Computer simulation of rod-sphere mixtures.

Results are presented from a series of simulations undertaken to investigate the effect of adding small spherical particles to a fluid of rods which would otherwise represent a liquid crystalline (LC) substance. Firstly, a bulk mixture of Hard Gaussian Overlap particles with an aspect ratio of 3:1 and hard spheres with diameters equal to the breadth of the rods is simulated at various sphere concentrations. Both mixing-demixing and isotropic-nematic transition are studied using Monte Carlo techniques. Secondly, the effect of adding Lennard-Jones particles to an LC system modelled using the well established Gay-Berne potential is investigated. These rod-sphere mixtures are simulated using both the original set of interaction parameters and a modified version of the rod-sphere potential proposed in this work. The subject of interest is the internal structure of the binary mixture and its dependence on density, temperature, concentration and various parameters characterising the in-termolecular interactions. Both the mixing-demixing behaviour and the transitions between the isotropic and any LC phases have been studied for four systems which differ in the interaction potential between unlike particles. A range of contrasting microphase separated structures including bicontinuous, cubic, and micelle-like arrangement have been observed in bulk. Thirdly, the four types of mixtures previously studied in bulk are subjected to a static magnetic field. A variety of novel phases are observed for the cases of positive and negative anisotropy in the magnetic susceptibility. These include a lamellar structure, in which layers of rods are separated by layers of spheres, and a configuration with a self-assembling hexagonal array of spheres. Finally, two new models are presented to study liquid crystal mixtures in the presence of curved substrates. These are implemented for the cases of convex and concave spherical surfaces. The simulation results obtained in these geometries indicate segregation of spheres at the topological defect of the director field induced by the surface

Sidechain control of porosity closure in multiple peptide-based porous materials by cooperative folding

Porous materials find application in separation, storage and catalysis. We report a crystalline porous solid formed by coordination of metal centres with a glycylserine dipeptide. We prove experimentally that the structure evolves from a solvated porous into a non-porous state as result of ordered displacive and conformational changes of the peptide that suppress the void space in response to environmental pressure. This cooperative closure, which recalls the folding of proteins, retains order in three-dimensions and is driven by the hydroxyl groups acting as H-bond donors in the peptide sequence through the serine residue. This ordered closure is also displayed by multipeptide solid solutions in which the combination of different sequences of amino acids controls their guest response in a non-linear way. This functional control can be compared to the effect of single point mutations in proteins, where the exchange of single amino acids can radically alter structure and functio

Orientational and phase-coexistence behaviour of hard rod-sphere mixtures

Results are presented from Monte Carlo simulations of bulk mixtures of Hard Gaussian Overlap particles with an aspect ratio of 3:1 and hard spheres with diameters equal to the breadths of the rods. For sphere number-concentrations of 50% and lower, compression of the isotropic fluid results in formation of a homogeneous (i.e. compositionally mixed) nematic phase. The volume fraction of this isotropic-nematic transition is found to increase approximately linearly with sphere concentration. On compression to higher volume fractions, however, this homogeneous nematic phase separates out into coexisting nematic and isotropic phases.</p

Incorporation of excluded volume correlations into Poisson-Boltzmann theory

We investigate the effect of excluded volume interactions on the electrolyte distribution around a charged macroion. First, we introduce a criterion for determining when hard-core effects should be taken into account beyond standard mean field Poisson-Boltzmann (PB) theory. Next, we demonstrate that several commonly proposed local density functional approaches for excluded volume interactions cannot be used for this purpose. Instead, we employ a non-local excess free energy by using a simple constant weight approach. We compare the ion distribution and osmotic pressure predicted by this theory with Monte Carlo simulations. They agree very well for weakly developed correlations and give the correct layering effect for stronger ones. In all investigated cases our simple weighted density theory yields more realistic results than the standard PB approach, whereas all local density theories do not improve on the PB density profiles but on the contrary, deviate even more from the simulation results.Comment: 23 pages, 7 figures, 1 tabl

Element selection for functional materials discovery by integrated machine learning of atomic contributions to properties

At the high level, the fundamental differences between materials originate from the unique nature of the constituent chemical elements. Before specific differences emerge according to the precise ratios of elements (composition) in a given crystal structure (phase), the material can be represented by its phase field defined simply as the set of the constituent chemical elements. Classification of the materials at the level of their phase fields can accelerate materials discovery by selecting the elemental combinations that are likely to produce desirable functional properties in synthetically accessible materials. Here, we demonstrate that classification of the materials phase field with respect to the maximum expected value of a target functional property can be combined with the ranking of the materials synthetic accessibility. This end-to-end machine learning approach (PhaseSelect) first derives the atomic characteristics from the compositional environments in all computationally and experimentally explored materials and then employs these characteristics to classify the phase field by their merit. PhaseSelect can quantify the materials potential at the level of the periodic table, which we demonstrate with significant accuracy for three avenues of materials applications: high-temperature superconducting, high-temperature magnetic and targetted energy band gap materials

