Carbon dioxide (CO2), as a greenhouse gas, has shown to achieve the highest level in history, causes the global warming issue, leading to a 1.2 ℃ increase of the global average temperature. The consumption of fossil fuels is one of the main reasons that cause CO2 emission. Current industrial production of chemicals accounts for 29% of total fossil fuels consumption, which can be the feedstock or raw materials for carbon source, or act as the fuel to generate heat and power. CO2 conversion technologies, e.g., thermo-catalytic reaction and electrochemical reduction, have drawn researchers' attention, since they have the potential to resolve the feedstock and fuel consumption sectors of chemical production at the same time. CO2 conversion technologies use CO2 as the direct carbon source of chemicals and store the intermittent renewable energies as the energy source, which can ultimately achieve a net-zero CO2 emission and produce value-added chemical products. However, there are challenges for a practical application of CO2 conversion technologies. For instance, electrochemical CO2 reduction reaction (ECO2RR) suffers from the low activity and selectivity, while thermocatalytic CO2 conversion, or the CO2 hydrogenation reaction, usually requires harsh reaction conditions and has a low selectivity. Nonetheless, the improvement of developing new promising catalysts remains limited, due to the lack of insights of the reactions. The complex reaction networks and kinetics lead to an elusive reaction mechanism, and various effects, e.g., solvation, potential, structure, and coverage, hinder our fundamental understanding of catalytic processes. Herein, we report the efforts that we have been put in to gain insights of reaction mechanism of CO2 reduction reactions. Bi has shown to reduce CO2 to formic acid (HCOOH), while we have found that, by constituting a Bi-Cu2S heterostructure catalyst, a better catalytic performance was achieved, due to the structural effect of the interface (Chapter 2). However, it is shown that the CO2 electrochemical reduction mechanism on Bi has changed when switching the electrolyte from water to aprotic media, e.g., ionic liquids, and CO was obtained as the main product instead of HCOOH, showing a shift of reaction pathway due to the electrolyte effect (Chapter 3). However, the fundamental understanding of reaction mechanism requires not only the reaction pathways, but the reaction kinetics under reaction conditions, where the lateral or adsorbate-adsorbate interactions play an important role. In this case, we summarized recent advances of applications of machine learning (ML) algorithms for adsorbate-adsorbate interaction model developments to deal with the realistic reaction kinetics (Chapter 4). The lattice based Kinetic Monte Carlo (KMC) has shown promising performances for considering the lateral interactions of surface reactions. We report the mechanistic and KMC kinetic study of CO2 hydrogenation on Cesium promoted Au(111) surface, to gain insights of alkali metal promoting effects under reaction conditions (Chapter 5). To expand the scope, the integration of CO2 reduction with the C-N bond formation provides a promising strategy to produce more value-added product such as urea. Recent studies show that urea can be produced by reducing CO2 and nitrate (NO3-) from wastewater, which mitigate both global warming and nitrate pollution issue. However, the reaction mechanism remains elusive due to the complicated reaction network. Therefore, we employed the first-principles molecular dynamics to reveal the reaction mechanism of C-N coupling and the effect of different reaction conditions including applied potential and electrolyte (Chapter 6). Although recent advances in the computational catalysis field have significantly push forward the understanding of the chemistry nature of heterogeneous catalysis, the gap between theory and experiment remains far beyond bridged due to the complexity nature of the problem in a wide range of time and length scales, hinders the development and discovery of active catalytic materials. Recent advances of narrowing and bridging the complexity gap between theory and experiment with machine learning have been summarized to emphasize the importance of utilizing machine learning for rational catalyst design (Chapter 7). / Doctor of Philosophy / Global warming issue is a rising topic in recent years which has severe impacts on environments. One of the main reasons is the increase level of greenhouse gases that prevent the release of heat that captured from the sun. Carbon dioxide (CO2) is achieving the highest level in history due to the human activities including the consumption of fossil fuels. Therefore, CO2 conversion technologies are needed to tackle reduce the CO2 level in the atmosphere and the emission of CO2 in industries. CO2 conversion technologies, e.g., thermo-catalytic reaction and electrochemical reduction, have drawn researchers' attention, since they have the potential to resolve the feedstock and fuel consumption sectors of chemical production at the same time. However, the complexity of the CO2 conversion processes hinders the development of new technologies. Since the nature of these technologies are heterogeneous catalytic reactions, all reactions are happening at the interface between catalysts and reactants/products, which calls for the understanding of interfacial mechanisms of CO2 reduction reactions. For this type of high degree of freedom problem where many phases including solid-solid, solid-liquid, and solid-gas phases exist, multiscale simulations turn out to be a proper approach since the wide time and length scale that can be covered. Herein, we employed different multiscale modeling methods to tackle various CO2 reduction problems. For electrochemical reduction of CO2, we designed a novel Bi-Cu2S hetero-structured catalyst, which has abundant interfacial sites between Bi and Cu2S, demonstrating the improved catalytic performance of ECO2RR toward formate production. At the same time, it has been found that in non-aqueous solution, the reaction pathway has been switched, where CO is obtained as the final product instead of formate. This effect has been investigated using constant potential calculation method to probe the reaction under reaction condition. For thermo-catalytic reactions, we studied the CO2 hydrogenation on Cesium promoted Au(111) surface using quantum mechanics and kinetic Monte Carlo (KMC) calculations, to gain insights of alkali metal promoting effects under reaction conditions. To expand the scope, the integration of CO2 electroreduction with C-N coupling is a promising strategy for global warming and pollution control, which utilizes the nitrate (NO3-) from wastewater and CO2 to produce high value-added product such as urea. The fundamental investigation of reaction mechanism of C-N coupling has been studied using first principles molecular dynamics.

