Browsing by master's degree program "Master's Programme in Materials Research"
Now showing items 1-20 of 56
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(2021)Halide perovskites are a promising materials class for solar energy production. The photovoltaic efficiency of halide perovskites is remarkable but their toxicity and instability have prevented commercialization. These problems could be addressed through compositional engineering in the halide perovskite materials space but the number of different materials that would need to be considered is too large for conventional experimental and computational methods. Machine learning can be used to accelerate computations to the level that is required for this task. In this thesis I present a machine learning approach for compositional exploration and apply it to the composite halide perovskite CsPb(Cl, Br)3 . I used data from density functional theory (DFT) calculations to train a machine learning model based on kernel ridge regression with the many-body tensor representation for the atomic structure. The trained model was then applied to predict the decomposition energies of CsPb(Cl, Br)3 materials from their atomic structure. The main part of my work was to derive and implement gradients for the machine learning model to facilitate efficient structure optimization. I tested the machine learning model by comparing its decomposition energy predictions to DFT calculations. The prediction accuracy was under 0.12 meV per atom and the prediction time was five orders of magnitude faster than DFT. I also used the model to optimize CsPb(Cl, Br)3 structures. Reasonable structures were obtained, but the accuracy was qualitative. Analysis on the results of the structural optimizations exposed shortcomings in the approach, providing important insight for future improvements. Overall, this project makes a successful step towards the discovery of novel perovskite materials with designer properties for future solar cell applications.
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(2020)Due to its exceptional thermal properties and irradiation resistance, tungsten is the material of choice for critical plasma-facing components in many leading thermonuclear fusion projects. Owing to the natural retention of hydrogen isotopes in materials such as tungsten, the safety of a fusion device depends heavily on the inventory of radioactive tritium in its plasma-facing components. The proposed methods of tritium removal typically include thermal treatment of massive metal structures for prolonged timescales. A novel way to either shorten the treatment times or lower the required temperatures is based performing the removal under an H-2 atmosphere, effectively exchanging the trapped tritium for non-radioactive protium. In this thesis, we employ molecular dynamics simulations to study the mechanism of hydrogen isotope exchange in vacancy, dislocation and grain boundary type defects in tungsten. By comparing the results to simulations of purely diffusion-based tritium removal methods, we establish that hydrogen isotope exchange indeed facilitates faster removal of tritium for all studied defect types at temperatures of 500 K and above. The fastest removal, when normalising based on the initial occupation of the defect, is shown to occur in vacancies and the slowest in grain boundaries. Through an atom level study of the mechanism, we are able to verify that tritium removal using isotope exchange depends on keeping the defect saturated with hydrogen. This study also works to show that molecular dynamics indeed is a valid tool for studying tritium removal and isotope exchange in general. Using small system sizes and spatially-parallelised simulation tools, we have managed to model isotope exchange for timescales extending from hundreds of nanoseconds up to several microseconds.
