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Coming dissertations at Uppsala university

  • Computational Modelling of Protein Dynamics, Specificity and Evolution Author: Andrey O. Demkiv Link: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-537049 Publication date: 2024-11-19 11:52

    Proteins are the foundational molecules driving nearly all biochemical processes essential for life. Their ability to catalyse reactions with high specificity and efficiency is key to biological function and holds significant potential for applications in drug discovery, disease treatment, and green chemistry. However, understanding the intricate mechanisms underlying enzyme catalysis and ligand binding requires not only structural insights but also a deep understanding of protein dynamics, which can be challenging to capture experimentally.

    This thesis leverages various computational methods to explore the dynamic behaviour of proteins, providing critical insights that complement experimental approaches. We developed an implementation of a replica exchange enhanced sampling technique to model enzymatic reactions with the EVB approach - Q-RepEx, which allows us to study the reaction within the context of larger protein motions. EVB and MD simulations enabled us to uncover the catalytic promiscuity of the lactonase GcL, revealing its ability to utilise multiple pathways depending on the substrate—a feature that could be exploited for designing selective quorum quenchers. Additionally, our MD studies on disembodied P-loop peptides provided new perspectives on their role as potential evolutionary precursors of the P-loop NTPase family, challenging existing hypotheses on their minimal functional ancestor. Overall, this work underscores the role of computational methods in advancing our understanding of protein dynamics and function, offering valuable insights that are essential for both fundamental biology and the development of novel biotechnological applications.

  • Dynamics of Solid Electrolyte Interphases in Li-ion Batteries : From Operando Analysis to Mechanistic Insights Author: Tim Melin Link: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-540994 Publication date: 2024-11-19 08:19

    Li-ion batteries (LIBs) play a crucial role in the transition from fossil fuel to renewable energy sources by providing energy storage solutions for numerous applications. The modern high energy density LIBs were realised largely by the stabilisation of the electrode/electrolyte interface at the negative electrode with the solid electrolyte interphase (SEI). The SEI forms through electrolyte reduction during the first couple of charge/discharge cycles. Despite extensive optimisation of LIBs through electrolyte and SEI development, fundamental understanding of the formation, composition, structure and operating mechanism of the SEI is yet to be established. In order to address this gap, operando analytical techniques and model electrode/electrolyte systems were developed and applied to systematically investigate the formation and evolution of gaseous, soluble and solid reaction products. The thesis provides insights into the mechanisms behind SEI formation as driven by several important electrolyte solvents and additives, namely ethylene carbonate (EC), propylene carbonate (PC), vinylene carbonate (VC), lithium bis(oxalato)borate (LiBOB), 1,3,2-dioxathiolane 2,2-dioxide (DTD), and prop-1-ene-1,3-sultone (PES). Key findings include that EC and PC are reduced via identical reaction pathways, but with product of different solubilities, which in turn explains the difference in their ability to passivate the electrode surface. For the layer-forming additives, reduction pathways and their impact on the SEI passivation properties were identified and discussed. Although VC significantly reduces the layer thickness, the SEI is much denser and therefore more resistive to ion transport. LiBOB, DTD and PES were all found to have similar influence, namely passivate the electrode and suppress EC reduction, but each with their own peculiarities. LiBOB was found to be reduced already at 1.8 V vs. Li+/Li to form primarily Li-oxalate based SEI along with electrolyte soluble borates. DTD reduces to primarily gaseous and solid products with a comparatively thicker SEI at 1.4 V vs. Li+/Li. PES leads primarily to electrolyte-soluble product at 1.4 V vs. Li+/Li, which in a subsequent step generates a comparatively thinner SEI. Both VC and PES reduced H2 evolution, which was explained by the H2O and H scavenging ability of their unsaturated carbon-carbon bonds. Based on the collective findings herein, an effective layer-former suppresses the reduction of both the electrolyte and its impurities and generates a 10 nm thick and dense SEI comprised primarily of inorganic Li-species. The insights into the SEI formation process on a fundamental level of the aforementioned solvents and additives showcase the ability of complementary operando analytical techniques to unravel the complexity of the elusive SEI. The insights thus gained guide the optimisation and development of electrolytes for current and future LIB chemistries.

  • Bounds for selection bias in causal inference Author: Stina Zetterström Link: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-540562 Publication date: 2024-11-15 10:47

    This thesis consists of four papers that study and propose several bounds of causal estimands under selection bias.

    Paper I investigates previously reported bounds. Importantly, we study the impact on the bounds when additional selections are made. This study highlights practical challenges when using the reported bounds. Additionally, Paper I also presents assumption-free bounds that are based on the observed data and the standard assumptions. These bounds are in many cases easier to use than the previously reported bounds, although they are sometimes conservative.

    Paper II proposes two alternative bounds for selection bias. These bounds utilize the observed data but requires the specification of unknown sensitivity parameters and additional assumptions. The bounds equal the corresponding assumption-free bound in Paper I when the sensitivity parameters are set to their most conservative values. For other choices of the sensitivity parameters, these bounds are tighter than the assumption-free bound.

    Paper III summarizes the results from Paper I and II in the R package SelectionBias to make the bounds easily accessible for practitioners, and compares the R package SelectionBias to existing software for calculating some of the bounds.

    Paper IV investigates properties of previously reported bounds. First, variation independence of the sensitivity parameters is shown, implying that the sensitivity parameters can be considered separately. Second, it is shown that the considered bounds are sharp under certain conditions, meaning that the bias can be as large as the bounds. Lastly, improved versions of the bounds in the non-sharp regions are presented.

    The bounds discussed in this thesis are valid for causal effects measured on a difference or ratio scale. The bounds can be used in different situations depending on the knowledge and/or data available. The presented R package is intended to make the research accessible to practitioners.

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