就是把可怕的自拍照放上來
上一頁下一頁
  • 人妖照一

    人妖照一

  • 人妖照二

    人妖照二

  • 人妖照三

    人妖照三

  • P1060197.jpg

    P1060197

  • P1060195.jpg

    P1060195

  • P1060186.jpg

    P1060186

  • P1060185.jpg

    P1060185

  • P1060184.jpg

    P1060184

  • P1060183.jpg

    P1060183

  • P1060182.jpg

    P1060182

  • P1060181.jpg

    P1060181

  • P1060164.jpg

    P1060164

  • P1060160.jpg

    P1060160

  • P1060159.jpg

    P1060159

  • P1060149.jpg

    P1060149

  • P1060145.jpg

    P1060145

  • P1060140.jpg

    P1060140

  • P1060135.jpg

    P1060135

  • P1060134.jpg

    P1060134

  • P1060105.jpg

    P1060105

  • P1060099.jpg

    P1060099

  • P1060096.jpg

    P1060096

  • P1060095.jpg

    P1060095

  • 1722080478.jpg

    1722080478

  • 1722080477.jpg

    1722080477

  • 1722080475.jpg

    1722080475

  • 1722080469.jpg

    1722080469

  • 1722080468.jpg

    1722080468

  • 1722080467.jpg

    1722080467

  • 1722080463.jpg

    1722080463

  • 1722080461.jpg

    1722080461

  • 1722080460.jpg

    1722080460

  • 1722080443.jpg

    1722080443

  • 1722080432.jpg

    1722080432

  • 1722080426.jpg

    1722080426

  • 1722080424.jpg

    1722080424

  • 1722080422.jpg

    1722080422

  • 1722080421.jpg

    1722080421

  • 1722080420.jpg

    1722080420

  • 1722080419.jpg

    1722080419

  • 1722080417.jpg

    1722080417

  • 1722080416.jpg

    1722080416

  • 1722080415.jpg

    1722080415

  • 1722080411.jpg

    1722080411

  • 1722080409.jpg

    1722080409

  • 1722080408.jpg

    1722080408

  • 1722080406.jpg

    1722080406

  • 1722080403.jpg

    1722080403

  • 1722080394.jpg

    1722080394

  • 1722080375.jpg

    1722080375

  • P1060082.JPG

    P1060082

  • P1060076.JPG

    P1060076

  • P1060075.JPG

    P1060075

  • P1060074.JPG

    P1060074

  • P1060073.JPG

    P1060073

  • P1060072.JPG

    P1060072

  • P1060069.JPG

    P1060069

  • P1060066.JPG

    P1060066

  • P1060065.JPG

    P1060065

  • 1201181472.jpg

    1201181472

  • 1201181471.jpg

    1201181471

  • 1201181469.jpg

    1201181469

  • 1201181468.jpg

    1201181468

  • 1201181465.jpg

    1201181465

  • 1201181463.jpg

    1201181463

  • 1201181462.jpg

    1201181462

  • 1201181461.jpg

    1201181461

  • 1201181459.jpg

    1201181459

  • 1201181457.jpg

    1201181457

  • 1201181456.jpg

    1201181456

  • 1201181450.jpg

    1201181450

  • 1201181449.jpg

    1201181449

  • 1692113255.jpg

    1692113255

  • 1692113252.jpg

    1692113252

  • 1692113250.jpg

    1692113250

  • 1692113249.jpg

    1692113249

  • 1692113247.jpg

    1692113247

  • 1692113238.jpg

    1692113238

  • 1692113221.jpg

    1692113221

  • 1692113216.jpg

    1692113216

上一頁下一頁

您尚未登入,將以訪客身份留言。亦可以上方服務帳號登入留言

其他選項
  • 葉青峻
    葉青峻 2021/03/10 10:41

    常見的半導體材料有矽、鍺、砷化鎵等
    /
    晶片測試
    晶片處理高度有序化的本質增加了對不同處理步驟之間度量方法的需求。晶片測試度量裝置被用於檢驗晶片仍然完好且沒有被前面的處理步驟損壞。如果If the number of dies—the 積體電路s that will eventually become chips—當一塊晶片測量失敗次數超過一個預先設定的閾值時,晶片將被廢棄而非繼續後續的處理製程。
    /
    晶片測試
    晶片處理高度有序化的本質增加了對不同處理步驟之間度量方法的需求。晶片測試度量裝置被用於檢驗晶片仍然完好且沒有被前面的處理步驟損壞。如果If the number of dies—the 積體電路s that will eventually become chips—當一塊晶片測量失敗次數超過一個預先設定的閾值時,晶片將被廢棄而非繼續後續的處理製程。

    /
    步驟列表

    晶片處理
    濕洗
    平版照相術
    光刻Litho
    離子移植IMP
    蝕刻(干法蝕刻、濕法蝕刻、電漿蝕刻)
    熱處理
    快速熱退火Annel
    熔爐退火
    熱氧化
    化學氣相沉積 (CVD)
    物理氣相沉積 (PVD)
    分子束磊晶 (MBE)
    電化學沉積 (ECD),見電鍍
    化學機械平坦化 (CMP)

    IC Assembly and Testing 封裝測試
    Wafer Testing 晶片測試
    Visual Inspection外觀檢測
    Wafer Probing電性測試
    FrontEnd 封裝前段
    Wafer BackGrinding 晶背研磨
    Wafer Mount晶圓附膜
    Wafer Sawing晶圓切割
    Die attachment上片覆晶
    Wire bonding焊線
    BackEnd 封裝後段
    Molding模壓
    Post Mold Cure後固化
    De-Junk 去節
    Plating 電鍍
    Marking 列印
    Trimform 成形
    Lead Scan 檢腳
    Final Test 終測
    Electrical Test電性測試
    Visual Inspection光學測試
    Baking 烘烤
    /
    有害材料標誌

    許多有毒材料在製造過程中被使用。這些包括:

    有毒元素摻雜物比如砷、硼、銻和磷
    有毒化合物比如砷化三氫、磷化氫和矽烷
    易反應液體、例如過氧化氫、發煙硝酸、硫酸以及氫氟酸

    工人直接暴露在這些有毒物質下是致命的。通常IC製造業高度自動化能幫助降低暴露於這一類物品的風險。
    /
    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 nm across, a particle only needs to be 20 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 those elements to not remain in contact with the silicon, as they could reduce yield. Chemical mixtures may be used to remove those elements from the silicon; different mixtures are effective against different elements.

    Several models are used to estimate yield. Those 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.[25]

    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. 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.[26]

相片最新留言

相簿列表資訊

最新上傳:
2009/08/28
全站分類:
女生個人
本日人氣:
0
累積人氣:
1061