MONET-Rf FT-NIR Analyzer

The MONET-Rf Fourier Transform Near-Infrared (FT-NIR) Spectrometer is an intelligent analytical instrument that are highly efficient, environmental friendly, and safe. At its core, the device innovatively employs two-dimensional scanning technology to achieve full-area, multi-channel sampling, greatly enhancing data representativeness and accuracy. Its fully automated AI modeling capabilities streamline complex modeling and analysis processes, significantly lowering technical barriers and labor costs. In addition, cloud platform support enables networked management across multiple devices. Samples require no complex pre-treatment, and the analysis process consumes no chemical reagents nor damages the samples, while maintaining low energy consumption. With rapid, multi-parameter analysis, the MONET-Rf provides efficient, green, and precise testing solutions for the feed, chemical, grain and oil, and scientific research sectors.

The circular display uses a color-coded UI to show various instrument statuses, providing richer and more intuitive information than traditional LED indicators, helping researchers more quickly read key data. The instrument’s height is optimized for easy sample handling from sitting or standing positions, and the light source and desiccant ports have quick-release designs for efficient maintenance.

Built with a fully sealed cast aluminum body rated IP65+, it protects internal components in harsh environments. Key parts last up to 100,000 operating hours, and the software meets FDA 21 CFR Part 11 standards, ensuring secure, stable operation and data protection.

The instrument features an innovative two-dimensional scanning device that performs full X–Y sample coverage, greatly expanding the scanning area and improving data accuracy and representativeness. It supports single- and multi-channel rotational scanning for liquids, small samples, and single grains, with sealed, corrosion-resistant PTFE cups for volatile or corrosive materials.

To overcome the limitations of traditional modeling method being time-consuming and expert-dependent, the system offers fully automated AI modeling. Using a proprietary algorithm library, it performs automatic data analysis and model building immediately after data import. This combination of advanced scanning and intelligent modeling enhances data reliability while reducing technical barriers and labor costs, ensuring precise and efficient analysis.