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Study on parameters for aggregation and precipitation in the switchable-linker based detection system using gold nanoparticles : 금나노 입자를 이용한 switchable-linker 기반 검출법의 응집과 침전반응에 영향을 미치는 요소에 관한 연구

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Authors

김재연

Advisor
최영진
Major
농업생명과학대학 농생명공학부
Issue Date
2018-08
Publisher
서울대학교 대학원
Description
학위논문 (석사)-- 서울대학교 대학원 : 농업생명과학대학 농생명공학부, 2018. 8. 최영진.
Abstract
Aggregation of gold nanoparticles (AuNPs) has been used in various fields for assorted purposes. In particular, detection of analytes through visual color changes induced by aggregation of AuNPs has been extensively studied in recent years. In our previous research, switchable-linker based detection system was introduced. In the system, sensing of specific targets is achieved based on the quantitative correlations between linkers, targets and particles. When the number of particles and linkers are ideally matched, a maximum aggregation occurs in suspension inducing aggregates settling. This linker range where aggregates precipitation dominantly occurs is called exhibiting visual color change (REVC). Since REVC plays a critical role in the system, it is important to gain an understanding of the factors that could affect in REVC formation. However, little research has been done about the basic mechanisms of REVC formation based on AuNPs aggregation and precipitation, especially focusing on the effects of particles size and surface area.

In this study, the effects of total surface area of AuNPs in REVC formation were identified by comparing 3 different cases. In the first case, 11 nm and 19 nm-sized particles were used in the previous study. Under the same plasmon absorbance, as the size of particle increased, the total surface area decreased. In this case, REVC appeared at lower linker concentrations with a narrower range. After the addition of target streptavidin, REVC shifted more in 19 nm particles which had smaller surface area. As for the second case, 12, 18, and 24 nm-sized particles were used. In this case, the number of particles was identically adjusted, thus as the particle size increased, the total surface area of AuNPs increased. In larger surface area, REVC appeared at higher linker concentrations in a broader range which correspondsss to the previous results. With the addition of target streptavidin, REVC shifted less as the surface area increased. Lastly, the surface area of AuNPs was identically adjusted by controlling the number of particles using 13, 21, 30, and 36 nm-sized particles. Under the same surface area, REVC was formed at a similar linker concentrations regardless of individual particle sizes and REVC shifting occurred identically under the addition of target streptavidin. Three cases indicated that as the surface area of AuNPs decreased, REVC worked more sensitively as a sensor.

As part of an effort to confirm the reaction time according to particles, the third case was intensively interpreted. When the surface area of AuNPs was identically controlled, it was observed that in 21 nm-sized particles, REVC was formed the slowest among others in observation time of 200 minutes. From DLS size measurements of aggregates and Stokes law, settling velocity of aggregates in REVC was calculated. At an early settling stage, aggregates of 30 and 36 nm-sized particles precipitated more rapidly. However, as time went by, settling speed of aggregates composed of 13 and 21 nm-sized particles reached beyond the speed of larger particles. At around 120 minutes, the settling velocity of aggregates composed of 13 nm-sized particles went over than that of 21 nm-sized particles. This phenomenon might be explained by the fact that smaller individual particles made clusters more rapidly in much bigger sizes, thus settling speed inversion seemed to be happened.

The results of this study suggest the importance of the surface area in REVC formation and the aggregates precipitation speed inversion was revealed by the actual calculations using Stokes law. These can be contributed to the further development of switchable-linker based detection system and can be used as clues in other aggregation-based applications.
Language
English
URI
https://hdl.handle.net/10371/144140
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