技术领域technical field
本发明涉及通过光学成像对硅晶圆进行质量鉴定。并且，本发明涉及一种测量用于制造光伏电池的半导体基板的特性的方法以及一种制造光伏电池的方法。The invention relates to quality identification of silicon wafers by optical imaging. Also, the present invention relates to a method of measuring characteristics of a semiconductor substrate for manufacturing a photovoltaic cell and a method of manufacturing a photovoltaic cell.
背景技术Background technique
光伏电池(例如太阳能电池)可由像硅这样的半导体材料的结晶态晶圆进行制造。结晶态晶圆含有例如在晶体成长过程期间因铸锭上的热应力造成的错位。错位密度随铸锭而变化，且错位的密度及空间分布因晶圆而异。在晶圆被处理成太阳能电池后，上述错位会缩短少数电荷载子的寿命。寿命的降低归因于不完美的晶体结构或制造太阳能电池期间未吸除或钝化的高浓度金属离子。少数电荷载子的寿命缩短造成太阳能(光伏)电池成品性能的降低。Photovoltaic cells, such as solar cells, can be fabricated from crystalline wafers of semiconductor materials like silicon. Crystalline wafers contain dislocations caused, for example, by thermal stress on the ingot during the crystal growth process. The dislocation density varies from ingot to ingot, and the density and spatial distribution of dislocations varies from wafer to wafer. These dislocations shorten the lifetime of minority charge carriers after the wafer is processed into a solar cell. The reduced lifetime is attributed to imperfect crystal structures or high concentrations of metal ions that are not gettered or passivated during the fabrication of solar cells. The reduced lifetime of the minority charge carriers results in reduced performance of the finished solar (photovoltaic) cell.
因此期望辨识出可能含有高错位密度的晶圆或晶圆区域。这可用于剔除晶圆或基于晶圆特性用于将所制造的电池依质量分类。以成本效益而言，在太阳能电池制造工艺中应尽早进行晶圆的质量鉴定，且晶圆的质量鉴定应当是可实时执行的(亦即除了捕获数据之外无须延迟制造工艺就可执行)，并且是非侵入式的。It is therefore desirable to identify wafers or regions of wafers that may contain high dislocation densities. This can be used to reject wafers or to sort manufactured cells by quality based on wafer characteristics. In terms of cost-effectiveness, wafer qualification should be performed as early as possible in the solar cell manufacturing process, and wafer qualification should be performed in real time (i.e., without delaying the manufacturing process other than data capture), And is non-intrusive.
可通过各种方法辨识出错位区域，例如光致发光(PL)、光学成像(OI)以及电致发光(EL)。光致发光及光学成像可应用于裸晶圆的方法。电致发光需要有电极存在，因此通常仅应用于太阳能电池成品。以光致发光而言，样本制备不是绝对需要的，但是在施用作为太阳能电池处理的部分的某些步骤(例如蚀刻)或施加发射层之后，常会得到较佳的图像。Dislocation regions can be identified by various methods, such as photoluminescence (PL), optical imaging (OI), and electroluminescence (EL). Photoluminescence and optical imaging can be applied to the bare wafer approach. Electroluminescence requires the presence of electrodes and is therefore usually only applied to finished solar cells. For photoluminescence, sample preparation is not strictly necessary, but better images are often obtained after applying certain steps as part of solar cell processing, such as etching, or applying an emissive layer.
光学成像可轻易地与熟知的数字图像处理方法结合。然后光学成像特性的质量鉴定可耦接至基于错位的存在预测性能的模型。Optical imaging can be easily combined with well-known digital image processing methods. The qualification of optical imaging properties can then be coupled to a model that predicts performance based on the presence of dislocations.
B.Sopori团队已于NREL从事通过光学成像来特性化晶圆。使用相机得到光学图像以高速特性化晶圆系描述于B.Sopori等人的文献“A reflectancespectroscopy-based tool for high-speed characterization of silicon wafers and solarcells in commercial production(用于高速特性化硅晶圆的基于反射光谱的工具以及商业生产中的太阳能电池)”,Photovoltaic Specialists Conference(PVSC)(光伏专家会议),201035th IEEE,002238-002241(2010)。重点在于以此方式可得到广泛的数据。Sopori已通过二维网络模型说明错位的影响。在名称为“Use ofoptical scattering to characterize dislocations in semiconductors(利用光学散射来特性化半导体中的错位)”的文献中(Appl.Opt.,27,4676-4683(1988))，Sopori已说明散射程度可作为测量错位密度、错位尺寸及制作错位映射的方法的基础。B.Sopori's group has been working at NREL on characterization of wafers by optical imaging. The use of cameras to obtain optical images to characterize wafers at high speeds is described in the document "A reflectancespectroscopy-based tool for high-speed characterization of silicon wafers and solar cells in commercial production" by B.Sopori et al. Reflectance spectroscopy-based tools and solar cells in commercial production), Photovoltaic Specialists Conference (PVSC), 2010 35th IEEE, 002238-002241 (2010). The point is that a wide range of data is available in this way. Sopori has illustrated the effect of misalignment through a two-dimensional network model. In a document entitled "Use of optical scattering to characterize dislocations in semiconductors" (Appl. Opt., 27, 4676-4683 (1988)), Sopori has shown that the degree of scattering can be As the basis for methods for measuring dislocation density, dislocation size and making dislocation maps.
