In Situ Raman Spectroscopy-Enabled Microfluidic Gel Chromatography for Revealing Real-Time Separation Dynamics of Single-Walled Carbon Nanotubes.

原位拉曼光谱辅助的微流控凝胶色谱法揭示单壁碳纳米管的实时分离动力学

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作者:Beom Byeongji, Jung Seung-Chan, Jang Wonjun, Won Jong-Keon, Jeong Jihoon, Choi Yu-Jeong, Moon Man-Ki, Han Jae-Hee
Single-walled carbon nanotubes (SWNTs) exhibit distinct electronic properties, categorized as metallic or semiconducting, determined by their chirality. The precise and selective separation of these electronic types is pivotal for advancing nanotechnology applications. While conventional gel chromatography has been widely employed for large-scale separations, its limitations in addressing microscale dynamics and electronic-type differentiation have persisted. Here, we present a polydimethylsiloxane (PDMS)-based microfluidic gel chromatography platform, coupled with real-time in situ Raman spectroscopy, designed to achieve the high-resolution electronic-type separation of SWNTs. This platform systematically isolates metallic- and semiconducting-enriched fractions (M1-M3 and S1-S3) while quantitatively analyzing separation dynamics through G-band spectral shifts and G(-)/G(+) intensity ratios. By normalizing the SDS concentration and calculating rate constants, we reveal the intrinsic elution kinetics of SWNTs, with metallic fractions exhibiting faster elution dynamics compared to their semiconducting counterparts. Our approach bridges the gap between microscale precision and industrial scalability, emphasizing the critical role of dispersant concentration in fine-tuning separation outcomes. This advancement not only resolves the challenges of electronic-type differentiation but also demonstrates the versatility of PDMS microfluidic systems in delivering real-time insights into nanomaterial purification processes. By integrating continuous dynamic analysis with gel chromatography, this study establishes a transformative framework for scaling nanomaterial separations and unlocking new potential in chirality-specific applications.

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