Pattern formation in binary fluid mixtures induced by short-range competing interactions

Molecular dynamics simulations and integral equation calculations of a simple equimolar mixture of diatomic molecules and monomers interacting via attractive and repulsive short-range potentials show the existence of pattern formation (microheterogeneity), mostly due to depletion forces away from the demixing region. Effective site-site potentials extracted from the pair correlation functions using an inverse Monte Carlo approach and an integral equation inversion procedure exhibit the features characteristic of a short-range attractive and long-range repulsive potential. When charges are incorporated into the model, this becomes a coarse grained representation of a room temperature ionic liquid, and as expected, intermediate range order becomes more pronounced and stable

Phase diagram of a two-dimensional lattice gas model of a ramp system

Using Monte Carlo Simulation and fundamental measure theory we study the phase diagram of a two-dimensional lattice gas model with a nearest neighbor hard core exclusion and a next-to-nearest neighbors finite repulsive interaction. The model presents two competing ranges of interaction and, in common with many experimental systems, exhibits a low density solid phase, which melts back to the fluid phase upon compression. The theoretical approach is found to provide a qualitatively correct picture of the phase diagram of our model system.Comment: 14 pages, 8 figures, uses RevTex

Spin injection in Silicon at zero magnetic field

In this letter, we show efficient electrical spin injection into a SiGe based \textit{p-i-n} light emitting diode from the remanent state of a perpendicularly magnetized ferromagnetic contact. Electron spin injection is carried out through an alumina tunnel barrier from a Co/Pt thin film exhibiting a strong out-of-plane anisotropy. The electrons spin polarization is then analysed through the circular polarization of emitted light. All the light polarization measurements are performed without an external applied magnetic field \textit{i.e.} in remanent magnetic states. The light polarization as a function of the magnetic field closely traces the out-of-plane magnetization of the Co/Pt injector. We could achieve a circular polarization degree of the emitted light of 3 % at 5 K. Moreover this light polarization remains almost constant at least up to 200 K.Comment: accepted in AP

Bio-based non-isocyanate poly(hydroxy urethane)s (PHU) derived from vanillin and CO₂

As an alternative to the use of hazardous phosgene-based isocyanates for polyurethane preparation, non-isocyanate poly(hydroxy urethanes) (PHU) based on 5-membered cyclic carbonates have been developed. However, to date, most aromatic PHUs are oil-based or based on toxic precursors such as bisphenol-A. In this work, bio-based non-isocyanate poly(hydroxy urethanes) (PHUs) prepared from vanillin are reported for the first time. First, three different vanillin-derived bis-cyclic carbonates were synthesized. Subsequently, each monomer was reacted with two different bis-amines to yield six different PHUs, which were characterized in depth by 1H and 13C NMR spectroscopy, FTIR, SEC and DSC. PHUs based on vanillic acid were found to exhibit thermal properties superior to bisphenol A-based PHUs, with a Tg of around 66 °C. It is envisioned that vanillin-based PHUs could potentially be a safer alternative to harmful bisphenol A-based PHUs and provide a useful strategy for CO2 revalorization, especially considering that vanillin is an abundant byproduct of Kraft lignin production

An efficient multi-scale Green’s function reaction dynamics scheme

Molecular Dynamics-Green’s Function Reaction Dynamics (MD-GFRD) is a multiscale simulation method for particle dynamics or particle-based reaction- diffusion dynamics that is suited for systems involving low particle densities. Particles in a low-density region are just diffusing and not interacting. In this case, one can avoid the costly integration of microscopic equations of motion, such as molecular dynamics (MD), and instead turn to an event-based scheme in which the times to the next particle interaction and the new particle positions at that time can be sampled. At high (local) concentrations, however, e.g., when particles are interacting in a nontrivial way, particle positions must still be updated with small time steps of the microscopic dynamical equations. The efficiency of a multi-scale simulation that uses these two schemes largely depends on the coupling between them and the decisions when to switch between the two scales. Here we present an efficient scheme for multi-scale MD-GFRD simulations. It has been shown that MD-GFRD schemes are more efficient than brute-force molecular dynamics simulations up to a molar concentration of 102 μM. In this paper, we show that the choice of the propagation domains has a relevant impact on the computational performance. Domains are constructed using a local optimization of their sizes and a minimal domain size is proposed. The algorithm is shown to be more efficient than brute-force Brownian dynamics simulations up to a molar concentration of 103 μM and is up to an order of magnitude more efficient compared with previous MD-GFRD schemes

Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics

Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training accurate CG models remains a challenge. A widely used methodology for learning CG force-fields maps forces from all-atom molecular dynamics to the CG representation and matches them with a CG force-field on average. We show that there is flexibility in how to map all-atom forces to the CG representation, and that the most commonly used mapping methods are statistically inefficient and potentially even incorrect in the presence of constraints in the all-atom simulation. We define an optimization statement for force mappings and demonstrate that substantially improved CG force-fields can be learned from the same simulation data when using optimized force maps. The method is demonstrated on the miniproteins Chignolin and Tryptophan Cage and published as open-source code.Comment: 44 pages, 19 figure

Variational Approach to Molecular Kinetics

The eigenvalues and eigenvectors of the molecular dynamics propagator (or transfer operator) contain the essential information about the molecular thermodynamics and kinetics. This includes the stationary distribution, the metastable states, and state-to-state transition rates. Here, we present a variational approach for computing these dominant eigenvalues and eigenvectors. This approach is analogous the variational approach used for computing stationary states in quantum mechanics. A corresponding method of linear variation is formulated. It is shown that the matrices needed for the linear variation method are correlation matrices that can be estimated from simple MD simulations for a given basis set. The method proposed here is thus to first define a basis set able to capture the relevant conformational transitions, then compute the respective correlation matrices, and then to compute their dominant eigenvalues and eigenvectors, thus obtaining the key ingredients of the slow kinetics