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(2020)Further proof of the unique morphologies of water-soluble poly(2-isopropyl-2-oxazoline)-block-poly(DL-lactide) and poly(2-isopropyl-2-oxazoline)-block-poly(L-lactide) (PiPOx-b-PDLLA and PiPOx-b-PLLA) nanoparticles was obtained via Fluorescence Spectroscopy. Additionally, loading and release studies were carried out with hydrophobic curcumin molecules to outline the potential of the amphiphilic block copolymers in drug delivery applications. To study the morphology of the nanoparticles, absorption and emission spectra of pyrene were measured in water dispersions of the nanoparticles at several concentrations. The obtained I1/I3, I337/I333.5 and partitioning constant (Kv) values were compared to corresponding data from a control core/shell nanoparticle poly(ethylene glycol)-block-poly(DL-lactide) (PEG-b-PDLLA). Of the three different amphiphilic polymers, PEG-b-PDLLA showed the smallest and PiPOx-b-PDLLA the highest Kv value. This indicates, that PiPOx-b-PDLLA core is less hydrophobic and looser compared to the dense cores of PEG-b-PDLLA and PiPOx-b-PLLA, making it capable of encapsulating the greatest amount of pyrene. In the loading and release studies, the nanoparticles were loaded with curcumin and placed in dialysis against PBS Tween® 80 solution. Curcumin content of the samples was monitored over a week by measuring the emission spectra of curcumin. PiPOx-b-PDLLA showed greater potential as a drug delivery agent: It formed more stable nanoparticles, showed higher loading capacities, higher encapsulation efficiencies and slower release rates. Flash nanoprecipitation method (FNP) was also used to prepare the same nanoparticles with and without encapsulated curcumin. In addition to the encapsulation efficiencies, sizes of the nanoparticles were determined via dynamic light scattering (DLS). PiPOx-b-PLLA forms the smallest nanoparticles with lowest encapsulation efficiencies, thus agreeing well with the higher density of PLLA core. All three investigated amphiphilic copolymers formed stable nanoparticles in water at room temperature. On the contrary, stability of the nanoparticles was found to be poor in saline solutions at body temperature. Mixing PEG-b-PDLLA with PiPOx-b-PLA in a ratio of 20:80 w-% increased the stability of the nanoparticles in physiological conditions simultaneously uncovering the thermoresponsive character of the PiPOx-blocks. Turbidity measurements of PEG-b-PDLLA mixed with PiPOx-b-PDLLA in ratio of 20:80 w-% showed slight decrease in transmittance at the 30 °C, which corresponds to the cloud point of PiPOx-b-PDLLA in PBS solution. However, it remains unclear, whether the increased stability is due to the PEG-b-PDLLA mixing in the same micelles with PiPOx-b-PDLLA, thus hindering the aggregation of the nanoparticles upon the cloud point of the PiPOx-blocks.
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(2024)Area selective etching (ASE) of polymers is a novel technique that enables self-aligned thin film patterning. The technique is simple and easy to process which makes less defects and cost effective. The etching reactions of polymers are due to the catalytic activity of the metallic compound underneath. The ambient gas molecules diffuse through the polymer and adsorb on the surface catalyzing polymer decomposition from the polymer-substrate interface. Decomposed gaseous products are diffused back through the polymer film leaving no residue. On the contrary, on noncatalytic surfaces, polymer film is not decomposed. Different polymers, on different surfaces, in the presence of different gases exhibit ASE differently. Different polymer-substrate-gas-temperature combinations were explored in this work. The main aim of the study is to expand the archive of catalytic and noncatalytic combinations that can be effectively utilized in ASE. In the literature review, an introduction to the existing patterning techniques, an overview of ASE, properties of polymers as common resist materials in the patterning of semiconductor devices and the catalytic properties of inorganic materials are provided. The experimental section brings the broad array of catalytic and noncatalytic combinations classified according to the polymer. Metal oxides (native SiO2, HfO2, ZrO2, Al2O3, Ta2O5, TiO2, CeO2 and NiO), metal nitrides (TiN and Si3N4), metal carbide (MoCx) and metal fluorides (MgF2, CaF2, and TbF3) were tested for their catalytic properties on decomposing PMMA and PLA. The behavior of ASE was compared in the presence of different atmospheric conditions: air, H2 and N2. CeO2 and NiO exhibited catalytic activity on decomposing both polymers and fluorides exhibited catalytic activity on PLA decomposition. The surface of MoCx was modified in the presence of air while native SiO2, HfO2, ZrO2, Al2O3, Ta2O5, TiO2, TiN and Si3N4 showed noncatalytic effects regardless of the polymer and the surrounding gas.
