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Negatively charged nanoparticles (NPs) in 1:1, 1:2, and 1:3 electrolyte solutions are studied in a primitive ion model using molecular dynamics (MD) simulations and classical density functional theory (DFT). We determine the conditions for attractive interactions between the like-charged NPs. Ion density profiles and NP-NP interaction free energies are compared between the two methods and are found to be in qualitative agreement. The NP interaction free energy is purely repulsive for monovalent counterions, but can be attractive for divalent and trivalent counterions. Using DFT, the NP interaction free energy for different NP diameters and charges is calculated. The depth and location of the minimum in the interaction depend strongly on the NPs' charge. For certain parameters, the depth of the attractive well can reach 8-10 kBT, indicating that kinetic arrest and aggregation of the NPs due to electrostatic interactions is possible. Rich behavior arises from the geometric constraints of counterion packing at the NP surface. Layering of counterions around the NPs is observed and, as secondary counterion layers form the minimum of the NP-NP interaction free energy shifts to larger separation, and the depth of the free energy minimum varies dramatically. We find that attractive interactions occur with and without NP overcharging. [ABSTRACT FROM AUTHOR]

Photoresponsive molecules can be integrated into glassy materials to probe the local environment and invoke responsive changes in polymer behavior. For example, recent experiments and simulations have studied increased stability in vapor-deposited glasses by examining the photoisomerization rate of a probe molecule. At the theoretical level, past work relied on coarse-grained simulations to explain the role of photoisomerization on glass behavior. In order to effectively exploit these molecular probes, an ability to quantify how the local environment influences the photoisomerization rate is needed. In this work, we present all-atom molecular-dynamics (MD) simulations of molecular glasses of photoresponsive azobenzene (AB) molecules. The stability of these in-silico samples is probed using photoisomerization, where AB molecules can undergo trans → cis transition upon light exposure. Vapor-deposited and bulk-cooled glasses of AB are simulated using a classical dihedral-switching potential developed by Böckmann et al. ( J. Phys. Chem. A 2010, 114, 745-754) to model the photoisomerization process. The MD simulations include thousands of molecules and run for tens of nanoseconds. These size and time scales allow us to explore the broad distribution of photoisomerization wait times, which yields two results. First, the wait-time distributions for both physical vapor deposition and bulk-cooled glasses depend strongly on sample and local density, showing that density or local packing is a primary factor in glass stability against photoisomerization and the experimentally measured photoresponse. Second, the distribution follows a power-law with exponent b ≈ 1.25-1.3 that extends to longer times with increasing density. The power-law distribution suggests a connection with previous experiments that related barriers to photoisomerization with an effective photoisomerization temperature.

Coarse-grained (CG) polymer simulations can access longer times and larger lengths than all-atom (AA) molecular dynamics simulations; however, not all CG models correctly reproduce polymer properties on all length scales. Here we coarse-grain atomistic position data from polyethylene (PE) and polytetrafluoroethylene (PTFE) melt simulations by combining λ backbone carbon atoms in a single CG bead. Resulting CG variables have correlations along the chain backbone that depend on the coarse-graining scale λ and are generally not reproduced by independent bond-length, bond-angle and torsion-angle distributions. By constructing distributions of CG variables equivalent to those from simulated CG potentials we are able to evaluate the bond-orientation correlation for different CG models at reduced computational cost. CG models and potentials that include only nonbonded, bond-length, and bond-angle interactions computed by Boltzmann inversion correctly reproduce the CG variable distributions but do not necessarily reproduce the chain stiffness, overestimating the persistence length L p and end-to-end distance ⟨ R 2 ⟩ 1/2 with increasing λ. While CG models that include an independent torsion angle match the bond-orientation correlation and ⟨ R 2 ⟩ 1/2 better, only approximate models that include correlations between bond and torsion angles match the true bond-orientation correlation.

The distinctive viscoelastic behavior of polymers results from a coupled interplay of motion on multiple length and time scales. Capturing the broad time and length scales of polymer motion remains a challenge. Using polyethylene (PE) as a model macromolecule, we construct coarse-grained (CG) models of PE with three to six methyl groups per CG bead and probe two critical aspects of the technique: pressure corrections required after iterative Boltzmann inversion (IBI) to generate CG potentials that match the pressure of reference fully atomistic melt simulations and the transferability of CG potentials across temperatures. While IBI produces nonbonded pair potentials that give excellent agreement between the atomistic and CG pair correlation functions, the resulting pressure for the CG models is large compared with the pressure of the atomistic system. We find that correcting the potential to match the reference pressure leads to nonbonded interactions with much deeper minima and slightly smaller effective bead diameter. However, simulations with potentials generated by IBI and pressure-corrected IBI result in similar mean-square displacements (MSDs) and stress autocorrelation functions G(t) for PE melts. While the time rescaling factor required to match CG and atomistic models is the same for pressure- and non-pressure-corrected CG models, it strongly depends on temperature. Transferability was investigated by comparing the MSDs and stress autocorrelation functions for potentials developed at different temperatures.