Statistical Mechanical Theory Research Articles

Microscopic activated dynamics theory of the shear rheology and stress overshoot in ultradense glass-forming fluids and colloidal suspensions

We formulate a particle and force level, activated dynamics-based statistical mechanical theory for the continuous startup nonlinear shear rheology of ultradense glass-forming hard sphere fluids and colloidal suspensions in the context of the elastically collective nonlinear Langevin equation approach and a generalized Maxwell model constitutive equation. Activated structural relaxation is described as a coupled local-nonlocal event involving caging and longer range collective elasticity which controls the characteristic stress relaxation time. Theoretical predictions for the deformation-induced enhancement of mobility, the onset of relaxation acceleration at remarkably low values of stress, strain, or shear rate, apparent power law thinning of the steady-state structural relaxation time and viscosity, a nonvanishing activation barrier in the shear thinning regime, an apparent Herschel–Buckley form of the shear rate dependence of the steady-state shear stress, exponential growth of different measures of a yield or flow stress with packing fraction, and reduced fragility and dynamic heterogeneity under deformation were previously shown to be in good agreement with experiments. The central new question we address here is the defining feature of the transient response—the stress overshoot. In contrast to the steady-state flow regime, understanding the transient response requires an explicit treatment of the coupled nonequilibrium evolution of structure, elastic modulus, and stress relaxation time. We formulate a new quantitative model for this aspect in a physically motivated and computationally tractable manner. Theoretical predictions for the stress overshoot are shown to be in good agreement with experimental observations in the metastable ultradense regime of hard sphere colloidal suspensions as a function of shear rate and packing fraction, and accounting for deformation-assisted activated motion appears to be crucial for both the transient and steady-state responses.

Statistical Mechanical Design Principles for Coarse-Grained Interactions across Different Conformational Free Energy Surfaces.

Systematic bottom-up coarse-graining (CG) of molecular systems provides a means to explore different coupled length and time scales while treating the molecular-scale physics at a reduced level. However, the configuration dependence of CG interactions often results in CG models with limited applicability for exploring the parametrized configurations. We propose a statistical mechanical theory to design CG interactions across different configurations and conditions. In order to span wide ranges of conformational space, distinct classical CG free energy surfaces for characteristic configurations are identified using molecular collective variables. The coupling interaction between different CG free energy surfaces can then be systematically determined by analogy to quantum mechanical approaches describing coupled states. The present theory can accurately capture the underlying many-body potentials of mean force in the CG variables for various order parameters applied to liquids, interfaces, and in principle proteins, uncovering the complex nature underlying the coupling interaction and imparting a new protocol for the design of predictive multiscale models.

Formalism for stochastic perturbations and analysis in relativistic stars

Perturbed Einstein’s equations with a linear response relation and a stochastic source, applicable to a relativistic star model are worked out. These perturbations which are stochastic in nature, are of significance for building a non-equilibrium statistical mechanics theory in connections with relativistic astrophysics. A fluctuation dissipation relation for a spherically symmetric star in its simplest form is obtained. The FD relation shows how the random velocity fluctuations in the background of the unperturbed star can dissipate into Lagrangian displacement of fluid trajectories of the dense matter. Interestingly in a simple way, a constant (in time) coefficient of dissipation is obtained without a delta correlated noise. This formalism is also extended for perturbed TOV equations which have a stochastic contribution, and show up in terms of the effective or root mean square pressure perturbations. Such contributions can shed light on new ways of analysing the equation of state for dense matter. One may obtain contributions of first and second order in the equation of state using this stochastic approach.

Interfacial microstructure of neutral and charged polymer brushes: A density functional theory study.

Polymer density functional theory (PDFT) is a computationally efficient and robust statistical mechanics theory for capturing the interfacial microstructure of grafted polymer brushes (PBs). Undoubtedly, the intramolecular and intermolecular interactions in PDFT (e.g., hard-core interactions and direct Coulomb interactions) are greatly affected by the grafting behavior of PBs. However, the combination of these interactions with the physical constraints on grafting behavior remains unclear and there is a remarkable difference in the density profile of grafted PB between PDFT and simulation. Herein, we propose a PDFT to study neutral and charged grafted PBs by incorporating the physical constraints of end-grafted PBs into the excess free energies due to intramolecular and intermolecular interactions. This PDFT has been successfully validated where the density distributions of neutral and weakly charged PBs predicted by the PDFT are in excellent agreement with the results of the Monte Carlo and molecular dynamics simulations. In addition, the significant contribution of grafting behavior to the free energy of PB systems is presented. Consequently, this work provides a powerful and accurate theoretical method to reveal the interfacial microstructure of grafted PBs.

