Lens-free chip enables microfluidic integration

Compiled by Photonics Spectra staff

A new lens-free chip and image processing algorithm combines optical sensors, holography and digital tomography to render high-resolution, high-contrast images while avoiding the limitations of lens-based optical microscopy.

Developed by scientists at the University of California, the “sensor” is a 5-megapixel CMOS chip with 2.2-μm pixels. It is similar to the sensors found in a Blackberry or iPhone, except that it is monochrome rather than RGB, said Aydogan Ozcan, associate professor of electrical engineering at UCLA’s Henry Samueli School of Engineering and Applied Science.

The team faced the challenge of reducing noise artifacts resulting from spatial and temporal coherence due to illuminating the sample with a laser – especially at oblique angles. To overcome this, the investigators replaced laser illumination with partially coherent light that emanated from an aperture of ~0.05 to 0.1 mm in diameter, with a bandwidth of 1 to 10 nm. They found that recording in-line holograms using partial coherence provided a gating function that allowed the device to filter noise that is beyond a defined resolution level.

They developed a sample illumination approach that rotates the partially coherent light source around the sample, rather than requiring the platform to be rotated within the illumination field. The lens-free optical tomographic microscope features many new innovations, but three are key, according to Ozcan: partially coherent illumination with unit-magnification, pixel superresolution to achieve deeply subpixel lateral resolution and dual-axis tomographic illumination.

Primary applications for the lens-free microscopy technique could include cell and developmental biology – especially in microfluidic integration.

“Microfluidic integration would permit rather interesting lab-on-a-chip devices that could do optofluidic microscopy and tomography (also known as holographic optofluidic microscopy, or HOM) on the same chip,” Ozcan said.

The technology also could enable in vivo applications, if further miniaturization and integration were to take place. The group’s work appeared April 19, 2011, in Proceedings of the National Academy of Sciences (doi: 10.1073/pnas. 1015638108).