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高温高压下金刚石生长的声发射实时动态检测与长大机制研究
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摘要
由于高温高压合成金刚石是在密闭的腔体中进行,所以直接获得金刚石单晶生长过程的实验数据十分困难。至今,对金刚石的生长机理研究主要基于高温高压合成后的金刚石单晶在常压、室温下进行静态观测和表征的实验结果与理论分析,或在特定的实验条件下进行高温高压金刚石合成过程的模拟研究与分析,而没有直接采集到高温高压状态下金刚石生长的真实信息。因此,找到一种能够实时反映金刚石在高温高压状态下生长信息的检测方法,对于弄清楚石墨是如何变成金刚石的,金刚石又是如何长大的,以及触媒金属或其合金如何起催化作用则具有重要的科学意义和应用价值。
     本文选用铁基触媒,以石墨为碳源,进行了高温高压条件下金刚石单晶的合成实验,同时利用声发射技术结合金刚石合成设备,建立了一套高温高压下金刚石单晶生长的实时动态检测系统,并利用该系统动态采集到金刚石生长过程中的声发射信号。利用金相显微镜、扫描电镜(SEM)、透射电镜(TEM)、X射线衍射仪(XRD)、场发射扫描电镜(FESEM)等现代分析和表征手段对常温常压下金刚石单晶及相关物相的形貌和微观结构进行了检测和分析;利用参数分析、小波分析等方法对金刚石生长过程中检测到的声发射信号进行了处理和分析,结合静态检测和表征结果,研究了声发射信号的变化规律及其与金刚石生长过程的相关性和一致性,进而综合分析金刚石单晶的长大机制。
     通过不同合成阶段的合成压块断面观察、金刚石单晶粒度分析、产量分析以及金属包膜界面观察,可以看出,随着合成时间的延长,金刚石单晶明显长大,并且金刚石在合成阶段的前期长大速率较快,在合成阶段的后期长大速率变慢。对金刚石单晶表面及其所对应铁基金属触媒包膜界面显微形貌的SEM和FESEM分析表明,对应金刚石(100)晶面的包膜界面上分布有大量棱锥状突起;对应金刚石(111)晶面的包膜界面上分布着片层状台阶。金刚石晶面间不同的生长方式导致与金刚石表面相对应的包膜界面具有不同的界面形貌。XRD和TEM表征分析则表明,金刚石形核生长所需的碳原子来源于金属碳化物的分解,而γ-(Fe,Ni)则在金刚石的生长过程中起催化作用。
     通过波导的引入和设计以及传感器的定位安装,将声发射实验中信号的采集区域限定在合成压块内部,使得有效的声发射信号能够通过波导传输到声发射仪器,并且保证了采集到的声发射信号是由高温高压状态下合成腔体内部的变化引起的。在进行声发射信号采集前,通过八个传感器反对称分布的空间定位以及对声发射仪检测参数的合理设置滤除绝大部分干扰噪声,确保了采集到的声发射信号的真实性、合理性和可靠性。同时,根据声发射信号的特性,利用参数分析和小波分析对检测到的声发射信号进行处理,获取与金刚石单晶生长有关的声发射源的信号特征。通过上述方法,建立了一套新的、完整的高温高压状态下金刚石生长的实时动态检测系统,为金刚石单晶的长大机制研究提供了有效、可靠的实验方法。
     基于小波变换对采集到的声发射信号进行了降噪处理,分析了小波基的确定、降噪方法的选择等一系列关键问题,为利用该方法对金刚石单晶生长声发射信号的分析处理做了实验准备。分析结果表明:经过降噪处理后的声发射信号,不但过滤了大部分噪声,而且没有破坏声发射信号的特性,能更准确地表征金刚石单晶生长所产生的声发射信号源的特征,为利用声发射技术研究金刚石的长大机制奠定了重要的基础。
     对高温高压条件下有、无金刚石生长时的声发射信号进行了对比参数分析。结果表明,金刚石单晶生长时会相应产生高幅度的声发射信号,并出现上升时间较长的特点;振铃计数率高的事件明显增多;声发射振铃计数、能量计数和持续时间的累计值和平均值都有所提高。没有金刚石单晶生长时的声发射信号频率主要集中在低于80kHz的低频段;当有金刚石单晶生长时,则在大于80kHz的频率段出现很多新的频率峰值。根据对比分析可知,这些新的频率峰是由金刚石单晶的生长引起的。
     对高温高压条件下金刚石单晶生长过程中声发射信号的参数分析表明,采集的声发射信号特征参数,如:振铃计数、能量计数、幅度和上升时间等随合成时间的延长呈现先增加、后降低的变化规律。结合合成压块的断口形貌观察及金刚石单晶生长参数测量结果表明,这些声发射信号特征参数的变化规律与金刚石单晶的生长过程一致,金刚石单晶在生长初期的长大速率随着合成时间的延长逐步增大,相应的声发射源活动性增加,长大速率达到最大值后将会逐步减小,声发射源的活动性也逐渐变弱。
     应用以小波包分析为基础的小波包频带能量算法,比较了不同频带信号能量的大小和峰值随金刚石单晶生长过程的变化情况,反映出了不同的声发射源模式激发的声发射信号在时间轴上的动态变化特性,这进一步说明声发射信号的频率可以作为区分金刚石生长过程中不同声发射源模式的有效手段。
It is very difficult to obtain directly the experimental data of diamond growth process, because the diamond crystals are synthesized in the airtight cavity under HPHT. Until now, the study on the growth mechanism of diamond is based on the static observation and characterization of diamond and related phases at atmospheric pressure and room temperature, or the process simulation and analysis of diamond synthesis under HPHT in the specific experimental conditions. And the real information about diamond growth under HPHT is not directly collected. Thus, finding a detection method to reflect real-time dynamic information about diamond growth under high pressure and high temperature is of great scientific significance and application value to figure out that how graphite become diamond, how the diamond grow up, and how the iron-based catalyst work.