Minimum perturbation theory of deep perceptual learning.

Perceptual learning (PL) involves long-lasting improvement in perceptual tasks following extensive training and is accompanied by modified neuronal responses in sensory cortical areas in the brain. Understanding the dynamics of PL and the resultant synaptic changes is important for causally connecting PL to the observed neural plasticity. This is theoretically challenging because learning-related changes are distributed across many stages of the sensory hierarchy. In this paper, we modeled the sensory hierarchy as a deep nonlinear neural network and studied PL of fine discrimination, a common and well-studied paradigm of PL. Using tools from statistical physics, we developed a mean-field theory of the network in the limit of a large number of neurons and large number of examples. Our theory suggests that, in this thermodynamic limit, the input-output function of the network can be exactly mapped to that of a deep linear network, allowing us to characterize the space of solutions for the task. Surprisingly, we found that modifying synaptic weights in the first layer of the hierarchy is both sufficient and necessary for PL. To address the degeneracy of the space of solutions, we postulate that PL dynamics are constrained by a normative minimum perturbation (MP) principle, which favors weight matrices with minimal changes relative to their prelearning values. Interestingly, MP plasticity induces changes to weights and neural representations in all layers of the network, except for the readout weight vector. While weight changes in higher layers are not necessary for learning, they help reduce overall perturbation to the network. In addition, such plasticity can be learned simply through slow learning. We further elucidate the properties of MP changes and compare them against experimental findings. Overall, our statistical mechanics theory of PL provides mechanistic and normative understanding of several important empirical findings of PL.

The influence of cross-interactions between dilute cosolutes upon liquid interfaces.

We employ a statistical mechanical dilute solution theory (DST) and lattice Monte Carlo simulations to investigate the interfacial properties of ternary solutions with a dominant solvent and two dilute cosolutes. We consider cosolutes with weak interfacial preferences in order to focus on the impact of cross-interactions between the two cosolute species. When the cross-interaction is properly balanced, the two cosolutes make independent, additive contributions to both bulk and interfacial properties. Conversely, repulsive cross-interactions slightly enhance the interfacial preference of both solutes. In contrast, attractive cross-interactions reduce interfacial preferences and can convert weak surfactants into weak depletants. We observe a particularly interesting transition in the symmetric case of two equivalent self-repelling cosolutes with attractive cross-interactions. In this regime, the major cosolute acts as a weak surfactant in order to avoid repulsive self-interactions, while the minor cosolute acts as a weak depletant in order to form attractive cross-interactions. The two equivalent cosolutes switch roles depending upon their relative concentration. DST very accurately describes the surface tension and surface excess of simulated lattice solutions up to molar concentrations. More importantly, DST provides quantitative and qualitative insight into the mechanism by which cosolute interactions modulate interfacial preferences.

Precise determination of pair interactions from pair statistics of many-body systems in and out of equilibrium.

The determination of the pair potential v(r) that accurately yields an equilibrium state at positive temperature T with a prescribed pair correlation function g_{2}(r) or corresponding structure factor S(k) in d-dimensional Euclidean space R^{d} is an outstanding inverse statistical mechanics problem with far-reaching implications. Recently, Zhang and Torquato [Phys. Rev. E 101, 032124 (2020)2470-004510.1103/PhysRevE.101.032124] conjectured that any realizable g_{2}(r) or S(k) corresponding to a translationally invariant nonequilibrium system can be attained by a classical equilibrium ensemble involving only (up to) effective pair interactions. Testing this conjecture for nonequilibrium systems as well as for nontrivial equilibrium states requires improved inverse methodologies. We have devised an optimization algorithm to precisely determine effective pair potentials that correspond to pair statistics of general translationally invariant disordered many-body equilibrium or nonequilibrium systems at positive temperatures. This methodology utilizes a parameterized family of pointwise basis functions for the potential function whose initial form is informed by small-, intermediate- and large-distance behaviors dictated by statistical-mechanical theory. Subsequently, a nonlinear optimization technique is utilized to minimize an objective function that incorporates both the target pair correlation function g_{2}(r) and structure factor S(k) so that the small intermediate- and large-distance correlations are very accurately captured. To illustrate the versatility and power of our methodology, we accurately determine the effective pair interactions of the following four diverse target systems: (1) Lennard-Jones system in the vicinity of its critical point, (2) liquid under the Dzugutov potential, (3) nonequilibrium random sequential addition packing, and (4) a nonequilibrium hyperuniform "cloaked" uniformly randomized lattice. We found that the optimized pair potentials generate corresponding pair statistics that accurately match their corresponding targets with total L_{2}-norm errors that are an order of magnitude smaller than that of previous methods. The results of our investigation lend further support to the Zhang-Torquato conjecture. Furthermore, our algorithm will enable one to probe systems with identical pair statistics but different higher-body statistics, which will shed light on the well-known degeneracy problem of statistical mechanics.

