碳达峰、碳中和是我国实现绿色可持续发展的重大战略。为实现这一战略目标，迫切需要发展可持续和可再生的绿色能源技术装备。因此，高功率和高能量密度的锂离子电池的开发受到越来越多的关注。以Ga₂O₃为代表的过渡金属氧化物（TMOs）材料因其理论容量高、资源丰富、价格低廉和环境友好具有巨大的应用前景。然而，Ga₂O₃在Li⁺插入/脱出过程中存在巨大的体积膨胀，导致结构稳定性问题，且实际可逆容量远低于理论值，这严重制约了其实际商业应用。针对上述不足，本论文综合利用纳米化和复合化手段提高氧化镓的倍率性能和长期循环稳定性。

通过探索不同水热温度和保温时间工艺对Ga₂O₃相结构及微观形貌的影响，摸索出

200 ℃，20 h保温条件下可获得类石榴籽结构的Ga₂O₃纳米球。在0.1 A g^-1的电流密度下，该材料初始放电容量为734.9 mAh g^-1，经过100圈循环后，其放电容量为207.8 mAh g^-1。同时基于神经网络理论，引入多层感知器（MLP）模型来预测Ga₂O₃循环性能，表明神经网络理论是一种有效的预测容量退化轨迹的方法。纳米结构也能有效缩短锂离子扩散路径，增加电极表面活性位点以及与电解液之间的比表面积。

在Ga₂O₃纳米球的工艺机理基础上，引入生物质碳合成制备了具有碳壳包覆类石榴状结构的Ga₂O₃@C复合材料。在0.1 A g^-1的电流密度下100次循环后，其放电容量高达553.49 mAh g^-1。在5 A g^-1的电流密度下，其可逆容量可达238.4 mAh g^-1。当用作锂离子电池（LIBs）的负极时，Ga₂O₃@C在电流密度为100 mA g-1时，表现出682 mAh g^-1的初始可逆容量，当电流密度提高到5 A g^-1时仍能保持238.4 mAh g^-1高可逆容量。类石榴状结构的碳涂层增强了复合结构的稳定性，提高了电导率，有效的改善了氧化镓库伦效率与反应动力学差的问题。

为了进一步提升氧化镓的循环稳定性，利用水热-冷干法构筑了多维态Ga₂O₃@rGO复合材料。在0.1 A g^-1电流密度下，Ga₂O₃@rGO的首次放电容量为1201.5 mAh g^-1。在0.5 A g^-1电流密度下初始放电容量为1510.2 mAh g^-1，500个循环周期后仍能保持490.5 mAh g^-1的放电容量。同时采用深度学习中长短期记忆网络（LSTM）模型对预测Ga₂O₃容量模型进一步改进，对比MLP网络具有更强的鲁棒性与确定性。石墨烯片层的高比表面积，可形成电解液存储孔隙，保证电极材料在电解液中充分浸润，促进电荷和离子的传输。三维的多孔结构可以容纳Ga₂O₃的体积变化并保持结构完整性，2D-3D rGO与Ga₂O₃之间产生的协同效应可以改善电荷传输和离子的扩散性能，提高电极的反应动力学和可逆性。

Carbon peaking and carbon neutrality are major strategies for China to realize green and sustainable development. In order to realize this strategic goal, there is an urgent need to develop sustainable and renewable green energy technology and equipment. Therefore, the development of high-power and high-energy-density lithium-ion batteries has received increasing attention. Transition metal oxides (TMOs) materials represented by Ga₂O₃ have great application prospects due to their high theoretical capacity, abundant resources, low price and environmental friendliness. However, Ga₂O₃ suffers from huge volume expansion during Li⁺ insertion/degassing, leading to structural stability problems, and the actual reversible capacity is much lower than the theoretical value, which seriously restricts its practical commercial application. To address these shortcomings, this thesis integrates the use of nanosizing and compositing to improve the multiplicity performance and long-term cycling stability of Ga₂O₃.

By exploring the effects of different hydrothermal temperatures and holding time processes on the Ga₂O₃ phase structure and microscopic morphology, it was figured out that Ga₂O₃ nanorods with pomegranate seed-like structure can be obtained under 200 °C and 20 h holding condition. The initial discharge capacity of the material was 734.9 mAh g^-1 at a current density of 0.1 A g^-1, and after 100 cycles, its discharge capacity was 207.8 mAh g^-1. Meanwhile, based on the neural network theory, a multilayer perceptron (MLP) model was introduced to predict the cycling performance of Ga₂O₃, which showed that the neural network theory is an effective method to predict the capacity degradation trajectory. The nanostructures can also effectively shorten the lithium ion diffusion path and increase the active sites on the electrode surface as well as the specific surface area with the electrolyte.

Ga₂O₃@C composites with carbon shell-coated pomegranate-like structure were prepared by introducing biomass carbon synthesis based on the process mechanism of Ga₂O₃ nanorods. The discharge capacity was as high as 553.49 mAh g^-1 after 100 cycles at a current density of 0.1 A g^-1, and the reversible capacity was as high as 238.4 mAh g^-1 at a current density of 5 A g^-1. When used as an anode in lithium-ion batteries (LIBs), Ga₂O₃@C exhibits an initial reversible capacity of 682 mAh g^-1 at a current density of 100 mA g^-1 and maintains a high reversible capacity of 238.4 mAh g^-1 when the current density is increased to 5 A g^-1. The carbon-coating with pomegranate-like structure enhanced the stability of the composite structure, increased the electrical conductivity, and improved the poor Gallium oxide Coulombic efficiency and reaction kinetics effectively.

In order to further enhance the cycling stability of gallium oxide, multidimensional state Ga₂O₃@rGO composites were constructed using hydrothermal-cold-drying method. The initial discharge capacity of Ga₂O₃@rGO is 1201.5 mAh g^-1 at a current density of 0.1 A g^-1. The initial discharge capacity was 1510.2 mAh g^-1 at a current density of 0.5 A g^-1, and the discharge capacity of 490.5 mAh g^-1 was still maintained after 500 cycle cycles. Meanwhile, the predicted Ga₂O₃ capacity model is further improved by using the deep learning long short-term memory network (LSTM) model, which has stronger robustness and determinism compared to the MLP network. The high specific surface area of graphene flakes can form electrolyte storage pores, which ensures that the electrode materials are fully infiltrated in the electrolyte and facilitates charge and ion transport. The three-dimensional porous structure can accommodate the volume change of Ga₂O₃ and maintain the structural integrity, and the synergistic effect generated between 2D-3D rGO and Ga₂O₃ can improve the charge transport and ion diffusion performance, and enhance the reaction kinetics and reversibility of the electrode.

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