使用能量分辨率收集EDS的数据

X-ray detectors for energy dispersive spectroscopy (EDS) have technologically improved since the introduction of the first Silicon Drift-based EDS detector (SDD) 15 years ago.

The first such EDS systems had 5mm²active area with 160-200eV energy resolution and an optimum collection rate reaching 100,000 input counts/second.

今天的商业上可获得的SDD的EDS探测器具有高达150mm的有源区²per device and feature multiple detectors working in tandem with collection rates of 1 million input counts/second and spectral energy resolution down to 121eV.

The detector performance is oversimplified because energy resolution as measured and reported becomes a key metric today. A more detailed evaluation and a much broader specification are crucial in actual end-user applications. These issues are addressed in this article.

能量分辨率和整个能谱

Since energy resolution has reached its theoretical limit, further improvements in energy resolution become important. Other factors or method may influence EDS data collection.

An EDS spectrum of a BN sample with surface contaminated by C and O is depicted in Figure 1, and Figure 2 shows an EDS spectrum of Be sample with surface contaminated by C and O.

Figure 1.使用具有超薄，聚合物窗口（蓝色）和模拟频谱的完全抽空的EDS X射线检测器获得的C和O表面污染的BN的谱。如果探测器模块用惰性N背部充填₂(red).

Figure 2.EDS spectrum of Be with C and O surface contamination as obtained with a fully evacuated EDS X-ray detector employing an ultra-thin, polymer window (blue) and the simulated spectrum if the detector module were back-filled with inert N₂(red).

在这些光谱中可以观察到非常干净且分离良好的BE或B峰和N，C和O峰。对于在MnKα测量的这些数据收集，EDS检测器使用122EV的能量分辨率。在两个光谱中，C峰的能量分辨率为39EV。

Only half of the improvement needed to generate the spectra described above is represented by the sophisticated SDD. Attenuation of low-energy X-rays is a major challenge in low energy X-ray analysis owing to the fact that these X-rays are attenuated by various sources:

• Low energy X-rays are absorbed by the window employed for isolating the SDD crystal from the microscope vacuum (or ambient while vented). Conventional Be windows would not transmit X-rays lower than the Na Ka line (~1keV) and must therefore be eliminated as an option.
• Low energy X-rays are absorbed by the inert gas present between the window and the SDD crystal. Inert N₂gas is used in most designs to back-fill the volume between the light-element window and the SDD crystal. It is possible to simulate the deterioration of low-energy sensitivity by inert N₂gas through the application of the X-ray absorption curves for N₂gas across the distance that must be travelled by the X-rays the N₂气体。Figures 1 and 2 show these simulated spectra. The variation in low energy sensitivity is stark when compared against a detector whose volume is fully evacuated rather than back-filled with N₂。
• Low energy X-rays are absorbed by the sample itself when they are produced deeper than the average escape depth for that energy. For instance, the escape depth of Li is only few tens of nm so that it is extremely difficult to detect Li with any EDS detector even in the presence of trace amounts of surface contamination.

因此，优选使用超薄，聚合物窗口（<300nm）或窗口的消除以有效地实现低能量检测。

In the case of detection below 300eV, the volume between the SDD module and the thin window should not be backfilled with N₂气体。理想选择是完全无窗口检测器或完全抽空的探测器模块。

Analysts must rely predominantly on analysis of the top 10-50nm of the sample due to the absorption of low energy X-rays by the sample itself. This implies that the sample surface has to be carefully prepared and preserved and the SEM needs to be operated at a shallow penetration depth (<5kV) to prevent dilution of the low energy analysis of the surface region with the high-energy X-rays produced from the overall bulk of the sample.

Energy Resolution and Count Rate

虽然121EV的能量分辨率延伸到Bremsstrahlung极限是显着的，但在正常操作期间几乎没有观察到。这种能量分辨率通常以每秒输入计数率的每秒小于5000计数。

可以在这些低速率下使用峰值时间，例如6.4ms。较短的峰值时间是高计数率采集的先决条件，而是导致获得的X射线的能量统计不确定性。这意味着能量分辨率较低。

在50％的最佳死区时间下，最佳峰值时间和对能量分辨率的最佳峰值时间和相应的效果50％的光谱采集所需的频谱采集所需的能量分辨率。在该图中，能量分辨率在0.2ms时的6.4ms的125EV变化。

Figure 3.Energy resolution as a function of input count rates at 50% dead time (output count rate is approximately half of input count rate)

Using an SDD, most mapping applications take place at an output count rate of a few hundred thousand counts per second. The ratio of input and output count rates is 2 at a dead time of 50%. At higher dead times, this ratio will be greater. Mapping at 200,000 input counts/ second (100,000 output counts/second) leads to a resolution deterioration of approximately 8eV at a 1 microsecond time constant.

通过长时间常数强制操作防止这种劣化，然而，当非常高的死区时间限制整体吞吐量时，导致非常慢的获取速率（每秒几千个输出计数）。

This scenario is not suitable for mapping. A de facto advantage in energy resolution can be achieved with a system that enables multiple peaking times rather than only 2 or 3 peaking times due to the possibility of automatic selection of the longest possible peaking time for any given input count rate.

Certain designs may exhibit 121eV energy resolution at <5000 input counts per second, but only reach 140-150eV energy resolution in mapping mode at output counts beyond 100,000 per second. Hence, a broader specification for energy resolution, including both high- and low-throughput requirements, is helpful to the users.