(Invited) Dielectric Screening of Ionic Liquids and Implications for Their Capacitance, Solvation, and Structural Properties

Development and utilization of ionic liquids for applications as electrolytes and solvents requires understanding their electrostatic interactions with solutes, co-solvents, and interfaces. In this regard, the bulk dielectric constant of an ionic liquid is of little use, but rather the dielectric response must be characterized at atomistic lengthscales. We will discuss the dielectric response of ionic liquids as computed from molecular dynamics simulations and statistical mechanical theory. We will then describe how the dielectric properties of ionic liquids are connected with observed trends in interfacial capacitance, solvation, and liquid structure. Comparisons will be made to aqueous electrolytes and molten salts, and similarities and differences will be discussed.

Theory of the Effects of Specific Attractions and Chain Connectivity on the Activated Dynamics and Selective Transport of Penetrants in Polymer Melts

We generalize and apply a microscopic force level statistical mechanical theory of activated spherical penetrant dynamics in glass-forming liquids to study the influence of semiflexible polymer connectivity and penetrant–polymer attractive interactions on the penetrant hopping rate. The detailed manner that attractions of highly variable strength and spatial range modify the penetrant size and polymer melt density (from the rubbery state to slightly beyond the kinetic glass transition) dependences of penetrant activation barriers is established. Of special interest are possible nonadditive consequences of physical bonding and steric caging, the degree of coupling of penetrant hopping and the Kuhn segment scale alpha relaxation process, the relative importance of local caging and long-range matrix collective elasticity as a function of penetrant size, and implications for optimizing transport selectivity. With increasing attraction strength, the repulsive caging-restriction effect on penetrant mobility is predicted to grow, in contrast to the effect of the equilibrium penetrant–matrix solvation shell size, which decreases. The former dynamical effect results in a significant enhancement of the importance of the local cage barrier, while the latter effect results in a decrease of the importance of the nonlocal collective elastic barrier. These two competing effects have a very strong influence on selective penetrant transport for different sized penetrants: selectivity varies nonmonotonically with attraction strength in the deeply supercooled state but decreases monotonically in the rubbery state and at fixed attraction strength, exhibits a nonmonotonic variation with the matrix packing fraction. By comparing results based on modeling the matrix as semiflexible polymer chains with analogous calculations using the same dynamical theory but for a disconnected hard sphere matrix, the effect of chain connectivity is revealed and found to have quantitative, but not qualitative, consequences on penetrant-activated dynamics.

New numerical methods for calculating statistical equilibria of two-dimensional turbulent flows, strictly based on the Miller–Robert–Sommeria theory

New numerical methods are proposed for the mixing entropy maximization problem in the context of Miller–Robert–Sommeria’s (MRS) statistical mechanics theory of two-dimensional turbulence, particularly in the case of spherical geometry. Two of the methods are for the canonical problem; the other is for the microcanonical problem. The methods are based on the original MRS theory and thus take into account all Casimir invariants. Compared to the methods proposed in previous studies, our new methods make it easier to detect multiple statistical equilibria and to search for solutions with broken zonal symmetry. The methods are applied to a zonally symmetric initial vorticity distribution which is barotropically unstable. Two statistical equilibria are obtained, one of which has a wave-like structure with zonal wavenumber 1, and the other has a wave-like structure with zonal wavenumber 2. While the former is the maximum point of the mixing entropy, the wavenumber 2 structure of the latter is nearly the same as the structure that appears in the end state of the time integration of the vorticity equation. The new methods allow for efficient computation of statistical equilibria for initial vorticity distributions consisting of many levels of vorticity patches without losing information about all the conserved quantities. This means that the statistical equilibria can be obtained from an arbitrary initial vorticity distribution, which allows for the application of statistical mechanics to interpret a wide variety of flow patterns appearing in geophysical fluids.

