Raman spectrometry has proven to be by far the most powerful noninvasive analytical technique for direct material identification. In this paper we introduce the first smart Raman device with a Cloud data platform and AI deep learning algorithms- the CloudMinds XI™. This smart phone operated Raman features high performance, fully automated operation, and capability for mixtures analysis in real time. This novel Cloud AI Raman spectrometer is fully integrated with the Android-based CloudMinds A1 smart phone. The A1 phone provides the full functionality of a smartphone including voice calls, emails, GPS location, and image capture by camera, and maintains constant Wi-Fi/blue tooth and 4G LTE connections, letting you stay connected to Raman data constantly. The cloudbased data platform not only allows speedy analysis but also enables spectral library expansion with ensured security. In addition, CloudMinds has developed its proprietary Al algorithm using Google Brain's second-generation machine learning system, TensorFlow. This technology improves analysis accuracy and gets continually better results as it learns and trains data while connected to the cloud. A mixture of three substances has been successfully analyzed with ratios within seconds by this handheld Raman spectrometer for the first time, and this paper will present the results from the mixture analysis. This Cloud AI handheld Raman is the best solution for many field applications, especially when real time analysis and central cloud data platform support are essential.
Hyperspectral imaging has emerged as a new technique for the identification and classification of biological tissue1. Benefitting recent developments in sensor technology, the new class of hyperspectral imagers can capture entire hypercubes with single shot operation and it shows great potential for real-time imaging in biomedical sciences. This paper explores the use of a SnapShot imager in fluorescence imaging via microscope for the very first time. Utilizing the latest imaging sensor, the Snapshot imager is both compact and attachable via C-mount to any commercially available light microscope. Using this setup, fluorescence hypercubes of several cells were generated, containing both spatial and spectral information. The fluorescence images were acquired with one shot operation for all the emission range from visible to near infrared (VIS-IR). The paper will present the hypercubes obtained images from example tissues (475-630nm). This study demonstrates the potential of application in cell biology or biomedical applications for real time monitoring.
We report on a variety of BaySpec’s newly developed Raman spectrometers and microscopes combining multiple
excitation wavelengths and detection ranges. Among those there are the world’s first dual-wavelength near infrared
(NIR) and infrared miniature Raman spectral engines built with Volume Phase Gratings (VPG<sup>TM</sup>), and the world’s first
three-wavelength (532, 785, and 1064-nm) excitation Raman microscope. Having multiple wavelength excitations in one
unit offers extreme flexibility and convenience to identify the best laser wavelength and investigate a great variety of
real-world samples. In real-world Raman measurements, fluorescence is the biggest obstacle which significantly reduces
the quality of the Raman spectra. We demonstrate many examples spanning from explosives to street drugs to conclude
that for those samples, 1064-nm Raman is fluorescence-free and best suited for identification. Other types of
miniaturized Raman spectrometers have been realized, enabling handheld, portable, or at-line/ on-line applications for
real-world sample measurements, such as threat determination of explosives, chemical and biological materials, quality
assurance and contamination control for food safety, and forensics such as evidence gathering, narcotics identification,
Fluorescence microscopy provides a non-invasive means for visualising dynamic protein interactions. As well as
allowing the calculation of kinetic processes via the use of time-resolved fluorescence, localisation of the protein within
cells or model systems can be monitored. These fluorescence lifetime images (FLIM) have become the preferred
technique for elucidating protein dynamics due to the fact that the fluorescence lifetime is an absolute measure, in the
main independent of fluorophore concentration and intensity fluctuations caused by factors such as photobleaching. In
this work we demonstrate the use of a time-resolved fluorescence microscopy, employing a high repetition rate laser
excitation source applied to study the influence of a metal surface on fluorescence tagged protein and to elucidate
viscosity using the fluorescence lifetime probe DASPMI. These were studied in a cellular environment (yeast) and in a
model system based on a sol-gel derived material, in which silver nanostructures were formed in situ using irradiation
from a semiconductor laser in CW mode incorporated on a compact time-resolved fluorescence microscope (HORIBA
Scientific DeltaDiode and DynaMyc).