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(2019)Ion beams have been the subject of significant industry interest since the 1950s. They have gained usage in many fields for their ability to modify material properties in a controlled manner. Most important has been the application to semiconductor devices such as diodes and transistors, where the necessary doping is commonly achieved by irradiation with appropriate ions, allowing the development of the technology that we see in everyday use. With the ongoing transition to ever smaller semiconductor devices, the precision required of the manufacturing process correspondingly increases. A strong suite of modeling tools is therefore needed to advance the understanding and application of ion beam methods. The binary collision approximation (BCA) as a simulation tool was first introduced in the 1950s. It allows the prediction of many radiation-related phenomena for single collision cascades, and has been adopted in many experimental laboratories and industries due to its efficiency. However, it fails to describe chemical and thermodynamic effects, limiting its usefulness where ballistic effects are not a sufficient description. Parallel to BCA, the molecular dynamics (MD) simulation algorithm was developed. It allows a more accurate and precise description of interatomic forces and therefore chemical effects. It is, however, orders of magnitude slower than the BCA method. In this work, a new variant of the MD algorithm is developed to combine the advantages of both the MD and the BCA methods. The activation and deactivation of atoms involved in atomic cascades is introduced as a way to save computational effort, concentrating the performed computations in the region of interest around the cascade and ignoring surrounding equilibrium regions. By combining this algorithm with a speedup scheme limiting the number of necessary relaxation simulations, a speedup of one order of magnitude is reached for covalent materials such as Si and Ge, for which the algorithm was validated. The developed algorithm is used to explain the behavior of Ge nanowires under Xe ion irradiation. The nanowires were shown experimentally to bend towards or away from the ion beam, and computational simulations might help with the understanding of the underlying physical processes. In this thesis, the high-fluence irradiation of a Ge nanowire is simulated and the resulting defect structure analyzed to study the bending, doubling as a second test of the developed algorithm.
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(2019)Tailoring a hybrid surface or any complex material to have functional properties that meet the needs of an advanced device or drug requires knowledge and control of the atomic level structure of the material. The atomistic configuration can often be the decisive factor in whether the device works as intended, because the materials' macroscopic properties - such as electrical and thermal conductivity - stem from the atomic level. However, such systems are difficult to study experimentally and have so far been infeasible to study computationally due to costly simulations. I describe the theory and practical implementation of a 'building block'-based Bayesian Optimization Structure Search (BOSS) method to efficiently address heterogeneous interface optimization problems. This machine learning method is based on accelerating the identification of a material's energy landscape with respect to the number of quantum mechanical (QM) simulations executed. The acceleration is realized by applying likelihood-free Bayesian inference scheme to evolve a Gaussian process (GP) surrogate model of the target landscape. During this active learning, various atomic configurations are iteratively sampled by running static QM simulations. An approximation of using chemical building blocks reduces the search phase space to manageable dimensions. This way the most favored structures can be located with as little computation as possible. Thus it is feasible to do structure search with large simulation cells, while still maintaining high chemical accuracy. The BOSS method was implemented as a python code called aalto-boss between 2016-2019, where I was the main author in co-operation with Milica Todorović and Patrick Rinke. I conducted a dimensional scaling study using analytic functions, which quantified the scaling of BOSS efficiency for fundamentally different functions when dimension increases. The results revealed the target function's derivative's important role to the optimization efficiency. The outcome will help people with choosing the simulation variables so that they are efficient to optimize, as well as help them estimate roughly how many BOSS iterations are potentially needed until convergence. The predictive efficiency and accuracy of BOSS was showcased in the conformer search of the alanine dipeptide molecule. The two most stable conformers and the characteristic 2D potential energy map was found with greatly reduced effort compared to alternative methods. The value of BOSS in novel materials research was showcased in the surface adsorption study of bifenyldicarboxylic acid on CoO thin film using DFT simulations. We found two adsorption configurations which had a lower energy than previous calculations and approximately supported the experimental data on the system. The three applications showed that BOSS can significantly reduce the computational load of atomistic structure search while maintaining predictive accuracy. It allows material scientists to study novel materials more efficiently, and thus help tailor the materials' properties to better suit the needs of modern devices.
