Traditional Lithium-Ion Batteries (LIBs) are a reliable and cost-efficient choice for energy storage. LIBs offer high energy density and low self-discharge. Recent developments in electric-based technologies push for replacing historically used Lead-Acid batteries with LIBs. However, LIBs do not yet meet the demands of modern technology. Silicon and graphene oxide (GO) have been identified as promising replacements to improve anode materials. Graphene oxide has a unique sheet-like structure that provides a mechanically stable, light weight material for LIB anodes. Due to its structure, reduced graphene oxide (rGO) is efficiently conductive and resistive to environmental changes. On the other hand, silicon-based anode materials offer the highest theoretical energy density and a high Li-ion loading capacity of various elements [20]. Silicon-based anodes that have previously been studied demonstrated extreme volumetric expansion over long cycles due to lithiation. Polysiloxane may be an interesting alternative as it is a Si-based material that can retain the high Li-ion loading capacity of Si while lacking the unattractive volumetric expansions of Si. Polymer derived ceramic-decorated graphene oxide anodes have been suggested to increase loading capacity, thermal resistance, power density, and mechanical stability of LIBs. Coupled with mechanically stable graphene oxide, polymer derived ceramic nanoparticle decorated graphene oxide anodes are studied to establish their efficiencies under operating conditions.

<p>In this study, we concentrate on spin-1/2 systems. A series of tools using the Liouville space method have been developed for simulating of NMR of arbitrary pulse sequences.</p> <p>We have calculated one- and two-spin symbolically, and larger systems numerically of steady states. The one-spin calculations show how SSFP converges to continuous wave NMR. A general formula for two-spin systems has been derived for the creation of double-quantum signals as a function of irradiation strength, coupling constant, and chemical shift difference. The formalism is general and can be extended to more complex spin systems.</p> <p>Estimates of transverse relaxation, R₂, are affected by frequency offset and field inhomogeneity. We find that in the presence of expected B₀ inhomogeneity, off-resonance effects can be removed from R₂ measurements, when ||omega||<= 0.5 gamma\,B₁ in Hahn echo experiments, when ||omega||<=gamma\,B₁ in CPMG experiments with specific phase variations, by fitting exact solutions of the Bloch equations given in the Lagrange form.</p> <p>Approximate solutions of CPMG experiments show the specific phase variations can significantly smooth the dependence of measured intensities on frequency offset in the range of +/- 1/2 gamma\,B₁. The effective R₂ of CPMG experiments when using a phase variation scheme can be expressed as a second-order formula with respect to the ratio of offset to pi-pulse amplitude.</p> <p>Optimization problems using the exact or approximate solution of the Bloch equations are established for designing optimal broadband universal rotation (OBUR) pulses. OBUR pulses are independent of initial magnetization and can be applied to replace any pulse of the same flip angles in a pulse sequence. We demonstrate the process to exactly and efficiently calculate the first- and second-order derivatives with respect to pulses. Using these exact derivatives, a second-order optimization method is employed to design pulses. Experiments and simulations show that OBUR pulses can provide more uniform spectra in the designed offset range and come up with advantages in CPMG experiments.</p> / Doctor of Philosophy (PhD)

Cellulosananofibriller (CNFs) hör till naturens mest fundamentala byggstenar och förser naturliga material, såsom den yttre cellväggen i trä, med en otrolig styrka och styvhet. Genom att imitera träets arkitektur öppnas möjligheter upp för tillverkning av nya, biobaserade och lättviktiga strukturella material med mekaniska egenskaper som överskrider de för glasfiber, metaller och legeringar. Den ingenjörsmässiga utmaningen ligger i att framgångsrikt lyckas överföra de önskade mekaniska egenskaperna hos CNFs till filament som kan användas i material för dagligt bruk. Vid flödesfokuserad spinning av extraherade CNFs påverkar många parametrar den slutgiltiga funktionaliteten och kvaliteten hos de resulterande filamenten. För att optimera dessa processparametrar är mätning av de spunna filamentens dimensioner ett viktigt moment. Av särskilt intresse är filamentbredden, eftersom den är avgörande för de mekaniska egenskaperna. Karakterisering av filamentbredden är i dagsläget en mycket tidskrävande process där varje filament mäts manuellt i optiskt mikroskop. Det huvudsakliga målet med detta projekt är att effektivisera den nuvarande mätprocessen med avseende på både hastighet och noggrannhet med hjälp av laserspridning. I denna rapport visar vi på minst en halvering av nuvarande mättid vid användandet