Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

Growth of (Perylene)(2) [PD(MNT)(2)] crystals

The conditions for [pd(mnt)(2)]he growth of [pd(mnt)(2)]Perylene) [pd(mnt)(2)] [Pd(mnt) [pd(mnt)(2)]] crystals either by chemical oxidation and electrochemical routes are [pd(mnt)(2)]escribed. The electrocrystallisation is limited by close [pd(mnt)(2)]roximity of [pd(mnt)(2)]he oxidation [pd(mnt)(2)]otentials of [pd(mnt)(2)]he [pd(mnt)(2)]erylene [pd(mnt)(2)]onor and [Pd(mnt) [pd(mnt)(2)]] - anion, and [pd(mnt)(2)]epending on [pd(mnt)(2)]he experimental conditions [pd(mnt)(2)]ifferent [pd(mnt)(2)]orphologies can be obtained. [pd(mnt)(2)]Per) [pd(mnt)(2)] [Pd(mnt) [pd(mnt)(2)]] crystals obtained by elecrocrystallisation were found [pd(mnt)(2)]o be [pd(mnt)(2)]ainly of [pd(mnt)(2)]he β-polymorph with [pd(mnt)(2)]roperties comparable [pd(mnt)(2)]o [pd(mnt)(2)]he Cu, Ni and Pt analogues [pd(mnt)(2)]reviously [pd(mnt)(2)]escribed at variance with [pd(mnt)(2)]hose obtained by chemical oxidation which are [pd(mnt)(2)]ainly of [pd(mnt)(2)]he α-polymorph.

Reactivity of bulky tris(Phenylpyrazolyl) methanesulfonate copper(I) complexes towards small unsaturated molecules

Reaction of the tris(3-phenylpyrazolyl)methane sulfonate species (Tpms(Ph))Li with the copper(I) complex [Cu(MeCN)(4)][PF6] affords [Cu(Tpms(Ph))(MeCN)] 1. The latter, upon reaction with equimolar amounts of cyclohexyl-(CyNC) or 2,6-dimethylphenyl (XylNC) isocyanides, or excess CO, furnishes the corresponding Cu(I)complexes [Cu(Tpms(Ph))(CNR)] (R = Cy 2, Xyl 3) or [Cu(Tpms(Ph))(CO)] 4. The ligated isocyanide in 2 or 3 (or the acetonitrile ligand in 1)is displaced by 3-iminoisoindolin-1-one to afford 5, the first copper(I) complex containing an 3-iminoisoindolin-1-one ligand. The ligated acetonitrile in 1 undergoes nucleophilic attack by methylamine to give the amidine complex [Cu(Tpms(Ph)){MeC(NH)NHMe}] 6, whereas only the starting materials were recovered from the attempted corresponding reactions of 2 and 3 with methylamine. Complexes 1 or 6 form the trinuclear hydroxo-copper(II)species [(mu-Cu){Cu(mu-OH) (2)(Tpms(Ph))}(2)] 7 upon air oxidation in moist methanol. In all the complexes the scorpionate ligand facially caps the metal in the N,N,O-coordination mode.