LED Production Yield Improvement Through Advanced In-Situ Metrology. Tom Thieme director marketing & sales

Transcription

1 LED Production Yield Improvement Through Advanced In-Situ Metrology Tom Thieme director marketing & sales

2 2 Outline - Introduction - In-situ metrology the concept - Up-time: fault detection and rapid root cause analysis - Yield: substrate evaluation and low defect buffers - Yield: tight control of InGaN MQW active layers - Yield: LED cap layer and final wafer bow - Summary 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology

3 3 Outline - Introduction - In-situ metrology the concept - Up-time: fault detection and rapid root cause analysis - Yield: substrate evaluation and low defect buffers - Yield: tight control of InGaN MQW active layers - Yield: LED cap layer and final wafer bow - Summary 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology

4 [$/µm*cm²] Introduction 4 Cost demands for LED manufacturing DOE SSL manufacturing roadmap: 2012 revision 0,5 0,4 0,3 0,2 0,1 0 Epitaxy cost Cost break down of packaged LEDs Epitaxy cost degradation by DoE SSL Epitaxy costs need to shrink to 10% of 2010 level!

5 Introduction 5 LED production mathematics yield of back-end reactor loading capacity # of reactors aver. LED selling price total costs of running the fab average yield up up-time ratio up This is where in-situ directly raises profits! Profit = Revenue - Costs LED production rate can be raised by: higher yield, higher up-time and shorter run-times!

6 Average deviation from target WL [nm] Epi Wafer % (2" equival.) LED Efficacy (w w, lm/w) Introduction 6 In-spec criteria getting tighter year-by-year! " " 0 2" More complex LED structures More challenging processes WIW + W2W + R2R WIW + W2W WIW Tighter uniformity targets See talk by Ivan TSOI, Philips Lumileds: Freedom from Binning Enhance LED to LED Consistency Data according to DoE SSL road-map and LEDinsight 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology

7 7 Outline - Introduction - In-situ metrology the concept - Up-time: fault detection and rapid root cause analysis - Yield: substrate evaluation and low defect buffers - Yield: tight control of InGaN MQW active layers - Yield: LED cap layer and final wafer bow - Summary 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology

8 In-situ metrology concept 8 Correlation of in-situ and LED parameters LED cross section Accessed in real-time by in-situ metrology Cap layer quality Surface morphology Final wafer bow MQW InGaN composition Growth rate & thickness GaN buffer quality and initial substrate bow - Nucleation layer - Recovery time - Growth rate & thickness - Surface morphology Optical & electrical properties (final LED) Outcoupling efficiency Emission wavelength and intensity Emission intensity, defect density, WIW uniformity

9 Temperature / C Reflectance In-situ metrology concept 9 Real time in-situ metrology data generation Substrate Buffer MQW Cap LED cross section Curvature / km Time / s 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology 26 March 2013

10 10 Outline - Introduction - In-situ metrology the concept - Up-time: fault detection and rapid root cause analysis - Yield: substrate evaluation and low defect buffers - Yield: tight control of InGaN MQW active layers - Yield: LED cap layer and final wafer bow - Summary 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology

11 Up-time: fault detection & rapid root cause analysis 11 Traffic lights: real-time information to operator - Specs, control limits & traffics lights - Example: growth temperature after stabilization

12 Up-time: fault detection & rapid root cause analysis 12 Traffic lights: real-time information to operator - Specs, control limits & traffics lights - Example: growth temperature after stabilization Out of control limits

13 Up-time: fault detection & rapid root cause analysis 13 Traffic lights: real-time information to operator - Specs, control limits & traffics lights - Example: growth temperature after stabilization Out of spec limits

14 Up-time: fault detection & rapid root cause analysis 14 Production environment (EpiGuard ) - Tool specific or central software control option - Real time in-situ process data supervision - Remote in-situ data analysis and control - Data base for SPC and traceability - Metrology data of all major MOCVD systems can be integrated. SECS/GEM or Interface A Office PC SECS/GEM or Interface A Data base SECS/GEM or Interface A SECS/GEM or Interface A

15 Up-time: fault detection & rapid root cause analysis 15 Failure detection and analysis EpiGuard In which MOCVD? In which step? Detailed root cause analysis by process engineer In which pocket?

