Single-Wafer Wetting Chamber: Chemical Dispense, Rotation, Film Thickness & Uniformity Analysis
CURRENT RECIPE:RCP-001Rev.01Default Single Wetting● MODIFIED
SOLVER 가동 중
FPS: 60
Δt: 5.0 ms
Sim Time: 00:00:00
PROCESS:Single Wafer Wetting
WAFER:Ø300 mm Silicon
NOZZLES:1 Active (N1 Center)
SPIN:100 RPM
CHEMICAL:DI Water (100%)
FLOW:15.0 mL/s
TEMP:25 °C
STATUS:● RUNNING
300mm 웨트 챔버 시뮬레이터: 웨이퍼 액막 두께 및 균일도 분석
300mm 반도체 단일 웨이퍼 습식 챔버 시뮬레이터에 오신 것을 환영합니다. 본 엔지니어링 툴은 첨단 반도체 제조 공정에서 약액 토출(Chemical Dispense), 웨이퍼 회전(Wafer Rotation), 원심력에 의한 방사상 전파(Radial Spreading), 액막 형성(Film Formation), 공간적 2D 액막 두께 분포(Film Thickness Map), 박막 균일도(Film Uniformity), 마랑고니 대류 및 비젖음(Dewetting Risk)을 정밀하게 분석하고 최적화할 수 있도록 설계된 축소차수(Reduced-Order) LUB-2D 윤활 이론 해석기입니다.
[Marangoni 재분포 및 비젖음 위험(Dewetting Risk) 한국어 해석 (Korean Engineering Conclusion)]
⚠️ Scientific Model & Engineering Limitation:
Marangoni-induced dewetting is represented as a reduced-order stability screening model.
Actual dewetting depends on wettability, contact angle, surface condition, chemical composition,
film thickness, evaporation, temperature, surface-tension gradients and transient flow.
⚖️ZONE E: MULTI-OBJECTIVE PROCESS OPTIMIZATION & BENCHMARKING
PARETO OPTIMIZATION & 4-CASE OVERLAY
⚖️V13.4-4 다목적 공정 최적화기 (Multi-Objective Process Optimizer)
📈Pareto Optimization Plot (X: Film Uniformity vs. Y: Dewetting Risk)Evaluated: 0 | Pareto Optimal: 0
• Legend: 💎 Pareto Front (Non-dominated) | ⭐ Best Balanced | ⭕ Current Baseline | 🔹 CandidatesClick any point to select
★ BEST BALANCED CONDITIONRank 1
Candidate Flow Distribution:
N1: 1500 / N2: 1000 mL/min (60:40)
1. Uniformity
82.5%
2. Thickness Range
717.4 µm
3. Dewetting Risk
0.24
4. Marangoni Risk
3.12 mm/s
Engineering Optimization Score (Higher = Better)
84.6 / 100 pts
*Only modifies chamber settings upon clicking this button.
[4. 주요 공정 조건 후보군 비교 (Key Candidate Solutions Comparison Deck)]*Do not call "Absolute Optimal" because result depends on weights & model
[5. 상위 후보군 종합 평가표 (Top Ranked Multi-Objective Candidates Table)]Click row to inspect or apply
Rank
Candidate Type
Flow Distribution (mL/min)
Uniformity (%)
Range Δh (µm)
Dewetting Risk
Marangoni Risk
Total Score
Pareto Status
Action
Press "Run Multi-Objective Optimizer" to evaluate candidate flow distributions across the 4 engineering objectives.
📋[다목적 공정 최적화 종합 엔지니어링 해석 결론 (Korean Engineering Conclusion)]
다목적 최적화 탐색을 실행하여 4가지 공정 지표(Film Uniformity, Thickness Range, Dewetting Risk, Marangoni Risk)의 종합 가중치 평가 및 Pareto Front 해를 도출하십시오.
⚠️ Scientific Model & Engineering Limitation:
The optimization result is dependent on objective weights and the current reduced-order engineering model.
Multi-objective trade-off frontiers are computed based on 2D depth-integrated lubrication approximations (LUB-2D) and simplified Marangoni instability screening. Final recipe deployment should be validated with chamber metrology.