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(2020)Tutkielman kirjallisuusosuudessa on käyty läpi erilaisia kaupallisia biopolymeerejä, niiden synteesiä, käyttöä ja biohajoamista. Tutkielman pääpaino on erilaisten materiaalien biohajoamisessa ja näiden materiaalien kaupallisessa käytössä. Biohajoamisen evaluointiin tarkoitettuja standardeja, tutkimusmenetelmiä ja hyväksyntäkriteerejä on esitelty laajasti. Tutkimusosuudessa on valmistettu PLA:n ja PBAT:n seoksesta puukomposiitti ja materiaalin termomekaaniset ominaisuudet on karakterisoitu. Tavoitteena oli luoda biohajoava materiaali, jonka ominaisuudet ovat sellaisia, että sen kaupallinen hyödyntäminen kertakäyttömuovin korvikkeena on järkevää. Materiaalin mekaaniset ominaisuudet karakterisoitiin lopputuotteen kestävyyden, ja sulaominaisuudet kaupallisen tuotannon mahdollistamisen takia. Termomekaanisia analyysejä tehtiin materiaalin säilyvyyden ja lämpöominaisuuksien karakterisoimiseksi. Työssä on tutkittu myös puhtaan PLA/puukomposiitin biohajoamista meriympäristössä. Tutkimuksen tuloksena saatiin luotua riittävällä nopeudella biohajoava puukomposiitti, jonka mekaaniset ominaisuudet ovat riittäviä korvaamaan erilaisia kertakäyttöisiä muovituotteita ja joka on prosesoitavissa nykyisillä ekstruusiolaitteistoilla.
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(2023)The diffusion of a single hydrogen atom through solid tungsten was studied using two separate computational methods: Molecular dynamics simulations and nudged elastic band calculations. Molecular dynamics was used to track the atom’s path in the tungsten lattice in several successive simulations to obtain its mean squared displacement. Results were obtained for temperatures between 400 K and 700 K. These were used to derive a temperature relation for the diffusion coefficient and an estimate for the diffusion energy barrier, which was 0.1985 eV. The nudged elastic band method was used to directly obtain an estimate for the diffusion energy barrier. The same tungsten lattice system as in the molecular dynamics simulations had the hydrogen atom relaxed into an interstitial position and then moved over the energy barrier into an adjacent site. If the tungsten atoms were allowed to relax during the motion, a comparable value of 0.2022 eV was obtained. Further computations were made with a fixed-length tungsten bond next to the hydrogen starting position, yielding energy barriers from 0.1 eV to 1.2 eV depending on the bond length, direction of the diffusion jump and tungsten relaxation. In conclusion, the two different computational methods do give results for the energy barrier that are comparable in magnitude, but further measurement of the tungsten bonds near the hydrogen atom during the molecular dynamics simulation may be needed for a more matching comparison from the nudged elastic band results.
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(2023)Power ultrasound increases production efficiency in the industry, and therefore reduces emissions. This advantage arises from the ability of ultrasound to mitigate fouling. Ultrasound solution requires clamping the transducers onto the external wall of the production equipment, typically made of steel. A challenge then arises, since mechanical loading by the wall hampers the natural resonating of the ultrasonic transducer and therefore reduces power transmission. To overcome this limitation, airgap contact coupling (ACC) is proposed. ACC features an airgap to reduce the mechanical loading and two protruding elements for mechanical contacting and sound delivery. Finite-element method (FEM) simulations are employed to evaluate the physical mechanisms behind ACC. For the comparison, direct traditional contact coupling (TCC) is evaluated. To assess the acoustic power delivery by ACC and TCC, calorimetric measurements were used. A water-filled stainless-steel pipe with a 2 mm thick wall and 136 mm outer diameter was sonicated. To prevent heat transmission to ambient air, it was covered by isolating foam. ACC and TCC were sonicated at their coupled resonance frequencies, respectively at 19.2 kHz and 28.1 kHz. A power delivery ratio was determined by the calorimetric power against the sonication power. ACC resulted in a power delivery ratio of 27.4±6.3 % whereas that for TCC was 6.1±0.6 %. ACC was thereby shown to transmit 6 dB more acoustic power than TCC. In conclusion, a novel contact coupling method is proposed for industrial metal-walled equipment. The proposed new approach enhances the utility of power ultrasound for online cleaning and prevention.