16 16 Outline - Introduction - In-situ metrology the concept - Up-time: fault detection and rapid root cause analysis - Yield: substrate evaluation and low defect buffers - Yield: tight control of InGaN MQW active layers - Yield: LED cap layer and final wafer bow - Summary 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology

17 Substrate evaluation and low defect buffers 17 Substrate sorting and defect density Defect density: Number and size of the GaN grains can be correlated to the reflectance recovery time after NL as well as the buffer layer curvature slope. (acc. to F. Brunner et al, JCG 310 (2008)) Substrate sorting: Quality variation of incoming wafers maintain throughout entire LED growth run Pre-sorting of substrates reduces W2W variation. Defect level, influencing LED brightness, is seen in in-situ data! 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology

18 Substrate evaluation and low defect buffers 18 InGaN/Si LEDs: defect density reduction MQW GaN:Mg GaN:Si LT-AlN GaN:Si AlN SiN x -mask GaN Al x Ga 1-x N AlN nucleation Si(111) x=0.2 x=0.4 x=0.6 x=0.8 Strain engineering supervised by in-situ curvature Acc. to: A. Krost et al., JCG 275 (2005) Complex device structures require advanced-resolution bow sensing

19 19 Outline - Introduction - In-situ metrology the concept - Up-time: fault detection and rapid root cause analysis - Yield: substrate evaluation and low defect buffers - Yield: tight control of InGaN MQW active layers - Yield: LED cap layer and final wafer bow - Summary 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology

20 Tight control of InGaN MQW active layers 20 Curvature, temperature and LED uniformity Emission D ~ 7nm In variation: ~1.3% Indium content Emission D ~ 25nm In variation: ~ 5% T variation: ~ 7K Wafer temperature T variation: ~ 20K Bow: 13µm Wafer curvature: 40 km -1 Bow: 50µm 2 Uniform pocket temperature 4

21 Tight control of InGaN MQW active layers 21 Curvature, temperature and LED uniformity Emission D ~ 7nm In variation: ~1.3% Indium content Emission D ~ 56nm In variation: ~ 11% T variation: ~ 7K Wafer temperature T variation: ~ 45K Bow: 13µm Wafer curvature: 40 km -1 Bow: 112µm 2 Uniform pocket temperature 6

22 Tight control of InGaN MQW active layers 22 Curvature, temperature and LED uniformity Zero Curvature: uniform InGaN composition 405nm Reflectance: MQW thickness monitored desorp. nucl. GaN buffer MQW cap QW 1... QW 5 Advanced resolution wafer bow measurement and 405nm reflectance take MQWs growth under tight control. 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology

23 Tight control of InGaN MQW active layers 23 UV pyrometry: Real GaN surface temperature - Wafer temperature scan at InGaN MQW (700 C) - Resolution at 700 C ±1K, repeatable - Ready for direct temperature feedback control Pyro 400 at work Precise temperature measurement and control enables 1nm emission wavelength W2W and R2R uniformity. 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology

24 Tight control of InGaN MQW active layers 24 Pyro 400: Real InGaN surface temperature vs. PL Pyro 400 Gen2 Now available! Visit us at booth 2304! R² > 0.9 (typical) > 90% correlation within the 1 nm range Precise correlation between InGaN MQW temp and PL (R² > 0.9)

25 25 Outline - Introduction - In-situ metrology the concept - Up-time: fault detection and rapid root cause analysis - Yield: substrate evaluation and low defect buffers - Yield: tight control of InGaN MQW active layers - Yield: LED cap layer and final wafer bow - Summary 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology

26 LED cap layer and final wafer bow 26 Multiple reflectance for cap layer analysis 633nm LED cross section thickness p-gan cap layer 405nm morphology p-gan cap layer: thickness and surface morphology is watched

27 curvature / km LED cap layer and final wafer bow Wafer bow during and after down-cooling desorp. nucl. GaN buffer MQW cap down-cool 100 LED cross section time / s Down-cooling of the final LED structure: - Thermal stress can cause relaxation. - Final bow can hinder further processing.

28 LED cap layer and final wafer bow 28 GaN/Si: strain engineering for minimum final bow - Process optimization by monitoring curvature - Shortening R&D cycles reduces implementation costs 1. LT AlN IL growth - time variation 2. LT AlN IL growth - temp. variation 45 sec 75 sec 150 sec 750 C 860 C 890 C flat at RT Data courtesy of S.Fritze; University Magdeburg

29 29 Outline - Introduction - In-situ metrology the concept - Up-time: fault detection and rapid root cause analysis - Yield: substrate evaluation and low defect buffers - Yield: tight control of InGaN MQW active layers - Yield: LED cap layer and final wafer bow - Summary 20 March 2013 LED Production Yield Improvement Through Advanced In-Situ Metrology

30 Summary 30 Optimized LED recipes using LayTec systems - Excellent PL results after process optimization WIW wavelength uniformity ±3 nm WIW wavelength uniformity ±1.5 nm WIW wavelength uniformity ±3 nm (incl. Edge exclusion) LayTec metrology systems enable highest LED emission wavelength uniformity (WIW, W2W, R2R).

31 Summary 31 - Increased LED production yield by advanced in-situ metrology - Improved emission wavelength uniformity, LED intensity and outcoupling efficiency for LEDs - Real time epi process optimization of the entire LED devices via: - Substrate quality inspection, - Nucleation and GaN buffer optimization, - Precise MQW temperature control, - Cap layer improvement and final wafer bow reduction - Increase amount of KGD accelerates ROI for metrology - Up time improvement by sustainable SPC and fast FDC

32 Knowledge is key