av en 3D-printad laseruppställning istället för ett optiskt mikroskop vid mätning av filamentbredd. Våra resultat indikerar att mätsäkerheten generellt är högre för lasermetoden jämfört med mikroskopin. Genomsnittliga standardavvikelser för mätvärden på tunnaste bredden från mikroskopi samt de två olika kurvanpassningsmetoderna vid lasermätning rapporteras vara 1.62, 0.85 (Curve fit) respektive 1.59 (Minima matching). Standardavvikelserna för tunnaste bredd korrelerar dock inte direkt mot metodernas noggrannhet eftersom de spunna filamenten uppvisar en stor variation i bredd längs med längden. En närmare jämförelse mellan mätvärden för matchade punkter på ideala och defekta filament demonstrerar att icke-uniforma och defekta filament påverkar mätnoggrannheten för laserspridningen negativt. Sammantaget stödjer våra resultat det faktum att ett tunnare filament resulterar i bättre upplösning och mindre mätfel vid mätning med laserspridning. Våra resultat visar på den stora potentialen för laserspridning som en mer effektiv mätmetod vid karakterisering av cellulosafilamentbredd. / Cellulose nanofibrils (CNFs) are one of nature’s most fundamental building blocks, providing incredible strength and stiffness to natural materials, such as the outer cell wall layer in wood. By mimicking the architecture of wood, possibilities opens up for the fabrication of new, biobased, light-weight structural materials with mechanical properties exceeding that of glassfibers, metals and alloys. However, the engineering challenge lies in successfully managing to translate the desirable mechanical properties of the CNFs into filaments that can be used in everyday life materials. Throughout the process of spinning the extracted CNFs into filaments, many factors and parameters affect the ultimate functionality and performance of the resulting filaments. Measuring the dimensions of the spun filaments is a crucial step in further optimizing process parameters. The width of the filament especially, impacts its mechanical performance. The characterization of the cellulose filament width is currently very time-consuming as each filament is manually measured using optical microscopy. The primary goal of this project is to make the current characterization process more effective, with respect to both accuracy and speed of measurement, by using laser scattering. In this report, we demonstrate a reduction by more than a half in measurement time using a 3D-printed laser scattering setup instead of an optical microscope when measuring filament width. Our results indicate that the certainty in measurement is generally higher for lase rscattering compared to optical microscopy. The mean standard deviations (SD) for the smallest widths estimated with optical microscopy and the two curve fitting methods used for the laser measurements are reported to be 1.62, 0.85 (Curve fit) and 1.59 (Minima matching) respectively. However, standard deviations for the thinnest width does not correlate directly to the accuracy of the methods since the spun filaments show a large variation in width along the length. A closer comparison between measurement values for matched points at ideal and non-uniform filaments demonstrate that the accuracy of the laser measurements are dependent on the uniformity of the filaments, with non-uniform filaments negatively impacting the accuracy. Our overall results supports the fact that a thinner filament gives a better resolution and smaller error when measuring with laser. Our results provide evidence for the great potential of laser scattering as a more efficient method for cellulose filament width determination.

A fairly new technology used to produce metallic components is powder metallurgy (PM). Among the advantages with this technique are decreased cost of production for complex-shaped parts, new alloys are made possible, reduced end processing, less material loss, and vibrational damping effects. The downside is the number of pores created which can alter the tribological properties of the material. The focus of this report is to investigate how lean PM steel behaves under tribological contacts.  Friction and wear will be investigated using a pin-on-disc setup to mimic the sliding part of a gear tooth mesh. Previous studies show that the amount of wear, and if the wear increases or decreases with increased density is dependent on the degree of porosity and the pore size. This means that the wear might be minimized by optimizing the number of pores in the material and their shape and size. The result of this study shows that the friction coefficient decreases with increasing density. The wear coefficient show signs of the same correlations but further tests are needed. The main wear comes from adhesive wear, with signs of abrasive wear. The amount of abrasive wear seems to increase with an increase in density, supporting previous studies claiming that pores can trap wear debris and decrease the number of abrasive particles in the contact.

