Abstract: Among all types of discovered crystals, those formed by organic molecules show the greatest diversity, which results from the intrinsic complexity of the organic molecules and the weak interactions between them. Even for a given compound, different crystal structures can exist. This feature is referred to as polymorphism in the modern crystallographic context and those different crystal forms are called polymorphs. In reality, the crystallization of organic molecules is often performed at the surface of a substrate, giving rise to heterogeneous crystallization. Except for the well-known catalyzing effects, the existence of substrates brings more possibilities to the polymorphic behaviors of organic molecules, promoting the formation of new polymorphs that are only stable in the vicinity of the substrates. For this reason, these new polymorphic forms are often described as substrate-induced polymorphs (SIPs). It is of great importance to understand the formation of SIPs for organic molecules as it has been reported that SIPs can show superior properties with respect to their bulk form counterparts. Up to now, most studies focus on the identifying and characterizing the presence of SIPs, which relies mainly on X-ray diffraction techniques. However, a detailed explanation about the origin of SIPs is still missing. In this work, we have combined several powerful experimental characterization techniques, including X-ray diffraction, transmission electron microscopy (TEM) and scanning tunneling microscopy (STM) in order to reach an integrated view over the formation of SIPs. These experimental studies are strongly supported by computational chemistry simulations, such as density functional theory and molecular dynamics. A big advantage of using atomistic simulations is that it enables the possibility to predict a priori the crystal structures of SIPs and to establish a posteriori the general rules for the formation of SIPs. In practice, this thesis employs state-of-art atomistic simulation approaches in order to bridge substrate-induced polymorphism with a conceptually-connected research area: the self-assembly of molecular networks (SAMNs), also called 2D crystallization. Unlike SIPs, which extend at least several molecular layers, SAMNs are composed of a single layer of molecules with ordered packing. Our simulations have enabled a more comprehensive understanding about the role of substrate during the formation of SIPs and we elucidate how the positional and orientational order of molecules propagates from the substrate to the upper 2D and even 3D crystal layers. In this way, a fundamental understanding of the substrate-induced crystallization is gained by connecting 2D and 3D crystallization using substrate-induced approaches.

Abstract: A shift from batch processing towards continuous processing is of interest in the pharmaceutical industry. However, this transition requires detailed knowledge and process understanding of all consecutive unit operations in a continuous manufacturing line to design adequate control strategies. This can be facilitated by developing mechanistic models of the multi-phase systems in the process. Since modelling efforts only started recently in this field, uncertainties about the model predictions are generally neglected. However, model predictions have an inherent uncertainty (i.e. prediction uncertainty) originating from uncertainty in input data, model parameters, model structure, boundary conditions and software. In this paper, the model prediction uncertainty is evaluated for a model describing the continuous drying of single pharmaceutical wet granules in a six-segmented fluidized bed drying unit, which is part of the full continuous from-powder-to-tablet manufacturing line (Consigma (TM), GEA Pharma Systems). A validated model describing the drying behaviour of a single pharmaceutical granule in two consecutive phases is used. First of all, the effect of the assumptions at the particle level on the prediction uncertainty is assessed. Secondly, the paper focuses on the influence of the most sensitive parameters in the model. Finally, a combined analysis (particle level plus most sensitive parameters) is performed and discussed. To propagate the uncertainty originating from the parameter uncertainty to the model output, the Generalized Likelihood Uncertainty Estimation (GLUE) method is used. This method enables a modeller to incorporate the information obtained from the experimental data in the assessment of the uncertain model predictions and to find a balance between model performance and data precision. A detailed evaluation of the obtained uncertainty analysis results is made with respect to the model structure, interactions between parameters and uncertainty boundaries. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: Plant leaves exhibit diverse shapes that enable them to utilize a light resource maximally. If there were a general parametric model that could be used to calculate leaf area for different leaf shapes, it would help to elucidate the adaptive evolutional link among plants with the same or similar leaf shapes. We propose a simplified version of the original Gielis equation (SGE), which was developed to describe a variety of object shapes ranging from a droplet to an arbitrary polygon. We used this equation to fit the leaf profiles of 53 species (among which, 48 bamboo plants, 5 woody plants, and 10 geographical populations of a woody plant), totaling 3310 leaves. A third parameter (namely, the floating ratio c in leaf length) was introduced to account for the case when the theoretical leaf length deviates from the observed leaf length. For most datasets, the estimates of c were greater than zero but less than 10%, indicating that the leaf length predicted by the SGE was usually smaller than the actual length. However, the predicted leaf areas approximated their actual values after considering the floating ratios in leaf length. For most datasets, the mean percent errors of leaf areas were lower than 6%, except for a pooled dataset with 42 bamboo species. For the elliptical, lanceolate, linear, obovate, and ovate shapes, although the SGE did not fit the leaf edge perfectly, after adjusting the parameter c, there were small deviations of the predicted leaf areas from the actual values. This illustrates that leaves with different shapes might have similar functional features for photosynthesis, since the leaf areas can be described by the same equation. The anisotropy expressed as a difference in leaf shape for some plants might be an adaptive response to enable them to adapt to different habitats.

