SOVLENT REACTIVITY AND INTERFACE EVOLUTION AT MODEL ELECTRODES FOR ENERGY APPLICATIONS

The Li-ion rechargeable battery (LIB) is widely used as an energy storage device, but has significant limitations in battery cycle life and safety. During initial charging, decomposition of the ethylene carbonate (EC)-based electrolytes of the LIB leads to the formation of a passivating layer on the anode known as the solid electrolyte interphase (SEI). The formation of an SEI has great impact on the cycle life and safety of LIB, yet mechanistic aspects of SEI formation are not fully understood. In this dissertation, two surface science model systems have been created under ultra-high vacuum (UHV) to probe the very initial stage of SEI formation at the model carbon anode surfaces of LIB. The first model system, Model System I, is an lithium-carbonate electrolyte/graphite C(0001) system. I have developed a temperature programmed desorption/temperature programmed reaction spectroscopy (TPD/TPRS) instrument as part of my dissertation to study Model System I in quantitative detail. The binding strengths and film growth mechanisms of key electrolyte molecules on model carbon anode surfaces with varying extents of lithiation were measured by TPD. TPRS was further used to track the gases evolved from different reduction products in the early-stage SEI formation. The branching ratio of multiple reaction pathways was quantified for the first time and determined to be 70.% organolithium products vs. 30% inorganic lithium product. The obtained branching ratio provides important information on the distribution of lithium salts that form at the very onset of SEI formation. One of the key reduction products formed from EC in early-stage SEI formation is lithium ethylene dicarbonate (LEDC). Despite intensive studies, the LEDC structure in either the bulk or thin-film (SEI) form is unknown. To enable structural study, pure LEDC was synthesized and subject to synchrotron X-ray diffraction measurements (bulk material) and STM measurements (deposited films). To enable studies of LEDC thin films, Model System II, a lithium ethylene dicarbonate (LEDC)-dimethylformamide (DMF)/Ag(111) system was created by a solution microaerosol deposition technique. Produced films were then imaged by ultra-high vacuum scanning tunneling microscopy (UHV-STM). As a control, the dimethylformamide (DMF)-Ag(111) system was first prepared and its complex 2D phase behavior was mapped out as a function of coverage. The evolution of three distinct monolayer phases of DMF was observed with increasing surface pressure — a 2D gas phase, an ordered DMF phase, and an ordered Ag(DMF)2 complex phase. The addition of LEDC to this mixture, seeded the nucleation of the ordered DMF islands at lower surface pressures (DMF coverages), and was interpreted through nucleation theory. A structural model of the nucleation seed was proposed, and the implication of ionic SEI products, such as LEDC, in early-stage SEI formation was discussed

DNA methylation and regulatory elements during chicken germline stem cell differentiation

Funding for Open Access provided by the UMD Libraries' Open Access Publishing Fund.The production of germ cells in vitro would open important new avenues for stem biology and human medicine, but the mechanisms of germ cell differentiation are not well understood. The chicken, as a great model for embryology and development, was used in this study to help us explore its regulatory mechanisms. In this study, we reported a comprehensive genome-wide DNA methylation landscape in chicken germ cells, and transcriptomic dynamics was also presented. By uncovering DNA methylation patterns on individual genes, some genes accurately modulated by DNA methylation were found to be associated with cancers and virus infection, e.g., AKT1 and CTNNB1. Chicken-unique markers were also discovered for identifying male germ cells. Importantly, integrated epigenetic mechanisms were explored during male germ cell differentiation, which provides deep insight into the epigenetic processes associated with male germ cell differentiation and possibly improves treatment options to male infertility in animals and humans

