# A Deep Learning Based Dislocation Detection Method for Cylindrical Crystal Growth Process
## 1 Introduction  
CZ crystal growth is one of the most important techniques for manufacturing single crystalline silicon, which is the mainstay of the microelectronic and photovoltaic industries [1]. The schematic illustration of the single crystal furnace structure is shown in Figure 1, which mainly consists of five parts: furnace, crystal and crucible pulling and rotating mechanism, atmosphere and pressure control system, electrical system, and thermal field. The quartz crucible is used to store a polycrystalline silicon ingot and is heated by the surrounding high-purity graphite heater. The crucible can be regulated precisely in the vertical direction by the crucible shaft mechanism beneath it. By heating the crucible to a prescribed temperature, the raw material is melted and forms a pool of silicon melt in the crucible. Then a monocrystalline seed is dipped into the silicon melt [2]. As the seed is slowly pulled upwards while being rotated at a prescribed pulling and rotation speed, a cylindrical crystal ingot is grown. A conical heat shield with a circular opening at its bottom is fixed inside the furnace. The gap distance between the melt surface and the bottom of the heat shield is referred to as the melt level. The cylindrical growth step is trying to maintain the diameter of the silicon ingot at a prescribed value during crystal growth. The cylindrical growth step is the most important step in the CZ crystal growth process, since usually it will last for more than 48h. Under normal growth conditions of single crystal silicon, the crystal ingot has a certain regularity. In the \(<\)100\(>\) crystallographic orientation growth process, there will be four habit lines on the surface of the ingot distributed at an angle of 90 degrees to each other, each one is continuous as shown in Figure 2, there will also be four corresponding nodes at the solid\(-\)liquid interface. These habit lines are grown in dislocation-free mono-Si due to undercooling in the \(<\)111\(>\) planes [3]. For the single crystal furnace used in the photovoltaic industry, growth problems occur frequently due to dislocations during the shouldering and cylindrical growth steps, which will seriously affect the quality of crystal silicon and the performance of the furnace and reduce the photoelectric conversion efficiency of solar cells. For example, when the thermal stress in the crystal exceeds the critical stress of silicon, dislocation of the crystal occurs. Besides, impure silicon material will also affect the dislocation-free growth of the crystal. Once the dislocations are generated in the \(<\)111\(>\) planes, it is easily noticed during the ingot pulling as it corresponds with the disappearance of the habit lines (DHL) on the edge of the ingot [3] as shown in Figure 2, then the normal crystal order can no longer be restored. This phenomenon can be used to determine whether crystalline silicon is growing without dislocation, that is, whether the growth state of the ingot changes from monocrystalline to polycrystalline. Figure 1: Structure of CZ single crystal furnace. When the DHL phenomenon occurs without human intervention, it will cause the liquid surface to be pulled off, causing a large amount of dislocation to occur at the interface. Meanwhile, the dislocations will propagate to the above, already-grown silicon ingot, which will affect crystal quality and significantly reduce the production yield of the CZ pulling [4,5]. At present, there is no technology for online prejudgment of the DHL phenomenon in the cylindrical growth step in production, it is manually inspected through the remote centralized control system by watching the growth process of all the furnaces, which is labor-intensive and time-consuming.