📁V13.4-5 공정 조건 비교 분석기 (Process Case Comparison & Radial Overlay)
Snapshot & LocalStorage Persistence
Up to 4-Case Radial Overlay
📸 [1. 현재 챔버 상태 스냅샷 저장 (Save Case Snapshot)]
Saved: 0 Cases
📋 [2. 저장된 공정 케이스 목록 (Case List & Compare Selection)](Select up to 4 cases to compare)Selected: 0 / 4
Compare
Tag
Case Name & Time
RPM / Temp
Nozzle / Chem / Flow
Uniformity
Avg h̄ (µm)
Dewet Risk
Re / We
Actions
No saved cases found. Click "Save Current State as Case" or "Reset Benchmark Presets".
📈[3. 반경별 액막 두께 중첩 비교 곡선 (Radial Film Thickness Overlay: h(r) Curve Comparison)]Hover to inspect exact thickness at radius r
Radius r = 0 mm (Center)r = 75 mm (Mid)r = 150 mm (Edge / Bevel)
📍 Radial Probe Cursor
Radius: r = 75.0 mm
Active Compared Cases:
[4. 공정 조건 및 지표 다중 비교 분석표 (Side-by-Side Comprehensive Comparison)]
Compared parameters & physics metrics (Up to 4 Cases)
📋[공정 조건 비교 종합 엔지니어링 결론 (Korean Comparison Conclusion)]
비교할 케이스를 2개 이상 선택(체크)하면 각 조건 간 액막 균일도, Dewetting Risk, Marangoni 속도, Re/We 무차원 수의 정량적 비교 결론이 자동 산출됩니다.
ℹ️ Process Case Storage & Metrology Notice:
Cases are saved directly into browser LocalStorage. Loading a case restores the complete chamber state (RPM, Temperature, Nozzle geometry, and flow rates). All comparative values are calculated dynamically using the unified physical solver.
📋ZONE F: DYNAMIC PROCESS ENGINEERING CONCLUSION & REPORT
SEMI E10 APC & METROLOGY SUMMARY
📑
300mm SEMICONDUCTOR PROCESS ENGINEERING ANALYSIS REPORT
Simulation Type:Reduced-Order Engineering ModelPurpose:Relative Process ScreeningTarget Wafer:300 mm Silicon Wafer (R=150 mm)Doc ID:RPT-2026-0813-01
[Calculated Values (수치 계산값)]: 챔버 작동 파라미터(RPM, 온도, 노즐 좌표, 토출 유량) 및 1D/2D 정상상태 연속방정식·무차원수($Re, We$) 기반 결정론적 물리 수치입니다.
[Engineering Screening (엔지니어링 스크리닝)]: 삭감 차원 모델(Reduced-Order Engineering Model)에 기반하여 비젖음(Dewetting), 마랑고니 대류, 국소 박막화 위험도를 신속 스크리닝하기 위한 상대 비교 지표입니다.
[Interpretation (공정 해석)]: 공정 엔지니어의 레시피 튜닝을 보조하기 위한 모델 기반 추론 가이드입니다.
중요 고지: 본 보고서에 제시된 스크리닝 결과는 실험적으로 최종 검증된 양산 장비 실측 예측값이 아니며, 공정 레시피 후보군 탐색 및 상대적 거동 비교(Relative Screening) 목적으로만 활용되어야 합니다.
🎯Nozzle Position Optimizer (V13.3-5)
Engineering Screening | Lightweight Reduced-Order Sweep
→
→
🗺️ Candidate Position Score Map & Top Ranking ComparisonCandidates evaluated: 0
[Top 5 Candidate Position Sweep Results Table]
Rank
X (mm)
Y (mm)
Uniformity (%)
Thickness Range (µm)
Dewetting Risk
Score
Action
Press "Run Nozzle Sweep" to evaluate candidate nozzle positions.
[노즐 위치 최적화 결과 및 공정 제언 (Korean Optimization Conclusion)]
탐색 버튼을 클릭하여 선택한 노즐 위치 범위에 대한 최적 배치 및 액막 품질 평가를 수행하십시오.
⚠️ Model Limitation:
Optimization is based on the current reduced-order model and should be interpreted as engineering screening.
💧Nozzle Flow Balance Optimizer (V13.3-6)
Flow Ratio Distribution Sweep | Constant Total Flow
📊 Flow Rate Ratio vs. Film Uniformity & Optimization Score ChartDistributions tested: 0
[Top Candidate Flow Distribution Results Table]
Rank
Flow Rates (mL/min)
Flow Ratio (%)
Uniformity (%)
Thickness Range (µm)
Dewetting Risk
Score
Action
Press "Run Flow Ratio Sweep" to evaluate candidate flow distributions.
[노즐 유량 분배 최적화 결과 및 공정 제언 (Korean Flow Optimization Conclusion)]
탐색 버튼을 클릭하여 총 유량 조건에 대한 노즐 간 최적 유량 분배 비율을 평가하십시오.