近来Korte等人于文献“Measurements of effective optical reflectivity using aconventional flatbed scanner-Fast assessment of optical layer properties(利用传统平板扫描仪测量有效光学反射率-快速评定光学层特性)”(Solar Energy Materialsand Solar Cells(太阳能材料及太阳能电池),92,844-850(2008))中说明使用平板扫描仪测量晶圆的光学反射率。其中的一特征为平板扫描仪或复印机捕获散射的光，亦即不包含镜面反射。复印机及平台扫描仪为类似的装置，其可快速扫描整个表面。可替代地，可使用相机。相机具有相反的特性：光从各个方向落在错位上，散射特性造成错位在相机方向上具有一些反射。Recently, people such as Korte wrote in the literature "Measurements of effective optical reflectivity using a conventional flatbed scanner-Fast assessment of optical layer properties (Using traditional flatbed scanners to measure effective optical reflectivity-fast assessment of optical layer properties)" (Solar Energy Materials and Solar Cells (Solar Energy Materials and Solar Cells) Materials and Solar Cells), 92, 844-850 (2008)) describes the use of a flatbed scanner to measure the optical reflectance of a wafer. One of these features is that flatbed scanners or copiers capture scattered light, ie do not contain specular reflections. Copiers and flatbed scanners are similar devices that can quickly scan an entire surface. Alternatively, a camera can be used. The camera has the opposite property: light falls on the dislocation from all directions, and the scattering properties cause the dislocation to have some reflections in the direction of the camera.
以光学成像而言，蚀刻工艺为必要的。已研发出特别设计的蚀刻(含有像HF、硝酸、醋酸的酸混合物〉来优化光学成像质量。蚀刻工艺导致错位部位具有较粗糙的纹理，这意味着在这些位置反射的光会高度散射。若无此种蚀刻过程，现有技术不能提供可靠的错位测量。For optical imaging, an etching process is necessary. A specially designed etch (containing an acid mixture like HF, nitric acid, acetic acid) has been developed to optimize the optical image quality. The etching process results in a rougher texture at the dislocations, which means that the light reflected at these locations is highly scattered. If Without such an etching process, the prior art cannot provide reliable dislocation measurements.
需要特殊蚀刻的电致发光方法及光学成像不适合用于制造工艺中。光致发光方法成本太高，且当应用于发射极扩散之前的阶段时似乎不能区别出永久缺陷与某些在后续工艺会消失的缺陷。Electroluminescent methods requiring special etching and optical imaging are not suitable for use in the manufacturing process. Photoluminescent methods are too costly and when applied at a stage prior to emitter diffusion do not seem to be able to distinguish permanent defects from some defects that disappear in subsequent processes.
US2011025839涉及使用发光图像检测太阳能电池中的缺陷，亦即通过激发太阳能电池材料产生的发光图像。该文献优选使用光激发，亦即光致发光，但是亦提及电致发光。并未讨论到光散射图像。该文献揭露晶圆在表面破坏蚀刻后、在发射极扩散后、在SiN沉积后及完成电池处理后的光致发光图像。发射极扩散及SiN沉积后的成像显示值得注意的结构。该文献揭露，虽然错位亦可通过原切割晶圆的光致发光进行检测，但在扩散步骤后进行测量可具有优势，因为光致发光强度通常在该步骤后会提升，容许较短时间的数据采集、较低质量的设备或造成较高的空间分辨率图像或其任何组合。US2011025839 relates to the detection of defects in solar cells using luminescence images, ie luminescence images produced by exciting solar cell materials. The document preferably uses photoexcitation, ie photoluminescence, but also mentions electroluminescence. Light scattering images are not discussed. This document discloses photoluminescence images of wafers after surface damage etching, after emitter diffusion, after SiN deposition and after completion of cell processing. Imaging after emitter diffusion and SiN deposition reveals noteworthy structures. The paper reveals that although dislocations can also be detected by photoluminescence of as-saw wafers, there can be advantages to measuring after the diffusion step, since photoluminescence intensity usually increases after this step, allowing for shorter periods of data Acquisition, lower quality equipment or resulting higher spatial resolution images or any combination thereof.
发明内容Contents of the invention
本揭露的一目的在于提供一种测量晶圆上的错位密度的方法，其兼容于制造工艺中晶圆的使用，并产生可靠的错位密度测量值。It is an object of the present disclosure to provide a method of measuring dislocation density on a wafer that is compatible with the use of the wafer in the manufacturing process and yields reliable dislocation density measurements.
提供根据权利要求1所述的太阳能电池制造方法。于此，在制造过程期间系使用光学检验。已经发现，到当得到散射光(而不是镜面反射光)的图像且该图像被处理以加强边缘(例如进行检测到边缘的图像位置的检测)时，可在用作为太阳能电池制造过程工艺的部分的蚀刻步骤后，评估缺陷密度。举例而言，缺陷数目可评估为检测到边缘的成像点数目。以此方式，可使用在线检验来控制太阳能电池制造期间后续工艺步骤的施用。A solar cell manufacturing method according to claim 1 is provided. Here, optical inspection is used during the manufacturing process. It has been found that when an image of scattered light (rather than specularly reflected light) is obtained and the image is processed to enhance edges (for example, to perform detection of the image location where an edge is detected), it can be used as part of the solar cell manufacturing process process. After the etching step, assess the defect density. For example, the number of defects can be evaluated as the number of imaged points where edges are detected. In this way, in-line inspection can be used to control the application of subsequent process steps during solar cell fabrication.
