很多年了，in-situ已经进行了电子显微镜中动态过程的观察。在发明第一个电子显微镜之后不久就开始了这个过程。
Over the past few decades, the instrumentation available to record such dynamic processes has undergone a dramatic improvement, to the extent that it is now routine to capture videos at frame rates significantly faster than the human eye can process.
加坦的最新相机in-situ透射电子显微镜（TEM）将其进一步进行。这种技术不仅可以促进这种提高速度的趋势，而且还允许通过直接检测，实时电子计数，使用尽可能少的电子进行高速数据捕获。
This article outlines low-dose observations of beam-induced dendritic growth. The electron beam reduces Cu metal dendrites’ growth as a metal-organic precursor. Two different experiments were performed.
其中的第一个要求使用摄像机以每秒75帧（FPS）捕获快速动力学。第二个实验需要使用相同的相机，但要以较低的剂量和帧速率捕获较慢的生长。
在这里，介绍了对第一数据集的增长率的分析，这表明通过最近引入综合Python脚本介绍到该数据集中的进一步可能性Gatan显微镜套件®(GMS) software。
High-Speed Observation
本文提出的第一个实验的目的是用最小电子剂量以高速捕获动力学。需要正确设置样品和摄像机的放大倍率，剂量速率以及帧速率，以获得此结果。
It is important that the TEM magnification is set as low as possible without losing the key features, given that low magnification allows the dose rate per camera pixel to be high, relative to the number of electrons per square angstrom of the sample.
这种情况有两个同时效应。首先，它可以最大程度地减少电子束对样品的影响，其次，它最大化了任何给定剂量率的信噪比。
相机帧速率需要很高才能高速捕获动态。但是，这里有不可避免的权衡 - 随着帧率的增加，为了维持每个相机框架的最小电子数量，需要更高的剂量率。
因此，需要将摄像机的帧速率设置为最低的帧率，该帧帧仍具有捕获感兴趣的动态事件的能力。
BeackBack™功能的使用K3™是相机允许从确切的树突生长开始捕获数据。即使在观察初始树突生长后，此功能也可以保存数据磁盘，并可以通过完成反应完成数据捕获。
如图1所示，从1秒长的视频获得树突生长的视频中有10帧，在75 fps以75 fps收集数据。有关数据集的相应视频，请参见下图1。
To set the optimal conditions for this experiment, a frame rate of 75 fps was chosen with a full 5760 x 4092 pix field of view - despite the fact the K3 IS can acquire data at frame rates in excess of 3500 fps. The dose rate was set at the sample (of 270 e-/一种2/s), and the magnification was set to provide 0.63 Å pixels.
This condition leads to a very low dose rate at the camera of 3.6 e-/一种2/frame (e.g., 1.4 e-/pix/frame). The images were binned x2 in order to increase the signal-to-noise ratio at the expense of a small decrease in the spatial resolution for data visualization and analysis.
关于bined图像，每个集合像素的剂量率为5.7 e-/pix/帧。鉴于电子束本身的泊松统计，这会导致单个集合像素为2.3的信噪比。
K3的实时电子计数算法可以使最终图像中微弱信号的准确检测，尽管传入电子束的信噪比非常低。
明确的视频开始出现，通过在数据上执行指数加权的运行平均值来结合几个帧的信号。因此，从有关低剂量TEM的这些计算中阐明了一个重要的一点。在低剂量速率下，75 fps接近最大有用的帧速率，从每个帧中可以从中提取完整分辨率的信息。
必须注意的是，即使是一个完美的检测器，即能够确定撞击它的每个电子的确切位置，也将受到帧量增加期间电子束本身的传入信号到噪声的限制。
Both a direct detection sensor and a real-time counting algorithm are employed by the K3 IS to provide closer and more accurate results than ever before.
直接检测传感器消除了基于闪烁体的相机中存在模糊和信号衰减的来源。同时，实时计数算法可以显着限制相机内噪声源的影响，从而使电子束本身的射击噪声成为主要噪声组件。
图1。10 Frames from a 1 s long video acquisition of dendrite growth. Data was collected at 75 fps. After drift correction, 5 frames were averaged using an exponentially weighted moving average to produce the images shown here. The cumulative dose is given in the top left of each frame, while the time (m:s:ms) is given in the bottom right. The total dose for the entire video was only 270 e-/A2。The full video is below. Image Credit: Gatan Inc.
