Recent Advances and Challenges in Nanoparticle Monitoring for the Semiconductor Industry. December 12, 2013
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1 Recent Advances and Challenges in Nanoparticle Monitoring for the Semiconductor Industry December 12, 2013
2 Agenda Introduction Wafer Environment Nano-Contamination Requirements State-of-the-Art Monitoring Solutions Aerosol/Gas Ultra-Pure Water Chemicals Airborne Molecular Contamination Conclusions
3 Background Founded in 1972 Invented the first laser-based particle counter Technology leader, holding more than 40 patents Global focus with local service and support in more than 70 countries Acquired by Spectris in 1996 London Exchange SXS 1.24B in 2012; ~7600 worldwide employees
4 Global Leader in Micro-Contamination Monitoring Products Particle Monitors Molecular Contamination Analyzers Nanoparticle Counters Microbiological Monitors Services What We Do Innovate Design Manufacture Service Educate
5 Wafer Environment Nano- Contamination Requirements 2013 ITRS Key Challenge for Yield Enhancement Determine process stability vs. absolute contamination levels Requires data for correlating defects caused by wafer environment/handling to yield Ultimately requires data to determine control limits for contamination in air, gases, chemicals, and ultrapure water Nanoparticle monitoring advances have recently been achieved to provide appropriate data Determination of contamination in the wafer environment is the necessary first step toward understanding and reducing defects caused by the wafer environment
6 Aerosol Particle Counter for 10 nm 10 nm Nanoparticle Counter, NPC-10 Able to detect contamination events unseen at 100 nm CPC technology designed for production monitoring Real-time data Low zero count for clean environments Unique Technical Characteristics Continuous recycling of working fluid High flow rate - better counting statistics Low background noise - ISO Class 1 Inert gas monitoring capability PMS CPC provides production worthy continuous monitoring
7 The Monitoring Gap ITRS critical or killer particle size is shrinking with device geometry Year Critical Particle Size (nm) Nanoparticles may condense/grow via AMC interactions KLA-Tencor Data PMS Data
8 Nanoparticle Growth From Mike Lercel s Presentation, 4/16/2013
9 Nanoparticle Counter: Making the Invisible Visible
10 Summed Particle Counts Over 8 Hours Location > 100 nm > 10 nm 10 nm/100nm Ratio A. Etch B. Chemical Hood C. Coater/Developer D. Stocker A large ratio of 10 nm:100 nm suggests particle generation in cleanroom/mini-environment Chemical formation
11 Laboratory Tests: ISO Class 1-4 Laboratory Test Bench Setup to Create Different ISO Class Levels The 10 nm Counter Out Counts the 100 nm Counter by a Greater Margin as the Environment becomes Cleaner Instrument (Particle counts per m3) ISO Class 1 ISO Class 2 ISO Class 3 ISO Class 4 Lasair II ,480 NPC10 unit ,160 17,719 Results Summary Count ratio NPC10 vs Lasair II Differential Particle Counts per m^3 0.1µm 0.2µm 0.3µm 0.5µ 1.0µm 5.0µm Class 1 test Class 2 test Class 3 test Class 4 test 3,
12 Pressurized Gas Monitoring with PMS Nanoparticle Counter
13 25 nm Monitoring in Ultrapure Water Ultra DI nm sensitivity 4 size channels (25, 50, 70, 100 nm) Flow Rate 40 ml/min Digital LCD screen Stainless steel enclosure: (d,w,h) (43 x 43 x 27 cm) Now with 25 nm sensitivity
14 Improved Detection of All Particles
15 UDI-25 vs. UDI nm filtration UDI-25: 986 particles/l, >25 nm UDI-50: 71 particles/l, >50 nm
16 UDI-25 vs. UDI-50: Comparison of 50 nm Channel Filter bypass 100 ml/min
17 40 nm Particle Counting in Chemicals Use proprietary digital imaging technology Divide sample volume into thousands or millions of parts Digitize signal No longer analog Allows correction for background light scattering 40, 70, 100, 125 nm channels In-Line UltraChem 40 Syringe Sampler SLS-1040
18 Limiting Factor in Traditional Chemical Particle Counters Molecular scattering from carrier fluid creates noise Scattering often much stronger than signal DC signal is blocked, noise is from variations in the background Noise is proportional to the square root of DC level Water molecules in 1 mm scatter ~2 times more light than a 50 nm particle
19 Using NanoVision Technology to Monitor High Molecular Scatter Chemicals Photoresist Solvent A (monitor mode) Typical of high-scatter fluid image Saturated detector elements (white)
20 NanoVision Technology Signal Processing Raw Background with particles Raw Background (Reference Frame) Background Subtracted Particle Fingerprints
21 Raw images of 100nm and 70 nm particles 100 nm 70 nm
22 Using NanoVision Technology to Monitor High Molecular Scatter Chemicals Photoresist Solvent A (high scatter mode) High scatter mode enables particles to be detected when traditional particle counters would be blinded by molecular light scattering
