo simulations where we compute the terms in the perturbation theory directly, we find that the shortcomings of the perturbation theory stem from an inaccurate representation of the second- and third-order perturbation terms, a2 and a3. As mixtures with molecules that differ significantly in size and depths of their interaction potentials are often encountered in industrial and natural applications, further development of the perturbation theory based on these results is an important future work.

Nonadditive strengthening functions for cold-worked cubic metals: Experiments and constitutive modeling

Strong metals are greatly desired for lightweight and energy-efficient industrial design. The strengthening of metals is traditionally accomplished by the additive contributions of various obstacle families (e.g., solid solutions, particles, and grain boundaries) and dislocation self-interactions that impede dislocation motion. In the present work, unlike a traditional additive understanding, a distinctive nonadditive strengthening mixture rule for obstacles and dislocations were validated based on experimental and modeling analyses in numerous cold-worked steels and aluminum alloys. Concretely, numerous well-annealed body-centered cubic steels and face-centered cubic aluminum alloys were prepared, in which the hierarchical strength levels of solid solutions, grain boundaries, and/or particles were estimated. The above specimens were then cold rolled to various strain levels. Dislocation densities were quantified by utilizing X-ray diffraction line-profile-analysis, and the dislocation density was found to increase faster with an increasing strain level when a high strength was presented in well-annealed specimens. When plotting the yield stresses as a function of the square roots of the dislocation densities in massive distorted samples based on the Taylor hardening law, it is interesting to note that an approximate single linearity was obtained. Individual dislocation strengthening was found to respond to the total strength in the deformed specimens, which indicated that the full nonadditive strengthening mixture rule was employed between the obstacle families and the dislocation contributions. The mechanisms of the observed nonadditive strengthening were also discussed by implementing additional experiments and transmission electron microscopy observations. Then, the modified constitutive models based on both one and two internal parameters’ Knocks-Mecking models were developed respectively, which excellently captured the effects of the various obstacle families on dislocation storage processes. The developed models also rationalized the observed nonadditive strengthening mixture rule.

Receiving Portland Cement from Technogenic Raw Materials of South Kazakhstan

A method of producing portland cement using the wastes of enrichment of polymetallic ores of "Achpolymetal" (Kentau, Kazakhstan) in the amount of 0.5 to 2.5% as a mineralizing additive in the raw mixture is proposed. This allows the clinker to be produced at a lower temperature (1300–1350 °C), resulting in lower fuel consumption and higher furnace productivity. The experimental clinker is better subjected to grinding, the electric power consumption for grinding cement decreases, the grinding bodies of cement mills decrease. In the waste, there are catalytic and modifying elements. Studies have shown that in the no-added raw mix the clinker formation processes are completed at 1450 °C. When 0.5 to 2.0% of the tailings are introduced, the complete binding of CaO is completed at 1400 °C, with the addition of 2.5% of tailings, lime binding is completed at 1300 or 150 °C lower than in the control non-additive raw mixture. In clinkers, only 1.09–1.32 % of free lime remains. The strength of cement when introduced into the raw mix from 0.5 to 2.0% of barite waste is increased. The compressive strength at 28 days of age for cement with an optimum dosage of 1‒2% of the tail increases from 414 kg/cm2 to 430‒432 kg/cm2 or by 3.9‒4.3%. Similarly, the strength of steamed samples increases by 4.7‒5.7%.

Linear viscoelasticity of a two-dimensional glass-former by stress-fluctuation formalism

Viscoelastic properties of dense colloids are investigated using the stress-fluctuation formalism and equilibrium molecular dynamics simulations. The focus is on a two-dimensional (2D) non-additive Lennard-Jones binary mixture, which is a glass-former. Its behaviour is compared with that of a one-component Lennard-Jones system, which forms a 2D crystal with triangular lattice at low temperatures. The systems are under fixed pressure and temperature conditions. The effects of the mixing, the temperature and the pressure are studied. Calculated functions include the shear modulus relaxation function, the dynamic moduli (storage modulus and loss modulus), the complex compliance and the dynamic viscosity. Both the liquid and the solid (crystal and glass) states are investigated. Qualitative aspects are discussed in the light of simple rheological models.

