Symmetry Energy and the Pauli Exclusion Principle

In this article we present a classical potential that respects the Pauli exclusion principle and can be used to describe nucleon-nucleon interactions at intermediate energies. The potential depends on the relative momentum of the colliding nucleons and reduces interactions at low momentum transfer mimicking the Pauli exclusion principle. We use the potential with Metropolis Monte Carlo methods and study the formation of finite nuclei and infinite systems. We find good agreement in terms of the binding energies, radii, and internal nucleon distribution of finite nuclei, and the binding energy in nuclear matter and neutron star matter, as well as the formation of nuclear pastas, and the symmetry energy of neutron star matter.

Classical and Quantum Gases on a Semiregular Mesh

The main objective of a statistical mechanical calculation is drawing the phase diagram of a many-body system. In this respect, discrete systems offer the clear advantage over continuum systems of an easier enumeration of microstates, though at the cost of added abstraction. With this in mind, we examine a system of particles living on the vertices of the (biscribed) pentakis dodecahedron, using different couplings for first and second neighbor particles to induce a competition between icosahedral and dodecahedral orders. After working out the phases of the model at zero temperature, we carry out Metropolis Monte Carlo simulations at finite temperature, highlighting the existence of smooth transitions between distinct “phases”. The sharpest of these crossovers are characterized by hysteretic behavior near zero temperature, which reveals a bottleneck issue for Metropolis dynamics in state space. Next, we introduce the quantum (Bose-Hubbard) counterpart of the previous model and calculate its phase diagram at zero and finite temperatures using the decoupling approximation. We thus uncover, in addition to Mott insulating “solids”, also the existence of supersolid “phases” which progressively shrink as the system is heated up. We argue that a quantum system of the kind described here can be realized with programmable holographic optical tweezers.

Electrostatics drive oligomerization and aggregation of human Interferon alpha-2a

Aggregation and oligomer formation are critical parameters in the field of protein therapeutics and can lead to loss of drug function or even immunogenic responses in patients. Currently two approaches are used to reduce aggregation: (1) finding a suitable formulation which is labor-intensive and requires large protein quantities or (2) engineering the protein by specific, stabilizing mutations, which requires specific knowledge about the protein aggregation pathway. We present a biophysical characterization of the oligomerization and aggregation process by Interferon alpha-2a, a protein drug with antiviral and immunomodulatory properties. We combine high throughput screening with detailed investigations by small-angle X-ray scattering and analytical ultracentrifugation. To get more insight into the molecular mechanism that drives oligomerization and aggregation, we apply molecular Metropolis Monte Carlo simulations. IFNα-2a forms soluble oligomers, which show a fast pH and concentration-dependent equilibrium. We show that attraction between monomers is mainly driven by molecular dipole-dipole interactions, which becomes more pronounced with increasing pH. Repulsion is dominated by ion-ion interaction leading to the formation of insoluble aggregates around the pI which could be prevented by the addition of salt. This study shows how a combination of several methods can help to understand the formation of aggregates and oligomers more systematically and comprehensively, which can lead to better strategies for avoiding aggregation.

Using Monte Carlo to Simulate Complex Polymer Systems: Recent Progress and Outlook

Metropolis Monte Carlo has been employed with remarkable success over the years to simulate the dense phases of polymer systems. Owing, in particular, to the freedom it provides to accelerate sampling in phase space through the clever design and proper implementation of even unphysical moves that take the system completely away from its natural trajectory, and despite that it cannot provide any direct information about dynamics, it has turned to a powerful simulation tool today, often viewed as an excellent alternative to the other, most popular method of Molecular Dynamics. In the last years, Monte Carlo has advanced considerably thanks to the design of new moves or to the efficient implementation of existing ones to considerably more complex systems than those for which these were originally proposed. In this short review, we highlight recent progress in the field (with a clear emphasis in the last 10 years or so) by presenting examples from applications of the method to several systems in Soft Matter, such as polymer nanocomposites, soft nanostructured materials, confined polymers, polymer rings and knots, hydrogels and networks, crystalline polymers, and many others. We highlight, in particular, extensions of the method to non-equilibrium systems (e.g., polymers under steady shear flow) guided by non-equilibrium thermodynamics and emphasize the importance of hybrid modeling schemes (e.g., coupled Monte Carlo simulations with field theoretic calculations). We also include a short section discussing some key remaining challenges plus interesting future opportunities.

