A 1024$\,\times\,$8, 700-ps Time-Gated SPAD Line Sensor for Planetary Surface Exploration With Laser Raman Spectroscopy and LIBS

Maruyama, Yuki; Blacksberg, Jordana; Charbon, Edoardo

doi:10.1109/jssc.2013.2282091

Cited by 87 publications

(75 citation statements)

References 15 publications

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“…Line sensors allow high fill-factor by allowing pulse processing electronics to be placed below the detectors. Advanced realizations of these line sensors are beginning to emerge for time-resolved Raman spectroscopy (Blacksberg et al, 2011;Kostamovaara et al, 2013;Maruyama et al, 2014;Nissinen et al, 2011).…”

Section: Spad Arraysmentioning

confidence: 99%

Fluorescence lifetime imaging (FLIM): Basic concepts and some recent developments

et al. 2015

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Section: Spad Arraysmentioning

confidence: 99%

Fluorescence lifetime imaging (FLIM): Basic concepts and some recent developments

et al. 2015

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“…In this paper, we mitigate much of the fluorescence by using time gating. Because fluorescence is not an instantaneous process, we minimize its' collection by using a nanosecond time-resolved Raman spectrometer with a single photon avalanche detector (SPAD) array, which acts as a photon counting detector [28]. This technique collects the Raman return synchronous with the subnanosecond laser pulse and rejects any fluorescence return with longer lifetime.…”

Section: A Raman Spectroscopymentioning

confidence: 99%

A Fast Classification Scheme in Raman Spectroscopy for the Identification of Mineral Mixtures Using a Large Database With Correlated Predictors

Cochrane

Blacksberg

2015

IEEE Trans. Geosci. Remote Sensing

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Robust classification methods are vital to the successful implementation of many material characterization techniques, particularly where large databases exist. In this paper, we demonstrate an extremely fast classification method for the identification of mineral mixtures in Raman spectroscopy using the large RRUFF database. However, this method is equally applicable to other techniques meeting the large database criteria, these including laser-induced breakdown, X-ray diffraction, and mass spectroscopy methods. Classification of these multivariate datasets can be challenging due in part to the various obscuring features inherently present within the underlying dataset and in part to the volume and variety of information known a priori. Some of the more specific challenges include the observation of mixtures with overlapping spectral features, the use of large databases (i.e., the number of predictors far outweighs the number of observations), the use of databases that contain groups of correlated spectra, and the ever present, clouding contaminants of noise, undesired background, and spectrometer artifacts. Although many existing classification algorithms attempt to address these problems individually, not many address them as a whole. Here, we apply a multistage approach, which leverages well-established constrained regression techniques, to overcome these challenges. Our modifications to conventional algorithm implementations are shown to increase speed and performance of the classification process. Unlike many other techniques, our method is able to rapidly classify mixtures while simultaneously preserving sparsity. It is easily implemented, has very few tuning parameters, does not require extensive parameter training, and does not require data dimensionality reduction prior to classification.Index Terms-Classification, elastic net (EN), planetary mineralogy, Raman spectroscopy, regression.

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“…Large single-photon avalanche diode arrays (more than hundreds of SPADs) have been developed for various applications, for example for fluorescence life time imaging, time-of-flight laser rangefinding, laser induced breakdown spectroscopy and for Raman spectroscopy [1,2,3,4]. Raman spectroscopy is one of the most recent applications where CMOS technology has been utilized to integrate the SPAD array with the time gating and the time interval measurement electronics on a single chip.…”

Section: Introductionmentioning

confidence: 99%

“…As mentioned above, CMOS technologies can be used to fabricate SPAD arrays and additionally, all the electronics can be integrated in the same die which makes it possible to design quite large arrays with time gating electronics for Raman spectroscopy [7,4].…”

Section: Introductionmentioning

confidence: 99%

On the time gating of SPADs in a synchronized time-gated SPAD array in Raman spectroscopy

Nissinen

Kostamovaara

2017

2017 Ieee Sensors

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Abstract-The effect of the timing of the biasing of a single photon avalanche diode (SPAD) on the accuracy of a time-gated SPAD array has been studied in this work. The measurement was realized in a time-gated Raman spectrometer utilizing a 16x256 CMOS SPAD array with on-chip time gating electronics. SPADs have to be biased into the Geiger-mode just before arriving Raman scattered photons from the sample to achieve synchronous measurements with a pulsed laser, and to minimize the dark count noise. The practical realization is, however, not straight-forward due to the strict timing requirements (~50ps). With the shown biasing arrangement high timing accuracy and low noise can be achieved without sacrificing the fill factor of the detector array.

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A 1024$\,\times\,$8, 700-ps Time-Gated SPAD Line Sensor for Planetary Surface Exploration With Laser Raman Spectroscopy and LIBS

Cited by 87 publications

References 15 publications

Fluorescence lifetime imaging (FLIM): Basic concepts and some recent developments

Fluorescence lifetime imaging (FLIM): Basic concepts and some recent developments

A Fast Classification Scheme in Raman Spectroscopy for the Identification of Mineral Mixtures Using a Large Database With Correlated Predictors

On the time gating of SPADs in a synchronized time-gated SPAD array in Raman spectroscopy

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