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(2024)Fibrous meat analogues (FMAs) are an emerging category of synthetic plant-based food materials intended to mimic animal meat in both taste and mouthfeel. However, replicating the texture of meat with plant matter is far from trivial. Designing a manufacturing process that gives the produced FMA the desired properties requires proper characterisation of the material and its behaviour. One source of such knowledge could be obtained through computed x-ray absorption microtomography (µCT) --- a microscopic technique capable of producing a 3D model of the internal structure of the target object without requiring its disassembly. Unfortunately, while the scanning itself can be rather straightforward, issues arise when the recorded imagery is to be processed for analysis, as the researcher's choices of the employed methods, algorithms and their parameters may become a potential source of bias, affecting the end results in unintended ways. In this work, we examine the data processing pipeline of µCT studies on FMA samples, discuss the shortcomings of some of the employed methods, and attempt to address these problems by modifying the steps as needed, the aim being to reduce the reliance of the utilised methods on the researcher's judgment. Our main focus is in particular on the segmentation step, where the values provided by the µCT scan are interpreted and simplified to a form that subsequent algorithm-based analysis methods can operate on.
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(2021)X-ray absorption spectroscopy(XAS) measures the absorption response of the system as a function of incident X-ray photon energy. XAS can be a great tool for material characterization due to its ability to reveal characteristic information specific to chemical state of element by using the core level electrons as a probe for empty electronic states just above the Fermi level of the material (XANES) or for the neighboring atoms (EXAFS). For years, the highly brilliant synchrotron light sources remained the center of attention for these XAS experiments, but the increasing competition for available beamtime at these facilities led to an increased interest in laboratory scale X-ray spectroscopy instruments. However, the energy resolution of laboratory scale instruments still remains sometimes limited as compared to their synchrotron counterparts. When operating at low Bragg angles, the finite source size can greatly reduce the energy resolution by introducing the effects of dispersion in the beam focus at the detector. One method to overcome this loss in resolution can be to use a position sensitive detector and use the 'pixel compensation correction' method in the post-processing of the experimental data. The main focus of this study was to improve the energy resolution of a wavelength dispersive laboratory-scale X-ray absorption spectrometer installed at the University of Helsinki Center for X-ray Spectroscopy. The project focuses on the case of Fe K-absorption edge at 7.112 keV energy and a Bragg angle of 71.74 degrees when using Silicon (5 3 1) monochromator crystal. Our results showed that the data that had been corrected using this method showed sharper spectral features with reduced effects of broadening. Moreover, contribution of other geometrical factors to the energy resolution of this laboratory X-ray spectrometer were also estimated using ray-tracing simulation and an expected improvement in resolution due to pixel compensation correction was calculated. The same technique can be extended to other X-ray absorption edges where a combination of a large deviation of Bragg angle from 90 degrees and a large source size contributes a dominant factor to the energy resolution of the instrument.
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(2020)The aim of the thesis was to study enzymatic treatment as a way to modify paper grade pulp to be a suitable raw material for the future textile industry. Wood as a raw material is an environmentally friendly option for textile production but its sustainable exploitation is not easy. Currently, ionic liquids are assumed to enable a safe and sustainable process for the production of wood-based regenerated fibres. These processes commonly use dissolving pulp as their raw material but replacing dissolving pulp with a paper grade kraft pulp would decrease environmental impact and production expenses. In this work, molar mass distribution of softwood paper grade kraft pulp was selectively modified using enzymes. Enzymes were utilized instead of acids because of their favourable abilities to selectively modify targeted polymers and to increase fibre porosity. Enzymatic modifications of softwood kraft pulp were performed to decrease degree of polymerization of cellulose and lower the quantity of hemicellulose. Hydrolysis of cellulose was catalysed with endo-1,4-β-glucanase (endoglucanase) and hemicellulose was degraded using endo-1,4-β-mannanase and endo-1,4-β-xylanase. The treatments were carried out both at high (20%) and low (3%) pulp consistency to examine the synergistic effect of enzymatic and mechanical action arising in the high consistency treatment. Additionally, influence of different enzyme combinations on the pulp properties was studied. The modified pulp samples were characterized by determining intrinsic viscosity, molar mass distribution, yield loss, and its composition. The fibres were imaged with light microscopy. The degree of polymerization of the pulp cellulose was successfully decreased with a relatively small endoglucanase dose. The amount of hemicellulose was reduced by removing 11% of the total galactoglucomannan and 40% of the total arabinoglucuronoxylan. The high consistency treatments decreased intrinsic viscosity 1.9 times more on average than the low consistency treatments. The high consistency treatments were effective with low enzyme doses, easy to control, and reliably repeated. Therefore, enzymatic pulp treatment at high consistency seems to be a compatible way to modify paper grade kraft pulp to suitable raw material for textile production. Further studies related to pulp dissolution in ionic liquids, fibre spinning, and fibre regeneration should be concluded to confirm applicability of the modified fibres.
