Self-organized nanostructures in silicon and glass for MEMS, MOEMS and BioMEMS

Lilienthal, Katharina; Fischer, M.; Stubenrauch, Mike; Schober, Andreas

doi:10.1016/j.mseb.2009.11.020

Cited by 12 publications

(4 citation statements)

References 10 publications

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“…The micropipettes with suitable geometry (smoothly tapered with tip size of 10 µm) were fabricated by adjusting the pulling program. The glass surfaces were cleaned with acetone, 2-propanol, deionized water and loaded into a reactive ion etcher (RIE) chamber to develop self-organized nanostructures under pseudo Bosch process [ 29 ]. The RIE was carried out for 20 min at RF/ICP powers of 600 W/30 W and etching gas (SF 6 : 100 sccm and O 2 : 10 sccm) while the chamber pressure stabilized at 20 torr.…”

Section: Methodsmentioning

confidence: 99%

Self-Organized Nanostructure Modified Microelectrode for Sensitive Electrochemical Glutamate Detection in Stem Cells-Derived Brain Organoids

et al. 2018

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Neurons release neurotransmitters such as glutamate to communicate with each other and to coordinate brain functioning. As increased glutamate release is indicative of neuronal maturation and activity, a system that can measure glutamate levels over time within the same tissue and/or culture system is highly advantageous for neurodevelopmental investigation. To address such challenges, we develop for the first time a convenient method to realize functionalized borosilicate glass capillaries with nanostructured texture as an electrochemical biosensor to detect glutamate release from cerebral organoids generated from human embryonic stem cells (hESC) that mimic various brain regions. The biosensor shows a clear catalytic activity toward the oxidation of glutamate with a sensitivity of 93 ± 9.5 nA·µM−1·cm−2. It was found that the enzyme-modified microelectrodes can detect glutamate in a wide linear range from 5 µM to 0.5 mM with a limit of detection (LOD) down to 5.6 ± 0.2 µM. Measurements were performed within the organoids at different time points and consistent results were obtained. This data demonstrates the reliability of the biosensor as well as its usefulness in measuring glutamate levels across time within the same culture system.

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Section: Methodsmentioning

confidence: 99%

Self-Organized Nanostructure Modified Microelectrode for Sensitive Electrochemical Glutamate Detection in Stem Cells-Derived Brain Organoids

et al. 2018

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“…Miniature analyzing systems have made significant progress with the rapid development of microelectronics and biomedical technologies [1,2]. Compared to traditional biomedical technologies, they have the advantages of high sensitivity, high throughput, rapidity, and low cost, indicating usefulness in in vitro tests and diagnoses [3,4].…”

Section: Introductionmentioning

confidence: 99%

Single-Cell Patterning Based on Immunocapture and a Surface Modified Substrate

Ayibaike¹,

Cui²,

Wei

2018

Applied Sciences

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Micropatterning technology offers powerful methods for biological analyses at the molecular level, enabling the investigation of cell heterogeneities, as well as high throughput detection. We herein propose an approach for single-cell patterning. The substrate was prepared using micro fabrication and surface modification processes, and the patterning template was prepared using bovine serum albumin and streptavidin, which can be employed for the patterning of any biological molecules containing biotin. Subsequent to photolithography, etching, chemical vapor deposition (CVD), and polyethylene glycol (PEG) treatment, the optimized patterns were obtained with high accuracy, strong contrast, and good repeatability, thus providing good foundations for the subsequent single-cell patterning. The surface passivation method was proven effective, preventing unwanted binding of the antibodies and cells. Based on this streptavidin template, the specific binding between the biotinylated antibodies and the antigens expressed on the surface of the cells was enabled, and we successfully achieved single-cell patterning with a single-cell capture rate of 92%. This single-cell array offers an effective method in the investigation of cell heterogeneity and drug screening. Further, these methods can be used in the final step for the screening and enrichment of certain cells, such as circulating tumor cells.

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“…However, they usually have inherent limits, such as large structure size, low-efficient, low aspect ratio and uncontrollability. Unlike those mask-based fabrication methods, an optimized DRIE process which is maskless, low-cost, high-efficient, single-step and controllable, was employed to achieve black silicon [7][8].…”

Section: Introductionmentioning

confidence: 99%

A three-step model of black silicon formation in Deep Reactive Ion Etching process

Zhu

Wang

Zhang

et al. 2015

2015 28th IEEE International Conference on Micro Electro Mechanical Systems (MEMS)

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A three-step model used for modeling and simulation of black silicon formation in DRIE (Deep Reactive Ion Etching) process is presented. It divides the plasma etching system into plasma layer, sheath layer and sample surface layer. At the same time, it combines quantum mechanics, sheath dynamics and diffusion theory together based on plasma environment to predict the probability distribution of etching particles so as to simulate the final etching results. The simulation results show very good coincidence with experimental images, proving the applicability of this theory and it's promising to make black silicon formation in DRIE process to be controllable and repeatable.

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Self-organized nanostructures in silicon and glass for MEMS, MOEMS and BioMEMS

Cited by 12 publications

References 10 publications

Self-Organized Nanostructure Modified Microelectrode for Sensitive Electrochemical Glutamate Detection in Stem Cells-Derived Brain Organoids

Self-Organized Nanostructure Modified Microelectrode for Sensitive Electrochemical Glutamate Detection in Stem Cells-Derived Brain Organoids

Single-Cell Patterning Based on Immunocapture and a Surface Modified Substrate

A three-step model of black silicon formation in Deep Reactive Ion Etching process

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