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Predicting collision efficiencies of colloidal nanoparticles in single spherical and fibrous collectors using an individual particle tracking method
- Lee, Handol;
- Kim, Seong Chan;
- Chen, Sheng-Chieh;
- Segets, Doris;
- Pui, David Y. H.
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25SCOPUS
25초록
We investigate the deposition of colloids onto granular and fibrous collectors by computational fluid dynamics (CFD) simulations. In particular the collision efficiency under unfavorable conditions, i.e., like-charged surfaces, was in focus. Particle trajectories were analyzed in a Lagrangian reference frame using a discrete phase model (DPM). By user-defined functions (UDFs) we incorporated interception as important deposition mechanism and calculated interaction energies between particle and collector surfaces utilizing the extended Derjaguin-Landau-Verwey-Overbeek (xDLVO) theory. Adhesive and hydrodynamic torques acting on deposited particles were compared through the developed UDFs to consider particle detachment. Within each DPM process, all above mentioned calculations on every particle are performed continuously, allowing to understand particle deposition under different physico-chemical conditions. Simulated data on collision efficiencies for the granular collector were in good agreement with theory and experiments. Simulations for the fibrous collector showed that with increasing fluid velocity the hydrodynamic torque acting on particles attached to smaller fibers was increased. This enhanced the detachment and significantly lowered the collision efficiency, especially for larger particles. In conclusion, the developed CFD methods for predicting the collision efficiency on granular and fibrous collectors provide a powerful tool for examining the deposition behaviors of colloidal particles in porous media.
키워드
- 제목
- Predicting collision efficiencies of colloidal nanoparticles in single spherical and fibrous collectors using an individual particle tracking method
- 저자
- Lee, Handol; Kim, Seong Chan; Chen, Sheng-Chieh; Segets, Doris; Pui, David Y. H.
- 발행일
- 2019-09-01
- 유형
- Article
- 권
- 222
- 페이지
- 202 ~ 213
- 언어
- ENG
- 출판사
- ELSEVIER SCIENCE BV
- 발행국가
- 네덜란드
- 분량
- 12 페이지
- ISSN
- E 1873-3794
P 1383-5866