The application of multivariate statistical analysis and batch process control in industrial processes

To manufacture safe, effective and affordable medicines with greater efficiency, process analytical technology (PAT) has been introduced by the Food and Drug Agency to encourage the pharmaceutical industry to develop and design well-understood processes. PAT requires chemical imaging techniques to be used to collect process variables for real-time process analysis. Multivariate statistical analysis tools and process control tools are important for implementing PAT in the development and manufacture of pharmaceuticals as they enable information to be extracted from the PAT measurements. Multivariate statistical analysis methods such as principal component analysis (PCA) and independent component analysis (ICA) are applied in this thesis to extract information regarding a pharmaceutical tablet. ICA was found to outperform PCA and was able to identify the presence of five different materials and their spatial distribution around the tablet.Another important area for PAT is in improving the control of processes. In the pharmaceutical industry, many of the processes operate in a batch strategy, which introduces difficult control challenges. Near-infrared (NIR) spectroscopy is a non-destructive analytical technique that has been used extensively to extract chemical and physical information from a product sample based on the scattering effect of light. In this thesis, NIR measurements were incorporated as feedback information into several control strategies. Although these controllers performed reasonably well, they could only regulate the NIR spectrum at a number of wavenumbers, rather than over the full spectrum.In an attempt to regulate the entire NIR spectrum, a novel control algorithm was developed. This controller was found to be superior to the only comparable controller and able to regulate the NIR similarly. The benefits of the proposed controller were demonstrated using a benchmark simulation of a batch reactor.EThOS - Electronic Theses Online ServicePfizer IncorporatedUniversity UKUniversity of ManchesterGBUnited Kingdo

Cloud condensation nuclei activity of six pollenkitts and the influence of their surface activity

The role of surfactants in governing water interactions of atmospheric aerosols has been a recurring topic in cloud microphysics for more than two decades. Studies of detailed surface thermodynamics are limited by the availability of aerosol samples for experimental analysis and incomplete validation of various proposed Kohler model frameworks for complex mixtures representative of atmospheric aerosol. Pollenkitt is a viscous material that coats grains of pollen and plays important roles in pollen dispersion and plant reproduction. Previous work suggests that it may also be an important contributor to pollen water uptake and cloud condensation nuclei (CCN) activity. The chemical composition of pollenkitt varies between species but has been found to comprise complex organic mixtures including oxygenated, lipid, and aliphatic functionalities. This mix of functionalities suggests that pollenkitt may display aqueous surface activity, which could significantly impact pollen interactions with atmospheric water. Here, we study the surface activity of pollenkitt from six different species and its influence on pollenkitt hygroscopicity. We measure cloud droplet activation and concentration-dependent surface tension of pollenkitt and its mixtures with ammonium sulfate salt. Experiments are compared to predictions from several thermodynamic models, taking aqueous surface tension reduction and surfactant surface partitioning into account in various ways. We find a clear reduction of surface tension by pollenkitt in aqueous solution and evidence for impact of both surface tension and surface partitioning mechanisms on cloud droplet activation potential and hygroscopicity of pollenkitt particles. In addition, we find indications of complex nonideal solution effects in a systematic and consistent dependency of pollenkitt hygroscopicity on particle size. The impact of pollenkitt surface activity on cloud microphysics is different from what is observed in previous work for simple atmospheric surfactants and more resembles recent observations for complex primary and secondary organic aerosol, adding new insight to our understanding of the multifaceted role of surfactants in governing aerosol-water interactions. We illustrate how the explicit characterization of pollenkitt contributions provides the basis for modeling water uptake and cloud formation of pollen and their fragments over a wide range of atmospheric conditions.Peer reviewe

Effect of recycled concrete aggregate features on adhesion properties of asphalt mortar-aggregate interface

Asphalt-aggregate interface’s adhesion properties commonly affect the damage initiation and evolution within asphalt concrete materials, related to pavement durability and quality. The scope of this research was to investigate the influence of Recycled Concrete Aggregate (RCA) features on asphalt mortar-aggregate interface adhesion. Firstly, a three-dimensional reconstruction model of RCA was carried out using X-ray CT tomography and digital image processing. In this regard, five feature indicators, namely cement mortar content, sphericity, flat and elongated ratio, angularity, and surface texture, were proposed. Based on a bilinear cohesive zone model, the interface damage behavior of asphalt mortar-RCA was investigated by using a uniaxial compression simu- lation. Finally, a GA-BP artificial neural network was conducted to predict and quantify the effect of each feature indicator of RCA on interface adhesion. The results showed that when RCA had lower cement mortar content, higher sphericity value, and smoother surface, the asphalt mortar-RCA system was less prone to interface adhesion failure. The 5-14-1 GA-BP artificial neural network proposed in this study showed very good perfor- mance in predicting the interfacial dissipation damage energy with a mean-squared error value of 3.52 × 10^-4 for testing dataset. The cement mortar content parameter exhibited a remarkable influence on the interface adhesion property, and its global contribution to the interfacial dissipation damage energy (0.3486) was more than twice that of the surface texture parameter (0.1316). In future studies, the performance characteristics of cement mortar can be further investigated, thereby proposing RCA’s performance optimization technology