1. C.V. S.W. T.S. L.G. X.S. M.S. IPHC-LBL meeting, January 22, 2013 1 1 1 Probe Test Results for 5 wafers of Ultimate-2 sensors Outline:  Yield and wafer maps  Summary

2. C.V. S.W. T.S. L.G. X.S. M.S. IPHC-LBL meeting, January 22, 2013 2 2 Yield and wafer maps – wafer 1,2 A01A02 B01B02B03B04B05B06 C01C02C03C04C05C06C07C08 D01D02D03D04D05D06D07D08 E01E02E03E04E05E06E07E08 F01F02F03F04F05F06F07F08 G01G02G03G04G05G06 H01H02 Wafer 1: good:3573% bad:1021% (?):36% Wafer 2: good:3675% bad:817% (?):48% A01A02 B01B02B03B04B05B06 C01C02C03C04C05C06C07C08 D01D02D03D04D05D06D07D08 E01E02E03E04E05E06E07E08 F01F02F03F04F05F06F07F08 G01G02G03G04G05G06 H01H02 Physical damage Failed JTAG or power Failed probe tests ? Hot/cold pixel <1% Hot/cold pixel >1% OK noisy Low VCLP Vref2 high Vref2 low

3. C.V. S.W. T.S. L.G. X.S. M.S. IPHC-LBL meeting, January 22, 2013 3 3 Yield and wafer maps – wafer 3,4 A01A02 B01B02B03B04B05B06 C01C02C03C04C05C06C07C08 D01D02D03D04D05D06D07D08 E01E02E03E04E05E06E07E08 F01F02F03F04F05F06F07F08 G01G02G03G04G05G06 H01H02 Wafer 3: good:1225% bad:3573% (?):12% Wafer 4: good:2654% bad:1940% (?):36% A01A02 B01B02B03B04B05B06 C01C02C03C04C05C06C07C08 D01D02D03D04D05D06D07D08 E01E02E03E04E05E06E07E08 F01F02F03F04F05F06F07F08 G01G02G03G04G05G06 H01H02 Physical damage Failed JTAG or power Failed probe tests ? Hot/cold pixel <1% Hot/cold pixel >1% OK noisy Low VCLP Vref2 high Vref2 low

4. C.V. S.W. T.S. L.G. X.S. M.S. IPHC-LBL meeting, January 22, 2013 4 4 Yield and wafer maps – wafer 5 A01A02 B01B02B03B04B05B06 C01C02C03C04C05C06C07C08 D01D02D03D04D05D06D07D08 E01E02E03E04E05E06E07E08 F01F02F03F04F05F06F07F08 G01G02G03G04G05G06 H01H02 Wafer 5: good:3573% bad:1225% (?):12% Physical damage Failed JTAG or power Failed probe tests ? Hot/cold pixel <1% Hot/cold pixel >1% OK noisy Low VCLP Vref2 high Vref2 low

5. C.V. S.W. T.S. L.G. X.S. M.S. IPHC-LBL meeting, January 22, 2013 5 5 Summary Probe testing of these 5 wafers took approximately 9 days Sensor selection based on hot/cold pixel counting + visual inspection of threshold scan plots – Selecting sensors with <1% of bad pixels The goal is to replace “visual inspection” with automated database queries using parameters such as: – Noise, FPN, threshold, and their distributions From the 5 wafers tested (240 sensors), we have selected 136 (primary) + 15 (optional/backup) chips – Final sensor yield is ~63% We are in the process of constructing 13 additional ladders using these sensors