Ultra-low detection of SARS-CoV-2 Virus Like Particles (VLPs) with functionalized gold plasmonic nanoresonator array
Nandi D., Fan J., Kang S., Gupta M.
Article, Biomedical Microdevices, 2025, DOI Link
View abstract ⏷
Localized surface plasmon resonance (LSPR) sensors have good potential for label-free non-invasive detection of biomolecules, healthcare diagnosis, disease monitoring, gas sensing, and food safety. For detection of low concentration small-sized bioanalytes (e.g., viruses, proteins, etc) the plasmonic field needs to be localized on a larger device surface area. Our study focuses on the optimization and fabrication of leaky Au nanoresonators based sensing platform for SARS-CoV-2 detection with uniform sensitivity over a 100 m 100 m active sensing area. The Au nanoresonator array was optimized to detect 100 nm sized bioanalytes as it matches the size of SARS-CoV-2. The performance of the optimized design was tested with 100 nm sized polystyrene beads which demonstrated a sensitivity of 17.05 ± 3.25 nm/decade. The Au nanoresonators were functionalized with anti-SARS-CoV-2 antibody to detect SARS-CoV-2. Our experimental results demonstrate the best detection sensitivity of 1.32 ± 0.08 nm/decade and limit of detection of 1 VLP L.
Pulsed laser deposition grown La0.3Ca0.7Fe0.7Cr0.3O3-δ thin films on yttria-stabilized zirconia substrates for fundamental electrochemical energy conversion studies
Ansari H.M., Gudi D., Nandi D., Pidburtnyi M., Valappil M.O., Yuan H., Botton G.A., Gupta M., Birss V.I.
Article, Thin Solid Films, 2023, DOI Link
View abstract ⏷
La0.3Ca0.7Fe0.7Cr0.3O3-δ (LCFCr) perovskites, normally deposited as a powder-based ink to form porous electrode layers, have been shown to be exceptional catalysts for the electrochemical splitting of CO2 to form CO at one electrode and O2 at the other during electrolysis in solid oxide cells, while also being highly active and stable under fuel cell conditions. This work constitutes the first report of thin film deposition of LCFCr via pulsed laser deposition on a 001-oriented yttria-stabilized zirconia substrate, used to simulate the ionically conducting electrolyte in operating cells. The primary goal of this work was to determine fundamental LCFCr properties and performance metrics without complications from morphology effects. Scanning Transmission Electron Microscopy and X-ray Photoelectron Spectroscopy analysis confirmed that oriented, dense, uniform, and smooth films with a thickness of ca. 25 nm and a RMS surface roughness of 0.2 nm are grown at 700 °C from a stoichiometric LCFCr target, while containing all the components of LCFCr in their expected oxidation states. These thin films have allowed the determination of the oxidation states of the redox active species on the electrode surface. Moreover, the preliminary electrochemical response of the LCFCr thin films in an air environment is shown to mimic the trends observed in more common highly porous LCFCr electrodes, thus arguing for a similar reaction mechanism and kinetics per real surface area.
Leaky MoS2 split-nanoring resonators for detection of small bioanalytes
Nandi D., Pico A.F., Gupta M.
Conference paper, Bio-Optics: Design and Application, BODA 2023, 2023, DOI Link
View abstract ⏷
Leaky MoS2 split-nanorings array are proposed to detect small size bioanalytes by measuring the resonance wavelength shift. The resonance field leaks out to the top surface and target bioanalytes disturb the resonance field.
Leaky MoS2 split-nanoring resonators for detection of small bioanalytes
Nandi D., Pico A.F., Gupta M.
Conference paper, Bio-Optics: Design and Application in Proceedings Biophotonics Congress: Optics in the Life Sciences 2023, OMA, NTM, BODA, OMP, BRAIN 2023, 2023, DOI Link
View abstract ⏷
Leaky MoS2 split-nanorings array are proposed to detect small size bioanalytes by measuring the resonance wavelength shift. The resonance field leaks out to the top surface and target bioanalytes disturb the resonance field.
Optimization of a leaky plasmonic metal-insulator-metal nanopillar array for low concentration biosensing applications
Nandi D., Zahurul Islam Md., Gupta M.
Article, Journal of the Optical Society of America B: Optical Physics, 2022, DOI Link
View abstract ⏷
The research focuses on optimization of a leaky metal-insulator-metal (MIM) nanopillar array design for the detection of sub-100 nm viruses. Here we have explored different MIM nanopillar and array geometries along with the insulator layer material to tune the plasmonic field leakage. For the optimized design, we observe a sensitivity of the surface refractive index change of -101.68 nm RIU-1. Using 100 nm diameter polystyrene particles, a sensitivity of 17.66 nm/decade was achieved with a detection limit of one particle. The optimized structures thus demonstrate a homogeneous surface sensitivity over a large active sensing area for sub-100 nm virus detection.