Energy Resolution and Post-Processing Algorithms

The actual spacing of the X-ray lines produced by the elements within the sample itself is another concern associated with improved energy resolution. While the value of animproved EDS detector由图1和2中的光谱证明，元素是，B，C，N和O导致在150-250eV中分离的光谱内的单个X射线线。

图4中示出了主要由Pb和S组成的Galena样品的EDS谱图，其中S K线（2.307kev）仅通过39EV与主PB M线（2.346Kev）分离。另外，也可以观察到多个PB M线。分别具有138EV和122EV的能量分辨率的两个不同的EDS探测器用于样品分析。

图4。能量色散x射线谱的方铅矿(primarily Pb and S) for: (a) an SDD at 138eV (circa 2002), (b) an SDD at 122eV (circa 2012), and (c) a MagnaRay WDS spectrometer.

AThermo Scientific™ MagnaRay™wavelength dispersive spectrometer (WDS) (Figure 5) was finally used for the sample analysis.

与138EV检测器的检测器相比，122EV检测器谱表示改进。然而，尽管能量分辨率的16EV改善，Pb和S峰值存在显着重叠，但能量分辨率和元素X射线线路不明确辨别。有必要在40EV低于40EV以达到峰的严重分离。

The S K-line and the Pb M-lines can be accurately resolved into separate peaks by a WDS, thanks to its superior energy resolution. Even if the best EDS detector is used, overlapping peaks will be there if closely spaced X-ray lines are present continuously, thus preventing direct analysis of unknown specimen elements and posing challenges to qualitative and quantitative analysis and effective element mapping. However, these challenges can be addressed with the appropriate application of post-processing algorithms.

The element maps of the galena sample plotted with "gross" X-ray counts (i.e., counts that were not corrected after collection) are presented in Figure 5a. The WDS element map for Pb and for F is also given for reference. The elements determined as present by the EDS spectrum are Pb, O, F, S, Ca, Mn, Cu, As and Sb. Within the map, three regions can be observed:

• 中左和中右的阶段1主要包括CA和F.
• Phase 2 at center composed mainly of Cu and S
• 第3阶段 - PB和S的基质材料

The mapped backgrounds are quite high for a number of elements such as O, Mn, Cu, and As, indicating a consistent, low-level distribution of these elements across the sample or consistent misidentification of the elements owing to overlapping of peaks within the spectrum.

第2阶段还包含CA和SB的“Ghost样”区域，这可能被解雇为伪影。然而，这是一个冒险的假设。此外，对于PB M-α线的PB和WDS图之间的EDS映射之间没有匹配，指示由于峰值重叠而导致的EDS映射中的误差。

The same element maps generated utilizing the exact same raw data are presented in Figure 5b. However, they are "quantitative elemental mapping" or "Quant maps" involving the application of peak deconvolution, a background subtraction algorithm, and a matrix correction to the acquired spectra in each pixel. The direct comparison of the element maps in Figures 5a and 5b clearly shows the impact of these Quant maps.

图5。(a) X-ray element maps of galena (PbS) sample exhibiting “gross” or uncorrected X-ray counts, (b) same X-ray element maps of (a) but with corrections for peak deconvolution and background subtraction

The overall image noise around the concentrations of several elements, especially O, Mn and Cu, falls to near zero or zero other than in the actual phase wherein it exists. The As counts go to zero everywhere, showing that the As that originally determined by the As K-line at 10.532keV is an overlap with the Pb L-lines at 10.549eV.

去除中央Cu-S区域（相位2）中的PB的EDS鉴定，使PB的WT％图与PB的WDS映射直接对准。S仍然存在于中心区域和矩阵区域中，从而有助于确定由PB-S，或Galena，阶段3中围绕的相位阶段的A和S的区域。

关于CA和Sb“幽灵状”分布在阶段2中，在Cu-S地区观察到的CA分布完全消失。这导致Ca和F的分离为阶段1.该区域被鉴定为萤石（CAF₂).

The presence of Sb, which is absent in Phase 1, in the Cu-S Phase 2 region is confirmed by the Quant map. This discards any assumption that the Sb located in this region is an artifact. The phase type is changed from copper sulfide to chal-costibite (CuSbS₂) due to the presence of Sb in Phase 2.

This mapping exercise determined six major errors in a single sample when analyzed using basic mapping techniques and an advanced EDS detector with 122eV resolution. Although EDS detectors have undergone many significant advances in terms of energy resolution over the past decade, it is clear that until energy resolution approaches the level of WDS, the role of efficient post-processing algorithms for enhancing element mapping will be more significant than any further enhancements in energy resolution.

结论

Energy resolution is one of the key factors in acquiring high-quality EDS data. Windowless or thin window technologies and the removal of any inert gas between the SDD crystal and thin window are crucial to low energy detection. Low capacitance SDDs and fast electronics are important for mapping applications to mitigate the energy resolution degradation, which takes place at output counts rates of a few hundred thousand per second.

While aesthetically pleasing spectra are generated with an extreme EDS energy resolution, the most robust lever short of full WDS element mapping) for generating world-class, accurate EDS elemental maps is provided by powerful post-processing algorithms.

虽然EDS探测器在过去的15年中见证了显着的发展，但能量分辨率规范现在达到了物理学的限制。EDS的其他进展现在侧重于EDS数据收集和分析的改进。

This information has been sourced, reviewed and adapted from materials provided by Thermo Fisher Scientific – Materials & Structural Analysis.

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