计数快速CU树突增长的视频
Video Credit: Gatan Inc.
K3与K2不同®和K2是给计数带来的好处in-situ视频获取。因此，结果是第一次，像这里看到的那样的低剂量视频。
因此，该结果证明了三个基本参数，必须适当平衡这些参数，以在电子束的入射信号中提供足够的信号到噪声：即时间分辨率，空间分辨率和电子剂量速率（或通量率））。
因此，必须降低空间分辨率，或者必须提高电子剂量速率以保持有用的信噪比，同时将时间分辨率提高。在空间分辨率和剂量率之间进行了权衡，其中所选条件以0.63Å/Pix的数据收集到270 e的剂量率。-/一种2/s。
尽管下一个数据集也将剂量率进一步降低至1.0 e-/一种2/s，it has to do this with a slightly worse spatial resolution. However, this lower dose condition arguably demonstrates another strength of the K3 IS: its pixel resolution and large field of view.
Observing a Large Field of View
Data from a related countedin-situ数据集如图2所示，该图还捕获了Cu树突的生长。再一次，生长是诱导的。在此实验中，观察到10 nm/s的生长速率降低，因为梁剂量速率降低至1.0 e-/一种2/s，
图1中的帧（用于比较）仅在75 fps的1 s中捕获。图2中的数据在8分钟内捕获（持续时间近500倍）。由于实验持续时间较长，剂量速率在图1中比图2高两个数量级，并且图2比单个典型的高分辨率TEM图像低三个数量级。
图2。a）从视频末端附近拍摄的静止框架，显示了整个视频中捕获的整个区域。彩色框表示B，C和D中更详细显示的区域。B）视频末端附近的一个总框架显示了所捕获的高分辨率信息。该框架是在漂移校正后总结100帧的结果。c）从在8分钟的树突增长中获得的视频中的6个总结帧。数据以5 fps收集。漂移校正后，求和10帧以产生所示的图像。累积剂量在每个帧的左上方给出，而时间（M：S：MS）在右下方给出。整个视频的总剂量仅为474 E-/A2。D) A smaller region processed in the same way as in C but displayed at a higher magnification so more detail is visible. Full videos can be found below. Image Credit: Gatan Inc.
计数慢速树突生长的视频（Zoomed）
Video Credit: Gatan Inc.
计数的视频缓慢CU树突生长
Video Credit: Gatan Inc.
The total dose throughout the experiment is 474 e-/一种2，或者在第一个视频中勉强只有2倍：正是这种剂量提供了将树突生长到这种尺寸所需的电子。
The data shown in Figure 2, in addition to capturing data with a lower dose rate, captured a much greater field of view of 5720 x 4060 nm or about 5.7 x 4.1 µm. Though this area is vast, it is sampled with pixels that measure just 0.5 nm in width.
在大面积上获取具有重要价值，但随后处理和分析从这样的实验中确实发生增长的位置的数据，在这种实验中确实永远无法确定树突在哪里生长。
鉴于同时观察到大量树突，也可以在动态过程上产生更好的统计数据。
对于这种类型的视野观察，K3使用的计数算法是相机是理想的。单个传入电子的位置确定为每个原始摄像头框架的准确度。
这种超分辨率模式导致具有> 9420万像素的图像，尽管K3的像素> 2350万像素，但该较大的视野可以连续捕获30 fps。
With all things considered, including the experimental trade-offs between electron dose rate, spatial resolution and temporal resolution, the ideal conditions for this experiment were as follows:
- 5 fps的帧速率
- 极低剂量率为1.0 e-/一种2/s
- 像素大小为0.5 nm
A dose rate of 4.8 e-/pix/frame was yielded by this combination, slightly lower than in the high-speed data, wherein the dose rate per binned pixel per frame was 5.7.
