平面的
螺旋(铁路)
微流控
纳米技术
材料科学
磁性纳米粒子
纳米颗粒
微流控芯片
炸薯条
实验室晶片
光电子学
计算机科学
工程类
电气工程
机械工程
计算机图形学(图像)
作者
Tuan Nguyen Van,Ho Anh Tam,Nguyễn Thị Ngọc,V.N. Thuc,Nguyễn Khắc Bình,Nguyen Thi Phuong Thao,Do Thi Hien,Brian Sang,Nam Hoang Nguyen,Vũ Đình Lãm,Le Van Lich,D.T. Huong Giang
出处
期刊:Lab on a Chip
[Royal Society of Chemistry]
日期:2025-01-01
卷期号:25 (12): 2977-2989
摘要
Magnetic nanoparticles have garnered significant attention in the biomedical field due to their remarkable biocompatibility and diverse applications. However, existing methodologies for quantifying magnetic-labeled samples face limitations, particularly regarding the stringent requirements for magnetic sensors and the complexities associated with integrating these systems into microfluidic platforms. This study introduces an innovative planar magnetoimpedance sensor for magnetic nanoparticle detection, designed with a micropatterned spiral configuration and integrated into a microfluidic channel. The spiral configurations of the planar sensor are designed and optimized through micromagnetic simulations, where the domain properties of the sensors are examined by varying the turn widths of the spiral micropatterns from 70 μm to 210 μm. The optimal width is identified at 70 μm for effective measurement of magnetic particles. The magnetoimpedance sensor is fabricated using wet chemical etching based on an FeSiC ribbon. The computation-guided design of the magnetoimpedance sensor achieves impressive sensitivity and resolution values of 2.5% Oe-1 and 0.01 Oe, respectively. The designed sensor, integrated with the microfluidic channel, can detect magnetic nanoparticles as small as 0.2 μg. Both experiment and simulation results demonstrate that the magnetoimpedance effect is significantly influenced by the configurations of the transverse magnetic domain, resulting in detectable variation of the stray field in the MI sensor's output signals. Integrating the magnetoimpedance sensor with the microfluidic system provides several advantages, including cost-effectiveness, rapid response times, and user-friendliness. This quantitative detection method for magnetic nanoparticles holds substantial promise for applications in biological concentration detection and other advanced research domains.
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