Optimization of growth parameters to obtain epitaxial large area growth of molybdenum disulfide using pulsed laser deposition
Gudi D., Sen P., Forero Pico A.A., Nandi D., Gupta M.
Article, AIP Advances, 2022, DOI Link
View abstract ⏷
2D transition metal dichalcogenides (TMDCs) are promising materials for device applications owing to their electronic, optical, and material properties varying with the number of monolayers. Synthesis of large area crystalline TMDC thin films is still challenging with techniques such as exfoliation and chemical vapor growth owing to the uncontrollability of deposition area and high temperature growths with toxic precursors, respectively. Pulsed laser deposition (PLD) is a technique that can overcome these challenges owing to stoichiometric layer by layer growth control by optimizing the growth parameters. In this study, we optimize parameters such as temperature, post-growth annealing, inert gas pressure, and substrate-target distance during PLD growth of MoS2 to obtain uniform and highly crystalline thin films on an ∼1 in.2 substrate. The optimized growth conditions are 800 °C with a 30 min post-growth annealing at a laser fluence of 2.2 J/cm2 with a substrate-target distance of 5 cm and 0.5 mTorr of argon partial pressure. An RMS roughness of 0.17 nm was obtained for 3 nm (4 monolayers) thick MoS2 films with a thin film conductivity of ∼4000 S/m.
Plasmonic Au nanodots array device for detection of SARS-CoV-2 virus
Nandi D., Fan J., Kang S., Gupta M.
Conference paper, Optics InfoBase Conference Papers, 2022,
View abstract ⏷
Localized surface plasmon resonance of Au nanodots array are very sensitive and resonance field disturbance due to 100 nm sized SARS-CoV-2 virus can be detected via resonance wavelength shift. We have proposed Au nanodots (100 nm diameter and 200 nm pitch) array plasmonic biosensing platform for SARS-CoV-2 virus detection.
Density functional theory – projected local density of states – based estimation of Schottky barrier for monolayer MoS2
Gao J., Nandi D., Gupta M.
Article, Journal of Applied Physics, 2018, DOI Link
View abstract ⏷
One of the biggest challenges so far in implementing 2D materials in device applications is the formation of a high quality Schottky barrier. Here, we have conducted density functional theory simulations and employed the projected local density of states technique to study the Schottky contact formation between monolayer (ML) MoS2 with different metal electrodes (Mo, W, and Au). Electrode formation on ML MoS2 changes it from intrinsic to a doped material due to metallization, which creates issues in the formation of a good Schottky contact. Amongst the metals studied here, we observe that Mo tends to form the best Schottky barrier with ML MoS2 based on both the vertical and lateral Schottky barrier heights (0.13 eV for the vertical Schottky barrier and 0.1915 eV for the lateral Schottky barrier) and the built-in potential (0.0793 eV). As compared to Mo, Au forms a high-resistance ohmic contact with a much larger vertical barrier height of 0.63 ± 0.075 eV and a negligible built-in potential. It is thus observed that ML MoS2 is very susceptible to strain and pinning of the Fermi level due to metal junction formation. Thus, understanding both the vertical and horizontal Schottky barrier heights along with the built-in potential is critical for designing high performance 2D semiconductor devices.
Parametric representation of excitation source information for language identification
Nandi D., Pati D., Rao K.S.
Article, Computer Speech and Language, 2017, DOI Link
View abstract ⏷
In this work, the linear prediction (LP) residual signal has been parameterized to capture the excitation source information for language identification (LID) study. LP residual signal has been processed at three different levels: sub-segmental, segmental and supra-segmental levels to demonstrate different aspects of language-specific excitation source information. Proposed excitation source features have been evaluated on 27 Indian languages from Indian Institute of Technology Kharagpur-Multi Lingual Indian Language Speech Corpus (IITKGP-MLILSC), Oregon Graduate Institute Multi-Language Telephone-based Speech (OGI-MLTS) and National Institute of Standards and Technology Language Recognition Evaluation (NIST LRE) 2011 corpora. LID systems were developed using Gaussian mixture model (GMM) and i-vector based approaches. Experimental results have shown that segmental level parametric features provide better identification accuracy (62%), compared to sub-segmental (40%) and supra-segmental level (34%) features. Excitation source features obtained from three levels show distinct language-specific evidence. Therefore, the scores from all three levels are combined to obtain the complete excitation source information for the LID task. LID performances achieved from both the excitation source and vocal tract system are compared. Finally, the scores obtained by processing the vocal tract and excitation source features are combined to achieve better improvement in LID accuracy. The best recognition accuracies obtained from stage-IV integrated LID systems I, II and III are 69%, 70% and 72% respectively.