在一实施例中，依据对性能的预测来调整在制造工艺期间金属化图案的施用。以此方式，可选择会产生最佳预测性能的金属化图案和/或金属化图案的方位，且可调整其余工艺步骤以应用所选择的图案和/或方位。In one embodiment, the application of the metallization pattern during the manufacturing process is adjusted based on the prediction of performance. In this way, the metallization pattern and/or orientation of the metallization pattern that yields the best predicted performance can be selected, and the remaining process steps can be adjusted to apply the selected pattern and/or orientation.
附图说明Description of drawings
通过参考以下图对示例性实施例的描述，可得知上述及其他目的与优点。The above and other objects and advantages will be apparent from the description of exemplary embodiments with reference to the following figures.
图1显示光学检验系统。Figure 1 shows the optical inspection system.
图2显示制造工艺的流程图。Figure 2 shows a flow chart of the manufacturing process.
具体实施方式Detailed ways
图1显示光学检验系统，其包含晶圆支撑台10、光源12、检测器14、扫描机构16以及计算机系统17。举例而言，晶圆18显示在晶圆支撑台10上。光源12可为例如线性光源，被配置为沿着晶圆18上的线产生光。类似地，检测器14可为线检测器，被配置为测量晶圆18在沿着该线的一连串位置的光强度。光源12及检测器14相对于彼此定位，而使得从光源12到晶圆的光方向及到检测器14的光方向相对于晶圆18表面的法线是在相互不同的角度(亦即是在检测器14不会捕获到镜面反射光的角度，其中当检测器14及光源12位于穿过在(穿过晶圆18表面法线的)法平面的相对侧上的线的平面中，相对于法平面在相同角度时，发生镜面反射光)。检测器14具有耦接至计算机系统17的输出。计算机系统17耦接至扫描机构16进而控制扫描或在扫描期间至少接收指示位置的信息。FIG. 1 shows an optical inspection system including a wafer support table 10 , a light source 12 , a detector 14 , a scanning mechanism 16 and a computer system 17 . By way of example, wafer 18 is shown on wafer support table 10 . Light source 12 may be, for example, a linear light source configured to generate light along a line on wafer 18 . Similarly, detector 14 may be a line detector configured to measure the light intensity of wafer 18 at a series of locations along the line. The light source 12 and the detector 14 are positioned relative to each other such that the direction of light from the light source 12 to the wafer and the direction of light to the detector 14 are at mutually different angles with respect to the normal to the surface of the wafer 18 (i.e., at Detector 14 does not capture specularly reflected light at angles where when detector 14 and light source 12 lie in a plane passing through a line on opposite sides of the normal plane (through the normal to the surface of wafer 18), relative to When the normal plane is at the same angle, specular reflection occurs). Detector 14 has an output coupled to computer system 17 . A computer system 17 is coupled to the scanning mechanism 16 to control scanning or at least receive information indicative of a location during scanning.
扫描机构16被配置为扫描支撑台10及光源12与检测器14相对于彼此的组合。支撑台10可于晶圆18上沿横穿线的方向移动。The scanning mechanism 16 is configured to scan the combination of the support table 10 and the light source 12 and detector 14 relative to each other. The support table 10 is movable on the wafer 18 in a direction transverse to the line.
图2显示制造工艺的流程图。在第一步骤21，切割晶圆。在第二步骤22，利用含有例如酸的混合液的酸性蚀刻剂，使用湿式化学工艺进行蚀刻工艺。此种蚀刻工艺在硅晶圆中的错位位置表面产生凹穴。可使用作为太阳能电池制造的习知部分的蚀刻工艺达到此目的。举例而言，蚀刻步骤可为蚀刻去除切割破坏和/或在晶圆表面产生二维纹理的蚀刻步骤。例如可使用湿式化学工艺，其利用像是氢氟酸、硝酸或醋酸等酸的混合液。此种工艺形成对错位区域敏感的表面纹理(具有变化的高度的图案)。使用的蚀刻剂较佳地在含有错位区域的晶圆表面上形成蚀刻凹穴。Figure 2 shows a flow chart of the manufacturing process. In a first step 21 the wafer is diced. In a second step 22, an etching process is performed using a wet chemical process using an acidic etchant containing a mixed solution such as an acid. This etching process creates pockets on the surface of the dislocations in the silicon wafer. This can be achieved using etching processes that are a known part of solar cell fabrication. For example, the etching step may be an etching step that removes dicing damage and/or creates a two-dimensional texture on the wafer surface. For example a wet chemical process can be used which utilizes a mixture of acids such as hydrofluoric acid, nitric acid or acetic acid. This process forms a surface texture (patterns with varying heights) that is sensitive to dislocation areas. The etchant used preferably forms etch pockets on the wafer surface containing the dislocation regions.
在第三步骤23，计算机系统17捕获来自检测器14的输出信号，该些信号为针对沿着晶圆18上的线的点以及针对扫描期间相继的线。所捕获的信号定义晶圆18的图像。In a third step 23, the computer system 17 captures output signals from the detector 14, both for points along a line on the wafer 18 and for successive lines during scanning. The captured signals define an image of wafer 18 .
