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Microstructure-based multiphysics modeling for semiconductor integration and packaging

  • Review
  • Materials Science
  • Published:
Chinese Science Bulletin

Abstract

Semiconductor technology and packaging is advancing rapidly toward system integration where the packaging is co-designed and co-manufactured along with the wafer fabrication. However, materials issues, in particular the mesoscale microstructure, have to date been excluded from the integrated product design cycle of electronic packaging due to the myriad of materials used and the complex nature of the material phenomena that require a multiphysics approach to describe. In the context of the materials genome initiative, we present an overview of a series of studies that aim to establish the linkages between the material microstructure and its responses by considering the multiple perspectives of the various multiphysics fields. The microstructure was predicted using thermodynamic calculations, sharp interface kinetic models, phase field, and phase field crystal modeling techniques. Based on the predicted mesoscale microstructure, linear elastic mechanical analyses and electromigration simulations on the ultrafine interconnects were performed. The microstructural index extracted by a method based on singular value decomposition exhibits a monotonous decrease with an increase in the interconnect size. An artificial neural network-based fitting revealed a nonlinear relationship between the microstructure index and the average von Mises stress in the ultrafine interconnects. Future work to address the randomness of microstructure and the resulting scatter in the reliability is discussed in this study.

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References

  1. Tummala RR (2012) The future of packaging. Chip Scale Rev 16:9–11

    Google Scholar 

  2. Tummala RR, Swaminathan M (2008) Introduction to system-on-package (SOP): miniaturization of the entire system. McGraw-Hill Companies, New York

    Google Scholar 

  3. Papanikolaou A, Soudris D, Radojcic R (2011) Three dimensional system integration: IC stacking process and design. Springer Science + Busines Media, LLC, New York

    Book  Google Scholar 

  4. Bakir MS, Meindl JD (2009) Integrated interconnect technologies for 3D nanoelectronic systems. Artech House, Norwood

    Google Scholar 

  5. Shen J, Liu YC, Gao HX (2006) Abnormal growth of Ag3Sn intemetallic compounds in Sn-Ag lead-free solder. Chin Sci Bull 51:1766–1770

    Article  Google Scholar 

  6. Wang XJ, Luo XX, Cong FG et al (2013) Research progress of microstructure control for aluminium solidification process. Chin Sci Bull 58:468–473

    Article  Google Scholar 

  7. McDowell DL (2011) Critical path issues in ICME. In: Arnold SM, Wong TT (eds) Models, databases, and simulation tools needed for the realization of integrated computational materials engineering. ASM International, Ohio, pp 31–37

    Google Scholar 

  8. Materials Genome Initiative for Global Competitiveness. The National Science and Technology Council, USA, June 2011

  9. Committee on Integrated Computational Materials Engineering (2008) Integrated computational materials engineering: a transformational discipline for improved competitiveness and national security. The National Academies Press, Washington

    Google Scholar 

  10. Lukas HL, Fries SG, Sundman B (2007) Computational thermodynamics: the CALPHAD method. Cambridge University Press, Cambridge

    Book  Google Scholar 

  11. Davies RH, Dinsdale AT, Gisby JA et al (2002) MTDATA: thermo-dynamic and phase equilibrium software from the National Physical Laboratory. Calphad-Comput Coupling Ph Diagrams Thermochem 26:229–271

    Article  Google Scholar 

  12. Sundman B, Jansson B, Andersson J (1985) The Thermo-calc databank system. Calphad-Comput Coupling Ph Diagrams Thermochem 9:153–190

    Article  Google Scholar 

  13. Huang Z, Conway PP, Liu C et al (2006) Modeling the interdependence of processing and alloy composition on the evolution of microstructure in Sn-based lead-free solders in fine pitch flip chip. IEEE Trans Compon Pack Technol 29:98–104

    Article  Google Scholar 

  14. Kroupa A, Dinsdale AT, Watson A et al (2007) The development of the COST 531 lead-free solders thermodynamic database. JOM 59:20–25

    Article  Google Scholar 

  15. Kroupa A, Dinsdale A, Watson A et al (2012) The thermodynamic database COST MP0602 for materials for high-temperature lead-free soldering. J Min Metall B 48:339–346

    Article  Google Scholar 

  16. Dinsdale AT, Davies RH, Mucklejohn SA (2012) Thermodynamic data for the (NaI-CeI3) system in the condensed & gas phases. In: 13th International symposium on the science and technology of lighting, Troy, USA pp 306

  17. Jain A, Hautier G, Moore C et al (2011) A high-throughput infrastructure for density functional theory calculations. Comput Mater Sci 50:2295–2310