Implicit processing of LP residual for language identification
Nandi D., Pati D., Rao K.S.
Article, Computer Speech and Language, 2017, DOI Link
View abstract ⏷
Present work explores the excitation source information for the language identification (LID) task. In this work, excitation source information is captured by implicit processing of linear prediction (LP) residual signal for discriminating the languages. Raw samples of LP residual signal, its magnitude, and phase components are processed independently at sub-segmental, segmental and suprasegmental levels for extracting the language-specific excitation source information. The LID studies are carried out using 27 Indian languages from Indian Institute of Technology Kharagpur-Multi Lingual Indian Language Speech Corpus (IITKGP-MLILSC) and 11 international languages from OGI-MLTS corpus. The Gaussian mixture models (GMMs) are used in this work to model the language-specific excitation source information for LID task. From the experimental results, it can be observed that, features extracted from segmental level yields better identification accuracy (50.92%), compared to sub-segmental (47.77%) and suprasegmental levels (43.88%). Further, the evidence from all three levels is combined to obtain the complete excitation source information. Finally, we have investigated the existence of non-overlapping language-specific information present in excitation source and vocal tract features.
Photoluminescence modulation due to conversion of trions to excitons and plasmonic interaction in MoS2-metal NPs hybrid structures
Singha S.S., Nandi D., Bhattacharya T.S., Mondal P.K., Singha A.
Article, Journal of Alloys and Compounds, 2017, DOI Link
View abstract ⏷
Interaction of two-dimensional (2D) transition metal dichalcogenides (TMDs) with noble metal nanoparticles (NPs) is of great interest from the perspective of fundamental science, as it develops an excellent platform to study plasmon-exciton interaction and charge transfer. Here, we report a method for the large-scale synthesis of noble metals (Ag, Au and Pt) NPs decorated MoS2 flake. We find that the NPs can affect the photoluminescence (PL) emission in two ways, namely plasmon–exciton interaction and charge transfer. The types of doping-induced by the Ag, Au and Pt NPs are determined from the spectral weight of neutral and charged excitons in the PL spectra. Our results provide a quantitative estimation of the origin of PL emission from MoS2 based 2D-0D heterostructures and suggest new avenues for 2D nanoelectronics, gas sensing, catalysis, and biosensing.
Parametric Excitation Source Features for Language Identification
Book chapter, SpringerBriefs in Speech Technology, 2015, DOI Link
View abstract ⏷
This chapter describes the proposed methods to extract parametric features at sub-segmental, segmental and supra-segmental levels to capture the language-specific excitation source information. In this work, glottal pulse, spectral and epoch parameters are used for representing sub-segmental, segmental and supra-segmental information present in excitation source signal. Further, these individual features are combined at score level to enhance the accuracy of LID systems by exploiting the non-overlapping information present among the features.
Tuning the photoluminescence and ultrasensitive trace detection properties of few-layer MoS2 by decoration with gold nanoparticles
Singha S.S., Nandi D., Singha A.
Article, RSC Advances, 2015, DOI Link
View abstract ⏷
We report an easy and inexpensive chemical route for the decoration of few-layer MoS2 with Au nanoparticles (NPs). The Au-NPs are formed on the defect sites of the MoS2 and localized by a non-covalent bond. The NPs act as a p-type dopant in the MoS2 layer. An enhancement in the photoluminescence (PL) intensity of the Au-MoS2 composite with respect to bare few-layer MoS2 has been observed. We also systematically observed a blue shift in the excitonic emission as the number and size of the Au-NPs on MoS2 increased. Both phenomena have been understood to result from the switching between charged exciton (trion) recombination and neutral exciton recombination. A potential application for the Au-MoS2 composite has been demonstrated, by using it as a substrate for surface-enhanced Raman scattering (SERS). The SERS measurements show a uniform, reproducible, and strong Raman signal from the adsorbed molecules with concentrations as low as 10-12 M. Our work provides a method to tune the optical and electronic properties of MoS2, and the Au-MoS2 composite might be useful as an efficient SERS substrate for the ultrasensitive detection of biomolecules.