Statistical-mechanical liquid theories reproduce anomalous thermodynamic properties of explicit two-dimensional water models.

We have developed an analytical theory for a simple model of liquid water. We apply Wertheim's thermodynamic perturbation theory (TPT) and integral equation theory (IET) for associative liquids to the rose model, which is among the simplest models of water. The particles interact through rose potentials for orientation dependent pairwise interactions. Modifying both the shape and range of a three-petal rose function, we construct an efficient and dynamical mimic of the two-dimensional (2D) Mercedes-Benz (MB) water model. The particles in 2D MB are 2D Lennard-Jones disks with three hydrogen bonding arms arranged symmetrically, resembling the Mercedes-Benz logo. Both models qualitatively predict both the anomalous properties of pure water and the anomalous solvation thermodynamics of nonpolar molecules. The IET is based on the orientationally averaged version of the Ornstein-Zernike equation. This is one of the main approximations in the present work. IET correctly predicts the pair correlation functions at high temperatures. Both TPT and IET are in semi-quantitative agreement with the Monte Carlo values of the molar volume, isothermal compressibility, thermal expansion coefficient, and heat capacity. A major advantage of these theories is that they require orders of magnitude less computer time than the Monte Carlo simulations.

Research on Rock Damage Evolution Based on Fractal Theory-Improved Dynamic Tensile-Compression Damage Model

According to the characteristics that the dynamic tension of rock material is elastic brittle and the dynamic compression is elastic plastic, based on previous studies, the influence of initial damage is considered in the established compression damage model, and the calculation formula of the damage threshold used to evaluate whether the surrounding rock is affected by blasting is given. According to the classic rock impact dynamic damage model and statistical damage mechanics theory, a rock compressive and tensile statistical damage constitutive model and impact damage model under blasting load is proposed. Based on the proposed damage model and the classic dynamic tensile damage model, the numerical simulation of blasting damage was carried out, and the numerical calculation results were compared with the field measurement results. Based on the established damage model, to further clarify the damage evolution characteristics of rock under blasting load, fractal dimension theory was introduced to analyze the rock damage under blasting loads with different blasting hole network parameters. The results show that compared with the axial direction of the blast hole, the direction of blast hole diameter is the main direction of blasting fracture extension. Tensile fracture mainly occurs along the hole diameter direction, and compression fracture mainly occurs below the hole bottom. Compared with the numerical calculation results based on the classical dynamic tensile damage model, the blasting fracture range obtained according to the damage model, especially the fracture depth below the bottom of the hole, was not much different from the measured value and was closest to the measured value. The crack density of 1 us, 90 aperture, and 130 aperture was larger than that of the other working conditions. Among them, the crack density of 130 aperture was the largest, followed by 90 aperture. At 2~3 us after initiation, cracks between two blast holes, radial cracks and circumferential cracks around two blast holes, and obvious cracks were formed around blastholes; at 4~5 us after initiation, the shock wave front decreased rapidly and propagated outward in the form of the compression wave. The crack propagation velocity was much smaller than that at 1~3 us after initiation. In summary, the proposed damage model is reasonable and has certain engineering practicability.

Rényi Entropy in Statistical Mechanics.

Rényi entropy was originally introduced in the field of information theory as a parametric relaxation of Shannon (in physics, Boltzmann–Gibbs) entropy. This has also fuelled different attempts to generalise statistical mechanics, although mostly skipping the physical arguments behind this entropy and instead tending to introduce it artificially. However, as we will show, modifications to the theory of statistical mechanics are needless to see how Rényi entropy automatically arises as the average rate of change of free energy over an ensemble at different temperatures. Moreover, this notion is extended by considering distributions for isospectral, non-isothermal processes, resulting in relative versions of free energy, in which the Kullback–Leibler divergence or the relative version of Rényi entropy appear within the structure of the corrections to free energy. These generalisations of free energy recover the ordinary thermodynamic potential whenever isothermal processes are considered.

