Continuous cell culture monitoring as a way of investigating growth, proliferation, and kinetics of biological experiments is in high demand. However, commercially available solutions are typically expensive and large in size. Digital inline-holographic microscopes (DIHM) can provide a cost-effective alternative to conventional microscopes, bridging the gap towards live-cell culture imaging. In this work, a DIHM is built from inexpensive components and applied to different cell cultures. The images are reconstructed by computational methods and the data are analyzed with particle detection and tracking methods. Counting of cells as well as movement tracking of living cells is demonstrated, showing the feasibility of using a field-portable DIHM for basic cell culture investigation and bringing about the potential to deeply understand cell motility.

Vertically aligned 3D gallium nitride (GaN) nanowire arrays with sub-50 nm feature sizes were fabricated using a nanosphere lift-off lithography (NSLL) technique combined with hybrid top-down etching steps (i.e., inductively coupled plasma dry reactive ion etching (ICP-DRIE) and wet chemical etching). Owing to the well-controlled chemical surface treatment prior to the nanobead deposition and etching process, vertical GaN nanowire arrays with diameter of ~35 nm, pitch of ~350 nm, and aspect ratio of >10 could be realized using 500 nm polystyrene nanobead (PN) masks. This work has demonstrated a feasibility of using NSLL as an alternative for other sophisticated but expensive nanolithography methods to manufacture low-cost but highly ordered 3D GaN nanostructures.

A compact lensless microscope comprising a custom-made LED engine and a CMOS imaging sensor has been developed for live-cell culture imaging inside a cell incubator environment. The imaging technique is based on digital inline-holographic microscopy, while the image reconstruction is carried out by angular spectrum approach with a custom written software. The system was tested with various biological samples including immortalized mouse astrocyte cells inside a petri dish. Besides the imaging possibility, the capability of automated cell counting and tracking could be demonstrated. By using image sensors capable of video frame rate, time series of cell movement can be captured.

Cell registration by artificial neural networks (ANNs) in combination with principal component analysis (PCA) has been demonstrated for cell images acquired by light emitting diode (LED)-based compact holographic microscopy. In this approach, principal component analysis was used to find the feature values from cells and background, which would be subsequently employed as neural inputs into the artificial neural networks. Image datasets were acquired from multiple cell cultures using a lensless microscope, where the reference data was generated by a manually analyzed recording. To evaluate the developed automatic cell counter, the trained system was assessed on different data sets to detect immortalized mouse astrocytes, exhibiting a detection accuracy of ~81% compared with manual analysis. The results show that the feature values from principal component analysis and feature learning by artificial neural networks are able to provide an automatic approach on the cell detection and registration in lensless holographic imaging.

The sensitivity of high-precision measurements is crucially affected by the mechanical losses of the involved materials. In systems incorporating highly reflective elements based on amorphous Bragg reflectors, the mechanical losses of the coating materials have to be minimized. In this contribution we report on the fabrication of SiO2 microcantilever arrays to study such mechanical losses. The fabrication steps, consisting of pattern transfer, anisotropic and isotropic dry etching, has been optimized to be employed on both thermally grown and sputtered SiO2 samples. The cantilevers released from the Si substrate show a deviation of only 2% from the design, confirming a high selectivity of the etching processes. The mechanical loss measurements of the cantilevers are carried out using a laser-based optical setup, revealing a mechanical loss of 1.2 × 10-3.