Dataset Information

Photoacoustic Detection of H2 and NH3 Using Plasmonic Signal Enhancement in GaN Microcantilevers.

ABSTRACT: Photoacoustic (PA) detection of H2 and NH3 using plasmonic excitation in Pt- and Pd-decorated GaN piezotransistive microcantilevers were investigated using pulsed 520-nm laser illumination. The sensing performances of 1-nm Pt and Pd nanoparticle (NP) deposited cantilever devices were compared, of which the Pd-coated sensor devices exhibited consistently better sensing performance, with lower limit of detection and superior signal-to-noise ratio (SNR) values, compared to the Pt-coated devices. Among the two functionalization layers, Pd-coated devices were found to respond only to H2 exposure and not to NH3, while Pt-coated devices exhibited repeatable response to both H2 and NH3 exposures, highlighting the potential of the former in performing selective detection between these reducing gases. Optimization of the device-biasing conditions were found to enhance the detection sensitivity of the sensors.

SUBMITTER: Khan D

PROVIDER: S-EPMC7407488 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Publications

Photoacoustic Detection of H2 and NH3 Using Plasmonic Signal Enhancement in GaN Microcantilevers.

Khan Digangana D Li Hongmei H Bayram Ferhat F Gajula Durga D Koley Goutam G

Micromachines 20200713 7

Photoacoustic (PA) detection of H2 and NH3 using plasmonic excitation in Pt- and Pd-decorated GaN piezotransistive microcantilevers were investigated using pulsed 520-nm laser illumination. The sensing performances of 1-nm Pt and Pd nanoparticle (NP) deposited cantilever devices were compared, of which the Pd-coated sensor devices exhibited consistently better sensing performance, with lower limit of detection and superior signal-to-noise ratio (SNR) values, compared to the ...[more]

PMID: 32668600

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Project description:Photoacoustic imaging (PAI) can be used to infer molecular information about myocardial health non-invasively in vivo using optical excitation at ultrasonic spatial resolution. For clinical and preclinical linear array imaging systems, conventional delay-and-sum (DAS) beamforming is typically used. However, DAS cardiac PA images are prone to artifacts such as diffuse quasi-static clutter with temporally varying noise-reducing myocardial signal specificity. Typically, multiple frame averaging schemes are utilized to improve the quality of cardiac PAI, which affects the spatial and temporal resolution and reduces sensitivity to subtle PA signal variation. Furthermore, frame averaging might corrupt myocardial oxygen saturation quantification due to the presence of natural cardiac wall motion. In this paper, a spatiotemporal singular value decomposition (SVD) processing algorithm is proposed to reduce DAS PAI artifacts and subsequent enhancement of myocardial signal specificity. Demonstrate enhancement of PA signals from myocardial tissue compared to surrounding tissues and blood inside the left-ventricular (LV) chamber using spatiotemporal SVD processing with electrocardiogram (ECG) and respiratory signal (ECG-R) gated in vivo murine cardiac PAI. In vivo murine cardiac PAI was performed by collecting single wavelength (850 nm) photoacoustic channel data on eight healthy mice. A three-dimensional (3D) volume of complex PAI data over a cardiac cycle was reconstructed using a custom ECG-R gating algorithm and DAS beamforming. Spatiotemporal SVD was applied on a two-dimensional Casorati matrix generated using the 3D volume of PAI data. The singular value spectrum (SVS) was then filtered to remove contributions from diffuse quasi-static clutter and random noise. Finally, SVD processed beamformed images were derived using filtered SVS and inverse SVD computations. Qualitative comparison with DAS and minimum variance (MV) beamforming shows that SVD processed images had better myocardial signal specificity, contrast, and target detectability. DAS, MV, and SVD images were quantitatively evaluated by calculating contrast ratio (CR), generalized contrast-to-noise ratio (gCNR), and signal-to-noise ratio (SNR). Quantitative evaluations were done at three cardiac time points (during systole, at end-systole (ES), and during diastole) identified from co-registered ultrasound M-Mode image. Mean CR, gCNR, and SNR values of SVD images at ES were 245, 115.15, and 258.17 times higher than DAS images with statistical significance evaluated with one-way analysis of variance. Our results suggest that significantly better-quality images can be realized using spatiotemporal SVD processing for in vivo murine cardiac PAI.

Dataset Information

Photoacoustic Detection of H2 and NH3 Using Plasmonic Signal Enhancement in GaN Microcantilevers.

Publications

Photoacoustic Detection of H<sub>2</sub> and NH<sub>3</sub> Using Plasmonic Signal Enhancement in GaN Microcantilevers.

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