Numerical Investigation of Interaction Mechanism between Hydraulic Fracture and Natural Karst Cave Based on Seepage-Stress-Damage Coupled Model

Oil/gas is mainly distributed in caves for fractured-vuggy carbonate reservoirs, it is therefore of significance to effectively connect caves for successful carbonate reservoir development. However, the mechanism and controlling factors that influence the connection between fractures and caves still remain unknown. To investigate how hydraulic fracture interacts with natural karst cave, a coupled seepage-stress-damage model for a vuggy carbonate reservoir is established based on statistical damage mechanics theory and finite element method. The accuracy of the proposed model is validated in comparison with experimental results. Some influencing factors, including fluid pressure in the cave, formation parameters, and construction parameters, are fully taken into account. The study results show that, when the fracture deflection degree is small, a hydraulic fracture can indirectly connect with the cave through high permeable damage units. The matrix heterogeneity that influences hydraulic fracture morphology almost does not affect the interactions between fracture and cave. The higher permeability can lead to insufficient net pressure in the fracture, which is detrimental to the connection between fracture and cave. The ability of the cave to repel fracture is proportional to the in-situ stress magnitude. The higher in-situ stress difference can cause hydraulic fracture extends along with its original path, hindering hydraulic fracture deflection. The compressive stress concentration effect around the cave weakens as the fluid pressure in the cave rises, causing the cave wall to gradually transform from a compressed to a tensioned state. The hydraulic fracture can propagate along its initial trajectory because of the high injection rate’s ability to lessen the impact of the cave. These findings achieve deep insights into interaction patterns between fracture and cave, as well as provide useful guidance for hydraulic fracturing treatment design in fractured-vuggy carbonate reservoirs.

A simple theory for interfacial properties of dilute solutions.

Recent studies suggest that cosolute mixtures may exert significant non-additive effects upon protein stability. The corresponding liquid-vapor interfaces may provide useful insight into these non-additive effects. Accordingly, in this work, we relate the interfacial properties of dilute multicomponent solutions to the interactions between solutes. We first derive a simple model for the surface excess of solutes in terms of thermodynamic observables. We then develop a lattice-based statistical mechanical perturbation theory to derive these observables from microscopic interactions. Rather than adopting a random mixing approximation, this dilute solution theory (DST) exactly treats solute-solute interactions to lowest order in perturbation theory. Although it cannot treat concentrated solutions, Monte Carlo (MC) simulations demonstrate that DST describes the interactions in dilute solutions with much greater accuracy than regular solution theory. Importantly, DST emphasizes a fundamental distinction between the "intrinsic" and "effective" preferences of solutes for interfaces. DST predicts that three classes of solutes can be distinguished by their intrinsic preference for interfaces. While the surface preference of strong depletants is relatively insensitive to interactions, the surface preference of strong surfactants can be modulated by interactions at the interface. Moreover, DST predicts that the surface preference of weak depletants and weak surfactants can be qualitatively inverted by interactions in the bulk. We also demonstrate that DST can be extended to treat surface polarization effects and to model experimental data. MC simulations validate the accuracy of DST predictions for lattice systems that correspond to molar concentrations.

Exploring the Interplay between Disordered and Ordered Oligomer Channels on the Aggregation Energy Landscapes of α-Synuclein.

The abnormal aggregation of α-synulcein is associated with multiple neurodegenerative diseases such as Parkinson's disease. The hydrophobic non-amyloid component (NAC) region of α-synuclein comprises the core of the fibril in vitro and in vivo. In this work, we study the aggregation landscape of the hydrophobic NAC region of α-synuclein using a transferrable coarse-grained force field, the associative memory water-mediated structure, and energy model (AWSEM). Using structural similarity, we can group metastable states on the free energy landscape of aggregation into three types of oligomers: disordered oligomers, prefibrillar oligomers with disordered tips, and ordered prefibrillar oligomers. The prefibrillar oligomers with disordered tips have more in-register parallel β strands than do the fully disordered oligomers but have fewer in-register parallel β strands than the ordered prefibrillar oligomers. Along with the ordered prefibrillar species, the disordered oligomeric states dominate at small oligomer sizes while the prefibrillar species with disordered tips thermodynamically dominate with the growth of oligomers. The topology of the aggregation landscape and observations in simulations suggest there is backtracking between ordered prefibrillar oligomers and other kinds of oligomers as the aggregation proceeds. The significant structural differences between the ordered prefibrillar oligomers and the disordered oligomers support the idea that the growth of these two kinds of oligomers involves kinetically independent parallel pathways. In contrast, the overall structural similarity between the fully ordered prefibrillar oligomers and the prefibrillar oligomers with disordered tips implies that two channels can interconvert on slower time scales. We also evaluate the effects of phosphorylation on the aggregation free energy landscape using statistical mechanical perturbation theory.