在第四步骤24，计算机系统17应用边缘检测运算符至图像。就本身而论，边缘为图像中强度的陡峭突然改变。一种熟知的检测边缘的方法为坎尼(Canny)边缘检测算法，其描述于出自R.C.Gonzalez和R.E.Woods的于2008年由Pearson Education International(皮尔森教育国际)发行的书“Digital ImageProcessing(数字图像处理)”的719-725页。Canny边缘检测包含利用多个梯度滤波器(例如四个滤波器)对图像进行滤波，可选地，结合例如通过例如高斯滤波器或近似高斯滤波器的FIR滤波器对图像进行平滑。梯度滤波器被设计用于产生图像位置的输出信号，其与预定方向的强度梯度成比例。例如可使用具有5x5像素的FIR滤波器。在Canny边缘检测器中，多个梯度滤波器含有针对不同方向的梯度的滤波器(例如水平方向、垂直方向及两个对角线方向(/和\))。通过在各像素位置结合分别应用梯度滤波器至图像所得的结果幅度可得到边缘信号。该结果代表基于像素位置的边缘幅度。抑制像素位置中结果值不是局部最大值的结果值。可应用双(低及高)阈值运算至该些结果，以降低错误边缘点的数量。实际上，可针对晶圆特性优化这些运算的参数。这些运算将图像转换为经处理的图像，称Canny边缘图像，像素在检测到边缘的位置具有第一值(阈值之间的数值)以及在未检测到边缘的位置具有不同的第二值。In a fourth step 24, the computer system 17 applies an edge detection operator to the image. Edges, as such, are steep, sudden changes in intensity in the image. A well-known method of detecting edges is the Canny edge detection algorithm described in the book "Digital Image Processing" by R.C. Gonzalez and R.E. Woods, published by Pearson Education International in 2008. processing)” at pp. 719-725. Canny edge detection involves filtering the image with multiple gradient filters (eg four filters), optionally in combination with smoothing the image eg by a FIR filter such as a Gaussian filter or an approximate Gaussian filter. A gradient filter is designed to produce an output signal at the image position that is proportional to the intensity gradient in a predetermined direction. For example a FIR filter with 5x5 pixels can be used. In the Canny edge detector, multiple gradient filters contain filters for gradients in different directions (such as horizontal, vertical, and two diagonal directions (/ and \)). The edge signal is obtained by combining the magnitudes resulting from applying a gradient filter to the image separately at each pixel location. The result represents the edge magnitude based on pixel location. Suppresses result values in pixel locations where the resulting value is not a local maximum. A double (low and high) thresholding operation can be applied to these results to reduce the number of false edge points. In practice, the parameters of these operations can be optimized for wafer characteristics. These operations convert the image into a processed image, called a Canny edge image, where pixels have a first value (value between thresholds) where an edge is detected and a different second value where no edge is detected.
在第五步骤25中，Canny边缘图像用于计算Canny边缘分率(Canny edgefraction)(CEF＝图像中边缘像素数/总图像像素数)或用于制作错位分布的(二进制)映射图。在一个实施例中，映射错位分布可包含：In a fifth step 25, the Canny edge image is used to calculate the Canny edge fraction (CEF=number of edge pixels in the image/total number of image pixels) or to make a (binary) map of the dislocation distribution. In one embodiment, mapping the misalignment distribution may include:
-将图像分成子区块并计算图像的每个子区块的边缘数；- Divide the image into sub-blocks and count the number of edges for each sub-block of the image;
-将边缘密度超过另一阈值的区块识别为错位区域。- Identify blocks with edge density exceeding another threshold as misaligned regions.
亦可使边缘信号(例如来自梯度滤波器的输出)取代二进制边缘检测，且边缘信号的值可用作为权重，藉此权衡相应边缘点对边缘计数的影响。在替代实施例中，在第四步骤24，可使用非Canny算法的另一边缘检测算法。亦可调谐此种边缘检测算法的参数。An edge signal (eg, output from a gradient filter) can also be used instead of binary edge detection, and the value of the edge signal can be used as a weight, thereby weighing the influence of the corresponding edge point on the edge count. In an alternative embodiment, in the fourth step 24, another edge detection algorithm other than the Canny algorithm may be used. The parameters of such edge detection algorithms can also be tuned.
在一实施例中，第五步骤25可包含权重运算，其中依据图像中的位置将边缘数乘以权重。在另一实施例中，可罩住所选的图像区域(对应于不是一就是零的权重)。In one embodiment, the fifth step 25 may include a weighting operation, wherein the number of edges is multiplied by the weight according to the position in the image. In another embodiment, selected image regions (corresponding to weights of either one or zero) may be masked.
在计算Canny边缘分率之前，可将线滤波器应用于Canny边缘图像，以去除检测中与错位无关的线性边缘，例如通过测试沿着线的像素位置组的Canny边缘图像值，以及若己针对治此线的预定长度片段的所有像素位置检测边缘点或不超过不形成连续子片段的像素位置的预定数的所有像素位置，则抑制边缘检测。Before computing the Canny edge fractions, a line filter can be applied to the Canny edge image to remove linear edges that are not relevant for misalignment in detection, e.g. by testing the Canny edge image values for groups of pixel locations along the line, and if Edge detection is suppressed for all pixel positions of a segment of a predetermined length of the line detecting edge points or for all pixel positions not exceeding a predetermined number of pixel positions that do not form consecutive sub-segments.
