A computational study of cellulose regeneration: Coarse-grained molecular dynamics simulations.

Understanding the microscopic mechanisms of regeneration of cellulose is prerequisite for engineering and controlling its material properties. In this paper, we performed coarse-grained Martini 3 molecular dynamics simulations of cellulose regeneration at a scale comparable to the experiments. The X-ray diffraction (XRD) curves were monitored to follow the structural changes of regenerated cellulose and trace formation of cellulose sheets and crystallites. The calculated coarse-grained morphologies of regenerated cellulose were backmapped to atomistic ones. After the backmapping we find that the regenerated coarse-grained cellulose structures calculated for both topology parameters of cellulose Iß and cellulose II/III, are transformed to cellulose II, where the calculated XRD curves exhibit the main peak at approximately 20-21 degrees, corresponding to the (110)/(020) planes of cellulose II. This result is in good quantitative agreement with the available experimental observations.

A computational study of cellulose regeneration: All-atom molecular dynamics simulations.

Processing natural cellulose requires its dissolution and regeneration. It is known that the crystallinity of regenerated cellulose does not match that of native cellulose, and the physical and mechanical properties of regenerated cellulose can vary dependent on the technique applied. In this paper, we performed all-atom molecular dynamics simulations attempting to simulate the regeneration of order in cellulose. Cellulose chains display an affinity to align with one another on the nanosecond scale; single chains quickly form clusters, and clusters then interact to form a larger unit, but the end results still lack that abundance of order. Where aggregation of cellulose chains occurs, there is some resemblance of the 1-10 surfaces found in Cellulose II, with certain indication of 110 surface formation. Concentration and simulation temperature show an increase of aggregation, yet it appears that time is the major factor in reclaiming the order of "crystalline" cellulose.

Microscopic Insight into the Structure-Processing-Property Relationships of Core-Shell Structured Dialcohol Cellulose Nanoparticles.

In the quest to develop sustainable and environmentally friendly materials, cellulose is a promising alternative to synthetic polymers. However, native cellulose, in contrast to many synthetic polymers, cannot be melt-processed with traditional techniques because, upon heating, it degrades before it melts. One way to improve the thermoplasticity of cellulose, in the form of cellulose fibers, is through chemical modification, for example, to dialcohol cellulose fibers. To better understand the importance of molecular interactions during melt processing of such modified fibers, we undertook a molecular dynamics study of dialcohol cellulose nanocrystals with different degrees of modification. We investigated the structure of the nanocrystals as well as their interactions with a neighboring nanocrystal during mechanical shearing, Our simulations showed that the stress, interfacial stiffness, hydrogen-bond network, and cellulose conformations during shearing are highly dependent on the degree of modification, water layers between the crystals, and temperature. The melt processing of dialcohol cellulose with different degrees of modification and/or water content in the samples was investigated experimentally by fiber extrusion with water used as a plasticizer. The melt processing was easier when increasing the degree of modification and/or water content in the samples, which was in agreement with the conclusions derived from the molecular modeling. The measured friction between the two crystals after the modification of native cellulose to dialcohol cellulose, in some cases, halved (compared to native cellulose) and is also reduced with increasing temperature. Our results demonstrate that molecular modeling of modified nanocellulose fibers can provide fundamental information on the structure-property relationships of these materials and thus is valuable for the development of new cellulose-based biomaterials.

The structure of cellulose nanofibril networks at low concentrations and their stabilizing action on colloidal particles.

The structure and dynamics of networks formed by rod-shaped particles can be indirectly investigated by measuring the diffusion of spherical tracer particles. This method was used to characterize cellulose nanofibril (CNF) networks in both dispersed and arrested states, the results of which were compared with coarse-grained Brownian dynamics simulations. At a CNF concentration of 0.2 wt% a transition was observed where, below this concentration tracer diffusion is governed by the increasing macroscopic viscosity of the dispersion. Above 0.2 wt%, the diffusion of small particles (20-40 nm) remains viscosity controlled, while particles (100-500 nm) become trapped in the CNF network. Sedimentation of silica microparticles (1-5 µm) in CNF dispersions was also determined, showing that sedimentation of larger particles is significantly affected by the presence of CNF. At concentrations of 0.2 wt%, the sedimentation velocity of 5 µm particles was reduced by 99 % compared to pure water.

PEDOT:PSS nano-particles in aqueous media: A comparative experimental and molecular dynamics study of particle size, morphology and z-potential.

PEDOT: PSS is the most widely used conducting polymer in organic and printed electronics. PEDOT: PSS films have been extensively studied to understand the morphology, ionic and electronic conductivity of the polymer. However, the polymer dispersion, which is used to cast or spin coat the films, is not well characterized and not well understood theoretically. Here, we study in detail the particle morphology, size, charge density and zeta potential (z-potential) by coarse-grained MD simulations and dynamic light scattering (DLS) measurements, for different pH levels and ionic strengths. The PEDOT:PSS particles were found to be 12 nm-19 nm in diameter and had a z-potential of -30 mV to -50 mV when pH was changed from 1.7 to 9, at an added NaCl concentration of 1 mM, as measured by DLS. These values changed significantly with changing pH and ionic strength of the solution. The charge density of PEDOT:PSS particles was also found to be dependent on pH and ionic strength. Besides, the distribution of different ions (PSS-, PEDOT+, Na+, Cl-) present in the solution is simulated to understand the particle morphology and molecular origin of z-potential in PEDOT:PSS dispersion. The trend in change of particle size, charge density and z- potential with changing pH and ionic strength are in good agreement between the simulations and experiments. Our results show that the molecular model developed in this work represents very well the PEDOT:PSS nano-particles in aqueous dispersion. With this study, we hope to provide new insight and an in-depth understanding of the morphology and z-potential evolution in PEDOT:PSS dispersion.