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(2021)High pressure inside e.g. blood vessels or other biological cavities is a major risk factor for many preventable diseases. Most of the measuring methods require physical contact or other kinds of projected forces. Both variants can be unpleasant for the patient and additionally physical contact might warrant for either continuous disinfecting or single-use probes, depending on the measurement method and the target body part. We have been experimenting with handheld non-contacting pressure measuring devices based on acoustic waves. These excite mechanical waves, whose velocity varies with pressure, on the surface of a biological cavity. The tried excitation methods are nearly unnoticeable for the patient, allowing for more pleasant and waste free measurements. Using the data from the latest clinical trial, a new analysis algorithm was devised to improve the accuracy of the pressure estimates. Instead of the time-of-flight (TOF) of the main mechanical wave (MMW), the new algorithm estimates the pressure using the MMW and a previously unseen feature, improving the R^2 from 0.60 to 0.72.
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(2021)High-intensity and -amplitude focused ultrasound has been used to induce cavitation for decades. Well known applications are medical (lithotripsy and histotripsy) and industrial ones (particle cleaning, erosion, sonochemistry). These applications often use low frequencies (0.1-5 MHz), which limits the spatial precision of the actuation, and the chaotic nature of inertial cavitation is rarely monitored or compensated for, constituting a source of uncertainty. We demonstrate the use of high-frequency (12 MHz) high-intensity (ISPTA=90 W/cm2 ) focused-ultrasound- induced cavitation to locally remove solid material (pits with a diameter of 20 µm to 200 µm) for non- contact sampling. We demonstrate breaking cohesion (aluminium) and adhesion (thin film on a substrate, i.e. marker ink on microscope glass). The eroded surfaces were analyzed with a scanning acoustic microscope (SAM). We present the assembly and the characterization of a focused ultrasound transducer and show quantification of the effect of different sonication parameters (amplitude, cycle count, burst count, defocus) on the size and shape of the resulting erosion pits. The quantitative precision of this method is achieved by systematic calibration measurements, linking the resulting erosion to acoustic parameters to ensure repeatability (sufficient probability of cavitation), and inertial cavitation monitoring of the focal echoes. We discuss the usability of this method for localized non-contact sampling.
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(2021)Plasmonic catalysis utilises light energy to drive chemical reactions. Compared to conventional catalytic processes, which are run by high temperatures and pressures, light-driven processes can lower energy consumption and increase selectivity. Conventional plasmonic nanoparticles (Ag, Au) are relatively scarce and expensive, and therefore the use of materials with earth-abundant elements in plasmonic catalysis is widely pursued. Despite their good optical properties, plasmonic nanoparticles are often unsuitable catalysts. Hybrid catalysts, structures consisting of a light-harvesting plasmonic part and a catalytical centre of different material, have emerged as an opportunity to address these challenges and obtain desired properties. This thesis consists of two parts: In the first part, properties of plasmonic materials are described, and previous studies of hybrid catalysts with earth-abundant plasmonic materials are reviewed. Experimental work on plasmonic-catalytic nanohybrids, with TiN as the plasmonic part and Pd as the catalytic entity, is described in the second part. In this context, a Pd/TiN (Pd nanoparticles supported into TiN) catalyst was synthesised, characterised and applied to test catalytical reactions. Contrary to the hypothesis, light-induced rate enhancement was not observed in our current catalytical studies. These results call for further optimisation of synthesis and reaction conditions to prepare an earth-abundant, light-active catalyst.
