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- Abrahamsson, Per, 1985, et al.
(författare)
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Analysis of mesoscale effects in high-shear granulation through a computational fluid dynamics–population balance coupled compartment model
- 2018
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Ingår i: Particuology. - : Elsevier BV. - 2210-4291 .- 1674-2001. ; 36, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- There is a need for mesoscale resolution and coupling between flow-field information and the evolution of particle properties in high-shear granulation. We have developed a modelling framework that compartmentalizes the high-shear granulation process based on relevant process parameters in time and space. The model comprises a coupled-flow-field and population-balance solver and is used to resolve and analyze the effects of mesoscales on the evolution of particle properties. A Diosna high-shear mixer was modelled with microcrystalline cellulose powder as the granulation material. An analysis of the flow-field solution and compartmentalization allows for a resolution of the stress and collision peak at the impeller blades. Different compartmentalizations showed the importance of resolving the impeller region, for aggregating systems and systems with breakage. An independent study investigated the time evolution of the flow field by changing the particle properties in three discrete steps that represent powder mixing, the initial granulation stage mixing and the late stage granular mixing. The results of the temporal resolution study show clear changes in collision behavior, especially from powder to granular mixing, which indicates the importance of resolving mesoscale phenomena in time and space.
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- Heffernan, C., et al.
(författare)
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Influence of Structurally Related Impurities on the Crystal Nucleation of Curcumin
- 2018
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Ingår i: Crystal Growth & Design. - : American Chemical Society (ACS). - 1528-7483 .- 1528-7505. ; 18:8, s. 4715-4723
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Tidskriftsartikel (refereegranskat)abstract
- In this work, the influence of the structurally related impurities, demethoxycurcumin (DMC) and bisde-methoxycurcumin (BDMC) on the primary nucleation of curcumin (CUR) has been investigated in propan-2-ol. The induction time for nucleation was measured at different CUR driving forces and impurity concentrations 0.10 mmol.dm(-3), 0.30 mmol.dm(-3), and 0.60 mmol.dm(-3) and the results are analyzed by the classical nucleation theory (CNT). The nucleation rate for the impure systems was noticeably lower than the nucleation rate of the pure system, and the times of growth to visibility were much longer for the impure systems. The pre-exponential factors are clearly lower for the impure system compared to the pure CUR system, while the increase in the solid-liquid interfacial energy is small. Density functional theory and metadynamic molecular modeling reveal that the 1:1 bonding between CUR and an impurity molecule is stronger than to another CUR molecule, thus suggesting that the developing CUR nucleus has to overcome a certain energy barrier in order to remove the impurity molecules from their surface, which may explain why nucleation of CUR is more difficult in the presence of the structurally related impurities, DMC and BDMC.
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- Hodnett, B. K., et al.
(författare)
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The SSPC : Leading the way for next-generation medicines manufacture
- 2015
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Ingår i: European Pharmaceutical Review. - : Russell Publishing. - 1360-8606. ; 20:4, s. 33-37
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Tidskriftsartikel (refereegranskat)abstract
- The Synthesis and Solid State Pharmaceutical Centre (SSPC), a global hub of pharmaceutical process innovation and advanced manufacturing, is funded by Science Foundation Ireland (SFI) and Industry, and represents a unique collaboration between 22 industry partners, nine research performing organisations and 12 international academic collaborators (Figure 1; page 34). It is a €42 million state-industry investment, which supports a globally-leading research team of 38 investigators, 34 post-doctoral researchers and 60 PhD candidates. As the largest research collaboration in Ireland and one of the largest globally within the pharmaceutical area, the SSPC transcends company and academic boundaries (Figure 2; page 34). Its role is to link experienced scientists and engineers in academia and the pharmaceutical industry, to address critical research challenges and to deliver industry-relevant solutions, which result in job growth and retention within the pharmaceutical industry.
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- Lynch, A., et al.
(författare)
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Face indexing and shape analysis of salicylamide crystals grown in different solvents
- 2019
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Ingår i: CrystEngComm. - : Royal Society of Chemistry. - 1466-8033. ; 21:16, s. 2648-2659
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Tidskriftsartikel (refereegranskat)abstract
- The effect of solvent on salicylamide's crystal habit was investigated. Crystals grown experimentally in acetone, acetonitrile and methanol matched the attachment energy predicted rectangle plate vacuum habit. However, in ethyl acetate irregular hexagonal plate crystals form. This change in habit was found to be caused by the stunted growth of specific crystal faces during the crystallisation process. Single crystal and powder X-ray diffraction was carried out to rule out the possibility of a new polymorph. Given no new polymorphs were discovered, the changing habit makes face indexing of experimentally grown crystals difficult. A combination of experimental and modelling prediction tools was employed for the face indexing process. The interfacial angle between faces combined with preferred orientation P-XRD was found to be the most accurate and reliable method leading to successful identification of each salicylamide crystal face. The surface chemistry of each face was examined on a molecular level with insights into the possible growth attachment sites being made. It is deduced that ethyl acetate is adsorbed more strongly on the faces, the increased size of which, can explain the shape change.
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- Rama Krishna, G., et al.
(författare)
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Prediction of Solid State Properties of Cocrystals Using Artificial Neural Network Modeling
- 2018
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Ingår i: Crystal Growth & Design. - : American Chemical Society (ACS). - 1528-7483 .- 1528-7505. ; 18:1, s. 133-144
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Tidskriftsartikel (refereegranskat)abstract
- Using Artificial Neural Networks (ANNs), four distinct models have been developed for the prediction of solid-state properties of cocrystals: melting point, lattice energy, and crystal density. The models use three input parameters for the pure model compound (MC) and three for the pure coformer. In addition, as an input parameter the model uses the pKa difference between the MC and the coformer, and a 1:1 MC−conformer binding energy as calculated by a force field method. Notably, the models require no data for the actual cocrystals. In total, 61 CCs (two-component molecular cocrystals) were used to construct the models, and melting temperatures and crystal densities were extracted from the literature for four MCs: caffeine, theophylline, nicotinamide, and isonicotinamide. The data set includes 14 caffeine cocrystals, 9 theophylline cocrystals, 9 nicotinamide cocrystals, and 29 isonicotinamide cocrystals. Model-I is trained using known cocrystal melting temperatures, lattice energies, and crystal densities, to predict all three solid-state properties simultaneously. The average relative deviation for the training set is 2.49%, 6.21%, and 1.88% for the melting temperature, lattice energy, and crystal density, respectively, and correspondingly 6.26%, 4.58%, and 0.99% for the valdation set. Model-II, model-III, and model-IV were built using the same input neurons as in model-I, for separate prediction of each respective output solid−state property. For these models the average relative deviation for the training sets becomes 1.93% for the melting temperature model-II, 1.29% for the lattice energy model-III, and 1.03% for the crystal density model-IV, and correspondingly 2.23%, 2.40%, and 1.77% for the respective validation sets.
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