Browsing by master's degree program "Kemian ja molekyylitieteiden maisteriohjelma"

Plasmonic is an emerging field which has showed application for photocatlysis. Here we investigate a gold/platinum bimetallic catalytic system, and try to show how the catalytic properties of gold nanoparticles can be us to harvest visible light energy to increase the catalytic activity of platinum. Platinum being are rare and expensive metal, we also took the opportunity to find the optimal amount of catalyst to reduce platinum use. The catalyst is composed of a core spherical gold nanoparticles, of around 15 nm diameter. They were synthesized using an inversed Turkevich method, based on trisodium citrate, gold precursor salt and done in solution. Various amount of platinum was deposited on those nanoparticles using seeded growth method. The amount of platinum varied for single atoms to an atomic monolayer. This suspension of nanoparticles was deposited on ultrafine silica powder to be used for certain reaction and characterization. The material was characterized via several technics. UV-Visible and Diffuse Reflectance Spectroscopy were used to characterize its optical properties and showed a absorption peak around 524 nm characteristic of gold nanoparticles of this size. Imaging was done using electron microscopy (SEM and TEM) to study the morphology and showed monodisperse and spherical particles. The exact composition of the different catalyst were obtain using Atomic Emission Spectroscopy. The study was conducted by using reduction reaction as tests to investigate differences in conversion and selectivity under dark and monochromatic 525 nm and 427 nm light conditions. We chose to work on reduction of 4-nitrophenol, phenylacetylene and nitrobenzene, because they are widely used both in research and industry, and are easy to set up. Some catalyst showed good enhancement under 525 nm light, especially the one with the least amount of platinum. Different selectivity were also observed, indicating the presence of different reaction pathways under light conditions.

Development of machine learning models for reaction design has garnered growing interest. Notably, the benefits of predictive models include the elimination of trial and error in selecting suitable reaction conditions. In addition, mechanistic insight may be gained to help rational catalyst design. The aim of this study is to develop modeling and parametrization method for transition metal complexes which would enable the combined parametrization of mono- and bidentate ligands for the first time. Performance of novel parametrization method is demonstrated through a ligand classification model for Suzuki–Miyaura reaction. In this literature review, an overview of the computational catalyst modeling and performance prediction is presented. The history of physical and computational chemistry is reviewed, ranging from early structure-property relationships and linear models to modern physical organic density functional theory (DFT) parameters and machine learning models. The necessary theoretical background for reaction modeling is presented in terms of transition state theory, which can be used to model selectivity or reaction rate. Additionally, the reaction yield is discussed as typical performance score for reaction modeling. Furthermore, the initial structures of typical transition metal complexes used for modeling are presented, along with the methods employed for structure optimization and ligand parametrization. By utilizing this background, the evolution of modeling methods from linear free energy relationships to machine learning is discussed. Additionally, modern classification methods for catalyst design are reviewed. Finally, the mechanistic details of Suzuki–Miyaura reaction are explored to justify the modeling methodologies in the experimental part. In the experimental study, a novel method to combine parametrization for mono- and bidentate ligands was successfully invented. As a proof of concept, performance classification of ligands for Suzuki– Miyaura reaction was conducted. Suzuki–Miyaura reaction was chosen as the model reaction due to wide data availability. Initial transition metal complexes were built according to ligation state of nickel. The initial structures always included two carbonyl ligands and either one bidentate ligand, or two monodentate ligands, or one bulky monodentate ligand. The structures were optimized with semiempirical quantum mechanical method xTB and parametrized using a newly developed in-house parametrization method. Calculated parameters include global and local steric and electronic descriptors, and local geometric descriptors. Classification models were built with selected training data. Models were used to predict the performance of new ligands. Successful results were achieved, and ligands that provided better yields were identified. In addition, it was discovered that model reaction proceeds without the presence of phosphine ligand if superbase is used as a base. Nitrogen-containing bases were screened, additional active superbases were found, and correlating descriptor with activity was detected. Based on results, more active superbases were designed.