在替代实施例中，第四步骤24包含使用梯度方法取代Canny边缘检测。梯度方法可由例如出自R.C.Gonzalez及R.E.Woods的书中706-714页得知。然后第四步骤24可包含应用高通滤波器(例如Laplacian罩)至所捕获的图像，而第五步骤25则可包含:In an alternative embodiment, the fourth step 24 involves using a gradient method instead of Canny edge detection. Gradient methods are known, for example, from pages 706-714 of the book by R.C. Gonzalez and R.E. Woods. A fourth step 24 may then comprise applying a high-pass filter (e.g. a Laplacian mask) to the captured image, while a fifth step 25 may then comprise:
-计算经滤波的图像的直方图(例如频率对强度值)或针对不同各子区块计算多个此种直方图；- computing a histogram (eg frequency versus intensity values) of the filtered image or computing a plurality of such histograms for different sub-blocks;
-针对各直方图，计算在直方图的低强度值与高强度值间的直方图的这些强度值的积分。- For each histogram, calculating the integral of these intensity values of the histogram between the low and high intensity values of the histogram.
在第六步骤26，第五步骤25所得的信息用于获得性能预测。可为此目的使用相关性。可配合相关预先储存的不同密度值，预先储存不同的预测性能值，且第五步骤的结果可用于获取相关的预测性能值。在一个实施例中，得自第五步骤25的平均错位密度(图像中边缘像素数除以总图像像素数)系用于获取预测的性能值。在另一实施例中，将错位子区块数除以总子区块数或错位子区块的全空间映射计算所得的平均密度用于获取预测的性能值。此引入两个附加的可调谐参数，即区块尺寸与选择错位区块的阈值。In a sixth step 26, the information obtained in the fifth step 25 is used to obtain a performance prediction. Correlation can be used for this purpose. Different predictive performance values may be pre-stored in conjunction with associated pre-stored different density values, and the result of the fifth step may be used to obtain the relevant predictive performance values. In one embodiment, the average dislocation density (the number of edge pixels in the image divided by the total number of image pixels) obtained from the fifth step 25 is used to obtain the predicted performance value. In another embodiment, the average density calculated by dividing the number of misaligned sub-blocks by the total number of sub-blocks or the full space map of misaligned sub-blocks is used to obtain the predicted performance value. This introduces two additional tunable parameters, the block size and the threshold for selecting misaligned blocks.
在第七步骤27，基于预测的性能进行评估，以控制例如晶圆的进一步使用。可比较预测的性能与性能的预设阈值。In a seventh step 27, an evaluation is performed based on the predicted performance to control eg further usage of the wafer. The predicted performance can be compared to a preset threshold of performance.
若晶圆符合阈值，则可使用已知的制造太阳能电池的预定制造工艺的其他步骤处理晶圆。若不符合，则对晶圆进行不同的处理。再者，若可依据测试结果在应用其他步骤前剔除晶圆，则可节省成本。If the wafer meets the threshold, the wafer may be processed using other steps of a predetermined manufacturing process known to make solar cells. If not, treat the wafer differently. Furthermore, cost savings can be achieved if wafers can be rejected based on test results before other steps are applied.
其他步骤可包含例如发射极扩散步骤，其中基板被掺杂以产生p-n结。蚀刻步骤可为发射极扩散之前的最后蚀刻步骤。优选地，第二步骤22的蚀刻工艺(在其后进行图像捕获步骤23)为最早的蚀刻步骤，例如去除切割破坏的步骤。Other steps may include, for example, an emitter diffusion step, where the substrate is doped to create a p-n junction. The etch step may be the last etch step before the emitter diffusion. Preferably, the etching process of the second step 22 (followed by the image capture step 23) is the earliest etching step, eg a step to remove cutting damage.
发射极扩散可具有使表面的错位隐藏(obscure)的效应，但是错位有可能贯穿晶圆，因此即使错位被隐藏仍可能会发生问题。类似地，稍后在硅表面添加额外层的步骤有可能隐藏错位。因此，优选地，在所捕获的硅表面不含有发射极扩散时，或更优选地，在所捕获的硅表面不含有其他扩散(例如背面或前面区域扩散)或稍后增加的覆盖层(例如介电层或导体层)时，进行图像的捕获。Emitter diffusion can have the effect of obscuring dislocations at the surface, but dislocations can potentially penetrate the wafer so problems can occur even if dislocations are obscured. Similarly, later steps that add additional layers to the silicon surface have the potential to hide dislocations. Therefore, preferably, when the trapped silicon surface contains no emitter diffusion, or more preferably, the captured silicon surface is free of other diffusions (such as backside or front area diffusions) or later added capping layers (such as Dielectric layer or conductive layer) for image capture.
在某些制造工艺中，通过在基板两侧进行掺杂而进行产生p-n结的掺杂，之后通过蚀刻去除任一侧的掺杂层，从而获得具有单一结的材料。本方法亦可通过如下方式来应用：执行图像捕获步骤23以捕获通过此种单侧蚀刻步骤所获得的蚀刻表面的图像。虽然这在施加发射极之后，但是单侧蚀刻确保无发射极扩散的表面可被捕获。In some fabrication processes, doping to create a p-n junction occurs by doping both sides of the substrate, followed by etching to remove the doped layers on either side, resulting in a material with a single junction. The method can also be applied by performing an image capture step 23 to capture an image of the etched surface obtained by such a single-sided etching step. Although this is after the emitter is applied, the single-sided etch ensures that the emitter-diffusion-free surface can be captured.
