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Abstract Thinning silicon wafers via wet etching is a common practice in the microelectromechanical system (MEMS) industry to produce membranes and other structures Wang (Nano Lett 13(9): 4393–4398, 2013). Controlling the thickness of a membrane is a critical aspect to optimize the functionality of these devices. Our research specifically focuses on the production of bio-membranes for lung-on-a-chip (LoaC) applications. In our fabrication, it is crucial for us to determine the membranes’ thickness in a non-invasive way. This study aims to address this issue by attempting to develop a tool that uses the optical properties of light transmission through silicon to find a correlation with thickness. To find this correlation, we conducted a small experimental study where we fabricated ultra-thin membranes and captured images of the light transmission through these samples. This paper will report the correlation found between calculated average intensities of these images and measurements done using scanning electron microscopy (SEM). Graphical abstract 

Raman spectroscopy is a common identification and analysis technique used in research and manufacturing industries. This study investigates the use of Raman spectroscopy and deep learning techniques for identifying various nanofabrication chemicals. Four solvents and SU-8 developer were identified inside common chemical storage and distribution containers. The containers attenuated the spectra and contributed varying amounts of background fluorescence, making manual identification difficult. Two varieties of SU-8 photoresist were differentiated inside amber glass jars, and cured samples of three ratios of polydimethylsiloxane (PDMS) were differentiated using Raman microscopy. The neural network accurately identified the nanofabrication chemicals 100% of the time, without additional preprocessing. This investigation demonstrates the use of Raman spectroscopy and neural networks for the identification of nanofabrication chemicals and makes recommendations for use in other challenging identification applications. 

The use of conventional in vitro and preclinical animal models often fail to properly recapitulate the complex nature of human diseases and hamper the success of translational therapies in humans [1-3] Consequently, research has moved towards organ-on-chip technology to better mimic human tissue interfaces and organ functionality. Herein, we describe a novel approach for the fabrication of a biocompatible membrane made of porous silicon (PSi) for use in organ-on-chip technology that provides key advantages when modeling complex tissue interfaces seen in vivo. By combining well-established methods in the semiconductor industry with organ-on-chip technology, we have developed a novel way of producing thin (25 μm) freestanding PSi biocompatible membranes with both nano (~15.5 nm diameter pores) and macroporous (~0.5 μm diameter pores) structures. To validate the proposed novel membrane, we chose to recapitulate the dynamic environment of the alveolar blood gas exchange interface in alveolar co-culture. Viability assays and immunofluorescence imaging indicate that human pulmonary cells remain viable on the PSi membrane during long-term culture (14 days). Interestingly, it was observed that macrophages can significantly remodel and degrade the PSi membrane substrate in culture. This degradation will allow for more intimate physiological cellular contact between cells, mimicking a true blood-gas exchange interface as observed in vivo. Broadly, we believe that this novel PSi membrane may be used in more complex organ-on-chip and lab-on-chip model systems to accurately recapitulate human anatomy and physiology to provide further insight into human disease pathology and pre-clinical response to therapeutics.