⚠️ Model Limitation:
Flow distribution optimization is based on the current reduced-order film thickness and Marangoni stability screening model.
🔬 SCIENTIFIC MODEL & ENGINEERING LIMITATIONS (CLICK TO TOGGLE)
⚠️ Model Scope & Limitations
• Reduced-Order Model: Uses 2D depth-integrated lubrication approximation (LUB-2D).
• Not 3D CFD / VOF: Does not resolve 3D navier-stokes or explicit phase-volume tracking.
• Representative Properties: Chemical physical constants are reference baseline values.
• Reaction Kinetics: Multi-chemical reaction enthalpy or complex phase changes are not explicitly modeled.
• Equipment Calibration: Actual chamber matching requires empirical process calibration constants.
① Continuous Spin Film Equation
h(r) = [ 3μQ / (2πρω²) ]1/3 · r-2/3
Balance between centrifugal force and viscous shear stress in steady-state spin coating (Emslie, Bonner, Peck 1958).
② Viscosity Temperature Dependency
μ(T) = μ25 · exp( -B · (T - 25) )
Andrade viscosity fitting model for thermal processing effects.
The 300mm Wet Chamber Simulator employs a depth-integrated, reduced-order physical framework designed to provide rapid, interactive insights into single-wafer semiconductor wet processing. Rather than solving transient, multi-phase 3D Navier-Stokes equations with Volume-of-Fluid (VOF) surface capturing—which typically requires hours of high-performance computing (HPC) time per process second—this tool uses an analytical and numerical Lubrication Approximation (LUB-2D) framework tailored for thin-film rotational flows.
1. Coordinate Systems: Chamber-Fixed vs. Wafer-Relative Rotating Frame
In an industrial 300mm single-wafer wet spin chamber, chemical dispensing nozzles are mounted on rigid swing arms positioned above the substrate at fixed Cartesian coordinates $(x_{\text{nozzle}}, y_{\text{nozzle}})$ relative to the stationary chamber bowl. As the wafer rotates at angular speed $\omega = \frac{2\pi \cdot \text{RPM}}{60}$, points on the substrate surface sweep beneath the dispense stream in a circular trajectory. The simulation transforms stationary nozzle discharge fluxes into rotating wafer-relative polar coordinates $(\tilde{r}, \tilde{\theta})$ through continuous azimuthal averaging and transient Lagrangian trace integration:
2. LUB-2D Thin Liquid Film Formulation & Radial Transport
Assuming the liquid film thickness $h(r) \ll R_{\text{wafer}}$ (typically $10\,\mu\text{m} \le h \le 800\,\mu\text{m}$ compared to wafer radius $R=150\,\text{mm}$), the Navier-Stokes equations simplify under boundary-layer lubrication scaling. The momentum balance in the radial direction equates centrifugal body force to viscous shear stresses:
$\rho \omega^2 r + \mu \frac{\partial^2 u_r}{\partial z^2} = 0 \quad \implies \quad u_r(z) = \frac{\rho \omega^2 r}{\mu} \left( h z - \frac{1}{2} z^2 \right)$
Integrating the parabolic velocity profile across the depth $z \in [0, h]$ yields the radial volumetric flux $q_r(r) = \int_0^h u_r(z) dz = \frac{\rho \omega^2 r h^3}{3 \mu}$. In steady state with a continuous volumetric inflow $Q$, mass continuity $2\pi r q_r(r) = Q$ leads to the classical Emslie-Bonner-Peck relationship:
Chemical viscosity varies strongly with process temperature $T$ (°C). The simulator applies an Andrade exponential fitting equation $\mu(T) = \mu_{25} \exp(-B \cdot (T - 25))$ where $B$ is the empirical thermal sensitivity constant. For multi-chemical dispense scenarios (e.g. simultaneous DHF and DIW or SC1 and SC2 mixtures), effective mixture density ($\rho_{\text{mix}}$), viscosity ($\mu_{\text{mix}}$), and surface tension ($\sigma_{\text{mix}}$) are evaluated via volume-weighted mixing rules.
