Mechanistic studies of first-row transition metal catalyzed homogeneous CO2 reduction via H2 using density functional theory

CO2 reduction has been quite a hot research topic, and its catalytic reduction mechanisms via H2 using homogeneous transition metal based catalysts, especially first-row transition metal (Cu and Mn) complex catalysts, haven’t been thoroughly studied yet. In this thesis, mechanistic studies using density functional theory (DFT) have been conducted to understand the reaction mechanisms and possible factors (e.g. basicity of added reagent) at the molecular level, which will fill the research gap in this area and provide insights for rational catalyst design. To sum up, the thesis contains two chapters to first introduce the research background and methodology (Chapter 1 and 2), two main chapters to present the DFT studies of Cu and Mn based systems (Chapter 3 and 4), and one extra chapter to demonstrate how the DFT studied have been expanded to other homogeneous catalytic systems (Chapter 5)

Synthesis of an isomer of lycoplanine a via cascade cyclization to construct the spiro-N,O-acetal moiety

An isomer of lycoplanine A with a 6/10/5/5 tetracyclic skeleton was synthesized using D–A reaction and cascasde reaction to respectively construct the [9.2.2] pentadecane skeleton and the challenging 1-oxa-6-azaspiro[4.4]nonane spirocenter. Morever, detailed DFT calculations were conducted to explain the selectivity in the D–A reaction. This study may provide sufficient experience for the total synthesis of lycoplanine A and other alkaloids with similar spiro-N,O-acetal cores

Mechanistic studies of first-row transition metal catalyzed homogeneous CO2 reduction via H2 using density functional theory

CO2 reduction has been quite a hot research topic, and its catalytic reduction mechanisms via H2 using homogeneous transition metal based catalysts, especially first-row transition metal (Cu and Mn) complex catalysts, haven’t been thoroughly studied yet. In this thesis, mechanistic studies using density functional theory (DFT) have been conducted to understand the reaction mechanisms and possible factors (e.g. basicity of added reagent) at the molecular level, which will fill the research gap in this area and provide insights for rational catalyst design. To sum up, the thesis contains two chapters to first introduce the research background and methodology (Chapter 1 and 2), two main chapters to present the DFT studies of Cu and Mn based systems (Chapter 3 and 4), and one extra chapter to demonstrate how the DFT studied have been expanded to other homogeneous catalytic systems (Chapter 5)

High ion conductive Sb2O5-doped beta-Li3PS4 with excellent stability against Li for all-solid-state lithium batteries

The combination of high conductivity and good stability against Li is not easy to achieve for solid electrolytes, hindering the development of high energy solid-state batteries. In this study, doped electrolytes of Li3P1-xSbxS4-2.5xO2.5x are successfully prepared via the high energy ball milling and subsequent heat treatment. Plenty of techniques like XRD, Raman, SEM, EDS and TEM are utilized to characterize the crystal structures, particle sizes, and morphologies of the glass-ceramic electrolytes. Among them, the Li3P0.98Sb0.02S3.95O0.05 (x = 0.02) exhibits the highest ionic conductivity (similar to 1.08 mS cm(-1)) at room temperature with an excellent stability against lithium. In addition, all-solid-state lithium batteries are assembled with LiCoO2 as cathode, Li10GeP2S12/Li3P0.98Sb0.02S3.95O0.05 as the bi-layer electrolyte, and lithium as anode. The constructed solid-state batteries delivers a high initial discharge capacity of 133 mAh g(-1) at 0.1C in the range of 3.0-4.3 V vs. Li/Li+ at room temperature, and shows a capacity retention of 78.6% after 50 cycles. Most importantly, the all-solid-state lithium batteries with the Li10GeP2S12/Li3P0.98Sb0.02S3.95O0.05 electrolyte can be workable even at - 10 degrees C. This study provides a promising electrolyte with the improved conductivity and stability against Li for the application of all-solid-state lithium batteries

High ion conductive Sb2O5-doped beta-Li3PS4 with excellent stability against Li for all-solid-state lithium batteries

The combination of high conductivity and good stability against Li is not easy to achieve for solid electrolytes, hindering the development of high energy solid-state batteries. In this study, doped electrolytes of Li3P1-xSbxS4-2.5xO2.5x are successfully prepared via the high energy ball milling and subsequent heat treatment. Plenty of techniques like XRD, Raman, SEM, EDS and TEM are utilized to characterize the crystal structures, particle sizes, and morphologies of the glass-ceramic electrolytes. Among them, the Li3P0.98Sb0.02S3.95O0.05 (x = 0.02) exhibits the highest ionic conductivity (similar to 1.08 mS cm(-1)) at room temperature with an excellent stability against lithium. In addition, all-solid-state lithium batteries are assembled with LiCoO2 as cathode, Li10GeP2S12/Li3P0.98Sb0.02S3.95O0.05 as the bi-layer electrolyte, and lithium as anode. The constructed solid-state batteries delivers a high initial discharge capacity of 133 mAh g(-1) at 0.1C in the range of 3.0-4.3 V vs. Li/Li+ at room temperature, and shows a capacity retention of 78.6% after 50 cycles. Most importantly, the all-solid-state lithium batteries with the Li10GeP2S12/Li3P0.98Sb0.02S3.95O0.05 electrolyte can be workable even at - 10 degrees C. This study provides a promising electrolyte with the improved conductivity and stability against Li for the application of all-solid-state lithium batteries