    Article  Google Scholar 

  18. Ong SP, Wang L, Kang B et al (2008) Li-Fe-P-O2 phase diagram from first principles calculations. Chem Mater 20:1798–1807

    Article  Google Scholar 

  19. Jain A, Hautier G, Ong SP et al (2011) Formation enthalpies by mixing GGA and GGA + U calculations. Phys Rev B 84:045115

    Article  Google Scholar 

  20. Thornton K, Agren J, Voorhees PW (2003) Modelling the evolution of phase boundaries in solids at the meso- and nano-scales. Acta Mater 51:5675–5710

    Article  Google Scholar 

  21. Huang ZH, Conway PP, Thomson RC et al (2008) A computational interface for thermodynamic calculations software MTDATA. Calphad-Comput Coupling Ph Diagrams Thermochem 32:129–134

    Article  Google Scholar 

  22. Xiong H, Huang ZH, Wu ZY et al (2011) A generalized computational interface for combined thermodynamic and kinetic modeling. Calphad-Comput Coupling Ph Diagrams Thermochem 35:391–395

    Article  Google Scholar 

  23. Borgenstam A, Engstrom A, Hoglund L et al (2000) DICTRA: a tool for simulation of diffusional transformations in alloys. J Phase Equilib 21:269–280

    Article  Google Scholar 

  24. Donea J, Huerta A (2003) Finite element methods for flow problems. Wiley, Chichester

    Book  Google Scholar 

  25. Gamsjäger E (2007) A note on the contact conditions at migration interfaces. Acta Mater 55:4823–4833

    Article  Google Scholar 

  26. Fischer FD, Waitz T, Vollath D et al (2008) On the role of surface energy and surface stress in phase-transforming nanoparticles. Prog Mater Sci 53:481–527

    Article  Google Scholar 

  27. Svoboda J, Fischer FD, Fratzl P et al (2001) Kinetics of interfaces during diffusional transformations. Acta Mater 49:1249–1259

    Article  Google Scholar 

  28. Provatas N, Elder K (2010) Phase-field methods in materials science and engineering. Wiley-VCH Verlag GmbH, Weinheim

    Book  Google Scholar 

  29. Chen LQ (2002) Phase-field models for microstructure evolution. Annu Rev Mater Res 32:113–140

    Article  Google Scholar 

  30. Luo BC, Wang HP, Wei BB (2009) Phase field simulation of monotectic transformation for liquid Ni-Cu-Pb alloys. Chin Sci Bull 54:183–188

    Article  Google Scholar 

  31. Zhao Y, Chen Z, Wang YX et al (2010) A phase field study for influence of elastic energy on L10 → L12 transient ordering in Ni75Al17Zn8. Chin Sci Bull 55:3044–3050

    Article  Google Scholar 

  32. Huh JY, Hong KK, Kim YB et al (2004) Phase field simulations of intermetallic compound growth during soldering reactions. J Electron Mater 33:1161–1170

    Article  Google Scholar 

  33. Hong KK, Huh JY (2006) Phase field simulations of morphological evolution and growth kinetics of solder reaction products. J Electron Mater 35:56–64

    Article  Google Scholar 

  34. Huang Z, Conway PP, Qin RS (2009) Modeling of interfacial intermetallic compounds in the application of very fine lead-free solder interconnections. Microsyst Technol 15:101–107

    Article  Google Scholar 

  35. Park MS, Arroyave R (2012) Concurrent nucleation, formation and growth of two intermetallic compounds (Cu6Sn5 and Cu3Sn) during the early stages of lead-free soldering. Acta Mater 60:923–934

    Article  Google Scholar 

  36. Elder KR, Katakowski M, Haataja M et al (2002) Modeling elasticity in crystal growth. Phys Rev Lett 88:245701

    Article  Google Scholar 

  37. Elder KR, Grant M (2004) Modeling elastic and plastic deformations in nonequilibrium processing using phase field crystals. Phys Rev E 70:051605

    Article  Google Scholar 

  38. Stefanovic P, Haataja M, Provatas N (2006) Phase-field crystals with elastic interactions. Phys Rev Lett 96:225504

    Article  Google Scholar 

  39. Stefanovic P, Haataja M, Provatas N (2009) Phase field crystal study of deformation and plasticity in nanocrystalline materials. Phys Rev E 80:046107

    Article  Google Scholar 

  40. Ofori-Opoku N, Fallah V, Greenwood M et al (2013) Multicomponent phase-field crystal model for structural transformations in metal alloys. Phys Rev B 87:134105