性能预测算法performance prediction algorithm
电池性能预测可预测性能特性的值，例如一旦经制造后太阳能电池的开路电势Voc，一且经制造后的电池效率η，或这两者。效率为评估性能的最相关的特性，但是通常Voc更容易计算，且可捕获到最多与低少数电荷载子寿命时间有关的效应。Cell performance prediction can predict the value of a performance characteristic, such as the open circuit potential Voc of the solar cell once fabricated, the cell efficiency η once fabricated, or both. Efficiency is the most relevant characteristic to evaluate performance, but usually Voc is easier to calculate and captures most effects related to low minority charge carrier lifetime time.
在一个实施例中，可使用“启发式模型(heuristic model)”，其中使用性能特性对错位分率的线性回归。错位分率可直接得自于Canny边缘计算或得自于基于Canny图像的子区块的中间映射，或根据线性回归计算Canny边缘计算的相关性能特性值。In one embodiment, a "heuristic model" may be used in which a linear regression of performance characteristics versus misalignment fractions is used. The dislocation fraction can be obtained directly from Canny edge computing or from the intermediate mapping based on the sub-blocks of the Canny image, or the relevant performance characteristic values of Canny edge computing can be calculated according to linear regression.
在一实施例中，可使用分析模型，其中光伏电池的物理特性被表征。此可基于光伏电池的等效电路来完成。In an embodiment, an analytical model may be used in which the physical properties of the photovoltaic cell are characterized. This can be done based on the equivalent circuit of a photovoltaic cell.
第一实例包括针对太阳能电池的单二极管等效电路运用方程式。区别出没有错位的区域(其指定第一(低)二极管暗饱和电流密度)以及具有错位的区域(其指定第二(较高)二极管暗饱和电流)。然后将二极管暗饱和电流的表面平均值用作为等效电路的参数，从而计算性能特性的值。The first example involves applying the equations for the single diode equivalent circuit of a solar cell. A distinction is made between regions without dislocations (which designate the first (lower) diode dark saturation current density) and regions with dislocations (which designate the second (higher) diode dark saturation current). The surface average value of the diode dark saturation current was then used as a parameter of the equivalent circuit to calculate the value of the performance characteristic.
再者，可通过相同程序但现在包含发射极层与金属化图案的串联电阻来获得改善的性能值η。此外，局部产生的光子电流密度可视错位的存在而定。此可类似于以下针对暗饱和电流的方法来完成：将某个值指派到没有错位的区域，而将更低的值指派到具有错位的区域。可通过等效电路中的额外元件，例如分路器、额外的二极管、串联电阻、接触电阻等，来扩展模型。Again, an improved performance value η can be obtained by the same procedure but now including the series resistance of the emitter layer and the metallization pattern. Furthermore, the locally generated photon current density can depend on the presence of dislocations. This can be done similarly to the approach for dark saturation current by assigning a certain value to regions without dislocations and a lower value to regions with dislocations. The model can be extended with additional elements in the equivalent circuit, such as shunts, additional diodes, series resistors, contact resistors, etc.
在第二实例中，可使用将太阳能电池描述为平行太阳能电池单二极管电路的二维网络的模型。该网络具有第一型及第二型(坏的及好的)二极管，且在网络中不同位置的二极管根据在图像中对应位置的子区块是否被识别为边缘区块或不对应上述映射而被选择成为第一型或第二型。In a second example, a model describing the solar cell as a two-dimensional network of single diode circuits of parallel solar cells can be used. The network has type 1 and type 2 (bad and good) diodes, and the diodes at different positions in the network are identified according to whether the sub-block at the corresponding position in the image is identified as an edge block or does not correspond to the above mapping Be chosen to be Type 1 or Type 2.
在该模型中，此二极管网络可结合在制造期间稍后可应用的金属化图案的模型。在此模型中，通过串联电阻来连接电路，这具有金属化及发射极电阻的结合效应。此定义于偏微分方程式，其中固定在电流收集点的电池电压作为边界条件。此微分方程式可利用适当的方法(例如有限元法(Finite Element Method))进行数值解答。In this model, this diode network can be combined with a model of the metallization pattern that can be applied later during fabrication. In this model, the circuit is connected by a series resistor, which has the combined effect of metallization and emitter resistance. This is defined in a partial differential equation with the battery voltage fixed at the current collection point as the boundary condition. This differential equation can be numerically solved using an appropriate method (eg, Finite Element Method).
暗饱和电流可用作为特性化错位的特性，但是在此状况下，可通过利用位置相关光子产生电流密度及通过添加额外元件到等效电路模型来扩展模型(参见上述2c)。此特定类型的建模使得能够使用错位的空间解析信息。Dark saturation current can be used as a property to characterize dislocations, but in this case the model can be extended by exploiting the position-dependent photon generation current density and by adding additional elements to the equivalent circuit model (see 2c above). This particular type of modeling enables the use of misplaced spatially resolved information.
如此可预测依赖于错位的不同的可用金属化图案的效应。在Sopori等人的文章“Performance limitations of mc-Si solar cells caused by defect clusters(由缺陷群组导致的多晶硅太阳能电池的性能限制)”(ECS Trans.,18,1049-1058(2009))以及“Influence of distributed defects on the photoelectric characteristics of alarge-area device(分布的缺陷对在大面积装置的光学特性的影响)”(J.Cryst.Growth,210,375-378(2000))中，己描述此种网络模型关于错位对太阳能电池性能的影响的研究。This predicts the effect of different available metallization patterns depending on the dislocation. In the article "Performance limitations of mc-Si solar cells caused by defect clusters" by Sopori et al. (ECS Trans., 18, 1049-1058 (2009)) and " Influence of distributed defects on the photoelectric characteristics of large-area device (the influence of distributed defects on the optical characteristics of large-area devices)" (J.Cryst.Growth, 210, 375-378 (2000)), this kind of network has been described Model studies on the effect of dislocations on solar cell performance.