En sjukdom kan många gånger härledas till en kaskadereaktion mellan proteiner, co-faktorer och substrat. Denna kaskadreaktion blir många gånger målet för att behandla sjukdomen med läkemedel. För att designa nya läkemedelsmoleyler används vanligen datorbaserade verktyg. Denna design av läkemedelsmolekyler drar stor nytta av att målproteinet är känt och då framförallt dess tredimensionella (3D) struktur. Är 3D-strukturen känd kan man utföra så kallad struktur- och datorbaserad molekyldesign, 3D-geometrin (f.f.a. för inbindningsplatsen) blir en vägledning för designen av en ny molekyl. Många faktorer avgör interaktionen mellan en molekyl och bindningsplatsen, till exempel fysikalisk-kemiska egenskaper hos molekylen och bindningsplatsen, flexibiliteten i molekylen och målproteinet, och det omgivande lösningsmedlet. För att strukturbaserad molekyldesign ska fungera väl måste två viktiga steg utföras: i) 3D anpassning av molekyler till bindningsplatsen i ett målprotein (s.k. dockning) och ii) prediktion av molekylers affinitet för bindningsplatsen. Huvudsyftena med arbetet i denna avhandling var som följer: i) skapa modeler för att prediktera affiniteten mellan en molekyl och bindningsplatsen i ett målprotein; ii) förfina molekyl-protein-geometrin som skapas vid 3D-anpassning mellan en molekyl och bindningsplatsen i ett målprotein (s.k. dockning); iii) karaktärisera proteiner och framför allt deras sekundärstruktur; iv) bedöma effekten av olika matematiska beskrivningar av lösningsmedlet för förfining av 3D molekyl-protein-geometrin skapad vid dockning och prediktion av molekylers affinitet för proteiners bindningsfickor. Ett övergripande syfte var att använda kemometriska metoder för modellering och dataanalys på de ovan nämnda punkterna. För att sammanfatta så presenterar denna avhandling metoder och resultat som är användbara för strukturbaserad molekyldesign. De rapporterade resultaten visar att det är möjligt att skapa kemometriska modeler för prediktion av molekylers affinitet för bindningsplatsen i ett protein och att dessa presterade lika bra som andra vanliga metoder. Dessutom kunde kemometriska modeller skapas för att beskriva effekten av hur inställningarna för olika parametrar i dockningsprogram påverkade den 3D molekyl-protein-geometrin som dockingsprogram skapade. Vidare kunde kemometriska modeller andvändas för att öka förståelsen för deskriptorer som beskrev sekundärstrukturen i proteiner. Förfining av molekyl-protein-geometrin skapad genom dockning gav liknande och ickesignifikanta resultat oberoende av vilken matematisk modell för lösningsmedlet som användes, förutom för ett fåtal (sex av 30) fall. Däremot visade det sig att användandet av en förfinad geometri var värdefullt för prediktion av molekylers affinitet för bindningsplatsen i ett protein. Förbättringen av prediktion av affintitet var markant då en Poisson-Boltzmann beskrivning av lösningsmedlet användes; jämfört med prediktionerna gjorda med ett dockningsprogram förbättrades korrelationen mellan beräknad affintiet och uppmätt affinitet med 0,7 (R2). / A disease is often associated with a cascade reaction pathway involving proteins, co-factors and substrates. Hence to treat the disease, elements of this pathway are often targeted using a therapeutic agent, a drug. Designing new drug molecules for use as therapeutic agents involves the application of methods collectively known as computer-aided molecular design, CAMD. When the three dimensional (3D) geometry of a macromolecular target (usually a protein) is known, structure-based CAMD is undertaken and structural information of the target guides the design of new molecules and their interactions with the binding sites in targeted proteins. Many factors influence the interactions between the designed molecules and the binding sites of the target proteins, such as the physico-chemical properties of the molecule and the binding site, the flexibility of the protein and the ligand, and the surrounding solvent. In order for structure-based CAMD to be successful, two important aspects must be considered that take the abovementioned factors into account. These are; i) 3D fitting of molecules to the binding site of the target protein (like fitting pieces of a jigsaw puzzle), and ii) predicting the affinity of molecules to the protein binding site. The main objectives of the work underlying this thesis were: to create models for predicting the affinity between a molecule and a protein binding site; to refine the geometry of the molecule-protein complex derived by or in 3D fitting (also known as docking); to characterize the proteins and their secondary structure; and to evaluate the effects of different generalized-Born (GB) and Poisson-Boltzmann (PB) implicit solvent models on the refinement of the molecule-protein complex geometry created in the docking and the prediction of the molecule-to-protein binding site affinity. A further objective was to apply chemometric methodologies for modeling and data analysis to all of the above. To summarize, this thesis presents methodologies and results applicable to structure-based CAMD. Results show that predictive chemometric models for molecule-to-protein binding site affinity could be created that yield comparable results to similar, commonly used methods. In addition, chemometric models could be created to model the effects of software settings on the molecule-protein complex geometry using software for molecule-to-binding site docking. Furthermore, the use of chemometric models provided a more profound understanding of protein secondary structure descriptors. Refining the geometry of molecule-protein complexes created through molecule-to-binding site docking gave similar results for all investigated implicit solvent models, but the geometry was significantly improved in only a few examined cases (six of 30). However, using the geometry-refined molecule-protein complexes was highly valuable for the prediction of molecule-to-binding site affinity. Indeed, using the PB solvent model it yielded improvements of 0.7 in correlation coefficients (R2) for binding affinity parameters of a set of Factor Xa protein drug molecules, relative to those obtained using the fitting software.