Nuclear power plant decommissioning is a difficult process that combines industrial decommissioning techniques, radiation safety standards, and legal requirements for the final disposal of nuclear waste. The goal of nuclear decommissioning is to completely purge the plant of all radioactive material so that it can be released from regulatory oversight. The range of corrosion products generated on the steel surface are known to have a significant impact on the corrosion process of steel. Corrosion products have a complicated structure. The corrosion products are created when metallic components, mostly iron, react with oxygen and water that are drawn from the atmosphere, and their structure is then significantly influenced by environmental factors. Quantitative characterisation of the atomic scale structure of corrosion products is critically needed for identifying the corrosion products reliably. This thesis provides the characterization process of corrosion products formed on the steel surfaces and this process was executed with the help of XRD (X-ray Diffraction), SEM/EDS Scanning Electron Microscope/ Energy Dispersive Spectrometry, and Raman spectroscopy. Within the scope of this project, besides characterization of steel samples, Loviisa ground water and synthetic water samples which have been in a long-term contact with activated steel samples were also examined. Separation processes was carried out for determining Fe-55 and Ni-63 in the waters and the presence of Co-60 was removed from the samples before the activity determination of Fe-55 and Ni-63 by LSC (Liquid Scintillation Counting). This master's thesis has been carried out in connection with the DEMONI project, which has been a coordinated project of VTT and the University of Helsinki (KYT2022 Research Program). The outcome of the thesis will benefit possible decommissioning and disposal strategies for the nuclear power plant's reactor pressure vessels.

The literature study of this thesis focuses on the different analytical methods used to analyse amino acids in food and beverage samples. Amino acids are essential organic molecules and their concentrations in foods and beverages constitute, inter alia, the product’s nutritional value, quality, freshness, and flavour. Amino acid analysis of foodstuff has various applications, which exploit several analytical methods. These reviewed methods are founded on academic articles published during the past two decades. This literature review discusses the different sample matrixes, sample preparation methods, ways to derivate analytes, and different separation and detection methods utilized in the recent amino acid studies. The experimental part of this thesis was a modification of L-asparagine and L-aspartic acid test (L-Asp/L-AspAc) in Thermo Fisher Scientific Oy industrial R&D laboratory. An enzymatic photometric method is used to determine L-Asp/L-AspAc amino acids in food samples. The modification process entailed pre-testing of several candidate methods, from which the most suitable one was selected. The feasibility of the chosen test was affirmed before verification and validation of the modified test.

The literature review of this thesis presents the most utilized sample preparation and analysis methods for determination of trace elements from refinery feedstocks and end products during the last decade. The advantages and disadvantages of used methods and trends are presented. The challenges associated especially on silicon determination are discussed and possible solutions provided by publications are highlighted. The experimental part of this thesis is conducted in Neste’s Research and Development unit in Porvoo. The experimental part includes method development, study of siloxane compounds behavior and method validation for various sample matrices. The method development was performed by introduction of peristaltic pump to inductively coupled plasma- mass spectrometer (ICP-MS) sample introduction for two different methods (ASTM D8110M, NM 534) to replace previously used free aspiration method. The study of behavior of volatile siloxane compounds in different sample matrices including liquified waste plastics (LWP), and determination of these compounds was done with ICP-MS. The studied siloxanes showed great challenges due to their high volatility with the chosen methods. The method (ASTM D8110M, NM534) validation for different sample matrices were also done with ICP-MS. The validated matrices included several renewable matrices such as liquified waste plastics, fatty acids and other liquified waste samples and heavy fossil distillates. Repeatabilities of silicon concentration of sample as such and as spiked in intra- and inter-day, and spiked recoveries played an important role for method validation.

