Research: Lensfree Microscopy & Sensing
In lensfree microscopy and sensing, a transparent object like a glass slide is placed on top of an image sensor such as that from a cell phone camera or webcam. Diffraction patterns of the object are captured by a computer connected to the image sensor. These patterns are then computationally reconstructed to form an in-focus image of the sample. Unlike conventional imaging, where resolution and field of view are coupled through the numerical aperture of the objective lens, lensfree holographic imaging can provide near diffraction-limited resolution across ultra large fields of view. The lensfree microscopy hardware is also typically much less expensive and bulky than that of lens-based microscopes, making lensfree microscopes suitable for field-portable applications.
Sensing Protein Biomarkers
We have combined lensfree holographic microscopy with a bead-based agglutination assay to sense specific proteins in solution in a microfluidic device. Micro-beads are coated with antibodies specific to a target protein. When the protein is introduced to the bead solution, the beads bind to the proteins, causing clusters to form. Automated image processing routines measure the degree of clustering, from which a protein concentration is inferred. Compressed sensing algorithms help to provide high-fidelity images of the micro-beads. The high space-bandwidth product of lensfree microscopy allows >104 beads or bead clusters to be identified and counted in a single image. Such large sample sizes improve the sensitivity and repeatability of the sensor. The low cost and compact size of lensfree holographic microscopes make this approach ideal for point-of-care applications. So far, we have used this approach to sense NeutrAvidin and interferon-gamma.
A few relevant articles include (see publications for all related articles):
- Zhen Xiong, Colin J. Potter, and Euan McLeod, “High-speed lens-free holographic sensing of protein molecules using quantitative agglutination assays,” ACS Sensors, 6 (3), 1208 (2021).
- Zhen Xiong, Jeffrey E. Melzer, Jacob Garan, and Euan McLeod, “Optimized sensing of sparse and small targets using lens-free holographic microscopy,” Optics Express, 26 (20), 25676-25692 (2018).
- Maryam Baker, Weilin Liu, and Euan McLeod, “Accurate and fast modeling of scattering from random arrays of nanoparticles using the discrete dipole approximation and angular spectrum method,” Optics Express, 29 (14), 22761-22777 (2021).
Self-assembled liquid nanolenses for nanoparticle and virus imaging
Here we combine holographic on-chip imaging with self-assembled liquid nanolenses to image virus-sized particles across ultra-large fields of view of 5 mm x 6 mm and larger. To make this approach sensitive enough to detect individual nanoparticles and viruses, we employ a liquid polymer that self-assembles into nanolenses around the target particles. The main goals of this research are to detect the smallest possible particles across the largest field of view, without the use of labels, and all within a low-cost and field-portable platform.
A few relevant articles include (see publications for all related articles):
- Euan McLeod, T. Umut Dincer, Muhammed Veli, Yavuz N. Ertas, Chau Nguyen, Wei Luo, Alon Greenbaum, Alborz Feizi, and Aydogan Ozcan, “High-throughput and label-free single nanoparticle sizing based on time-resolved on-chip microscopy,” ACS Nano, 9 (3), 3265-3273 (2015).
- Euan McLeod, Chau Nguyen, Patrick Huang, Wei Luo, Muhammed Veli, and Aydogan Ozcan, “Tunable vapor-condensed nanolenses,” ACS Nano, 8 (7), 7340-7349 (2014).
- Onur Mudanyali*, Euan McLeod*, Wei Luo, Alon Greenbaum, Ahmet F. Coskun, Yves Hennequin, Cédric P. Allier, and Aydogan Ozcan, “Wide-field optical detection of nano-particles using on-chip microscopy and self-assembled nano-lenses,” Nature Photonics, 7, 247-254 (2013).