Journals / International Journal of Automotive Engineering and Technologies / 2026 / Cilt: 4 Sayı: 1

Design and Optimization of Chemical Mixing System for Vacuum Chambers Base of Simulation Results / Vakum Odaları için Kimyasal Karıştırma Sisteminin Tasarım ve Optimizasyonunun Simülasyon Sonuçları

Pages
23–32
Publication Date
2015-01-16
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Parametrik çalışma gösterdi ki CFD, huni üzerindeki gaz akışı-yapısı etkileşimi problemini çalışmak için çok güçlü bir araçtır ve farklı çalışma şartları altında gazın yolununun görselleştirilmesini sağlayabilen bir araçtır.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Computational fluid dynamics (CFD) is widely used in device design to determine gas flow patterns and turbulence levels.
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Key Findings & Data:The results presented have been analyzed for a total of 11 different cases by varying neck and nozzle angles for a process gas.
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Conclusion & Impact:Parametrik çalışma gösterdi ki CFD, huni üzerindeki gaz akışı-yapısı etkileşimi problemini çalışmak için çok güçlü bir araçtır ve farklı çalışma şartları altında gazın yolununun görselleştirilmesini sağlayabilen bir araçtır.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Vacuum Chamber · Atomic layer deposition (ALD) · Computational fluid dynamics (CFD)

Abstract

Computational fluid dynamics (CFD) is widely used in device design to determine gas flow patterns and turbulence levels. CFD is also used to simulate particles and droplets, which are subjected to various forces, turbulence and wall interactions. These studies can now be performed routinely because of the availability of commercial software containing high quality turbulence and particle models. In order to understand how the gas is brought down to wafer, it is necessary to have a knowledge of the gas flow behavior very early in the design spiral of the Tantalum nitride-Atomic layer deposition (TaN-ALD) chamber by undertaking parametric investigation of the interaction effect between gas flow and the funnel structure. This paper presents such a parametric investigation on a generic TaN-ALD chamber using CFD. The results presented have been analyzed for a total of 11 different cases by varying neck and nozzle angles for a process gas. The gas flow was mainly investigated for the nozzle angles of 4.5, 9, 12 and 20 and the film thickness results were compared with numerical flow patterns. CFD simulations using the turbulence model in ANSYS Fluent v.13 are undertaken. The parametric study has demonstrated that CFD is a powerful tool to study the problem of gas flow–structure interaction on funnel and is capable of providing a means of visualizing the path of the gas under different operating conditions. Özet: Hesaplamalı akışkanlar mekaniği (CFD), gaz akış modelleri ve türbülans seviyelerini belirlemek için tasarlanan cihazlarda yaygın olarak kullanılmaktadır. CFD, türbülans ve cidar etkileşimlerinde farklı kuvvetlere maruz kalan parçacık ve damlacıklarının simülasyonu için de kullanılır. Günümüzde bu çalışmalar, yüksek kalitede türbülans ve parçacık modelleri içeren ticari yazılımların kullanılması ile yapılabilmektedir. Bir gazın nasıl levhamsı haline geldiğini anlamak için, gaz akışı ve huni yapı arasındaki etkileşim etkisinin taahhütlü parametrik araştırma ile Tantalum nitride-Atomic tabaka katmanı odasının (TaN-ALD) spiral tasarımındaki en erken gaz akış davranışının bilinmesi gerekir. Bu makale, CFD kullanılan kapsamlı bir TaN-ALD odası üzerine parametrik bir incelemeyi sunmaktadır. Bir gaz prosesi için toplamda 11 farklı boğaz ve meme açısının sonuçlarının analizi sunulmuştur. Gaz akışı, 4.5o, 9o, 12o ve 20o meme açısı değerleri için incelenmiş ve film kalınlığı sonuçları nümerik akış modelleri ile karşılaştırılmıştır. ANSYS Fluent v.13’de türbülans modeli kullanan CFD simülasyonu üstlenilmiştir. Parametrik çalışma gösterdi ki CFD, huni üzerindeki gaz akışı-yapısı etkileşimi problemini çalışmak için çok güçlü bir araçtır ve farklı çalışma şartları altında gazın yolununun görselleştirilmesini sağlayabilen bir araçtır.