In this work, molecular mass determination by diffusion-ordered nuclear magnetic resonance spectroscopy was obtained for a series of poly(2-oxazoline)s, polypeptoids and poly(2-oxazine)s. The samples included linear, star like and cyclized homopolymers and block copolymers. The data was calibrated against polyethylene glycol, polystyrene and poly(methyl methacrylate) standards. The results were compared with those obtained by matrix-assisted laser desorption/ionization spectrometry, size exclusion chromatography, rolling-ball viscometry and end-group analyses based on proton nuclear magnetic resonance. It was concluded that in general diffusion-ordered spectroscopy tends to give a very accurate estimation of the masses up to 30 kg/mol in deuterated water and dimethyl sulfoxide, especially after viscosity correction. In addition, nuclear magnetic resonance spectroscopy provides a wealth of information about the samples including their structure and possible impurities. In summary, this methodology could be successfully applied to different polymers and it is invaluable in the case of absence of the standards with similar solubility to analyzed polymers since the viscosity correction enables a comparison of the results measured in different solvents.

Poly(2-oxazoline)/poly(2-oxazine)-based block copolymers have gained significant attention in recent years for their potential use in drug delivery systems. The architecture of amphiphilic poly(2-oxazoline)/poly(2-oxazine) based block copolymers, consisting of hydrophilic outer blocks and a hydrophobic inner block, allows the formation of micelles. The hydrophobic drug is encapsulated within the core, and the hydrophilic shell provides the stability and solubility in aqueous solution. The size and properties of the micelles can be tuned by adjusting the composition of the copolymer, making them a versatile platform for drug delivery. In this work, three different poly(2-oxazoline)/poly(2-oxazine)-based triblock, diblock and gradient copolymers were synthesized via cationic ring-opening polymerization and compared in terms of their drug formulation capability. Triblock copolymers consisting of three polymer blocks, can be tailored to have different hydrophobic and hydrophilic block ratios, allowing for tunable drug release profiles. However, triblock copolymers are more difficult to synthesize, especially if one aims to produce symmetrical ratio of hydrophilic blocks. Diblock copolymers, consisting of two polymer blocks, can also self-assemble into micelles in aqueous solutions and can encapsulate hydrophobic drugs, however, the lower stability of their formulations compared to that of triblock copolymers can limit their drug loading capacity and drug release profiles. In theory, entropy wise, when forming a micelle, the diblock copolymer should be favorable as it doesn’t need to fold, unlike the triblock copolymers, however, the drug formulations by triblock copolymers has shown to be more stable than that of diblock copolymers. Thus, more detailed analysis is needed since the lack of literature on the systematic comparison of these different architectures. Gradient copolymers, consisting of two or more types of monomers that are incorporated into a polymer chain with a gradually changing composition, have more variable properties and are easier to synthesize through one step, than block copolymers. This makes their usage in drug formulation very attractive. However, depending on the reactivity of monomers added, the resulting product can be very different, thus, the kinetics of the copolymerization deserves an attention of the study as well.