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(2023)Eye plaque radiotherapy is a treatment method of ocular tumors: A sealed radiation source is temporarily placed on the surface of the eye in day surgery. Compared to externally delivered conventional radiation treatments, more precisely targeted brachytherapy allows a higher dose in the target tissue while keeping the dose to healthy tissue relatively low. In Finland, all eye plaque treatments are centralised in Helsinki and brachytherapy of the eye is performed annually on approximately 70 patients. Patient specific anatomy takes into account determination of specific location and shape of the tumor in respect of radio-biologically critical structures of the eye. Until now, this has not been systematically modeled in dose calculation of eye plaque brachytherapy at HUS. The new version of Plaque Simulator, a 3D treatment simulation and modeling package for I-125, Pd-103, Ir-192 and Ru-106 plaque therapy of ocular tumors, enables importation and digitisation of patient imaging data (fundus imaging, CT and MRI) which consequently allows for systematically accurate estimation of dose distribution not only in the tumor but also in surrounding healthy tissues. The aim of this Master’s thesis is to prepare the new version of Plaque Simulator simulation and modeling package for clinical use in patient dose calculation at HUS. A comparison is done between the dose calculation method of the old and the new version of Plaque Simulator, and the dose calculation parameters as well as the plaque modeling parameters are reviewed. The function of the image-based dose calculation method is also tested with an anonymised patient treated for a tumor of a more peculiar shape. The absorbed dose to water on the central axis of the radiation source is measured experimentally for two individual I-125-seed along with Ru-106-CCB-, I-125-CCB-, and two I-125-COB-plaques. Experimental results are compared with the results obtained from Plaque Simulator. Individual I-125-seed is used to calibrate the detector at a distance of 10 mm, yielding to a calibration factor of 0.808. The use of the gold parameter in the dose calculation is justified, and a dosimetry modifier of Plaque Simulator is found to be 1.226 for I-125-plaques. Ru-106-plaque measurements are not calibrated, making them only relative. However, an excellent correspondence is observed between Ru-106-plaque dose calculations in Plaque Simulator and the manufacturer’s certificate. The measurements are normalized to the manufacturer’s certificate with a normalisation factor of 1.117.
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(2021)Atomic force microscopy (AFM) is a widely utilized characterization method capable of capturing atomic level detail in individual organic molecules. However, an AFM image contains relatively little information about the deeper atoms in a molecule and thus interpretation of AFM images of non-planar molecules offers significant challenges for human experts. An end-to-end solution starting from an AFM imaging system ending in an automated image interpreter would be a valuable asset for all research utilizing AFM. Machine learning has become a ubiquitous tool in all areas of science. Artificial neural networks (ANNs), a specific machine learning tool, have also arisen as a popular method many fields including medical imaging, self-driving cars and facial recognition systems. In recent years, progress towards interpreting AFM images from more complicated samples has been made utilizing ANNs. In this thesis, we aim to predict sample structures from AFM images by modeling the molecule as a graph and using a generative model to build the molecular structure atom-by-atom and bond-by-bond. The generative model uses two types of ANNs, a convolutional attention mechanism to process the AFM images and a graph neural network to process the generated molecule. The model is trained and tested using simulated AFM images. The results of the thesis show that the model has the capability to learn even slight details from complicated AFM images, especially when the model only adds a single atom to the molecule. However, there are challenges to overcome in the generative model for it to become a part of a fully capable end-to-end AFM process.