An edge streaming data processing framework for autonomous driving

In recent years, with the rapid development of sensing technology and the Internet of Things (IoT), sensors play increasingly important roles in traffic control, medical monitoring, industrial production and etc. They generated high volume of data in a streaming way that often need to be processed in real time. Therefore, streaming data computing technology plays an indispensable role in the real-time processing of sensor data in high throughput but low latency. However, there are two problems in deploying streaming data process ability in cloud computing data centre. Firstly, massive sensor nodes simultaneously upload data to the remote cloud computing data centre, which requires a large number of bandwidth resources supports. The existing network infrastructure cannot provide enough bandwidth at a reasonable price. Secondly, due to the geographical distribution characteristics of the cloud computing data centre, there will inevitably be large transmission delay during the process of data transmission. Such end-to-end delay is intolerable to mobile applications especially for those latency sensitive tasks. In view of the above problems, this paper proposes an autonomous driving oriented edge streaming data processing framework, which migrates the computing and storage capability from the remote cloud data centre to the edge data centre. It focuses on the change of vehicle flow in a specific geographical area, and uses the computing power sunk to edge node to process the massive streaming data generated by autonomous vehicles nearby. The proposed framework is implemented on top of Spark Streaming, which builds up a gray model based traffic flow monitor, a traffic prediction orientated prediction layer and a fuzzy control based Batch Interval dynamic adjustment layer for Spark Streaming. It could forecast the variation of sensors data arrive rate, make streaming Batch Interval adjustment in advance and implement real-time streaming process by edge. Therefore, it can realise the monitor and prediction of the data flow changes of the autonomous driving vehicle sensor data in geographical coverage of edge computing node area, meanwhile minimise the end-to-end latency but satisfy the application throughput requirements. The experiments show that it can predict short-term traffic with no more than 4% relative error in a whole day. By making batch consuming rate close to data generating rate, it can maintain system stability well even when arrival data rate changes rapidly. The Batch Interval can be converged to a suitable value in two minutes when data arrival rate is doubled. Compared with vanilla version Spark Streaming, where there has serious task accumulation and introduces large delay, it can reduce 35% latency by squeezing Batch Interval when data arrival rate is low; it also can significantly improve system throughput by only at most 25% Batch Interval increase when data arrival rate is high

Oxidation decomposition mechanism of fluoroethylene carbonate-based electrolytes for high-voltage lithium ion batteries: a DFT calculation and experimental study

The oxidative decomposition mechanism of fluoroethylene carbonate (FEC) used in high-voltage batteries is investigated by using density functional theory (DFT). Radical cation FEC•+ is formed from FEC by transferring one electron to electrode and the most likely decomposition products are CO2 and 2-fluoroacetaldehyde radical cation. Other possible products are CO, formaldehyde and formyl fluoride radical cations. These radical cations are surrounded by much FEC solvent and their radical center may attack the carbonyl carbon of FEC to form aldehyde and oligomers of alkyl carbonates, which is similar with the oxidative decomposition of EC. Then, our experimental result reveals that FEC-based electrolyte has rather high anodic stability. It can form a robust SEI film on the positive electrode surface, which can inhibit unwanted electrolyte solvent and LiPF6 salts decomposition, alleviate Mn/Ni dissolution and therefore, improve the coulombic efficiency and the cycling stability of high voltage LiNi0.5Mn1.5O4 positive electrodes. This work displays that FEC-based electrolyte systems have considerable potential replacement of the EC-based electrolyte for the applications in 5 V Li-ion batteries

Toward a General Glycosylation Strategy: Exploring the Dual Functions of Acyl Group Direction in Various Nucleophilic Environments

A universal glycosylation strategy could significantly simplify glycoside synthesis. One approach to achieving this goal is through acyl group stereodirecting participation for the corresponding 1,2-, 1,3-, 1,4-, or 1,6-trans glycosylation; how-ever, this approach had been challenging for glycosidic bonds that require distal equatorial-acyl group direction. We have developed an approach in weakly nucleophilic environments for selective 1,4-trans glycosylation directed by the equato-rial-4-O-acyl group. Here, we explored this condition in other distal acyl groups and found, besides stereodirecting partic-ipation, acyl groups also mediated hydrogen bonding between acyl groups and alcohols. The latter showed a diverse ef-fect and classified the acyl group direction into axial and equatorial categories. Corresponding glycosylation conditions were distinguished as guidance for acyl group direction from either category. Hence, the acyl group direction may serve as a general glycosylation strategy