Microbial groups and their functions control the decomposition of coniferous litter: A comparison with broadleaved tree litters

The conversion of secondary forests to pure coniferous plantations leads to a decrease in soil quality partly because of the slow decomposition rate of coniferous litter. Microbial decomposers directly regulate the decomposition process. However, little is known about how litter type and microbial communities including both bacteria and fungi interact to affect decomposition rates. A field experiment was performed consisting of seven treatments (i.e., four tree litters: Quercus mongolica, Juglans mandshurica, Acer mono, and Larix gmelinii) in which either monospecific litters or mixtures of larch litter with each broadleaved tree litter (mass ratio was 1:1) were placed into litterbags, and the microbial community composition and enzyme activities were measured. The results showed that in monospecific litters, the highest mass loss was observed in Acer litter, followed by Quercus, Juglans, and Larix litters. Furthermore, synergistic non-additive mixture effects were found in the Larix-Acer and Larix-Quercus mixtures. Most of the abundant bacterial taxa and potential functional genes encoding the hydrolytic enzymes were not significantly affected by the litter type. In contrast, each litter type was characterized by a specific fungal community, as well as different patterns of extracellular enzyme activity. The most abundant fungal decomposers in Larix litter during the first 540 days of decomposition, such as Meria, Lambertella, Venturia, and Ochroconis, were negatively correlated with most of the enzymatic activities, which possibly explains the slower decomposition rate of Larix litter. In conclusion, mixing Larix litter with broadleaved litters could change the microbial community composition, and accelerate the decomposition of hemicelluloses and lignin. Introducing broadleaved tree species with fast litter turnover rates by allowing natural regeneration and planting broadleaved tree species in pure larch plantations may be an effective way to restore soil quality in temperate forest regions.

Litter species diversity is more important than genotypic diversity of dominant grass species Stipa grandis in influencing litter decomposition in a bare field

Studies have indicated that plant litter diversity can affect litter decomposition at both species diversity and genotypic diversity level within a species. However, the essence and relative importance of these two diversity levels on litter decomposition remain unknown. Here, two independent one-factor experiments, litter species diversity and litter genotypic diversity of the dominant species—Stipa grandis, were carried out to explore the effects of initial litter quality, litter composition and diversity on decomposition of mass, nitrogen (N), carbon (C) and phosphorus (P) simultaneously. The results showed that: (1) there were significant relationships between the initial litter N, C/N, lignin/N and the decomposition rate of N, between the initial litter P, N/P and the decomposition rate of P, and the litter composition significantly influenced litter mass, N, C and P remaining in both litter species and genotypic diversity experiments; and (2) litter species diversity significantly affected litter mass, N, C and P remaining, and non-additive relative mixture effects were mainly contributed by synergistic effects especially in 6-species mixtures; however, similar patterns were not found in litter genotypic diversity experiment. The present results emphasized that initial litter quality played the most important role in influencing litter decomposition of mass N, C and P, and suggested that litter species mixtures rather than litter genotypic mixtures of a dominant species could favor nutrient cycling in ecosystem of the semi-arid Inner Mongolia Steppe of China.

The influence of complex thermal treatment on mechanical properties of amorphous materials

We study the effect of periodic, spatially uniform temperature variation on mechanical properties and structural relaxation of amorphous alloys using molecular dynamics simulations. The disordered material is modeled via a non-additive binary mixture, which is annealed from the liquid to the glassy state with various cooling rates and then either aged at constant temperature or subjected to thermal treatment. We found that in comparison to aged samples, thermal cycling with respect to a reference temperature of approximately half the glass transition temperature leads to more relaxed states with lower levels of potential energy. The largest energy decrease was observed for rapidly quenched glasses cycled with the thermal amplitude slightly smaller than the reference temperature. Following the thermal treatment, the mechanical properties were probed via uniaxial tensile strain at the reference temperature and constant pressure. The numerical results indicate an inverse correlation between the levels of potential energy and values of the elastic modulus and yield stress as a function of the thermal amplitude.