Gradients in chemical species concentration ($C$) and liquid surface temperature ($T$) create spatial surface tension gradients ($\nabla \sigma = \frac{\partial \sigma}{\partial T} \nabla T + \sum \frac{\partial \sigma}{\partial C_i} \nabla C_i$). These gradients exert a tangential shear stress $\tau_{\text{surf}} = \nabla \sigma$ on the free liquid surface, inducing a Marangoni screening velocity:
When volatile solvents like IPA (low surface tension $\approx 21.7\,\text{mN/m}$) are dispensed adjacent to aqueous solutions (high surface tension $\approx 72.8\,\text{mN/m}$), intense solutocapillary Marangoni forces pull liquid toward the higher surface tension zone, creating rapid localized thinning or film retraction.
5. Dewetting Risk Screening Index ($i_{\text{Dewet}}$)
Dewetting occurs when the liquid film thickness falls below a critical stabilization margin ($h_{\text{crit}} \approx 10\,\mu\text{m}$) or when outward Marangoni stresses exceed the viscous replenishment capacity. The simulator calculates a composite dimensionless Dewetting Risk Index $i_{\text{Dewet}} \in [0, 1]$ based on local thinning ratio ($h/h_{\text{center}}$), surface tension gradient magnitude ($|\nabla \sigma|$), and local Weber number ($We = \frac{\rho u^2 h}{\sigma}$).
⚠️ Scientific Scope & Model Limitation Notice:
This simulator is a reduced-order engineering visualization and analysis tool and is not a full CFD solver. It is developed to support preliminary recipe formulation, qualitative parameter sensitivity studies, and engineering education. Industrial process qualification requires empirical chamber matching and hardware-in-the-loop experimental verification.
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📖 How to Use the 300mm Wet Chamber Simulator
Follow this comprehensive step-by-step user guide to configure recipes, evaluate thin-film hydrodynamics, optimize nozzle flow distribution, and interpret process results:
STEP 1
Set Wafer Spin Speed (RPM)
Adjust wafer rotation between 100 and 3000 RPM using the slider or numeric input. Observe how centrifugal acceleration changes radial liquid transport velocity and film thickness.
STEP 2
Set Process Temperature (°C)
Configure process discharge temperature from 10°C to 180°C. Temperature directly modifies fluid dynamic viscosity via the Andrade thermal model and changes evaporation kinetics.
Adjust nozzle discharge radius from -140 mm to +140 mm relative to wafer center. You can also drag nozzle icons directly inside the interactive Wafer Side View canvas.
STEP 5
Configure Nozzle Flow Rate
Set volumetric flow rate ($0.1 - 25.0\,\text{mL/s}$ or equivalent $\text{mL/min}$) for each active nozzle arm. Toggle unused nozzle arms ON/OFF to simulate single-arm or multi-arm recipes.
STEP 6
Run / Pause / Reset Simulation
Click "시뮬레이션 일시정지" (Toggle Play/Pause) or "초기화" (Reset). On mobile devices, use the floating sticky bottom control bar for quick single-tap execution.
STEP 7
Observe 2D Film Thickness Distribution
Examine Card 1 (2D Plan View) with 11 distinct visualization modes including Thickness Deviation, Marangoni Velocity Vectors, Chemical Concentration, and 2D Dewetting Risk Maps.
STEP 8
Evaluate Uniformity (%) & Profile
Check Card 3 (Radial Film Thickness Profile) and the Live KPI summary to evaluate center thickness ($h_0$), edge thickness ($h_{150}$), radial thickness range ($\Delta h$), and wafer uniformity.
STEP 9
Inspect Marangoni & Dewetting Behavior
Review the Marangoni vector overlay and Dewetting Warning Shader in Card 4 (Wafer Side View & Radial Film Transport) to check for edge dry patches or local liquid starvation.
STEP 10
Use Flow Balance Optimizer
Expand the Nozzle Flow Balance Optimizer panel to automatically sweep candidate flow ratios, ranking configurations by wafer uniformity (%) and minimum dewetting risk score.
STEP 11
Review Conclusion & Export Report
Read the real-time dynamic Korean engineering conclusion and export a complete PDF/Print-ready Engineering Analysis Report containing full process metrics and charts.
📊 Engineering Interpretation & Physical Concepts
What does film thickness uniformity mean?
In semiconductor single-wafer wet processing, film thickness uniformity represents the spatial consistency of the liquid boundary layer covering the 300mm silicon surface. Uniformity is quantified using the standard half-range metric:
A high uniformity value (typically $> 85\%$) indicates consistent chemical replenishment across all wafer dies from center to bevel. Poor uniformity leads to radial etch rate gradients, non-uniform particle removal efficiency, and localized chemical under-etch or over-etch defects.
What is radial liquid transport?