Implicit Excitation Source Features for Language Identification
Book chapter, SpringerBriefs in Speech Technology, 2015, DOI Link
View abstract ⏷
This chapter discusses about the proposed approaches to model the implicit features of excitation source information for language identification. Excitation source features such as raw LP residual samples, its magnitude and phase components are processed at three different levels: sub-segmental, segmental and supra-segmental levels to capture different aspects of excitation source information for LID task. Further, LID systems are developed by combining the evidences obtained from LID systems built using individual features.
Language Identification—A Brief Review
Book chapter, SpringerBriefs in Speech Technology, 2015, DOI Link
View abstract ⏷
This chapter provides compendious reviews about both the explicit and implicit LID systems present in the literature. Existing works related to language identification in Indian context are briefly discussed. The related works about the excitation source features are also presented here. Various speech features and models proposed in the context of language identification are briefly reviewed in this chapter. The motivation for the present work from the existing literature is briefly discussed.
Complementary and Robust Nature of Excitation Source Features for Language Identification
Book chapter, SpringerBriefs in Speech Technology, 2015, DOI Link
View abstract ⏷
This chapter discusses about the combination of implicit and parametric features of excitation source to enhance the LID accuracy. Further, complementary nature of excitation source and vocal tract features is exploited for improving the LID accuracy. The robustness of proposed language-specific excitation source features is investigated on various noisy background environments.
Preface
Sreenivasa Rao K., Nandi D.
Editorial, SpringerBriefs in Speech Technology, 2015, DOI Link
Introduction
Book chapter, SpringerBriefs in Speech Technology, 2015, DOI Link
View abstract ⏷
This chapter introduces the basic goal of language identification (LID) and its impacts on real-life applications. A brief overview of the basic features used for developing LID systems has been given and different categories of LID systems are also discussed here. Eventually, the primary issues in developing LID systems and the major contributions of this book towards solving those issues have been highlighted.
Summary and Conclusion
Book chapter, SpringerBriefs in Speech Technology, 2015, DOI Link
View abstract ⏷
This chapter summerizes the overall contents of the book. Major contributions and future scope of work have been highlighted.
Implicit excitation source features for robust language identification
Nandi D., Pati D., Rao K.S.
Article, International Journal of Speech Technology, 2015, DOI Link
View abstract ⏷
In present work, the robustness of excitation source features has been analyzed for language identification (LID) task. The raw samples of linear prediction (LP) residual signal, its magnitude and phase components are processed at sub-segmental, segmental and supra-segmental levels for capturing the robust language-specific phonotactic information. Present LID study has been carried out on 27 Indian languages from Indian Institute of Technology Kharagpur-Multi Lingual Indian Language Speech Corpus (IITKGP-MLILSC). Gaussian mixture models are used to develop the LID systems using robust language-specific excitation source information. Robustness of excitation source information has been evinced in view of (i) background noise, (ii) varying amount of training data and (iii) varying length of test samples. Finally, the robustness of proposed excitation source features is compared with the well-known spectral features using LID performances obtained from IITKGP-MLILSC database. Segmental level excitation source features obtained from raw samples of LP residual signal and its phase component perform better at low SNR levels, compared with the vocal tract features.
Sub-segmental, segmental and supra-segmental analysis of linear prediction residual signal for language identification
Nandi D., Pati D., Rao K.S.
Conference paper, 2014 International Conference on Signal Processing and Communications, SPCOM 2014, 2014, DOI Link
View abstract ⏷
In this work, excitation source information is explored for language identification (LID) task. The excitation signal is represented by linear prediction (LP) residual. Different aspects of the excitation source information can be captured by processing LP residual signal at sub-segmental, segmental and supra-segmental levels. Gaussian mixture modelling (GMM) technique is used to build the language models. Present LID study has been carried out on IITKGP-MLILSC speech database. Individually, the segmental level information provides good LID accuracy followed by sub-segmental and supra-segmental level information. Combined evidences from all three levels represent the complete excitation source information. Finally, a comparative study has been carried out between the vocal tract and excitation source features, which portrays the distinct nature of these two features. Combination of both the features, yield an improvement of 10.01% in LID accuracy than only excitation source information. This observation indicates the significance of excitation source information for LID task.
Film segmentation and indexing using autoassociative neural networks
Rao K.S., Nandi D., Koolagudi S.G.