New Patchy Particle Model with Anisotropic Patches for Molecular Dynamics Simulations: Application to a Coarse-Grained Model of Cellulose Nanocrystal.

Self-assembly is ubiquitous in nature and underlies the formation of many complex systems from the molecular to the macroscopic scale. Kern-Frenkel-like patchy particles are powerful models to investigate this phenomenon by computational methods such as Monte Carlo or molecular dynamics simulations. However, in these models the interactions are mediated by circular patches at the particle surface, which can be hardly mapped to realistic systems, containing for instance faceted particles with rectangular surfaces. In this paper we extend the model to take into account such geometries, and we use it to build a supra coarse-grained model of the cellulose nanocrystal where the interactions are parametrized against all-atomistic molecular dynamics simulations. The formation of cholesteric ribbons and defects in cholesteric droplets of the cellulose nanocrystal are investigated and confirm experimental behavior reported in the literature. The flexibility of this new patchy particle model makes it a powerful tool to develop supra coarse-grained models of self-assembly for large space and time scales and should find a broad range of applications for self-assembly in chemical and biological systems.

Selective Charging Behavior in an Ionic Mixture Electrolyte-Supercapacitor System for Higher Energy and Power.

Ion-ion interactions in supercapacitor (SC) electrolytes are considered to have significant influence over the charging process and therefore the overall performance of the SC system. Current strategies used to weaken ionic interactions can enhance the power of SCs, but consequently, the energy density will decrease due to the increased distance between adjacent electrolyte ions at the electrode surface. Herein, we report on the simultaneous enhancement of the power and energy densities of a SC using an ionic mixture electrolyte with different types of ionic interactions. Two types of cations with stronger ionic interactions can be packed in a denser arrangement in mesopores to increase the capacitance, whereas only cations with weaker ionic interactions are allowed to enter micropores without sacrificing the power density. This unique selective charging behavior in different confined porous structure was investigated by solid-state nuclear magnetic resonance experiments and further confirmed theoretically by both density functional theory and molecular dynamics simulations. Our results offer a distinct insight into pairing ionic mixture electrolytes with materials with confined porous characteristics and further propose that it is possible to control the charging process resulting in comprehensive enhancements in SC performance.

Density Functional Theory Study on the Interactions of Metal Ions with Long Chain Deprotonated Carboxylic Acids.

In this work, interactions between carboxylate ions and calcium or sodium ions are investigated via density functional theory (DFT). Despite the ubiquitous presence of these interactions in natural and industrial chemical processes, few DFT studies on these systems exist in the literature. Special focus has been placed on determining the influence of the multibody interactions (with up to 4 carboxylates and one metal ion) on an effective pair-interaction potential, such as those used in molecular mechanics (MM). Specifically, DFT calculations are employed to quantify an effective pair-potential that implicitly includes multibody interactions to construct potential energy curves for carboxylate-metal ion pairs. The DFT calculated potential curves are compared to a widely used molecular mechanics force field (OPLS-AA). The calculations indicate that multibody effects do influence the energetic behavior of these ionic pairs and the extent of this influence is determined by a balance between (a) charge transfer from the carboxylate to the metal ions which stabilizes the complex and (b) repulsion between carboxylates, which destabilizes the complex. Additionally, the potential curves of the complexes with 1 and 2 carboxylates and one counterion have been examined to higher separation distance (20 Å) by the use of relaxed scan optimization and constrained density functional theory (CDFT). The results from the relaxed scan optimization indicate that near the equilibrium distance, the charge transfer between the metal ion and the deprotonated carboxylic acid group is significant and leads to non-negligible differences between the DFT and MM potential curves, especially for calcium. However, at longer separation distances the MM calculated interaction potential functions converge to those calculated with CDFT, effectively indicating the approximate domain of the separation distance coordinate where charge transfer between the ions is occurring.

Ab Initio Molecular Dynamics Study on the Interactions between Carboxylate Ions and Metal Ions in Water.

The interaction between a carboxylate anion (deprotonated propanoic acid) and the divalent Mg(2+), Ca(2+), Sr(2+), Ba(2+) metal ions is studied via ab initio molecular dynamics. The main focus of the study is the selectivity of the carboxylate-metal ion interaction in aqueous solution. The interaction is modeled by explicitly accounting for the solvent molecules on a DFT level. The hydration energies of the metal ions along with their diffusion and mobility coefficients are determined and a trend correlated with their ionic radius is found. Subsequently, a series of 16 constrained molecular dynamics simulations for every ion is performed, and the interaction free energy is obtained from thermodynamic integration of the forces between the metal ion and the carboxylate ion. The results indicate that the magnesium ion interacts most strongly with the carboxylate, followed by calcium, strontium, and barium. Because the interaction free energy is not enough to explain the selectivity of the reaction observed experimentally, more detailed analysis is performed on the simulation trajectories to understand the steric changes in the reaction complex during dissociation. The solvent dynamics appear to play an important role during the dissociation of the complex and also in the observed selectivity behavior of the divalent ions.