The results of the sixth blind test of organic crystal structure prediction methods are presented and discussed, highlighting progress for salts, hydrates and bulky flexible molecules, as well as on-going challenges.

We investigate the ability of current ab initio crystal structure prediction techniques to identify the polymorphs of 5-methyl-2-[(2-nitrophenyl)amino]-3-thiophenecarbonitrile, also known as ROY because of the red, orange and yellow colours of its polymorphs. We use a methodology combining the generation of a large number of structures based on a computationally inexpensive model using the CrystalPredictor global search algorithm, and the further minimization of the most promising of these structures using the CrystalOptimizer local minimization algorithm which employs an accurate, yet efficiently constructed, model based on isolated-molecule quantum-mechanical calculations. We demonstrate that this approach successfully predicts the seven experimentally resolved structures of ROY as lattice-energy minima, with five of these structures being within the 12 lowest energy structures predicted. Some of the other low-energy structures identified are likely candidates for the still unresolved polymorphs of this molecule. The relative stability of the predicted structures only partially matches that of the experimentally resolved polymorphs. The worst case is that of polymorph ON, whose relative energy with respect to Y is overestimated by 6.65 kJ mol(-1). This highlights the need for further developments in the accuracy of the energy calculations.

9Shale gas is an unconventional source of energy, which has attracted a lot of attention during the 10 last years. Kerogen is a prime constituent of shale formations and plays a crucial role in shale gas 11 technology. Significant experimental effort in the study of shales and kerogen has produced a 12 broad diversity of experimentally determined structural and thermodynamic properties even for 13 samples of the same well. Moreover, proposed methods reported in the literature for constructing 14 realistic bulk kerogen configurations have not been thoroughly investigated. One of the most 15 important characteristics of kerogens is their porosity due to its direct connection with their 16 transport properties and its potential as discriminating and classifying metric between samples. In 17 this study, Molecular Dynamics (MD) simulations are used to study the porosity of model 18 2 kerogens. The porosity is controlled effectively with systematic variation of the number and the 1 size of dummy LJ particles that are used during the construction of system's configuration. The 2 porosity of each sample is characterized with a newly proposed algorithm for analyzing the free 3 space of amorphous materials. It is found that with moderately sized configurations, it is possible 4 to construct percolated pores of interest in shale gas industry. 5

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Kerogen is a micro-porous amorphous solid, which consist the major component of the organic matter scattered in the potentially lucrative shale formations hosting shale gas. Deeper understanding of the way kerogen porosity characteristics affect the transport properties of hosted gas is important for the optimal design of the extraction process. In this work, we employ molecular simulation techniques in order to investigate the role of porosity on the adsorption and transport behavior of shale gas in overmature type II kerogen found at many currently productive shales. To account for the wide range of porosity characteristics present in the real system, a large set of 60 kerogen structures that exhibit a diverse set of void space attributes was used. Grand Canonical Monte Carlo (GCMC) simulations were performed for the study of the adsorption of CH4, C2H6, n-C4H10 and CO2 at 298.15 K and 398.15 K and a variety of 2 pressures. The amount adsorbed is found to correlate linearly with the porosity of the kerogen. Furthermore, the adsorption of a quaternary mixture of CH4, C2H6, CO2 and N2 was investigated in the same conditions, indicating that the composition resembling that of the shale gas is achieved under higher temperature and pressure values, i.e. conditions closer to these prevailing in the hosting shale field. The diffusion of CH4, C2H6 and CO2, both as pure components and as components of the quaternary mixture, was investigated using equilibrium Molecular Dynamics (MD) simulations at temperatures of 298.15 and 398.15 K and pressures of 1 and 250 atm. In addition to the effect of temperature and pressure, the importance of limiting pore diameter (LPD), maximum pore diameter (MPD), accessible volume (Vacc) and accessible surface (Sacc) on the observed adsorbed amount and diffusion coefficient was revealed by qualitative relationships. The diffusion across the models was found to be anisotropic and the maximum component of the diffusion coefficient to correlate linearly with LPD, indicating that the controlling step of the transport process is the crossing of the limiting pore region. Finally, the transport behavior of the pure compounds was compared with their transport properties when in mixture and it was found that the diffusion coefficient of each compound in the mixture is similar to the corresponding one in pure. This observation agrees with earlier studies in different kerogen models comprising wider pores that have revealed negligible cross-correlation Onsager coefficients.

The adsorption behavior inside kaolinite mesopores of aqueous solutions of various salts and additives is investigated using Molecular Dynamics simulations. In particular, we examine the various combinations of water + salt, water + additive, and water + salt + additive mixtures, where the salts examined are NaCl, CsCl, SrCl2 and RaCl2 and the additives are methanol and citric acid.Citric acid is modeled in two forms, namely fully protonated (H3A) and fully deprotonated (A 3-), the latter being prevalent in neutral pH conditions, in accordance with the kaolinite structure employed. The force fields used for the individual system components include CLAYFF for the kaolinite mesopores, SPC/E for water, parameters optimized for the SPC/E water model based on hydration free energies (HFE) for ions and general Amber force field (GAFF) for the additives.The spatial distributions along the kaolinite pore are delineated and reveal the preferential adsorption behavior of the various species with respect to the gibbsite and siloxane surface, as well as the effect on this behavior of the interactions between the various species. Furthermore, we examine the hydrogen bonds formed between the kaolinite surfaces and water molecules as well as the additives. For the case of citric acid, which tends to aggregate, a cluster analysis is also carried out, in order to examine the effect of the various ions on the cluster formation. Finally, through the calculation of lateral diffusion coefficients and mean residence times, we provide insights on the mobility of the various species inside the kaolinite mesopores.

Personal assistive robots to be realized in the near future should have the ability to seamlessly coexist with humans in unconstrained environments, with the robot's capability to understand and interpret the human behavior during human-robot cohabitation significantly contributing towards this end. Still, the understanding of human behavior through a robot is a challenging task as it necessitates a comprehensive representation of the high-level structure of the human's behavior from the robot's low-level sensory input. The paper at hand tackles this problem by demonstrating a robotic agent capable of apprehending human daily activities through a method, the Interaction Unit analysis, that enables activities' decomposition into a sequence of units, each one associated with a behavioral factor. The modelling of human behavior is addressed with a Dynamic Bayesian Network that operates on top of the Interaction Unit, offering quantification of the behavioral factors and the formulation of the human's behavioral model. In addition, lightweight human action and object manipulation monitoring strategies have been developed, based on RGB-D and laser sensors, tailored for onboard robot operation. As a proof of concept, we used our robot to evaluate the ability of the method to differentiate among the examined human activities, as well as to assess the capability of behavior modeling of people with Mild Cognitive Impairment. Moreover, we deployed our robot in 12 real

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