氨（NH₃）是众多工业化学品的原料，同时也是未来发展低碳甚至无碳社会的潜在能源载体。目前，世界上大部分工业NH₃都来自于哈勃工艺（H-B），但是该工艺需要高温、高压和高能耗，使得H-B工艺变得不可持续。电催化氮还原（eNRR）是一种无碳绿色技术，利用电化学电势提供热力学驱动力，以H₂O和空气中的N₂为原料生产NH₃。但是由于N₂分子的惰性和竞争析氢反应（HER）等问题制约着eNRR的发展，因此开发高效的电催化剂是一个重要的研究方向。氮化硼纳米片（h-BNNs）因其一个空轨道可以接受外来孤对电子，同时B原子显示出路易斯酸特性，在eNRR中表现出一定的电催化性能，但是其法拉第效率（FE）较低。应变工程是提高催化剂活性的有效策略。基于此，本文围绕h-BNNs的应变效应开展研究，将h-BNNs分别与碳基材料碳纳米管（CNTs）或氧化石墨烯（GO）复合，制备了h-BNNs/CNTs和h-BNNs/GO复合催化剂；重点对h-BNNs的应变效应进行探究，并研究了其在eNRR中的性能。使用密度泛函理论（DFT）探究了h-BNNs/CNTs的催化机理。本论文的主要研究内容如下：

（1）使用液相超声剥离法将六方氮化硼剥离得到h-BNNs纳米片，在超声作用下在h-BNNs中引入CNTs，制备了复合催化剂h-BNNs/CNTs，并对其进行了物理化学特性表征。X射线光电子能谱（XPS）和拉曼（Raman）光谱等表明h-BNNs中应变的存在，且应变的产生伴随着新化学键的生成（C-B、C-N）。利用Raman对h-BNNs的应变进行估算，同时考察了超声时间（1-4 h）对h-BNNs应变大小的影响，即超声3 h时，复合材料的应变力达到最大，为0.18％。将制备的复合催化剂h-BNNs/CNTs应用于eNRR中。考察了介质的酸碱性、施加电位和复合催化剂含量配比对电催化性能的影响。在中性介质（0.1 M Na₂SO₄）中，施加-0.691 V（vs RHE）的电压，66.8％h-BNNs/CNTs复合催化剂得到最高的产NH₃速率为36.5 μg h^-1 mg_cat.^-1，同时FE达到63.9％，和单独的h-BNNs（4.7％）相比，电催化活性大大提高。DFT中h-BNNs/CNTs的优化模型证实了应变效应的存在。通过DFT对h-BNNs和h-BNNs/CNTs表面eNRR和HER的反应势垒进行了计算，*N*N是eNRR中的决定步骤（RDS），相比于h-BNNs中RDS（2.34 eV）的能垒降低了0.36 eV。h-BNNs/CNTs复合催化剂在HER中RDS的显著升高（h-BNNs/CNTs的能垒为4.66 eV），表明该复合催化剂极大的抑制了HER活性，增加了eNRR的选择性。

（2）通过超声将h-BNNs与GO复合，得到复合催化剂h-BNNs/GO，对其进行了物理化学特性表征。Raman表明h-BNNs/GO中存在应变效应，估算的应变大小为0.06％，并比较了h-BNNs与GO和CNTs之间产生应变的不同。将h-BNNs/GO应用于eNRR中，对其催化性能和稳定性进行测试。考察了介质的酸碱性、电位和复合催化剂含量配比对催化性能的影响。在中性介质0.1 M Na₂SO₄电解液中，施加-0.691 V（vs RHE）的电压，66.8％h-BNNs/GO催化剂得到最高的产NH₃速率为25.0 μg h^-1 mg_cat.^-1，同时FE达到52.6％，且具有良好的稳定性。h-BNNs/GO产生的应变效应改变了h-BNNs的电子结构，改善了h-BNNs/GO的导电性，加快了eNRR中电子的转移，提高了h-BNNs/GO的催化活性。

