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In this study, a new green synthesis method for two-dimensional (2D) copper nanosheets is developed using methylsulfonylmethane (DMSO2). The chemical composition and light absorption of 2D copper nanosheets are also studied. A new green method is mainly to utilize DMSO2, which is environmentally friendly enough to be considered a food-grade chemical, unlike the conventional method using toxic chemicals, such as ammonia and hydrazine (N2H4). With a reducing agent, the aggregation of uncertain copper products was produced in the absence of DMSO2, while 2D copper nanosheets were formed in the presence of DMSO2. The optimum concentration of DMSO2 as a surfactant was determined to be 2 M, resulting in large surface areas with regular edges. FTIR spectrum confirmed C–H bonding from DMSO2 used to synthesize 2D copper nanosheets. The light absorption peak was revealed at 800 nm in the UV–vis spectrum. This proposed new green method not only has a simpler process than the conventional methods, such as hydrothermal method and chemical bath deposition, but also substitutes toxic chemicals with DMSO2. 2D copper nanosheets can be used for various applications, including conductive filler or ink in the flexible electronics and laser photonics fields.

The purpose of machining operations is to make specific shapes or surface characteristics for a product. Conditions for machining operations were traditionally selected based on geometry and surface finish requirements. However, nowadays, many researchers are optimizing machining parameters since high-quality products can be produced using more expensive and advanced machines and tools. There are a few methods to optimize the machining process, such as minimizing unit production time or cost or maximizing profit. This research focused on maximizing the profit of computer numerical control (CNC) milling operations by optimizing machining parameters. Cutting speeds and feed are considered as the main process variables to maximize the profit of CNC milling operations as they have the greatest effect on machining operation. In this research, the Nelder–Mead simplex method was used to maximize the profit of CNC milling processes by optimizing machining parameters. The Nelder–Mead simplex method was used to calculate best, worst, and second-worst value based on an initial guess. The possible range of machining parameters was limited by several constraints. The Nelder–Mead simplex method yielded a profit of 3.45 ($/min) when applied to a commonly used case study model.