23 Distinct Advantages of NanoVision Technology over Traditional Analog Methods Signal Discrimination Light scattered by a particle exhibits a predictable and repeatable fingerprint that travels in the direction of the flow Now possible to discern the particle light scatter fingerprint from traditional noise sources Molecular scatter of the fluid Random stray high energy photons (cosmic rays) High Sensitivity and Good Resolution Large Sample Volume % Less time to obtain statistical significance in ultra-clean systems Less Susceptibility to Contamination on Capillary Walls Reference frame generation periodically adjusts to changes Visual Troubleshooting/Data Verification See what the particle counter sees
24 Particle Measuring Systems AMC Began AMC Monitoring in 1999 Acquisition of Molecular Analytics in 2004 Recent product AirSentry II Ion Mobility Spectrometer (IMS) technology with Ionization Control Reagents ~2,000 AMC Analyzers in the Field Heavy use in leading semiconductor manufacturing facilities Used by all top 10 semiconductor companies Industry experts in continuous AMC monitoring
25 AMC Challenges Yield losses vary by species and process step Direct product impact T-Topping Thin Film Adhesion Corrosion Tool performance impact Optical Hazing Wafer Pod Contamination Species characteristics influence ideal monitoring solution AMC species impacting product and tool performance
26 AMC Monitoring Considerations Sample collection methodologies Types time stamp Short term event ID Long-term event ID Data accuracy Cost / Point Cost / Measure Human Error Real-Time Solutions Continuous Point of use EXCELLENT EXCELLENT EXCELLENT EXCELLENT HIGH LOW LOW Non-Continuous Manifolds MEDIUM POOR EXCELLENT MEDIUM MEDIUM LOW LOW Laboratory Solutions Grab samples Impingers POOR POOR EXCELLENT EXCELLENT LOW HIGH HIGH Sorbent Tubes POOR POOR EXCELLENT EXCELLENT LOW HIGH HIGH Test Wafer POOR POOR EXCELLENT EXCELLENT LOW HIGH HIGH Witness Pieces POOR POOR EXCELLENT EXCELLENT LOW HIGH HIGH Application requirements drive different ideal solutions
27 Guidelines for AMC Monitoring Not everywhere in the cleanroom has the same risk level monitoring strategy should be flexible Monitor locations where sensitive products or processes are located Monitor locations near potential AMC sources in the cleanroom Make-up air Process areas using chemistries known to be contamination issue Rule of Thumb If a process or area is important enough to require chemical filtration or purge gas, it is important enough to require AMC monitoring to verify contamination levels Without Measurement There is No Control
28 New AMC Monitoring Strategies Classifying cleanroom, equipment, and process into critical and non-critical points for AMC monitoring Critical locations require more stringent monitoring requirements Non-critical locations have more relaxed monitoring requirements The difference between these two classifications is driving new tactics and monitoring methodologies Critical Locations Requirements: High Sensitivity (pptv) Real-time Data (< 5 minutes) Point-of-Use Locations Photolithography Reticle/Wafer Stockers, Chemical Filters, Etch, Clean, CMP Process Areas Make-up Air Handlers, EFEM Non-Critical Locations Requirements: Good Sensitivity (ppbv) Periodic Data (2-3 times/day) Area Monitoring with Manifold Locations Recirculation Air Handlers Process Bays (Diffusion, Inspect, etc.) Cleanroom Environmental Trending Troubleshooting is most effective with AMC Mobile Cart monitoring
29 AMC Monitoring Approaches Critical - Continuous Continuous data for critical locations Best limit of detection (70 pptv) NH 3, Amines, Acids, Cl x Cost / sample ~$0.04 Troubleshooting - Mobile Rapid identification of AMC sources On-board Vacuum & CDA generation Cost / sample ~$ ~$0.17 (1-3 chemistries) Non-Critical, Semi-continuous Permanent, periodic monitoring Up to 30 sample points 75 m sample lengths NH 3, Amines, Acids, Cl x, HF, SO 2 Cost / sample ~$ ~$0.57 (1-3 chemistries)
30 Continuous vs. Weekly Monitoring Weekly impinger sample taken over a 6 hour period
31 Ammonia Data Time Plot Ammonia Concentration Monitoring in Photo Bay Ammonia (ppb) Monitoring Adhesion Area of Track Tool Down for PM New Oven Process Starts 12/17 12/19 12/21 12/23 12/25 12/27 12/29 12/31 1/2 1/4 1/6 1/8 1/10 1/12 1/14 1/16
32 AMC Detection Thin Films Monitoring Thin Film process bay CVD Tool - Ar, N 2, H 2, He, TDMAT TDMAT is a liquid precursor used in Titanium Nitride barrier coatings AirSentry II Amines analyzer detects spikes Spikes correlate to production activity Ammonia & Dimethylamine are byproducts of process Vented into cleanroom when opening chamber
33 Conclusions Key Challenge for Yield Enhancement is to Determine Process Stability vs. Absolute Contamination Levels This requires data for correlating defects caused by wafer environment/handling to yield Ultimately requires data to determine control limits for contamination in air, gases, chemicals, and ultrapure water Nanoparticle monitoring advances have recently been achieved to provide appropriate data Determination of contamination in the wafer environment is the necessary first step toward understanding and reducing defects caused by the wafer environment
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