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Cite This Article

Unker, F., Ünker, F., Kaplan, E., Cuvalci, O., Çuvalcı, O. (2015). Design and Optimization of Chemical Mixing System for Vacuum Chambers Base of Simulation Results / Vakum Odaları için Kimyasal Karıştırma Sisteminin Tasarım ve Optimizasyonunun Simülasyon Sonuçları. International Journal of Automotive Engineering and Technologies, Cilt: 4 Sayı: 1, 23–32. https://doi.org/10.18245/ijaet.39044

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References (47)

  1. ISO/DIS 3570/1, 1975.
  2. Poulter K.F., “The calibration of vacuum gauges,” J. Phys. E: Sci. Instrum., vol. 10, pp.112. 1977.
  3. Szwemin P., “The influence of the blocking plate diameter on the gas flux distribution
  4. chamber”,Vacuum, vol. 73, pp.263. 2004. the
  5. calibration 4. Maev R., and Leshchynsky
  6. V., Introduction to
  7. dynamic spray. Weinheim, Germany: Wiley-Vch. 2008. C., 5. Cai and Boyd I.D.,
  8. Nov. “Collisionless Gas Flow Expanding into Vacuum,” Journal of Spacecraft and Rockets, vol.44, pp.1326-1330. 2007.
  9. Versteeg H.K., and Malalasekera W., An Introduction to Computational Fluid Dynamics.
  10. Approach, Addison Wesley Longman, Harlow, UK. 1995. Finite Volume J.H., and Methods for
  11. Fluid Computational Dynamics. 2002.
  12. Launder B.E., and Spalding D.B., “The numerical computation of turbulent flows,” Comput. Meth. Appl. Mech. Eng. vol.3, pp. 269–289. 1974.
  13. Menter F.R., “Two-equation eddy– turbulence viscosity
  14. engineering applications,” AIAA J., vol32, pp.1598–1605. August 1994.
  15. Versteeg H.K., Hargrave G., Harrington L., Shrubb I., and Hodson D., “The use of computational fluid dynamics (CFD) to predict pMDI air flows and aerosol plume formation,” Respiratory Drug Delivery VII, vol.1, pp. 257–264. 2000.
  16. Lai Jr. M., Huang C.Y., Chen C.H., Linliu K., and Lin J.D., “Influence of liquid passage
  17. dynamics in a drop ejection process,” J. Micromech. Microeng. vol. 20, 015033, p.14. 2010. and
  18. nozzle onmicrofluidic 14. Nichols S.C., and Wynn E., “New approaches to optimizing dispersion in dry powder inhalers — dispersion force mapping and adhesion measurements,” Respir. Drug Deliv., vol. 1, pp. 175–184. 2008.
  19. Coates M.S., Chan H.-K., Fletcher D.F., and Raper J.A., “Influence of air flow on the performance of a dry powder inhaler using computational and experimental analyses,” Pharm. Res., vol. 22, pp. 1445–1453. 2005.
  20. Coates M.S., Fletcher D.F., Chan H.-K., and Raper J.A., “Effect of design on the performance of a dry powder inhaler using computational fluid dynamics. Part 1: grid structure and mouthpiece length,” J. Pharm. Sci., vol. 93, pp. 2863–2876. 2004.
  21. Coates M., Chan H.-K., Fletcher D. F., and Chiou H., “Influence of mouthpiece geometry on the aerosol delivery performance of a dry powder inhaler,” Pharm. Res., vol. 24, pp. 1450–1456. 2007.
  22. Coates M.S., Chan H.-K., Fletcher D.F., and Raper J.A., “Effect of design on the performance of a dry powder inhaler using computational fluid dynamics. Part 2: air inlet size,” J. Pharm. Sci., vol. 95, 1382–1392. 2006.
  23. Calvert G., Ghadiri M., and Tweedie R., “Aerodynamic dispersion of cohesive powders: a review of understanding and technology,” Adv. Powder Technol.,vol. 20, pp. 4–16. 2009.