PO-200 Research on the running ability of young male soccer player

Objective Running is the main form of sports in a football match, and running distance is an important factor affecting the outcome. Monitoring the running ability of the athletes in the competition can fully understand the load and physical fitness of the athletes, and provide data reference for the coaches to formulate scientific and systematic training programs. Methods The first 7 warm-up matches of the Guangdong U18 men's football team in 2017 were selected as the research object, and the MT-sports football training monitoring system was used to collect the running data of 10 first players. According to the position on the field, they are divided into the outside fullback, the center back, the center defence midfield, the center attack midfield, the outside attackers and striker. For the purpose of comparison, this study used the running grade standard formulated by Danish scholar Bosber. Results (1)overall movement of athletes The average running distance of the 7 warm-up matches is 7945m, and the jogging distance is 4368m, accounting for 55% of the total running distance; the middle speed running distance is 2574m, accounting for 32.4% of the total running distance; the running distance above the high speed running is 1006m, accounting for 12.6% of the total running distance. The average running speed of the 7 games is 1.30m/s, and the average maximum speed is 7.80m/s.  (2)The running distance of athletes at different speeds on different positions The average total running distance of the center attack midfield is 8759m, and the high-speed running distance is 1226m, which is the highest, and the high-speed running distance accounts for 13.9% of the total running distance. The high speed running distance between the outside fullback and the outside attackers is basically equal, the field is 1215m and 1158m respectively, but the high speed running distance has the highest total distance, reaching 14.7% and 15.3% respectively. The average running distance of the striker is 8134m, and the distance from the high speed running is 1027m, which is only higher than that of the center defence midfield and the center back. The running distance and the high speed distance of the center backs are below the average. Conclusions (1)There is a certain gap between athletes and elite athletes in running ability, but in high-intensity running ability is more prominent. (2)Athletes have more walking distance, which suggests that players should be encouraged to move actively in the future training process. (3) The center attack midfield has prominent running ability and strong speed running ability in the competition. (4) The running situation of the center defence midfield is similar to that of the center attack midfield, but the high-speed running distance of the center defence midfield is only slightly higher than that of the center back, which also reflects the running form of the center defence midfield players. (5) The striker's running ability is general in the competition. The high-intensity running distance is lower than that between the center attack midfield and the outside attackers, even the the Outside fullback, which may lead to tactical failure

Lightweight and Adaptive FDD Massive MIMO CSI Feedback with Deep Equilibrium Learning

In frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems, downlink channel state information (CSI) needs to be sent from users back to the base station (BS), which causes prohibitive feedback overhead. In this paper, we propose a lightweight and adaptive deep learning-based CSI feedback scheme by capitalizing on deep equilibrium models. Different from existing deep learning-based approaches that stack multiple explicit layers, we propose an implicit equilibrium block to mimic the process of an infinite-depth neural network. In particular, the implicit equilibrium block is defined by a fixed-point iteration and the trainable parameters in each iteration are shared, which results in a lightweight model. Furthermore, the number of forward iterations can be adjusted according to the users' computational capability, achieving an online accuracy-efficiency trade-off. Simulation results will show that the proposed method obtains a comparable performance as the existing benchmarks but with much-reduced complexity and permits an accuracy-efficiency trade-off at runtime.Comment: submitted to IEEE for possible publicatio

An Adaptive and Robust Deep Learning Framework for THz Ultra-Massive MIMO Channel Estimation

Terahertz ultra-massive MIMO (THz UM-MIMO) is envisioned as one of the key enablers of 6G wireless networks, for which channel estimation is highly challenging. Traditional analytical estimation methods are no longer effective, as the enlarged array aperture and the small wavelength result in a mixture of far-field and near-field paths, constituting a hybrid-field channel. Deep learning (DL)-based methods, despite the competitive performance, generally lack theoretical guarantees and scale poorly with the size of the array. In this paper, we propose a general DL framework for THz UM-MIMO channel estimation, which leverages existing iterative channel estimators and is with provable guarantees. Each iteration is implemented by a fixed point network (FPN), consisting of a closed-form linear estimator and a DL-based non-linear estimator. The proposed method perfectly matches the THz UM-MIMO channel estimation due to several unique advantages. First, the complexity is low and adaptive. It enjoys provable linear convergence with a low per-iteration cost and monotonically increasing accuracy, which enables an adaptive accuracy-complexity tradeoff. Second, it is robust to practical distribution shifts and can directly generalize to a variety of heavily out-of-distribution scenarios with almost no performance loss, which is suitable for the complicated THz channel conditions. For practical usage, the proposed framework is further extended to wideband THz UM-MIMO systems with beam squint effect. Theoretical analysis and extensive simulation results are provided to illustrate the advantages over the state-of-the-art methods in estimation accuracy, convergence rate, complexity, and robustness.Comment: 15 pages, 11 figures, 5 tables, accepted by IEEE Journal of Selected Topics in Signal Processing (JSTSP

The Prospect of Natural Gas Storage

The first chapter of the actual paper is assigned to shed light on the current situation in the European gas market—the pivotal introduction into pivotal theme. The up-to-date information on the biggest consumers and the biggest exporters aims at giving the general idea about what countries are the main market players regardless of what role do they play. In addition, the first chapter of the work pursues the gas storage necessity proof—why such an expensive process is currently employed by the industry is explained taking the hydrocarbon production conditions of the XXI century into consideration. The actual natural gas market performance and storage justification is followed by the discovery of demand and supply concepts in chapter two. These phenomena represent the characterization of relationship between the gas supplier and the customer. Issues to be addressed are demand nature, types of supply, balancing the demand and supply and the security of supply. Finally, the chapter three gives an insight into how the industry stores the gas. The discussion there goes around the storage opportunities, their positive and negative features and how do they differ. The storage performance criteria are also subjects of the chapter. After the three main questions of the topic have been addressed, the summary of the work concludes it logically by highlighting the most important arguments and facts