Publications by authors named "Rajendhar Junjuri"

Raman spectroscopy, renowned for its unique ability to provide a molecular fingerprint, is an invaluable tool in industry and academic research. However, various constraints often hinder the measurement process, leading to artifacts and anomalies that can significantly affect spectral measurements. This review begins by thoroughly discussing the origins and impacts of these artifacts and anomalies stemming from instrumental, sampling, and sample-related factors.

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Article Synopsis
  • Broadband Coherent anti-Stokes Raman (BCARS) microscopy is a fast imaging technique that captures full Raman spectra of biological samples, but the results can be distorted by a non-resonant background (NRB) signal.
  • Traditionally, NRB was removed with complex numerical algorithms, but recent advancements in deep learning have made it possible to automate and speed up this process.
  • The paper reviews existing deep-learning models for NRB removal and introduces two new architectures, finding that CNN + GRU and VECTOR networks offer the best accuracy, while GAN excels in identifying true positive peaks and is suitable for real-time processing.
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We report the standoff/remote identification of post-consumer plastic waste by utilizing a low-cost and compact standoff laser-induced breakdown spectroscopy (ST-LIBS) detection system. A single plano-convex lens is used for collecting the optical emissions from the plasma at a standoff distance of 6.5 m.

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Broadband Coherent Anti-Stokes Raman Scattering (BCARS) is a valuable spectroscopic imaging tool for visualizing cellular structures and lipid distributions in biomedical applications. However, the inevitable biological changes in the samples (cells/tissues/lipids) introduce spectral variations in BCARS data and make analysis challenging. In this work, we conducted a systematic study to estimate the biological variance in BCARS data of two commonly used cell lines (HEK293 and HepG2) in biomedical research.

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The nonresonant background (NRB) contribution to the coherent anti-Stokes Raman scattering (CARS) signal distorts the spectral line shapes and thus degrades the chemical information. Hence, finding an effective approach for removing NRB and extracting resonant vibrational signals is a challenging task. In this work, a bidirectional LSTM (Bi-LSTM) neural network is explored for the first time to remove the NRB in the CARS spectra automatically, and the results are compared with those of three DL models reported in the literature, namely, convolutional neural network (CNN), long short-term memory (LSTM) neural network, and very deep convolutional autoencoders (VECTOR).

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We report the retrieval of the Raman signal from coherent anti-Stokes Raman scattering (CARS) spectra using a convolutional neural network (CNN) model. Three different types of non-resonant backgrounds (NRBs) were explored to simulate the CARS spectra (1) product of two sigmoids following the original SpecNet model, (2) Single Sigmoid, and (3) fourth-order polynomial function. Later, 50 000 CARS spectra were separately synthesized using each NRB type to train the CNN model and, after training, we tested its performance on 300 simulated test spectra.

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Reported here is a rapid and simplified approach for modeling the temporal evolution of the plasma temperature. The use of only two emission lines makes this technique simple, accurate, and fast. Usually, multiple emission lines are required for estimating plasma temperature using Boltzmann/Saha-Boltzmann plots.

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We present the spatial and temporal characterization of the copper (Cu) plasma produced by the femtosecond laser filaments. The filaments of various lengths and intensities were generated with the aid of three different focusing lenses. Further, the filamentation induced breakdown spectroscopy (FIBS) measurements were carried out for each filament at three different positions along the length of the filament.

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We present, rapid and efficient identification of ten different types of post-consumer plastics obtained from a local recycling unit by deploying a low cost, compact CCD spectrometer in laser-induced breakdown spectroscopy (LIBS) technique. For this investigation, spectral emissions were collected by an Echelle spectrograph equipped with an intensified charge-coupled device (ES-ICCD) as well as a non-gated Czerny Turner CCD spectrometer (NCT-CCD). The performance is evaluated by interrogating the samples in a single-shot as well as accumulation mode (ten consecutive laser shots).

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