  24. Wong W., Fletcher D.F., Traini D., Chan H.K., Crapper J., and Young P.M., “Particle aerosolisation and break-up in dry powder inhalers 1: evaluation and modelling
  25. agglomerated systems,” Pharm. Res., vol. 27, pp. 1367–1376. 2010.
  26. for Wong W., Fletcher D.F., Traini D., Chan H.-K., Crapper J., and Young P.M., “Particle aerosolisation and break- up in dry powder inhalers: evaluation and modelling of impaction effects for agglomerated systems,” J. Pharm. Sci.,vol. 100, pp. 2744–2754. 2011.
  27. Kleinstreuer C., Shi H., and Zhang Z., “Computational
  28. pressurized metered dose inhaler and a new
  29. methodology,” J. Aerosol Med., vol.20, pp. 294–309. 2007. of a drug–aerosol
  30. targeting 23. Longest P.W, Hindle M., Das Choudhuri S., and Xi J., “Comparison of ambient and spray aerosol deposition in a standard induction port and more realistic mouth–throat geometry,” J. Aerosol Sci., vol. 39, pp. 572–591. 2008.
  31. Longest P.W, Hindle M., Choudhuri S. D., and Byron P.R., “Numerical simulations
  32. generation: CFD model development and comparisons with experimental data,” Aerosol Sci. Technol., vol 41, pp. 952–973. 2007.
  33. Longest P.W, Hindle M., Choudhuri S. D., “Effects of generation time on spray aerosol transport and deposition in models of the mouth–throat geometry,” J. Aerosol Med. Pulm., vol. D 22, pp. 67–84. 2009.
  34. Longest P.W, Hindle M., “Quantitative analysis and design of a spray aerosol inhaler. Part 1: effects of dilution air inlets and flow paths,” J. Aerosol Med. Pulm., vol 22 (3), pp. 271-283. 2009. 27. Amirav I., and Newhouse
  35. M.T., “Aerosol therapy with valved holding chambers in young children: importance of the facemask seal,” Pediatrics, vol. 108, pp. 389–394. 2001.
  36. Shen S.-C., Wang Y.-J., and Chen Y.- Y., “Design and fabrication of medical micronebulizer,” Sens. Actuators, vol. 144, pp. 135–143. 2008.
  37. Coates M.S., Fletcher D.F., Chan H.-K., and Raper J.A., “A comparative study of two marketed pulmonary drug delivery devices
  38. dynamics,” Respiratory Drug Delivery IX, vol. 3, pp. 821–824. 2004.
  39. fluid 30. Tibbatts J., Mendes P.J., and Vlllax P., “Understanding the power requirements for efficient dispersion in powder inhalers: comparing CFD predictions and
  40. Respir. Drug Deliv., vol. 1, pp. 323–330. 2010. 31. Arulmuthu
  41. measurements,” E.R., Williams
  42. D.J., Baldascini H., Versteeg H.K., and Hoare M., “Studies on aerosol delivery of plasmid DNA using a mesh nebulizer,” Biotechnol. Bioeng., vol. 98, pp. 939– 955. 2007.
  43. Jeng, Y.R. Su C.C., Feng G.H., and Peng Y.Y., “An investigation into a piezoelectrically actuated nebulizer with μEDM-made micronozzle array,” Exp. Therm Fluid Sci., vol. 31, pp.1147– 1156. 2007.
  44. Zhu H., Zhou Z., Yang R., and Yu A., “Discrete particulate simulation of systems:
  45. theoretical developments,” Chem. Eng. Sci., vol. 62, pp. 3378–3396. 2007.
  46. Zhu H.P., Zhou Z.Y., Yang R.Y., and Yu A.B., “Discrete particle simulation of particulate systems: a review of major applications and findings,” Chem. Eng. Sci., vol. 63, pp. 5728–5770. 2008.
  47. Coates M., Chan H.-K., Fletcher D., and Chiou H., “Influence of mouthpiece geometry on the aerosol delivery performance of a dry powder inhaler,” Pharm. Res., vol. 24, pp. 1450–1456. 2007.