Functional evenness of N-to-P ratios of evergreen-deciduous mixtures predicts positive non-additive effect on leaf litter decomposition

The effects of litter diversity on litter decomposition remain debated. We tested to what extent the community-weighted means (CWM; functional composition) versus Rao’s dissimilarity of litter nitrogen (N)-to-phosphorus (P) ratios explain the non-additive mixture effect on decomposition rate (k) and associated N release. We carried out a one-year field decomposition experiment with a range of five litter types ranging from three evergreens only (high N/P and low specific leaf area, SLA) to three deciduous species only (low-N/P and high-SLA), with 30:70, 50:50 and 70:30% mixtures of these two extremes in between, in subtropical forest of China. There were tight hump-backed relationships of absolute k-values and N release, respectively, with the CWMSLA. The mixtures with the highest functional evenness in terms of CWMN/P caused the highest positive non-additivity on decomposition (R2 = 0.72) and N release (R2 = 0.95) rates. In contrast, the mixing effect on k or N release was weakly positively correlated with Rao’s dissimilarity of N/P (R2 = 0.38 and 0.27 respectively). Our results provide a strong framework for predicting litter decomposition rates and associated N release versus immobilization in mixtures of deciduous versus evergreen species based on their differences in initial stoichiometry.

Unsupervised machine learning for detection of phase transitions in off-lattice systems. II. Applications.

We outline how principal component analysis can be applied to particle configuration data to detect a variety of phase transitions in off-lattice systems, both in and out of equilibrium. Specifically, we discuss its application to study (1) the nonequilibrium random organization (RandOrg) model that exhibits a phase transition from quiescent to steady-state behavior as a function of density, (2) orientationally and positionally driven equilibrium phase transitions for hard ellipses, and (3) a compositionally driven demixing transition in the non-additive binary Widom-Rowlinson mixture.

The effect of cryogenic thermal cycling on aging, rejuvenation, and mechanical properties of metallic glasses

The structural relaxation, potential energy states, and mechanical properties of a model glass subjected to thermal cycling are investigated using molecular dynamics simulations. We study a non-additive binary mixture which is annealed with different cooling rates from the liquid phase to a low temperature well below the glass transition. The thermal treatment is applied by repeatedly heating and cooling the system at constant pressure, thus temporarily inducing internal stresses upon thermal expansion. We find that poorly annealed glasses are relocated to progressively lower levels of potential energy over consecutive cycles, whereas well annealed glasses can be rejuvenated at sufficiently large amplitudes of thermal cycling. Moreover, the lowest levels of potential energy after one hundred cycles are detected at a certain temperature amplitude for all cooling rates. The structural transition to different energy states is accompanied by collective nonaffine displacements of atoms that are organized into clusters, whose typical size becomes larger with increasing cooling rate or temperature amplitude. We show that the elastic modulus and the peak value of the stress overshoot exhibit distinct maxima at the cycling amplitude, which corresponds to the minimum of the potential energy. The simulation results indicate that the yielding peak as a function of the cycling amplitude for quickly annealed glasses represents a lower bound for the maximum stress in glasses prepared with lower cooling rates.

Non-additive symmetric mixtures at selective walls

The results of Monte Carlo simulation of adsorption and wetting behaviour of a highly non-additive symmetric mixture at selective walls is discussed. We have concentrated on the interplay between the surface induced demixing in the adsorbed films and the properties of the bulk mixture, which exhibits a closed immiscibility loop. It has been shown that the wetting behaviour depends on the absolute values of the parameters determining the strengths of interaction between the mixture components and the surface, as well as on their difference. In general, an increase of the difference between the adsorption energies of the components leads to a decrease of the wetting temperature. In the cases when the wetting of non-selective walls occurs at the temperatures above the onset of demixing transition in the bulk, an increasing wall selectivity leads to a gradual decrease of the wetting temperature towards the triple point, in which the vapour coexists with the mixed and demixed liquid phases. When the wetting temperature at the non-selective wall is located below the onset of the demixing transition in the bulk mixture, an increase of the adsorption energy of the selected component causes the developing adsorbed films to demix and to show the reentrant mixing upon approaching the bulk coexistence. At the temperatures above the onset of the demixing transition in the bulk, the adsorbed films remain demixed up to the bulk coexistence and undergo the first-order wetting transition. A rather unexpected finding has been the observation of a gradual increase of the wetting temperature at highly selective walls.