本研究为eNRR开发了新型高效复合催化剂h-BNNs/CNTs和h-BNNs/GO，应变效应为提高复合材料的电催化活性提供了新策略，为eNRR研究提供了参考。

Ammonia (NH₃) is a feedstock for many industrial chemicals and a potential energy carrier for the development of a low-carbon or even carbon-free society in the future. Currently, the Haber-Bosch process (H-B) has become unsustainable, due to the high temperature, high pressure and high energy consumption required by the process, most of the world's industrial NH₃ comes from the H-B process. Electrocatalytic nitrogen reduction (eNRR) uses the electrochemical potential to provide the thermodynamic driving force, the production of NH₃ from H₂O and N₂ in the air, a carbon-free green technology. The development of high-efficiency electrocatalyst is an important research direction, due to the inertization of N₂ molecules and competitive hydrogen evolution reaction (HER), the development of eNRR is restricted. Boron nitride nanosheets (h-BNNs) exhibit some electrocatalytic properties in eNRR, because one of its empty orbitals can accept foreign lone pairs of electrons, while B atoms exhibit Lewis acid properties, their Faraday efficiency (FE) is low. It is worth noting that strain engineering is an effective strategy to improve catalyst activity. Based on this, the strain effect of h-BNNs was studied in this paper, and h-BNNs/CNTs and h-BNNs/GO composite catalysts were prepared by combining h-BNNs with carbon-based carbon nanotubes (CNTs) or graphene oxide (GO) respectively; the strain effect of h-BNNs was investigated and its performance in eNRR was studied. Density functional theory (DFT) was used to investigate the catalytic mechanism of h-BNNs/CNTs. The main research contents of this paper are as follows:

(1) The h-BNNs nanosheets were obtained from hexagonal boron nitride by liquid phase sonication exfoliation. CNTs were introduced into h-BNNs under sonication action to prepare composite catalyst h-BNNs/CNTs, and their physicochemical properties were characterized. X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy show the existence of strain, and the generation of strain is accompanied by the formation of new chemical bonds (C-B, C-N). Raman is used to estimate the strain of h-BNNs, and the influence of sonication time (1-4 h) on the strain size of h-BNNs is investigated. In other words, the strain strength of the composite reaches the maximum at 3 h of sonication, which is 0.18%. The prepared composite catalyst h-BNNs/CNTs was applied to eNRR. The effects of the acidity and alkalinity of the medium, the applied potential and the content ratio of the composite catalyst on the electrocatalytic efficiency were investigated. The h-BNNs/CNTs catalysts showed an NH₃ yield rate of 36.5 μg h^-1 mg_cat.^-1 and an enhanced FE of 63.9% at -0.691 V (vs RHE) in a N₂-saturated 0.1 M Na₂SO₄ electrolyte. Compared with h-BNNs alone (4.7%), the electrocatalytic activity was greatly improved. The optimal model of h-BNNs/CNTs in DFT confirmed the existence of strain effects. The reaction barriers in eNRR and HER were calculated by DFT, and *N*N is the decision step (RDS) in NRR, which reduces the energy barrier by 0.36 eV compared to RDS (2.34 eV) in h-BNNs. The RDS of h-BNNs/CNTs composite catalyst increased significantly in HER (the energy barrier of h-BNNs/CNTs was 4.66 eV), which greatly inhibited the activity of HER and increased the selectivity of eNRR.

(2) The composite catalyst h-BNNs/GO was obtained by sonication combination of h-BNNs and GO, and its physicochemical properties were characterized. Raman shows the existence of strain effect in h-BNNs/GO, and the estimated strain size is 0.06%. The strain effects of h-BNNs on layered nanomaterials (GO) and tubular nanomaterials (CNTs) were compared under the same preparation method. The h-BNNs/GO was applied to eNRR to test its catalytic performance and stability. The effects of acidity and alkalinity of the medium, potential and content ratio of the composite catalyst on the catalytic performance were investigated. The h-BNNs/GO catalysts showed an NH₃ yield rate of 25.0 μg h^-1 mg_cat.^-1 and an enhanced FE of 52.6% at -0.691 V (vs RHE) in a N₂-saturated 0.1 M Na₂SO₄ electrolyte. The long time current curve and cycle test show that the catalyst has good stability. The existence of strain effect in h-BNNs/GO regulates the electronic structure of the catalyst, greatly improves the conductivity of h-BNNs/GO, improves the electron transfer in eNRR, and improves the catalytic activity of h-BNNs/GO.

In this study, new and efficient composite catalysts h-BNNs/CNTs and h-BNNs/GO were developed for eNRR, and strain effect regulation provided a new strategy to improve the electrocatalytic activity of catalysts, which provided a reference for the study of eNRR.

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