Morphology prediction

The morphology and habit exhibited by a crystal are controlled by a combination of the internal crystal structure of the unit cell and the external growth parameters. The morphology that is observed is in general a consequence of 

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Diffraction experiments have discovered values of a that span nearly the entire range 0 < a < 1, see Fig. 2. Theories for the coarsening of self-similar morphologies predict a = l/i,i = 3,4,5 the value of i depends on assumptions about the geometry of the roughness (e.g., 1-D vs. 2-D) and mechanisms for mass-transport many of the experiments have indeed found 1/5 < a < 1/3. We note however, that in our opinion, the interpretation of these diffraction experiments is greatly complicated by the fact that the variation of the step density in the plane of the surface, the lateral characteristic... 

In summary, the described aerosol technique offers a new way to produce exceedingly pure and morphologically predictable colloids. The products should especially find applications in areas of high value materials. While the principles of the procedure have been well established, it is now necessary to concentrate efforts on equipment designs that will yield large amounts of uniform droplets. 

Jonas JB, Marms P, Budde WM, Hayler J. Morphologic predictive factors for development of optic disc hemorrhages in glaucoma. Invest Ophthalmol Vis Sci 2002 43 2956-2961. 

Crystallite morphology prediction and morphology control are important for several kinds of applications. Zeolite membranes can require alignment of many distinct crystallites, this being facilitated by having uniformly shaped... 

Morphology predictions based on the AE method also assume that crystals are grown in vacuo, i.e., in the absence of solvent. Consequently, the solvent effects on morphology are ignored using this method. Roberts and coworkers have developed a method that calculates a modified AE which can be used to predict the effects of solvents as well as other additives on crystal morphology.f " ... 

Identification of the fastest growing faces of the stable crystalline modification (from experimental data as well as morphology predictions). 

Chen et al. [39] and Jonsson et al. 140,41] independently proved that the composite particle morphology could be brought towards the equilibrium morphology predicted by the thermodynamic model by a post-polymerization swelling treatment of the composite latexes with solvents. 

Crystal Morphology Predictive Techniques To Characterize Crystal Habit Application to Aspirin (C9Hg04)... 

MEENAN Crystal Morphology Prediction Applied to Aspirin 3... 

MEENAN Crystal Morphology Prediction AppUed to Aspirin... 

Theoretical approximations and morphology predictions were recently carried out for miktoarm star terpolymers of the ABC type. The literature concerning theoretical predictions for this complex architeaure is rather limited, as the synthesis of such materials leading to morphologically three-phase stmaures has been developed rather recently. The behavior of miktoarm star terpolymers was simulated using the Monte Carlo calculation method. This approach was already used for the microdomain structural behavior of diblock copolymers of the AB type, and the consideration that needed to be taken into account for the calculations was the addition of the C chain at the common junction point of the A... 

Hieoretical works have focused on morphology predictions in order to address the property charaaeristics of photovoltaic devices consisting of rod-coil block copolymers. For this purpose, a continuum formalism termed the drift diffusion model has been adopted. This characterizes the transport of excitons, electrons, and holes under photoadsorption to render predictions regarding the device characteristics. ... 

Ma, G. G., Zhang, M. Q., and Rong, M. Z. 2007. Morphology prediction of ternary polypropylene composites containing elastomer and calcium carbonate nanoparticles filler. Journal of Applied Polymer Science 103 1578-1584. 

R. Aratijo, A. de. Swarm-based translation-invariant morphological prediction method for financial time series forecasting. Inf. Sd. 180, 4784-4805 (2010)... 

As could be expected, challenges facing the pharmaceutical industry contribute to the advancement of the computational soUd-state chemistry. For example, some of the virtual screening and other CPSSC methods were developed specifically to help address issues of the pharmaceutical industry. Significant progress has been made recently in many traditional applications (e.g., solubility prediction [55], CSP [56], and morphology prediction [25, 57, 58]) in order to accommodate predictions for complex pharmaceutical systems (solid and liquid multicomponent phases of relatively large and flexible molecules). 

Fig. 20.6 Possible morphology predicted for anatase (TiO ) with (a) hydrogenated surfaces, (b) with hydrogen-rich surface adsorbates, (c) hydrated surfaces, (d) hydrogen-poor adsorbates, and (e) oxygenated surfaces (Reprinted with permission from Barnard and Curtiss 2005, Copyright 2005 Royal Society of Chemistry)...

Solvent composition-driven assembly represents an interesting process. This highlights the difficulties in assuming a simple packing parameter or volume fraction approach to morphology prediction. In this case, the BCP is initially dissolved in a solvent that is nonselective. A selective... 

Harrats, G. and N. Mekhilef, Co-continuous phase morphologies predictions, generation, and practical applications, in Micro- and Nanostructured Multiphase Polymer Blend Systems Phase Morphology and Interfaces, C. Harrats, S. Thomas, and G. Groeninckx (Eds.), Taylor Francis, CRC Press, New York, 2006. 

Industrial crystallization processes rarely involve pure materials, but are rather used as purification process to achieve purified material and are often conducted from melt or solution. The presence of any other molecules but the crystalline material (substrate) frequently causes significant changes in the crystalline morphology [42—45]. Components denoted as additives or impurities predominantly occur in small amounts, whereas a solvent is represented by a large number of molecules in a mixed system. Here, the modeling procedure conducted for morphology prediction in the presence of additives is described. 

Berkovitch-Yellin [46] introduces a simple approach for the morphology prediction in the presence of additives. Herein, the additive molecule is build into the unit cell to replace each of the host molecules stepwise. The structure of the polar surfaces is analyzed and the mappings of the corresponding electrostatic potentials are employed to determine the solvent effect. The method supphes accurate results and considers the solvent and the additive effect, respectively. Nonetheless, it is lacking the implementation of the concentration of solute, solvent, and potential additives in the solution. 

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