Data Analysis
使用漂移校正，融资和指数加权的移动平均线（随着时间的时间而不是空间）来处理图1和2中显示的数据。但是，下一步得出基于数据的科学结论是对分析进行分析树突增长率。
尽管从GMS软件中的标准用户界面提供了许多用于处理和可视化的工具，但几乎没有工具可以进行分析。
GMS has always had scripting capabilities (typically called DM-scripts to supplement the user interface with additional flexibility and power). One of the key advantages of scripting within GMS is that the results of such scripted acquisition or processing can be visualized and manipulated using the standard user interface.
However, the scripting language therein has been GMS-specific. Though this has also limited the use of other open-source libraries within GMS during TEM data collection, it is also able to be uniquely tailored to the needs of microscopists.
Gatan has integrated Python scripting into the GMS, starting in GMS version 3.4.0, which added the potential to run and edit Python (v 3.7) code directly from the scripting interface.
如图3所示，使用GMS中的Python显示了两个明确的示例，以分析图1中的树突生长数据。
As displayed by the first example, the code obtains a one-dimensional profile (shown in 3A) from the image as a function of time. This information is then presented as a kymograph, shown in part F, where a clear boundary can be observed, with its slope representing the average growth rate.
当数据播放时，对配置文件进行了实时测量（也可以在数据采集期间测量）。
第二个分析示例描述了如何使用Scikit-image Python软件包的阈值和形态图像处理函数实现的更复杂的图像分割技术，用于测量相同的树突生长。
由于输入数据（图3A和C）是嘈杂的，因此在同一脚本中预处理。图3D和3E分别显示了所选帧的最终分段结果，以及在被过滤的最后一帧顶部的彩色覆盖层。
因此，Scikit-image软件包中的另一个功能可以帮助轻松从分段框架中获得各种测量。图3F描绘了两项结果测量值，其中绘制了树突的面积和长度随时间绘制。
The entire process took <10 seconds or 0.4 seconds per million image pixels on a PC with an Intel Core i7 8850H at 2.6 GHz. Though it must be noted that this rate is far too slow to process all the data coming from the K3 IS camera in real-time, it would be possible to process a subset of the data live in this manner.
Figure 3.显微镜的处理和分析。来自1S的数据，用K3捕获的视频计数摄像头。最终帧中的原始数据显示在a）中，以及用于在b）中产生kymograph的配置文件，其中轮廓随着时间的推移进行采样。具有对应于平均线性生长速率的蓝线和垂直绿线的相同基仪，指示哪个轮廓是根据a）在c）中显示了75个原始框架的选择，在a）中显示了75个原始帧的选择，并在相应的分段图像中显示D）。最终（过滤）帧在E中显示，以及相应的分段框架和连接分段区域的过滤框架上的颜色覆盖。在F）中给出了树突长度和面积作为时间函数的最终测量值。Image Credit: Gatan Inc.
Conclusion
使用两个截然不同的时间尺度来捕获束诱导的Cu树突的生长：均使用K3 ISin countedin-situmode. The incoming signal reaching the camera was very weak in both of these cases.
At high speed, this can be attributed to trade-offs that are necessary to balance spatial resolution, framerate and electron dose rate.
缓慢速度下的弱传入信号主要是由于仅1 E的剂量速率非常低。-/一种2/s - three orders of magnitude less than that of a typical HRTEM image. These dose rates, whilst small, were still big enough to drive dendrite growth, though it must be acknowledged that the growth rate was much lower for the lower dose rate.
通过GMS中的Python的整合来促进对这种增长的分析：将来，可以在获取过程中对原始数据的子集进行实时分析。
致谢
西北大学NU的Epic设施为这项工作提供了促进ANCECenter, which has received support from myriad programs, including the Soft and Hybrid Nanotechnology Experimental (SHyNE) Resource (NSF ECCS-1542205); the MRSEC program (NSF DMR-1720139) at the Materials Research Center; the International Institute for Nanotechnology (IIN); the Keck Foundation and the State of Illinois, through the IIN.
Kun He (NUANCE) provided the sample used in this work. Ben Miller (Gatan), Paul Smeets and Roberto dos Reis collected data (NUANCE).
This information has been sourced, reviewed and adapted from materials provided by Gatan Inc.
有关此消息来源的更多信息，请访问Gatan Inc.