    Article  Google Scholar 

  41. COMSOL multiphysics user’s guide. Version 4.3a. COMSOL AB, Stockholm, 2012

  42. Bohme T, Muller WH, Weinberg K (2009) Numerical modeling of diffusion induced phase transformations in mechanically stressed lead-free alloys. Comput Mater Sci 45:837–844

    Article  Google Scholar 

  43. Roters F, Raabe D, Gottstein G (2000) Work hardening in heterogeneous alloys: a microstructural approach based on three internal state variables. Acta Mater 48:4181–4189

    Article  Google Scholar 

  44. Roters F, Eisenlohr P, Hantcherli L et al (2010) Overview of constitutive laws, kinematics, homogenization and multiscale methods in crystal plasticity finite-element modeling: theory, experiments, applications. Acta Mater 58:1152–1211

    Article  Google Scholar 

  45. Hansen N, Ralph B (1982) The strain and grain size dependence of the flow stress of copper. Acta Metall 30:411–417

    Article  Google Scholar 

  46. Ceric H, Selberherr S (2011) Electromigration in submicron interconnect features of integrated circuits. Mater Sci Eng R Rep 71:53–86

    Article  Google Scholar 

  47. Chou CK, Chen CA, Liang SW et al (2006) Redistribution of Pb-rich phase during electromigration in eutectic SnPb solder stripes. J Appl Phys 99:054502

    Article  Google Scholar 

  48. Lin HW, Chen C, Kuo JC, et al (2009) Effects of electromigration on grain rotation behavior of SnAg solders. In: IEEE, ed. 4th International microsystems, packaging, assembly and circuits technology conference (IMPACT), Taipei pp 166–168

  49. Chen LD, Huang M (2009) Effect of electromigration on intermetallic compound formation in Cu/Sn/Cu interconnect. In: Bi K, Cai J (eds) International conference on electronic packaging technology & high density packaging (ICEPT-HDP). Piscataway, NJ, USA: IEEE, pp 666–669

  50. Barrett JW, Garcke H, Nurnberg R (2007) A phase field model for the electromigration of intergranular voids. Interface Free Bound 9:171–210

    Article  Google Scholar 

  51. Kim D (2009) Evolution of micro solder joints under electro migration and elastic field. J Mech Sci Technol 23:489–497

    Article  Google Scholar 

  52. Zikopoulos PC, deRoos D, Parasuraman K et al (2013) Harness the power of big data. McGraw-Hill Companies, New York

    Google Scholar 

  53. Golub GH, Van Loan CF (1996) Matrix computations. The John Hopkins University Press, Baltimore

    Google Scholar 

  54. Bhadeshia HKDH (1999) Neural networks in materials science. ISIJ Int 39:966–979

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Natural Science Foundation of China (51004118), the Pearl River New Science Star Program of Guangzhou (2012J2200074), the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry (30000-4105346), the 100 Talents Program of Sun Yat-sen University, and the Basic Research Foundation of Northwestern Polytechnical University (JCY20130114). The authors acknowledge Robinson Jim of the National Physical Laboratory for conducting the calculations in MTDATA and plotting Fig. 1. Technical supports from Dr. Gang Wang of CnTech on various issues of COMSOL Multiphysics are also gratefully acknowledged.

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Authors and Affiliations

  1. School of Physics and Engineering, Sun Yat-sen University, Guangzhou, 510275, China

    Zhiheng Huang, Hua Xiong & Zhiyong Wu

  2. Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University, Loughborough, LE11 3TU, UK

    Paul Conway

  3. National Physical Laboratory, Teddington, TW11 0LW, UK

    Hugh Davies & Alan Dinsdale

  4. China Electronic Produce Reliability and Environmental Testing Research Institute, Guangzhou, 510610, China

    Yunfei En

  5. School of Materials Science and Engineering, Northwestern Polytechnical University, Xi’an, 710072, China

    Qingfeng Zeng

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  1. Zhiheng Huang
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  2. Hua Xiong
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  3. Zhiyong Wu
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  4. Paul Conway
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  8. Qingfeng Zeng
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Correspondence to Zhiheng Huang.

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SPECIAL ISSUE: Materials Genome

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Huang, Z., Xiong, H., Wu, Z. et al. Microstructure-based multiphysics modeling for semiconductor integration and packaging. Chin. Sci. Bull. 59, 1696–1708 (2014). https://doi.org/10.1007/s11434-013-0103-7

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  • DOI: https://doi.org/10.1007/s11434-013-0103-7

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