Editing Semiconductor device fabrication (section)

==Device yield==
Device yield or die yield is the number of working chips or dies on a wafer, given in percentage since the number of chips on a wafer (Die per wafer, DPW) can vary depending on the chips' size and the wafer's diameter. Yield degradation is a reduction in yield, which historically was mainly caused by dust particles, however since the 1990s, yield degradation is mainly caused by process variation, the process itself and by the tools used in chip manufacturing, although dust still remains a problem in many older fabs. Dust particles have an increasing effect on yield as feature sizes are shrunk with newer processes. Automation and the use of mini environments inside of production equipment, FOUPs and SMIFs have enabled a reduction in defects caused by dust particles. Device yield must be kept high to reduce the selling price of the working chips since working chips have to pay for those chips that failed, and to reduce the cost of wafer processing. Yield can also be affected by the design and operation of the fab.

Tight control over contaminants and the production process are necessary to increase yield. Contaminants may be chemical contaminants or be dust particles. "Killer defects" are those caused by dust particles that cause complete failure of the device (such as a transistor). There are also harmless defects. A particle needs to be 1/5 the size of a feature to cause a killer defect. So if a feature is 100&nbsp;nm across, a particle only needs to be 20&nbsp;nm across to cause a killer defect. Electrostatic electricity can also affect yield adversely. Chemical contaminants or impurities include heavy metals such as iron, copper, nickel, zinc, chromium, gold, mercury and silver, alkali metals such as sodium, potassium and lithium, and elements such as aluminum, magnesium, calcium, chlorine, sulfur, carbon, and fluorine. It is important for these elements to not remain in contact with the silicon, as they could reduce yield. Chemical mixtures may be used to remove these elements from the silicon; different mixtures are effective against different elements.

Several models are used to estimate yield. They are Murphy's model, Poisson's model, the binomial model, Moore's model and Seeds' model. There is no universal model; a model has to be chosen based on actual yield distribution (the location of defective chips). For example, Murphy's model assumes that yield loss occurs more at the edges of the wafer (non-working chips are concentrated on the edges of the wafer), Poisson's model assumes that defective dies are spread relatively evenly across the wafer, and Seeds's model assumes that defective dies are clustered together.<ref>{{Cite web |url=https://dokumente.unibw.de/pub/bscw.cgi/d10465215/%C3%9Cbung-1.pdf |title=Advanced MOSFETs and Novel Devices |access-date=2020-10-23 |archive-date=2020-10-26 |archive-url=https://web.archive.org/web/20201026052856/https://dokumente.unibw.de/pub/bscw.cgi/d10465215/Übung-1.pdf |url-status=dead}}</ref>

Smaller dies cost less to produce (since more fit on a wafer, and wafers are processed and priced as a whole), and can help achieve higher yields since smaller dies have a lower chance of having a defect, due to their lower surface area on the wafer. However, smaller dies require smaller features to achieve the same functions of larger dies or surpass them, and smaller features require reduced process variation and increased purity (reduced contamination) to maintain high yields. Metrology tools are used to inspect the wafers during the production process and predict yield, so wafers predicted to have too many defects may be scrapped to save on processing costs.<ref name="ceicm-chapter-3" />