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(2024)Monoenergetic neutron reference fields are used in neutron metrology for the calibration of different neutron detectors, including dose rate meters. The International Standardization Organization ISO has composed guidelines and requirements for the production of narrow energy spread neutron fields using a particle accelerator. The objective of this Thesis was to investigate a target material that could be used to produce a monoenergetic neutron field by irradiating it with protons. A broader energy distribution was deemed satisfactory in regard to the initial phase of the station’s development, as significant modifications to the beamline would be necessary to acquire more precise beam current values and to achieve proton energies closer to the reaction threshold energy. The target material was chosen to be lithium fluoride (LiF) based on a literature review and Monte Carlo simulations. The simulations were executed with the proton energy of 2.5 MeV, which is close to the threshold energy of the 7Li(p, n)7Be reaction, and with the fixed energy 10 MeV of the IBA cyclotron used to conduct the experiment. The simulations were executed with the MCNP6 code, and the results were compared to those obtained from equivalent Geant4 simulations. The simulations suggested two wide peaks around 3 MeV and 0.6 MeV at the proton energy of 10 MeV. The irradiation experiment included two phases, one of which entailed the use of a shadow cone to estimate the number of scattered neutrons in the neutron yield. The maximum neutron fluence of (2.62 ± 0.78)∙109 s-1 was measured at the pop-up probe current of (8.3 ± 0.8) µA. Gamma spectrometry was utilized after the experiment to further evaluate the number of 7Li(p,n)7Be reactions taken place in the target by calculating the number of 7Be nuclei in the LiF plate. Altogether, lithium fluoride exhibits promising characteristics as a target material for accelerator-based monoenergetic neutron production, although its application demands further considerations regarding for instance, the decrement of the proton energy and the aiming and measurement of the proton beam. These results contribute to the future development of a neutron irradiation station at the University of Helsinki.
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(2021)The rapidly increasing global energy demand has led to the necessity of finding sustainable alternatives for energy production. Fusion power is seen as a promising candidate for efficient and environmentally friendly energy production. One of the main challenges in the development of fusion power plants is finding suitable materials for the plasma-facing components in the fusion reactor. The plasma-facing components must endure extreme environments with high heat fluxes and exposure to highly energetic ions and neutral particles. So far the most promising materials for the plasma-facing components are tungsten (W) and tungsten-based alloys. A promising class of materials for the plasma-facing components is high-entropy alloys. Many high-entropy alloys have been shown to exhibit high resistance to radiation and other wanted properties for many industrial and high-energy applications. In materials research, both experimental and computational methods can be used to study the materials’ properties and characteristics. Computational methods can be either quantum mechanical calculations, that produce accurate results while being computationally extremely heavy, or more efficient atomistic simulations such as classical molecular dynamics simulations. In molecular dynamics simulations, interatomic potentials are used to describe the interactions between particles and are often analytical functions that can be fitted to the properties of the material. Instead of fixed functional forms, interatomic potentials based on machine learning methods have also been developed. One such framework is the Gaussian approximation potential, which uses Gaussian process regression to estimate the energies of the simulation system. In this thesis, the current state of fusion reactor development and the research of high-entropy alloys is presented and an overview of the interatomic potentials is given. Gaussian approximation potentials for WMoTa concentrated alloys are developed using different number of sparse training points. A detailed description of the training database is given and the potentials are validated. The developed potentials are shown to give physically reasonable results in terms of certain bulk and surface properties and could be used in atomistic simulations.
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(2024)This thesis presents an acoustic microscope that is using coded signals to improve the signal-to-noise ratio (SNR) without increasing the voltage applied to the transducer. The operating principle of an acoustic microscope is presented with a detailed description of the coded excitation scanning acoustic microscope (CESAM). Acoustic microscopy is compared to other non-destructive testing (NDT) methods, and developments to improve acoustic imaging with coded signals are presented. Biological sample images from a rabbit femur bone are presented, and issues with surface roughness related to imaging bone structures in general are discussed. The increase of bone content with increased time post operation is calculated. Surface roughness of a rabbit femur bone sample containing a bioactive glass implant is analyzed, and acoustic impedance map of this sample is presented.
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