     In the paper, the diamond was synthesized under HPHT using graphite as the carbon source and iron-based metallic catalyst produced by powder metallurgy. And the real-time dynamic detection system of diamond growth under high pressure and high temperature was established using acoustic emission instrument and diamond synthesis equipment, which was used to collect dynamically acoustic emission signals of diamond growth process. The morphology and microstructure of diamond and related phases were studied at atmospheric pressure and room temperature by means of metallographic microscope, scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM). Meanwhile, the acoustic emission signals detected in the diamond growth process were processed and analyzed using parametric analysis, wavelet analysis and other methods. With the results of the static detection and characterization, the relevance and consistency of the variation of acoustic emission signals of diamond growth process were studied, and comprehensive analysis of the growth mechanism of diamond was carried out.
     According to the analysis on the fracture morphologies of the synthesis block, granularity distribution of diamond grains, production quantities of the diamonds and morphologies of the inside surface of iron-based metallic film in the different synthetic time, the growth rate of diamond growth process is faster in the earlier stage and slower in the later stage. SEM and FESEM study indicates that the nanoscale pyramid cone shapes exist on the metallic film interface (100), while serrate steps are found on the metallic film interface (111). The diamond growth units have different accumulation mode on different diamond interfaces, which leads to different morphologies of diamond corresponding metallic film interfaces. According to XRD and TEM analysis, the carbon source for diamond growth with iron-based metallic catalyst under HPHT comes from the carbon atomics separated from Fe3C, and y-(Fe,Ni) plays a role of catalysis phase in the process.
     Through introduction and design of the waveguides and installation of the sensors, the acquisition area of acoustic emission signals is limited within the synthesis block, which makes the acoustic emission signals effectively transmitted through the waveguide to the acoustic emission instrument. And it is sure that the acoustic emission signals collected are caused by the change in the synthesis cavity under high pressure and high temperature. The space location of eight sensors by the method of antisymmetric distribution and reasonable settings of acoustic emission testing parameters could remove the most of the interference noise, and ensure the acoustic emission signals authenticity, rationality and reliability. Meanwhile, according to the characteristics of acoustic emission signals, the detected acoustic emission signals are processed using parameters analysis and wavelet analysis. Through these methods, a new real-time detection system of diamond growth under HPHT is established, which could provide an effective experimental method for growth mechanism research of diamond.
     Based on wavelet transform, the de-noising treatment of acoustic emission signals collected is carried out, in which the selection of wavelet bases, the choice of de-noising methods and so on are analyzed. De-noising results show that the acoustic emission signals after de-noising treatment filter out most noise, and there is no damage to the characteristics of acoustic emission signals, which could more accurately characterize the characteristics of acoustic emission signals of diamond crystals growth.
     According to the contrastive analysis on acoustic emission signals with or without diamond growth, it shows that the high amplitude signals are produced correspondingly with diamond crystal growth, and the cumulative value and the average value of rise time, event count rate, ring-down counts, energy counts and duration time of recorded acoustic emission signals with diamond growth have increased. When there is no diamond crystals growth, the acoustic emission signals are mainly in the low frequency band below 80 kHz; When diamond crystals grow, there are many new frequency peaks in the frequency range that is higher than 80 kHz. Comparative analysis shows that these new frequency peaks are caused from the growth process of diamond crystals.
     By analyzing parameters of acoustic emission signals from diamond growth process, it shows that the characteristic parameters of acoustic emission signals, such as energy counts, amplitude and rise time increase firstly and then decrease with the synthesis time. With observation of the fracture morphologies of the synthesis block and parameter analysis results, it shows that the variation of the characteristic parameters of acoustic emission signals fit in with the diamond crystal growth process. In the earlier stage, diamond growth rate gradually increases with the extension of synthesis time, and the acoustic emission source activity correspondingly increases. When the growth rate decreases after reaching the maximum rate, the activity of acoustic emission source gradually becomes weak.
     According to the analysis on acoustic emission signals from diamond crystals growth based on wavelet packet energy algorithm, the value of the signal energy and peak in different frequency bands are compared along with the diamond growth process. And it has reflected the dynamic changes in the time domain of the acoustic emission signals stimulated by the different acoustic emission sources. It also shows that the frequency of acoustic emission signals could be used as the effective means to distinguish the different acoustic emission sources in the diamond growth process.
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