P300 is a high-end custom laser confocal Raman spectrometer developed by HOOKE INSTRUMENTS. The instrument integrates higher stability, higher resolution and more efficient signal acquisition. Modular design, flexible coupling with multiple instruments; A multi-dimensional correction device is built into the instrument to ensure that the sample spectrum is not disturbed by the testing environment and meet the requirements of spectral stability for the construction of Raman database. Automatic data acquisition, greatly improve the efficiency of scientific research; Equipped with advanced deep learning algorithms, the exclusive database is built by itself. The instrument is simple and convenient to operate, and provides a new tool for material identification, composition analysis, biological detection and interdisciplinary research in many fields.
P300 (including combined products) has more than 10 users, including Shanghai Jiao Tong University, Fudan University, the Third Institute of Oceanography of the Ministry of Natural Resources, BGI Qingdao Research Institute, Sun Yat-sen University Cancer Hospital, etc. It is in good use and well received by users.
1, Light flux increased by 30%, efficient collection of single cell weak signal
The HOOKE P300 has excellent spectral resolution and data signal-to-noise ratio, which meets the needs of biological testing. The unique high-pass confocal optical path design enables the maximum collection of weak signals and the rapid acquisition of high-quality single-cell Raman spectra.
2. The spectral repeatability of the multi-dimensional correction algorithm is better than 0.01cm-1
The built-in software and hardware correction system ensures the repeatability of the test results at different times through multi-dimensional correction of peak intensity, peak position and background noise, and truly achieves the same "sample" and "spectrum", and meets the requirements of spectral stability for the construction of Raman database.
3. Morphological reconstruction technology, automatic collection, unattended
Automatic data acquisition, intelligent image recognition function, can according to the target information such as size, shape, form, with test samples for automatic identification, number and location, with automatic focusing and multiple vision image matching function, the combination of the lot, automation Raman detection of the target, greatly improve the test efficiency;
4, visual index analysis, help spectral depth analysis
Equipped with advanced deep learning algorithms, it can generate analysis reports with one click, and expand the intelligent data analysis platform based on artificial intelligence algorithms. Integration of single spectrum processing, multi-spectrum batch processing, cluster analysis, classification analysis, spectral imaging, one-click production report and other spectral analysis functions.
5, 3D custom sample label, support users to build database
With the function of self-building Raman data database and Raman spectrum retrieval, the library construction process is provided. The user can import the collected Raman data into the system, retrieve according to the spectral characteristics of the test data, and determine the sample information.
6, low Raman background chip, signal acquisition efficiency increased by 50%
The self-developed ultra-low background Raman chip improves the signal acquisition efficiency by more than 50% compared with the traditional chip, eliminates the interference of background noise, and obtains the real Raman fingerprint of biological samples.
7, the system is flexible, can be coupled with a variety of modules
Open multi-system coupling interface can be coupled with single cell sorting, bacteria picking workstation, particulate matter and optical tweezers module to achieve more functions.
1. Microbial species identification and functional bacteria screening
2. Dynamic detection of stem cell differentiation in situ
3. Pharmacokinetic research Drug quality testing
4. Disease diagnosis Intraoperative tumor navigation
5. Detection and analysis of environmental pollutants