Abstract: Precise control of elemental configurations within multimetallic nanoparticles could enable access to functional nanomaterials with significant performance benefits. Here, we present a one-pot synthesis of supported Ag@PdAg core-shell catalyst with an ordered PdAg alloy shell and an Ag core. Both the relative reduction potential and ratio of metal precursors are essential for this synthesis strategy. The distinguished properties of Ag@PdAg, particularly the electronic structure, indicates the existence of electron modification not only between Pd and Ag on PdAg shell, but between Ag core and alloy shell. The Ag@PdAg catalyst displays 97% ethene yield in the partial hydrogenation of acetylene, which is 2.0 and 8.1 times that of over PdAg alloy and pure Pd catalysts, and this is the most selective catalyst reported to data under industrial evaluation conditions. Moreover, this core-shell structure exhibits preferable stability with comparison to PdAg alloy catalyst. The facile synthesis of core-shell architecture with alloy shell structure provides a new platform for efficient catalytic transfer of chemical resource. (C) 2018 Elsevier Inc. All rights reserved.

Abstract: The investigation of thermal transport properties of novel two-dimensional materials is crucially important in order to assess their potential to be used in future technological applications, such as thermoelectric power generation. In this respect, the lattice thermal transport properties of the monolayer structures of group VA elements (P, As, Sb, Bi, PAs, PSb, PBi, AsSb, AsBi, SbBi, P3As1, P3Sb1, P1As3, and As3Sb1) with a black phosphorus like puckered structure were systematically investigated by first-principles calculations and an iterative solution of the phonon Boltzmann transport equation. Phosphorene was found to have the highest lattice thermal conductivity, , due to its low average atomic mass and strong interatomic bonding character. As a matter of course, anisotropic was obtained for all the considered materials, owing to anisotropy in frequency values and phonon group velocities calculated for these structures. However, the determined linear correlation between the anisotropy in the values of P, As, and Sb is significant. The results corresponding to the studied compound structures clearly point out that thermal (electronic) conductivity of pristine monolayers might be suppressed (improved) by alloying them with the same group elements. For instance, the room temperature of PBi along the armchair direction was predicted to be as low as 1.5 W m(-1) K-1, whereas that of P was predicted to be 21 W m(-1) K-1. In spite of the apparent differences in structural and vibrational properties, we peculiarly revealed an intriguing correlation between the values of all the considered materials as = c(1) + c(2)/m(2), in particular along the zigzag direction. Furthermore, our calculations on compound structures clearly showed that the thermoelectric potential of these materials can be improved by suppressing their thermal properties. The presence of ultra-low values and high electrical conductivity (especially along the armchair direction) makes this class of monolayers promising candidates for thermoelectric applications.

Abstract: As decentralized electricity generation is supporting grid development into the prosumer era, this paper investigates the economic viability of adding batteries to residential microgrids powered by photovoltaic units, under various electricity pricing schemes. Batteries bring the benefits of grid-stabilization and congestion relief, and they are also becoming cheaper. The problem identified is that the main grid effectively acts as a lossless storage system, especially under the net-metering scheme, whereas using a battery involves investment costs and energy losses. This mismatch is addressed by analysing residential microgrid projects under seven tariff designs, each in seven countries of the European Union, and compare the economic viability of photovoltaic systems with and without batteries. The findings show that the conditions most favourable to batteries are given by a capacity tariff scheme allowing price arbitrage. Based on these findings, the paper discusses possibilities for further support in order to bring the economic viability of microgrids with batteries on par with that of microgrids without batteries.

Abstract: The molecular genetics of flower development have been studied extensively for more than two decades. Fusion of organs and the tendency to oligomery, important characteristics of flower evolution, so far have remained fairly elusive. We present a geometric model for shape and fusion in the corolla of Asclepiads. Examples demonstrate how fusion of petals creates stable centers, a prerequisite for the formation of complex pollination structures via congenital and postgenital fusion events, with the formation of de novo organs, specific to Asclepiads. The development of the corolla reduces to simple inequalities from the MATHS-BOX. The formation of stable centers and of bell and tubular shapes in flowers are immediate and logical consequences of the shape. Our model shows that any study on flowers, especially in evo-devo perspective should be performed within the wider framework of polymery and oligomery and of fusion and synorganization.

Abstract: The study presents a 2D fluid plasma model of a gliding arc discharge for dissociation of CO2 which allows its subsequent conversion into value-added chemicals. The model is based on the balance equations of charged and neutral particles, the electron energy balance equation, the gas thermal balance equation and the current continuity equation. By choosing the modeling domain to be the plane perpendicular to the arc current, the numerical calculations are significantly simplified. Thus, the model allows us to explore the influence of the gas instabilities (turbulences) on the energy efficiency of CO2 conversion. This paper presents results for plasma parameters at different values of the effective turbulent thermal conductivity leading to enhanced energy transport.

Abstract: Metal halide perovskite (MHP) quantum dots (QDs) offer immense potential for several areas of photonics research due to their easy and low-cost fabrication and excellent optoelectronic properties. However, practical applications of MHP QDs are limited by their poor stability and, in particular, their tendency to aggregate. Here, we develop a two-step double-solvent strategy to grow and confine CsPbBr3 QDs within the three-dimensional (3D) cavities of a mesoporous SBA-16 silica scaffold (CsPbBr3@SBA-16). Strong confinement and separation of the MHP QDs lead to a relatively uniform size distribution, narrow luminescence, and good ambient stability over 2 months. In addition, the CsPbBr3@SBA-16 presents a high activity and stability for visible-light-driven photocatalytic toluene C(sp(3))-H bond activation to produce benzaldehyde with similar to 730 mu mol g(-1) h(-1) yield rate and near-unity selectivity. Similarly, the structural stability of CsPbBr3@SBA-16 QDs is superior to that of both pure CsPbBr3 QDs and those confined in MCM-41 with 1D channels.