Radial liquid transport is the outward convective displacement of liquid chemical driven by centrifugal acceleration ($a_r = \omega^2 r$) on the rotating wafer surface. Because centrifugal acceleration increases linearly with radius $r$, liquid accelerates toward the wafer edge, driving a continuous outward thinning profile. Understanding radial transport velocity ($u_r \propto \omega^2 r h^2$) is essential for optimizing chemical residence time, boundary layer thickness, and chemical consumption efficiency.
What is the Marangoni effect (Solutocapillary & Thermocapillary)?
The Marangoni effect is mass transfer along an interface between two fluids driven by a surface tension gradient ($\nabla \sigma$). In wet processing, surface tension variations arise from:
Solutocapillary Marangoni Flow: Concentration gradients caused by dispensing chemicals with different surface tensions (e.g. IPA vs. DIW or concentrated acid vs. rinse water). Liquid is drawn from lower surface tension regions toward higher surface tension zones.
Thermocapillary Marangoni Flow: Temperature gradients across the wafer surface caused by hot chemical dispense, heated chucks, or evaporative cooling ($\frac{d\sigma}{dT} < 0$ for most liquids).
What is dewetting and why do dry spots form on rotating wafers?
Dewetting refers to the rupture and retraction of a liquid film from a solid wafer surface, resulting in dry patches or droplets. Dewetting occurs when:
Centrifugal thinning reduces the liquid film thickness below the critical stabilization threshold ($h < h_{\text{crit}} \approx 10\,\mu\text{m}$).
Marangoni shear stresses pull liquid away from local hot spots or solvent-rich regions faster than outward bulk flow can replenish it.
Evaporative loss at elevated temperatures and high spin speeds depletes the thin liquid boundary layer near the wafer bevel.
What does nozzle flow balance mean in multi-arm single-wafer chambers?
In advanced multi-nozzle wet chambers, dispensing chemical from a single central nozzle often results in excessive center film thickness ($h_{\text{center}} > 600\,\mu\text{m}$) and inadequate edge coverage ($h_{\text{edge}} < 30\,\mu\text{m}$). Nozzle flow balance is the strategic division of total volumetric flow ($Q_{\text{total}}$) among center, mid-radius, and outer-radius nozzle arms. Allocating a fraction of the chemical flux to mid-radius nozzles compensates for centrifugal thinning, significantly improving wafer-wide thickness uniformity and mitigating edge dewetting risks.
What is the physical relationship between wafer RPM and radial liquid transport?
Wafer spin speed (RPM) exerts a quadratic influence on centrifugal body forces ($F_{\text{cent}} \propto \omega^2$). Under steady-state lubrication theory, liquid film thickness scales inversely with angular velocity:
Doubling spin speed from 500 RPM to 1000 RPM increases outward radial velocity by approximately $58.7\%$ and decreases film thickness by approximately $37.0\%$, reducing chemical residence time on the substrate surface.
❓ Frequently Asked Questions (FAQ)
Q1. What is a 300mm wet chamber simulator?
A 300mm wet chamber simulator is an engineering software tool that models liquid chemical dispensing, rotational fluid dynamics, centrifugal radial transport, and thin-film flow behavior on a rotating 300 mm silicon semiconductor wafer during wet cleaning, etching, stripping, and rinsing processes.
Q2. How does wafer spin affect liquid film transport?
Wafer spin imparts a centrifugal body force proportional to mass density, angular velocity squared (omega^2), and radius. This centrifugal acceleration drives liquid radially outward across the wafer surface against viscous shear resistance at the substrate boundary.
Q3. How does nozzle position affect film thickness?
Nozzle position determines the local chemical source radius. Dispensing near the wafer center allows centrifugal force to spread liquid across the entire radius, whereas outer nozzle positions reinforce edge film thickness but do not supply chemical inward.
Q4. How does nozzle flow rate affect uniformity?
Higher volumetric flow rates increase convective film thickness according to lubrication theory (h ~ Q^(1/3)). Balanced flow rates across center and intermediate nozzle arms minimize radial thickness variance and improve film uniformity.
Q5. What is Marangoni-driven dewetting?
Marangoni-driven dewetting occurs when gradients in chemical concentration or temperature create surface tension gradients (grad sigma). Liquid flows from regions of low surface tension toward high surface tension, potentially causing local film thinning and dry patch formation.
Q6. Why can a rotating wafer develop non-wetting regions?
Non-wetting regions (dry spots or dewetting) develop when centrifugal thinning reduces film thickness below a critical stability threshold, or when surface tension gradients and high evaporation rates overcome fluid replenishment.