Entanglement Phase Transition with Spin Glass Criticality.

We define an ensemble of random Clifford quantum circuits whose output state undergoes an entanglement phase transition between two volume-law phases as a function of measurement rate. Our setup maps exactly the output state to the ground space of a spin glass model. We identify the entanglement phases using an order parameter that is accessible on a quantum chip. We locate the transition point and evaluate a critical exponent, revealing spin glass criticality. Our Letter establishes an exact statistical mechanics theory of an entanglement phase transition.

Statistical–mechanical theory of topological indices

Topological indices (TI) are algebraic invariants of molecular graphs representing the topology of a molecule, which are very valuable in quantitative structure–property relations (QSPR). Here we prove that TI are the partition functions of such molecules when the temperature of the thermal bath at which they are submerged is very high. These partition functions are obtained by describing molecular electronic properties through tight-binding Hamiltonians (TBH), where the hopping parameters are topological properties describing atom–atom interactions. We prove that the TBH proposed here are non-Hermitian diagonalizable Hamiltonians which can be replaced by symmetric ones. In this way we propose a statistical–mechanical theory for TI, which is exemplified by deriving the Randić, Zagreb, Balaban, Wiener and ABC indices. The work also illuminates how to improve QSPR models using the current theoretical framework as well as how to derive statistical–mechanical parameters of molecular graphs.

Elasticity-associated rebinding rate of molecular bonds between soft elastic media

A quantitative understanding of how cells interact with their extracellular matrix via molecular bonds is fundamental for many important processes in cell biology and engineering. In these interactions, the deformability of cells and matrix are usually comparable with that of the bonds, making their rebinding events globally coupled with the deformation states of whole systems. Unfortunately, this important principle is not realized or adopted in most conventional theoretical models for analyzing cellular adhesions. In this study, we considered a new theoretical model of a cluster of ligand-receptor bonds between two soft elastic bodies, in which the rebinding rates of ligands to receptors are described, by considering the deformation of the overall system under the influence of bond distributions. On the basis of theory of continuum and statistical mechanics, we obtained an elasticity-associated rebinding rate of open bonds in a closed analytical form that highly depends on the binding states and distributions of all other bonds as well as on the overall deformation energy stored in the elastic bodies and all closed bonds. On the basis of this elasticity-associated rebinding rate and by performing Monte Carlo simulations, we uncovered new mechanisms underlying the adhesion stability of molecular-bond clusters associated with deformable elastic bodies. Moreover, we revealed that the rebinding processes of molecular bonds is not only dependent on interfacial separation but is related to overall energy. This newly proposed rebinding rate may substantially improve our understanding of how cells adapt to their microenvironments by adjusting their mechanical properties through cytoskeleton remodeling.

Rubber elasticity of polymer networks in explicitly non-Gaussian states. Statistical mechanics and LF-NMR inquiry in hydrogel systems

We present a statistical mechanics theory of rubber-like elasticity in swollen and unswollen polymer networks characterized by explicitly non-Gaussian distribution functions (Laplace’s, Cauchy’s, and continuous Poisson’s in the exponential limit). An important outcome is the derivation of new families of statistical and mechanical laws, including a discussion of energy functions of strain invariants, which are reasonably simple for a model comparison with available data on polymer networks. Accordingly, a theoretical–experimental approach based on LF-NMR was devised to identify the most likely end-to-end length distribution in an arbitrary network. When this strategy is applied to agar 1 %, alginate 1 %, and scleroglucan 2 % hydrogels, it turns out that the end-to-end distribution should be never regarded as Gaussian even if, as in agar and scleroglucan systems, the normal statistics is the best among those here regarded. Remarkably, Poisson’s distribution is proved instead to be the most realistic for the alginate hydrogel.