Raman spectroscopy is an emerging technique in bioanalysis and imaging of biomaterials
owing to its unique capability of generating spectroscopic fingerprints. Imaging cells and …

Background The rapid and reliable detection of pathogenic bacteria at an early stage is a
highly significant research field for public health. However, most traditional approaches for …

Machine learning methods have found many applications in Raman spectroscopy,
especially for the identification of chemical species. However, almost all of these methods …

In this work we show that convolutional neural networks (CNNs) can be efficiently used to
classify vibrational spectroscopic data and identify important spectral regions. CNNs are the …

The steady progress in medical diagnosis and treatment of diseases largely hinges on the
steady development and improvement of modern imaging modalities. Raman spectroscopy …

Combining the advanced approaches of surface functionalization and chemistry,
plasmonics, surface enhanced Raman spectroscopy (SERS), and machine learning, we …

In general, most of the substances in nature exist in mixtures, and the noninvasive
identification of mixture composition with high speed and accuracy remains a difficult task …

In recent years, vibrational spectroscopic techniques based on Fourier transform infrared
(FTIR) or Raman microspectroscopy have been suggested to fulfill the unmet need for …

With its low-cost, label-free and non-destructive features, Raman spectroscopy is becoming
an attractive technique with high potential to discriminate the causative agent of bacterial …

Mechanochemistry offers a unique opportunity to modify and manipulate crystal forms, often
providing new products as compared with conventional solution methods. While promising …