Article, International Journal of Speech Technology, 2014, DOI Link
View abstract ⏷
In this paper, Autoassociative Neural Network (AANN) models are explored for segmentation and indexing the films (movies) using audio features. A two-stage method is proposed for segmenting the film into sequence of scenes, and then indexing them appropriately. In the first stage, music and speech plus music segments of the film are separated, and music segments are labelled as title and fighting scenes based on their position. At the second stage, speech plus music segments are classified into normal, emotional, comedy and song scenes. In this work, Mel frequency cepstral coefficients (MFCCs), zero crossing rate and intensity are used as audio features for segmentation and indexing the films. The proposed segmentation and indexing method is evaluated on manual segmented Hindi films. From the evaluation results, it is observed that title, fighting and song scenes are segmented and indexed without any errors, and most of the errors are observed in discriminating the comedy and normal scenes. Performance of the proposed AANN models used for segmentation and indexing of the films, is also compared with hidden Markov models, Gaussian mixture models and support vector machines. © 2013 Springer Science+Business Media New York.
Significance of CV transition and steady vowel regions for language identification
Nandi D., Dutta A.K., Rao K.S.
Conference paper, 2014 7th International Conference on Contemporary Computing, IC3 2014, 2014, DOI Link
View abstract ⏷
The present work explores the significance of the consonant-vowel (CV) transition and steady vowel (SV) regions for language identification (LID) task. The language-specific vocal tract information represented by Mel-frequency cepstral coefficients (MFCCs), extracted from the CV transition and steady vowel regions for LID task. The duration of CV transition and steady vowel regions are varied to analyze LID performance. The evidences obtained from the CV transition and steady vowel regions are combined to investigate the existence of complementary information in these two regions. The LID study carried out on 27 Indian languages from IITKGP-MLILSC speech database. The Gaussian mixture modelling (GMM) technique has been used for developing the language models. The average LID performances obtained by processing CV transition region and steady vowel regions are 70% and 71% respectively. In contemporary works, LID system has been developed by processing whole speech utterances, which provides 72% recognition accuracy.
Language identification using Hilbert envelope and phase information of linear prediction residual
Nandi D., Pati D., Rao K.S.
Conference paper, 2013 International Conference Oriental COCOSDA Held Jointly with 2013 Conference on Asian Spoken Language Research and Evaluation, O-COCOSDA/CASLRE 2013, 2013, DOI Link
View abstract ⏷
In this paper, magnitude and phase components of excitation source information are explored for language identification (LID) study. The linear prediction (LP) residual of speech signal represents the excitation source information. The magnitude and phase components of LP residual are processed individually at sub-segmental, segmental and supra-segmental levels. Evidences from both magnitude and phase components of LP residual are combined to capture the language-specific excitation source information. The LID studies are carried out on IITKGP-MLILSC speech database. The segmental level information yields better performance compared to sub-segmental and supra-segmental level information. The combined evidences from three levels represent the excitation source information. This study shows that, both magnitude and phase of LP residual contains significant language-specific excitation source information. From the LID performances of this study, it is observed that the phase component of LP residual contains more language discriminative information than the magnitude component of LP residual. © 2013 IEEE.
Multilingual speaker recognition on Indian languages
Sarkar S., Rao K.S., Nandi D., Kumar S.B.S.
Conference paper, 2013 Annual IEEE India Conference, INDICON 2013, 2013, DOI Link
View abstract ⏷
In this paper we explore the performance of multilingual speaker recognition systems developed on the IITKGP-MLILSC speech corpus. Closed-set speaker identification and speaker verification experiments are individually conducted on 13 widely spoken Indian languages. In particular, we focus on the effect of language mismatch in the speaker recognition performance of individual languages and all languages together. The standard GMM-based speaker recognition framework is used. While the average language-independent speaker identification rate is as high as 95.21%, an average equal error rate of 11.71% shows scope for further improvement in speaker verification performance. © 2013 IEEE.
IITKGP-MLILSC speech database for language identification
Maity S., Kumar Vuppala A., Rao K.S., Nandi D.
Conference paper, 2012 National Conference on Communications, NCC 2012, 2012, DOI Link
View abstract ⏷
In this paper, we are introducing speech database consists of 27 Indian languages for analyzing language specific information present in speech. In the context of Indian languages, systematic analysis of various speech features and classification models in view of automatic language identification has not performed, because of the lack of proper speech corpus covering majority of the Indian languages. With this motivation, we have initiated the task of developing multilingual speech corpus in Indian languages. In this paper spectral features are explored for investigating the presence of language specific information. Melfrequency cepstral coefficients (MFCCs) and linear predictive cepstral coefficients (LPCCs) are used for representing the spectral information. Gaussian mixture models (GMMs) are developed to capture the language specific information present in spectral features. The performance of language identification system is analyzed in view of speaker dependent and independent cases. The recognition performance is observed to be 96% and 45% respectively, for speaker dependent and independent environments. © 2012 IEEE.