Crystal Structure Prediction via Oblivious Local Search

We study Crystal Structure Prediction, one of the major problems in computational chemistry. This is essentially a continuous optimization problem, where many different, simple and sophisticated, methods have been proposed and applied. The simple searching techniques are easy to understand, usually easy to implement, but they can be slow in practice. On the other hand, the more sophisticated approaches perform well in general, however almost all of them have a large number of parameters that require fine tuning and, in the majority of the cases, chemical expertise is needed in order to properly set them up. In addition, due to the chemical expertise involved in the parameter-tuning, these approaches can be {\em biased} towards previously-known crystal structures. Our contribution is twofold. Firstly, we formalize the Crystal Structure Prediction problem, alongside several other intermediate problems, from a theoretical computer science perspective. Secondly, we propose an oblivious algorithm for Crystal Structure Prediction that is based on local search. Oblivious means that our algorithm requires minimal knowledge about the composition we are trying to compute a crystal structure for. In addition, our algorithm can be used as an intermediate step by {\em any} method. Our experiments show that our algorithms outperform the standard basin hopping, a well studied algorithm for the problem

Peptide Metal-Organic Frameworks for Enantioselective Separation of Chiral Drugs

We report the ability of a chiral Cu(II) 3D MOF based on the tripeptide Gly-L-His-Gly (GHG) for the enantioselective separation of metamphetamine and ephedrine. Monte Carlo simulations suggest that chiral recognition is linked to preferential binding of one of the enantiomers as result of either stronger or additional H-bonds with the framework that lead to energetically more stable diastereomeric adducts. Solid phase extraction (SPE) of a racemic mixture by using Cu(GHG) as extractive phase permits isolating more than 50% of the (+)-ephedrine enantiomer as target compound in only four minutes. To the best of our knowledge, this represents the first example of a MOF capable of separating chiral polar drugs

Conformational control of structure and guest uptake by a tripeptide-based porous material

Chemical processes often rely on the selective sorting and transformation of molecules according to their size, shape and chemical functionality. For example, porous materials such as zeolites achieve the required selectivity through the constrained pore dimensions of a single structure.1 In contrast, proteins function by navigating between multiple metastable structures using bond rotations of the polypeptide,2,3 where each structure lies in one of the minima of a conformational energy landscape and can be selected according to the chemistry of the molecules interacting with the protein.3 Here we show that rotation about covalent bonds in a peptide linker can change a flexible metal-organic framework (MOF) to afford nine distinct crystal structures, revealing a conformational energy landscape characterised by multiple structural minima. The uptake of small molecule guests by the MOF can be chemically triggered by inducing peptide conformational change. This change transforms the material from a minimum on the landscape that is inactive for guest sorption to an active one. Chemical control of the conformation of a flexible organic linker offers a route to modify the pore geometry and internal surface chemistry and thus the function of open-framework materials

Differential guest location by host dynamics enhances propylene/propane separation in a metal-organic framework

Energy-efficient approaches to propylene/propane separation such as molecular sieving are of considerable importance for the petrochemical industry. The metal organic framework NbOFFIVE-1-Ni adsorbs propylene but not propane at room temperature and atmospheric pressure, whereas the isostructural SIFSIX-3-Ni does not exclude propane under the same conditions. The static dimensions of the pore openings of both materials are too small to admit either guest, signalling the importance of host dynamics for guest entrance to and transport through the channels. We use ab initio calculations together with crystallographic and adsorption data to show that the dynamics of the two framework-forming units, polyatomic anions and pyrazines, govern both diffusion and separation. The guest diffusion occurs by opening of the flexible window formed by four pyrazines. In NbOFFIVE-1-Ni, (NbOF5)2- anion reorientation locates propane away from the window, which enhances propylene/propane separation

Superionic lithium transport via multiple coordination environments defined by two-anion packing

Fast cation transport in solids underpins energy storage. Materials design has focused on structures that can define transport pathways with minimal cation coordination change, restricting attention to a small part of chemical space. Motivated by the greater structural diversity of binary intermetallics than that of the metallic elements, we used two anions to build a pathway for three-dimensional superionic lithium ion conductivity that exploits multiple cation coordination environments. Li 7 Si 2 S 7 I is a pure lithium ion conductor created by an ordering of sulphide and iodide that combines elements of hexagonal and cubic close-packing analogously to the structure of NiZr. The resulting diverse network of lithium positions with distinct geometries and anion coordination chemistries affords low barriers to transport, opening a large structural space for high cation conductivity. </jats:p