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Ein der Biologie zugrunde liegender Prozess ist die Fortpflanzung. Einzeller wachsen dazu heran und teilen sich. Grundlage hierfür sind ausreichend Nahrung und Ressourcen, um die eigene Masse und alle Zellbestandteile, insbesondere die DNS, zu verdoppeln. Fehler bei der Wachstumsregulation oder der DNS-Verdopplung können schwerwiegende Folgen haben und stehen beim Menschen im Zusammenhang z.B. mit Krebs. In dieser Arbeit werden mathematische Modelle für die Mechanismen zur Wachstumsregulierung und DNS-Verdopplung in der Bäckerhefe, Saccharomyces cerevisiae, vorgestellt. Modellierung kann entscheident zum Verstehen von komplexen, dynamischen Systemen beitragen. Wir haben ein Modell für Einzellerwachstum entwickelt und leiten das Wachstumsverhalten von Zellkulturen von diesem Modell, mittels einer hierfür programmierten Software, ab. Außerdem haben wir ein Model für die Verdopplung der DNS entwickelt, um Auswirkungen verschiedener Aktivierungsmuster auf die Replikation zu testen. Zusätzlich wurde die Verlängerung entstehender DNS Stränge, Elongation, mit einem detaillierten, stochastischen Modell untersucht. Wir haben unsere Ergebnisse zur DNS-Verdopplung mit einer abschließenden Untersuchung ergänzt, die funktionelle Beziehungen von Genen aufzeigt, welche sich in der Nähe von Aktivierungsstellen der Verdopplung befinden. Folgende Einsichten in die komplexe Koordination von Wachstum und Teilung wurden gewonnen: (i) Wachstumskontrolle ist eine inhärente Eigenschaft von Hefezellpopulationen, welche weder Signale noch Messmechanismen benötigt, (ii) DNS Verdopplung ist robuster in kleinen Chromosomen mit hoher Dichte an Aktivierungsstellen, (iii) Elongation ist weitgehend uniform, weicht aber an genau definierten Stellen signifikant ab und (iv) katabole Gene häufen sich nahe der frühen Aktivierungsstellen und anabole Gene nahe der späten. Unsere Ergebnisse tragen zum Verständniss von zellulären Mechanismen zur Wachstumskontrolle und DNS-Verdopplung bei. / One of the most fundamental processes in biology is reproduction. To achieve this, single cellular organisms grow, proliferate and divide. The prerequisite for this is acquiring sufficient resources to double size and cellular components, most importantly the DNA. Defects in either sufficient gain in size or chromosomal doubling can be severe for the organism and have been related to diseases in humans, such as cancer. Therefore, the cell has developed sophisticated regulatory mechanisms to control the orderly fashion of growth and duplication. We have developed mathematical models to study systemic properties of size control and DNA replication in the premier eukaryotic model organism Saccharomyces cerevisiae. Modeling can help understanding the complex nature of dynamic systems. We provide a single cell model to explore size control. We deduced population behavior from the single cell model through multi-cell simulations using a tailor-made software. Also, we implemented an algorithm that simulates the DNA replication process to test the impact of different replication activation patterns. Additionally, elongation dynamics were assessed with a fine-grained stochastic model for the replication machinery motion. We complemented our analysis of DNA replication by studying the functional association of genes and replication origins. Our systems-level analysis reveals novel insights into the coordination of growth and division, namely that (i) size regulation is an intrinsic property of yeast cell populations and not due to signaling or size sensing, (ii) DNA replication is more robust in small chromosomes with high origin density, (iii) the elongation process is strongly biased at distinct locations in the genome and (iv) catabolic genes are over-represented near early origins and anabolic genes near late origins. Our results contribute to explaining mechanisms of size control and DNA replication.