评估步骤Evaluation steps
基于在制造工艺早期的蚀刻步骤后且在制造太阳能电池的工艺中的其余步骤之前所捕获的图像而得到预测的性能。比较预测的晶圆性能与预设的阈值。可测试预测效率是否高于阈值，可测试预测的Voc是否高于此阈值，或测试这两者。若预测的晶圆性能符合阈值，则以预定方式进行工艺的其余步骤。The predicted performance is based on images captured after the etch step early in the fabrication process and before the remaining steps in the process of fabricating the solar cell. Compare predicted wafer performance with preset thresholds. It can be tested whether the predicted efficiency is above a threshold, whether the predicted Voc is above this threshold, or both. If the predicted wafer performance meets the threshold, the remaining steps of the process proceed in a predetermined manner.
若预测的晶圆性能不符合预设的性能阈值，可实行许多手段其中的一种：If the predicted wafer performance does not meet preset performance thresholds, one of a number of approaches can be implemented:
1)可剔除晶圆，亦即不进行制造太阳能电池所需的其余工艺步骤。1) The wafer can be discarded, ie the remaining process steps required for the manufacture of solar cells are not carried out.
2)针对次等晶圆而言，可将晶圆传送至不同的生产线。2) For inferior wafers, the wafers can be transferred to different production lines.
3)可依据预测性能来调整施加于晶圆的生产工艺。3) The production process applied to the wafer can be adjusted based on the predicted performance.
在后者情况的实施例中，可调整对晶圆进行金属化的工艺步骤。举例而言，当使用“H”图案或交指“E”图案的金属化时，可在相对于晶圆为零或九十度旋转的状况下将图案应用到晶圆(亦即可在施用这些步骤之前旋转晶圆以进行金属化，或可旋转用于施用图案的设备(例如印花网版)，或可使用不同的印刷图案)。可依据利用具有不同旋转角度的金属化图案的模型获得的性能预测，来选择选转角度，其中选择具有最佳预测性能的旋转角度。如此可得到较佳的性能。对2D模型网络的研究已显示错位位置对金属化有显著重要性。In an embodiment of the latter case, the process steps for metallizing the wafer may be adjusted. For example, when using metallization with an "H" pattern or an interdigitated "E" pattern, the pattern can be applied to the wafer with zero or ninety degree rotation relative to the wafer (i.e. These steps are preceded by spinning the wafer for metallization, or the equipment used to apply the pattern (such as a printed screen) can be rotated, or a different printed pattern can be used). The rotation angle may be selected based on performance predictions obtained using models of metallization patterns with different rotation angles, wherein the rotation angle with the best predicted performance is selected. This results in better performance. Studies of 2D model networks have shown that the dislocation location is of significant importance for metallization.
在一个经调整的实施例中，可调整金属化图案的手指的间距。可依据利用具有不同间距的手指的金化图案的模型的性能预测，来选择间距，其中选择具有最佳预测性能的间距。此可结合旋转角度的选择，或可使用预定的旋转角度被应用。In one adjusted embodiment, the spacing of the fingers of the metallization pattern can be adjusted. The pitch may be selected based on performance predictions from models using goldization patterns for fingers with different pitches, where the pitch with the best predicted performance is chosen. This can be combined with the selection of the rotation angle, or can be applied using a predetermined rotation angle.
在一个实施例中，可使用金属化施用技术，例如喷墨印刷法，使金属化图案比仅仅旋转及/或间距有更多的变化。可依据使用具有该金属化图案的模型获得的性能预测来选择图案，其中选择具有最佳预测性能的图案。In one embodiment, a metallization application technique, such as inkjet printing, can be used to allow more variation in the metallization pattern than just rotation and/or pitch. A pattern can be selected based on performance predictions obtained using a model with that metallization pattern, where the pattern with the best predicted performance is selected.
以并发的性能预测监控晶圆质量可识别出生产中的不稳定性或问题，亦即可区分这些问题与晶圆质量变异。在一个实施例中，在完成制造工艺之后，或在捕获图像阶段之后的制造阶段，进行性能(例例如Voc或效率)测量。比较测量的晶圆性能与预测的晶圆性能，且若偏差超过阈值，则产生警报，表示生产工艺可能发生错误。若不使用预测，则可能无法检测此种错误，因为不能将其与未知的晶圆缺陷效应区分开。Monitoring wafer quality with concurrent performance predictions can identify instabilities or issues in production, ie distinguish these issues from wafer quality variation. In one embodiment, performance (such as Voc or efficiency) measurements are made after completion of the manufacturing process, or at a manufacturing stage after the image capture stage. Measured wafer performance is compared to predicted wafer performance, and if the deviation exceeds a threshold, an alert is generated, indicating a possible error in the production process. Without the use of prediction, such errors may not be detected because they cannot be distinguished from unknown wafer defect effects.
