journal article·2010-09

Combined modeling and experimental studies of hydroxylated silica nanoparticles

D. Makimura, C. Metin, T. Kabashima, T. Matsuoka, Q. P. Nguyen, Caetano R. Miranda

Journal of Materials Science· Volume 45· Issue 18
Publisher page

Abstract

Nanotechnology offers several opportunities to solve problems related with Oil and Gas industry. One of them is the possibility to use hard nanoparticles to control the wettability phenomena between the three-phase system (oil–water–minerals) at reservoir conditions of temperature, pressure, and salinity. Here, we present a combined experimental and modeling study of hydroxylated silica nanoparticles as candidate for improved oil recovery applications. In this work, we mainly focus on development of more realistic SiO2-nanoparticle models and validating them against the experimental data. An efficient Monte Carlo scheme is proposed to generate realistic SiO2 nanoparticle atomistic models (3–5 nm). Structural and spectroscopic properties such as Raman and Infrared were obtained through Molecular Dynamics (MD) calculations using a force field that mimics an ab initio data. We have also used Fourier transform infrared spectroscopy to identify chemical functional groups present in 5 nm unmodified (bare) silica nanoparticle dispersions. A good agreement between the MD simulations and experiments has been observed.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Enhanced Oil Recovery Techniques · Hydrocarbon exploration and reservoir analysis · Phase Equilibria and Thermodynamics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (23)

Show source-provided references
1. Mokhatab S, Fresky MA, Islam MR (2006) J Petrol Technol 58:410.2118/0406-0048-JPT ↗
2. Miranda CR, Matsuoka T, Nanogeoscience (2008) Geochim Cosmochim Acta 72:A634
3. Tweheyo MT, Zhang P, Austad T (2006) Paper SPE 99438, presented at the symposium on improved oil recovery, Tulsa, Oklahoma, 22–26 April
4. Zhang DL, Liu S, Puerto M, Miller CA, Hirasaki GJ (2006) J Petrol Sci Eng 52:21310.1016/j.petrol.2006.03.009 ↗
5. Vafaei S, Borca-Tasciuc T, Podowski MZ, Purkayastha A, Ramanath G, Ajayan PM (2006) Nanotechnology 17:252310.1088/0957-4484/17/10/014 ↗
6. Owens WW, Archer DL (1971) J Petrol Technol 23:87310.2118/3034-PA ↗
7. Hirasaki GJ, Zhang DL (2004) SPEJ 9:15110.2118/88365-PA ↗
8. Seethepalli A, Adibhatla B, Mohanty KK (2004) Paper SPE 89423 presented at the Symposium on Improved Oil Recovery, Tulsa, Oklahoma, 17–21 April
9. Hoang VV (2007) J Phys Chem B 111:1264910.1021/jp074237u ↗
10. Barbier D, Brown D, Grilet A-C, Neyertz S (2004) Macromolecules 37:469510.1021/ma0359537 ↗
11. Jenkins S, Kirk SR, Persson M, Carlen J, Abbas Z (2007) J Chem Phys 127:22471110.1063/1.2803897 ↗
12. Liang Y, Miranda CR, Scandolo S (2007) Phys Rev Lett 99:21550410.1103/PhysRevLett.99.215504 ↗
13. Liang Y, Miranda CR, Scandolo S (2007) Phys Rev B 75:02420510.1103/PhysRevB.75.024205 ↗
14. Rimola A, Sodupe M, Ugliengo P (2009) J Phys Chem C 113:574110.1021/jp811193f ↗
15. Camarota B, Ugliengo P, Garrone E et al (2008) J Phys Chem C 112:1956010.1021/jp805981a ↗
16. Pedone A, Malavasi G, Menziani MC, Segre U, Musso F, Corno M, Civalleri B, Ugliengo P (2008) Chem Mater 20:252210.1021/cm703437y ↗
17. Vink RLC, Barkema GT (2003) Phys Rev B 67:24520110.1103/PhysRevB.67.245201 ↗
18. Zhuravlev LT (2000) Colloids Surf A Physiochem Eng 173:110.1016/S0927-7757(00)00556-2 ↗
19. Gale JD, Rohl AL (2003) Mol Simul 29:29110.1080/0892702031000104887 ↗
20. Yalamanchili MR, Atia AA, Miller JD (1996) Langmuir 12:417610.1021/la950340b ↗
21. Asay DB, Kim SH (2005) J Phys Chem B 109:1676010.1021/jp053042o ↗
22. Morrow BA, Molapo DT (2006) Surfactant Sci Ser 131:287
23. Dowty E (1987) Phys Chem Miner 19:6710.1007/BF00311150 ↗