Q7. How does the simulator estimate film thickness?
The simulator uses a 2D depth-integrated lubrication approximation (LUB-2D) coupled with steady-state continuous spin-coating theory (Emslie-Bonner-Peck model), temperature-dependent Andrade viscosity, and radial superposition of multi-nozzle chemical sources.
Q8. What is the Flow Balance Optimizer?
The Flow Balance Optimizer is an automated engineering tool that sweeps candidate flow rate allocations across active nozzles to find flow ratios that maximize wafer-wide film thickness uniformity and minimize dewetting risk.
Q9. Is this simulator a CFD simulation?
No. This simulator is a reduced-order engineering analysis and visualization tool based on lubrication theory and analytical fluid dynamics approximations, rather than a 3D full Navier-Stokes CFD solver.
Q10. Can the simulator be used for process engineering studies?
Yes. It serves as an effective engineering pre-screening and qualitative sensitivity analysis tool for evaluating nozzle configurations, spin recipes, temperature effects, and chemical combinations prior to physical chamber testing.
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ℹ️ About This Simulator
The 300mm Wet Chamber Simulator was created to bridge the gap between high-overhead 3D CFD simulations and empirical fab trial-and-error in semiconductor wet processing. In advanced nodes (GAA FETs, EUV patterning cleans, high-aspect-ratio 3D NAND contact etching), wet chemical delivery requires fine-grained balance between spin recipe, nozzle positioning, and multi-chemical interactions.
What the model represents: Reduced-order depth-integrated lubrication theory, continuous rotating wafer source transformations, thermal viscosity scaling, solutocapillary/thermocapillary Marangoni screening, and multi-objective flow balancing.
What the model does not represent: Turbulent gas-liquid droplet atomization, full 3D Volume-of-Fluid (VOF) free-surface splashing, reactive chemical kinetics (e.g. exothermic reaction heat generation), or chamber bowl exhaust aerodynamics.
🔒 Privacy Policy & Consent Preferences
We value your privacy and transparency. This Privacy Policy details our data processing practices for this engineering simulation platform:
1. Local Browser Storage: This application utilizes window.localStorage exclusively on your client device to preserve customized process recipes, nozzle spatial coordinates, and selected UI view preferences. This data remains on your local machine and is never transmitted to or stored on external servers.
2. Google AdSense & Advertising Cookies: We use Google AdSense to serve non-intrusive advertisements. Google and its certified third-party advertising partners utilize cookies (including the DoubleClick cookie) to serve ads based on user visits to this website and other websites across the Internet. You can learn more, opt out of personalized advertising, or customize your ad settings at Google Ads Settings.
3. European Economic Area (EEA), UK & Switzerland Consent: For users in the EEA, United Kingdom, and Switzerland, advertising consent is managed via Google-certified Consent Management (Privacy & Messaging CMP). Where applicable, the Google consent dialogue allows users to grant, deny, or customize consent for advertising cookies and personalized data processing.
4. Analytics & Personal Data: No personally identifiable information (PII) is collected, gathered, sold, or shared by this simulator. Standard anonymous web server HTTP request logs may be maintained solely for cybersecurity and infrastructure reliability.
5. Managing Consent & Browser Cookies: You may adjust your browser cookie preferences, block third-party trackers, or clear stored local cache at any time via your browser settings.
📜 Terms of Use
1. Purpose of Service: The 300mm Wet Chamber Simulator is provided solely for engineering analysis, preliminary screening, research, and educational purposes.
2. Model-Based Estimates: All numerical values, film thickness estimates, Marangoni vectors, dewetting risk indices, and flow balance optimizations generated by this software are simplified model-based calculations. They do not constitute guaranteed equipment performance or physical wafer yields.
3. Independent Validation: Users must independently evaluate and validate all process parameters, chemical compatibility, safety hazards, and recipe formulations on certified semiconductor equipment before physical wafer fabrication.
4. Limitation of Liability: Under no circumstances shall the developers, contributors, or publishers be liable for any direct, indirect, incidental, or consequential damages resulting from the use or inability to use this simulation tool.
✉️ Contact & Engineering Feedback
We welcome inquiries, feedback, and technical discussions regarding single-wafer wet processing simulation, thin-film hydrodynamics, or tool enhancements.
Engineering Contact:CONTACT_EMAIL
Project Repository / Web:CANONICAL_SITE_URL/
When submitting recipe questions, please provide your wafer RPM, process temperature, nozzle coordinates, and chemical species.