In Finland, the final disposal of spent nuclear fuel will start in the 2020s where spent nuclear fuel will be disposed 400-450 meters deep into the crystalline bedrock. Disposal will follow Swedish KBS-3 principle where spent nuclear fuel canisters will be protected by multiple barriers, which have been planned to prevent radionuclides´ migration to the surrounding biosphere. With multiple barriers, failure of one barrier will not endanger the isolation of spent nuclear fuel. Insoluble spent nuclear fuel will be stored in ironcopper canisters and placed in vertical tunnels within bedrock. Iron-copper canisters are surrounded with bentonite buffer to protect them from groundwater and from movements of the bedrock. MX-80 bentonite has been proposed to be used as a bentonite buffer in Finnish spent nuclear fuel repository. In a case of canister failure, bentonite buffer is expected to absorb and retain radionuclides originating from the spent nuclear fuel. If salinity of Olkiluoto island´s groundwater would decrease, chemical erosion of bentonite buffer could result in a generation of small particles called colloids. Under suitable conditions, these colloids could act as potential carriers for immobile radionuclides and transport them outside of facility area to the surrounding biosphere. Object of this thesis work was to study the effect of MX-80 bentonite colloids on radionuclide migration within two granitic drill core columns (VGN and KGG) by using two different radionuclides 134Cs and 85Sr. Batch type sorption and desorption experiments were conducted to gain information of sorption mechanisms of two radionuclides as well as of sorption competition between MX-80 bentonite colloids and crushed VGN rock. Colloids were characterized with scanning electron microscopy (SEM) and particle concentrations were determined with dynamic light scattering (DLS). Allard water mixed with MX-80 bentonite powder was used to imitate groundwater conditions of low salinity and colloids. Strontium´s breakthrough from VGN drill core column was found to be successful, whereas caesium did not breakthrough from VGN nor KGG columns. Caesium´s sorption showed more irreversible nature than strontium and was thus retained strongly within both columns. With both radionuclides, presence of colloids did not seem to enhance radionuclide´s migration notably. Breakthrough from columns was affected by both radionuclide properties and colloid filtration within tubes, stagnant pools and fractures. Experiments could be further complemented by conducting batch type sorption experiments with crushed KGG and by introducing new factors to column experiments. The experimental work was carried out at the Department of Chemistry, Radiochemistry in the University of Helsinki.

A geopolymer waste form containing gasified ion exchange resin loaded with stable analogues of radionuclides (e.g., Sr, Co, Ni, Cr, Cs) was studied using semi-dynamic batch leaching experiments. The experiments were conducted for 180 days using an alkaline groundwater simulant in a glove box with controlled N2 atmosphere with < 10 ppm CO2 and O2. The experiments were conducted to investigate the leaching behavior of the geopolymer in conditions relevant to a low- and intermediate-level waste repository. The leaching results of the geopolymers showed leaching of cesium, sodium, aluminum, and silicon from the geopolymer, while potassium and calcium in the leachant sorbed to the geopolymer. The leaching and sorption rates were at their highest for the first 28 days of the experiment, before slowing down to a steady state which were maintained until the end of the experiment. This suggests that the geopolymers immobilized the waste analogues effectively with exception of cesium which had leached by 55 wt% of the initial fraction by day 180. The leaching indices of sodium, aluminum, silicon, and cesium were determined as: 9.9 ± 0.38, 10.1 ± 0.47, 10.5 ± 0.40, and 9.1 ± 0.30 respectively. The leaching indices are well above 6, which is considered a minimum value for WAC of cementitious waste forms by USNRC. The solid phase analysis of the geopolymer samples showed both presence of calcium rich secondary phases and increasing calcium concentration in the bulk matrix on the leachant contact surface of the geopolymer. It was concluded that the secondary phases consisted of CaCO3 minerals.

Inductively coupled mass spectrometry (ICP-MS) is a state-of-the-art technique for elemental analysis. The technique allows fast and simultaneous analysis of multiple elements with a wide dynamic range and low detection limits. However, multiple adjustable parameters and the complex nature ICP-MS instruments can make the development of new analysis methods a tedious process. Design of experiments (DOE) or experimental design is a statistical approach for conducting multi- variate experiments in a way that gives maximal amount of information from each experiment. By using DOE the number of experiments needed for analytical method optimization can be minimized and information about interrelations of di↵erent experimental variables can be obtained. The aim of this thesis is to address the utilization of DOE for ICP-MS method developement as a more e cient mean to optimize analytical methods. The first part of this two part thesis gives an overview on the basics of ICP-MS and DOE. Then a literature review on applying experimental design for ICP-MS method optimization is given and the current state of the research is discussed. In the second part, two new ICP-MS methods for simultaneous determination of 28 elements from six middle distillate fuels, diluted with xylene or kerosine, are presented. The method developement involved optimization of the integration times and optimization of test sample dilution ratios and viscosities using univariate techniques. In addition, experimental designs were succesfully utilized together with desirability approach in multivariate optimizations of the plasma conditions and sample matrix compositions to achieve the best possible analyte recoveries from various matrices.