3D Bioprinting of Model Tissues That Mimic the Tumor Microenvironment

The tumor microenvironment (TME) influences cancer progression. Therefore, engineered TME models are being developed for fundamental research and anti-cancer drug screening. This paper reports the biofabrication of 3D-printed avascular structures that recapitulate several features of the TME. The tumor is represented by a hydrogel droplet uniformly loaded with breast cancer cells (106 cells/mL); it is embedded in the same type of hydrogel containing primary cells—tumor-associated fibroblasts isolated from the peritumoral environment and peripheral blood mononuclear cells. Hoechst staining of cryosectioned tissue constructs demonstrated that cells remodeled the hydrogel and remained viable for weeks. Histological sections revealed heterotypic aggregates of malignant and peritumoral cells; moreover, the constituent cells proliferated in vitro. To investigate the interactions responsible for the experimentally observed cellular rearrangements, we built lattice models of the bioprinted constructs and simulated their evolution using Metropolis Monte Carlo methods. Although unable to replicate the complexity of the TME, the approach presented here enables the self-assembly and co-culture of several cell types of the TME. Further studies will evaluate whether the bioprinted constructs can evolve in vivo in animal models. If they become connected to the host vasculature, they may turn into a fully organized TME.

Optimization and Computational Approach to Understand the Adsorption Behavior of Alizarine Red S on the Surface of Fish Scales

The key components of fish scales are hydroxyapatite and collagen, which form a natural composite. In this present study, fish scales were used as biosorbent to uptake Alizarine Red S dyes from the wastewaters. Here, dye concentration, adsorbent amount, pH, and temperature were optimized using complete factorial design analysis. Sixteen experiments were required, and a linear mathematical model representing the influence of the different variables and their interactions was obtained. The discussion covered analysis of variance (ANOVA), normal probability plots of residuals, and surface plots. Theoretical calculations by Metropolis Monte Carlo (MC) methods, the density functional theory (DFT), and the electrostatic potential surface (ESP) analysis were achieved to obtain a more understanding of the dyes adsorption mechanism on both collagen and hydroxyapatite (HDA) surfaces. The findings results exhibited that the ARS dye presents more tendency of adsorption on the collagen than on the HDA surface.

Single Chain Mean-Field Theory Study on Responsive Behavior of Semiflexible Polymer Brush

The application of single chain mean-field theory (SCMFT) on semiflexible chain brushes is reviewed. The worm-like chain (WLC) model is the best mode of semiflexible chain that can continuously recover to the rigid rod model and Gaussian chain (GC) model in rigid and flexible limits, respectively. Compared with the commonly used GC model, SCMFT is more applicable to the WLC model because the algorithmic complexity of the WLC model is much higher than that of the GC model in self-consistent field theory (SCFT). On the contrary, the algorithmic complexity of both models in SCMFT are comparable. In SCMFT, the ensemble average of quantities is obtained by sampling the conformations of a single chain or multi-chains in the external auxiliary field instead of solving the modified diffuse equation (MDE) in SCFT. The precision of this calculation is controlled by the number of bonds Nm used to discretize the chain contour length L and the number of conformations M used in the ensemble average. The latter factor can be well controlled by metropolis Monte Carlo simulation. This approach can be easily generalized to solve problems with complex boundary conditions or in high-dimensional systems, which were once nightmares when solving MDEs in SCFT. Moreover, the calculations in SCMFT mainly relate to the assemble averages of chain conformations, for which a portion of conformations can be performed parallel on different computing cores using a message-passing interface (MPI).

Non-equilibrium metal oxides via reconversion chemistry in lithium-ion batteries

Binary metal oxides are attractive anode materials for lithium-ion batteries. Despite sustained effort into nanomaterials synthesis and understanding the initial discharge mechanism, the fundamental chemistry underpinning the charge and subsequent cycles—thus the reversible capacity—remains poorly understood. Here, we use in operando X-ray pair distribution function analysis combining with our recently developed analytical approach employing Metropolis Monte Carlo simulations and non-negative matrix factorisation to study the charge reaction thermodynamics of a series of Fe- and Mn-oxides. As opposed to the commonly believed conversion chemistry forming rocksalt FeO and MnO, we reveal the two oxide series topotactically transform into non-native body-centred cubic FeO and zincblende MnO via displacement-like reactions whose kinetics are governed by the mobility differences between displaced species. These renewed mechanistic insights suggest avenues for the future design of metal oxide materials as well as new material synthesis routes using electrochemically-assisted methods.

Monte Carlo simulations of weak polyampholyte microgels: pH-dependence of conformation and ionization

We performed Metropolis Monte Carlo simulations to investigate the impact of varying acid and base dissociation constants on the pH-dependent ionization and conformation of weak polyampholyte microgels under salt-free conditions...