The study of two- dimensional (2D) materials is a rapidly growing area within nanomaterials research. However, the high equipment costs, which include the processing systems necessary for creating these materials, can be a barrier to entry for some researchers interested in studying these novel materials. Such process systems include those used for chemical vapor deposition, a preferred method for making these materials. To address this challenge, this article presents the first open-source design for an automated chemical vapor deposition system that can be built for less than a third of the cost for a comparable commercial system. The materials and directions for the system are divided by subsystems, which allows the system to be easily built, customized and upgraded, depending upon the needs of the user. We include the details for the specific hardware that will be needed, instructions for completing the build, and the software needed to automate the system. With a chemical vapor deposition system built as described, a variety of 2D nanomaterials and their heterostructures can be grown. Specifically, the experimental results clearly demonstrate the capability of this open-source design in producing high quality, 2D nanomaterials such as graphene and tungsten disulfide, which are at the forefront of research in emerging semiconductor devices, sensors, and energy storage applications.
This work aims to investigate the influence of various electrode materials on the signal‐to‐noise ratio (SNR) of passive microelectrode arrays (MEAs) intended for use in neural interfaces. Noise reduction substantially improves the performance of systems which electrically interface with extracellular solutions. The MEAs are fabricated using gold, indium tin oxide (ITO), inkjet printed (IJP) graphene, and chemical vapor deposited (CVD) graphene. 3D‐printed Nylon reservoirs are adhered to glass substrates with identical MEA patterns and filled with neuronal cell culture media. To precisely control the electrode area and minimize the parasitic coupling of metal interconnects and solution, SU‐8 photoresist is patterned to expose only the area of the electrode to solution and cap the remainder of the sample. Voltage signals with varying amplitude and frequencies are applied to the solution using glass micropipettes, and the response is measured on an oscilloscope from a microprobe placed on the contact pad external to the reservoir. The time domain response signal is transformed into a frequency spectrum, and SNR is calculated. As the magnitude or the frequency of the input signal gets larger, a significantly increased signal‐to‐noise ratio was observed in CVD graphene MEAs compared to others. This result indicates that 2‐dimensional nanomaterials such as graphene can provide better signal integrity and potentially lead to improved performance in hybrid neural interface systems.
Graphene, an atomically thin layer of carbon atoms arranged in a hexagonal lattice, has gained interest as a bioscaffold for tissue engineering due to its exceptional mechanical, electrical, and thermal properties. Graphene's structure and properties are tightly coupled to synthesis and processing conditions, yet their influence on biomolecular interactions at the graphene-cell interface remains unclear. In this study, C2C12 cells were grown on graphene bioscaffolds with specific structure property processing performance (SP3) correlations. Bioscaffolds were prepared using three different methods - chemical vapor deposition (CVD), sublimation of silicon carbide (SiC), and printing of liquid phase exfoliated graphene. To investigate the biocompatibility of each scaffold, cellular morphology and gene expression patterns were investigated using the bipotential mouse C2C12 cell line. Using a combination of fluorescence microscopy and qRT-PCR, we demonstrate that graphene production methods determine the structural and mechanical properties of the resulting bioscaffold, which in turn determine cell morphology, gene expression patterns, and cell differentiation fate. Therefore, production methods and resultant structure and properties of graphene bioscaffolds must be chosen carefully when considering graphene as a bioscaffold for musculoskeletal tissue engineering.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.