可将质量问题反馈给晶圆供应商，可提供改善晶体生长工艺的建议。Quality problems can be fed back to the wafer supplier, and suggestions for improving the crystal growth process can be provided.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112986259A (en)* | 2021-02-09 | 2021-06-18 | 清华大学 | Defect detection method and device for manufacturing process of intelligent terminal OLED panel |
| CN114975157A (en)* | 2022-08-01 | 2022-08-30 | 波粒（北京）光电科技有限公司 | Photoluminescence detection device of solar cell |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102014208462B4 (en)* | 2014-05-06 | 2016-04-14 | Forschungszentrum Jülich GmbH | Method for measuring and evaluating power losses in solar cell, solar module and solar systems by means of photographic luminescence and thermography measurements |
| US9996766B2 (en) | 2015-05-01 | 2018-06-12 | Corning Incorporated | Imaging-based methods for detecting and measuring defects in extruded cellular ceramic articles |
| CN107646124B (en) | 2015-05-21 | 2021-04-02 | 康宁股份有限公司 | Method for inspecting porous articles |
| CN105719984A (en)* | 2016-02-22 | 2016-06-29 | 成都振中电气有限公司 | Solar cell performance detection system |
| JP6341229B2 (en)* | 2016-05-30 | 2018-06-13 | 株式会社Sumco | Crystal defect evaluation method, silicon wafer manufacturing method, and crystal defect evaluation apparatus |
| CN112381759B (en)* | 2020-10-10 | 2022-10-14 | 华南理工大学 | Defect detection method of single crystal silicon solar wafer based on optical flow method and confidence method |
| CN117241483B (en)* | 2023-10-25 | 2024-04-12 | 广东达源设备科技有限公司 | Spraying device and method for circuit board production |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5581346A (en)* | 1993-05-10 | 1996-12-03 | Midwest Research Institute | System for characterizing semiconductor materials and photovoltaic device |
| US5757474A (en)* | 1993-05-10 | 1998-05-26 | Midwest Research Institute | System for characterizing semiconductor materials and photovoltaic devices through calibration |
| CN101365937A (en)* | 2005-10-11 | 2009-02-11 | Bt成像股份有限公司 | Method and system for inspecting a bandgap semiconductor structure |
| CN102017191A (en)* | 2008-03-31 | 2011-04-13 | Bt成像股份有限公司 | Method and apparatus for wafer imaging and processing |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5581346A (en)* | 1993-05-10 | 1996-12-03 | Midwest Research Institute | System for characterizing semiconductor materials and photovoltaic device |
| US5757474A (en)* | 1993-05-10 | 1998-05-26 | Midwest Research Institute | System for characterizing semiconductor materials and photovoltaic devices through calibration |
| CN101365937A (en)* | 2005-10-11 | 2009-02-11 | Bt成像股份有限公司 | Method and system for inspecting a bandgap semiconductor structure |
| CN102017191A (en)* | 2008-03-31 | 2011-04-13 | Bt成像股份有限公司 | Method and apparatus for wafer imaging and processing |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112986259A (en)* | 2021-02-09 | 2021-06-18 | 清华大学 | Defect detection method and device for manufacturing process of intelligent terminal OLED panel |
| CN114975157A (en)* | 2022-08-01 | 2022-08-30 | 波粒（北京）光电科技有限公司 | Photoluminescence detection device of solar cell |
| Publication number | Publication date |
|---|---|
| WO2013085385A1 (en) | 2013-06-13 |
| TW201330136A (en) | 2013-07-16 |
| NL2007941C2 (en) | 2013-06-11 |
| Publication | Publication Date | Title |
|---|---|---|
| CN104067512A (en) | Qualification of silicon wafers for photovoltaic cells by optical imaging | |
| TWI609177B (en) | Wafer imaging and processing method and device | |
| CN103210482B (en) | Persistent feature detection | |
| Spataru et al. | Automatic detection and evaluation of solar cell micro-cracks in electroluminescence images using matched filters | |
| CN102144284B (en) | For the method and apparatus of defects detection | |
| KR101372995B1 (en) | Defect Inspection Method | |
| Trupke et al. | Progress with luminescence imaging for the characterisation of silicon wafers and solar cells | |
| WO2010130013A1 (en) | Material or device characterisation with non-homogeneous photoexcitation | |
| Sio et al. | Imaging surface recombination velocities of grain boundaries in multicrystalline silicon wafers via photoluminescence | |
| Höffler et al. | Statistical Evaluation of a Luminescence-based Method for imaging the series resistance of solar cells | |
| Bakowskie et al. | Fast method to determine the structural defect density of 156 x 156 mm2 Mc-Si wafers | |
| Demant | Quality Rating of Silicon Wafers: A Pattern Recognition Approach | |
| CN103871939B (en) | Method for separating for producing sapphire pattern substrate | |
| Wolf et al. | Uniformity analysis of metallization-induced recombination losses by photoluminescence imaging | |
| Turek et al. | Solar cell performance prediction using advanced analysis methods on optical images of as-cut wafers | |
| JP2012043870A (en) | Method for manufacturing photovoltaic module | |
| CN103364704B (en) | A kind of Forecasting Methodology of polysilicon chip open circuit voltage | |
| Mei et al. | Automated optical inspection for die prep | |
| Sopori et al. | Online monitoring for Si solar cell manufacturing | |
| CN101587078B (en) | Rapid detection method of silicon chip | |
| Höffler et al. | Statistical Evaluation of a Luminescence-based imaging Method |
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|---|---|---|---|
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| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| AD01 | Patent right deemed abandoned | ||
| AD01 | Patent right deemed abandoned | Effective date of abandoning:20180608 |