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For decades, near-infrared (NIR) spectroscopy has been a valuable tool for material analysis in a variety of applications, ranging from industrial process monitoring to quality assessment. Traditional spectrometers are typically bulky, fragile and expensive, which makes them unsuitable for portable and in-field use. Thus, there is a growing interest for miniaturized, robust and low-cost NIR sensors. In this study, we demonstrate a handheld NIR spectral sensor module, based on a fully-integrated multipixel detector array, sensitive in the 850-1700 nm wavelength range. Differently from a spectrometer, the spectral sensor measures a limited number of NIR spectral bands. The capabilities of the spectral sensor module were evaluated alongside a commercially available portable spectrometer for two application cases: to quantify the moisture content in rice grains and to classify plastic types. Both devices achieved the two sensing tasks with comparable performance. Moisture quantification was achieved with a root mean square error (RMSE) prediction of 1.4% and 1.1% by the spectral sensor and spectrometer, respectively. Classification of the plastic type was achieved with a prediction accuracy on unknown samples of 100% and 96.4% by the spectral sensor and spectrometer, respectively. The results from this study are promising and demonstrate the potential for the compact NIR modules to be used in a variety of NIR sensing applications.

Illicit-drug production, trafficking and seizures are on an all-time high. This consequently raises pressure on investigative authorities to provide rapid forensic results to assist law enforcement and legal processes in drug-related cases. Ideally, every police officer is equipped with a detector to reliably perform drug testing directly at the incident scene. Such a detector should preferably be small, portable, inexpensive and shock-resistant but should also provide sufficient selectivity to prevent erroneous identifications. This study explores the concept of on-site drugs-of-abuse detection using a 1.8 × 2.2 mm 2 multipixel near-infrared (NIR) spectral sensor that potentially can be integrated into a smartphone. This integrated sensor, based on an InGaAs-on-silicon technology, exploits an array of resonant-cavity enhanced photodetectors without any moving parts. A 100% correct classification of 11 common illicit drugs, pharmaceuticals and adulterants was achieved by chemometric modelling of the response of 15 wavelength-specific pixels. The performance on actual forensic casework was investigated on 246 cocaine-suspected powders and 39 MDMA-suspected ecstasy tablets yielding an over 90% correct classification in both cases. These findings show that presumptive drug testing by miniaturized spectral sensors is a promising development ultimately paving the way for a fully integrated drug-sensor in mobile communication devices used by law enforcement., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Spectral sensing is increasingly used in applications ranging from industrial process monitoring to agriculture. Sensing is usually performed by measuring reflected or transmitted light with a spectrometer and processing the resulting spectra. However, realizing compact and mass-manufacturable spectrometers is a major challenge, particularly in the infrared spectral region where chemical information is most prominent. Here we propose a different approach to spectral sensing which dramatically simplifies the requirements on the hardware and allows the monolithic integration of the sensors. We use an array of resonant-cavity-enhanced photodetectors, each featuring a distinct spectral response in the 850-1700 nm wavelength range. We show that prediction models can be built directly using the responses of the photodetectors, despite the presence of multiple broad peaks, releasing the need for spectral reconstruction. The large etendue and responsivity allow us to demonstrate the application of an integrated near-infrared spectral sensor in relevant problems, namely milk and plastic sensing. Our results open the way to spectral sensors with minimal size, cost and complexity for industrial and consumer applications., (© 2022. The Author(s).)

The low throughput of atomic force microscopy (AFM) is the main drawback in its large-scale deployment in industrial metrology. A promising solution would be based on the parallelization of the scanning probe system, allowing acquisition of the image by an array of probes operating simultaneously. A key step for reaching this goal relies on the miniaturization and integration of the sensing mechanism. Here, we demonstrate AFM imaging employing an on-chip displacement sensor, based on a photonic crystal cavity, combined with an integrated photodetector and coupled to an on-chip waveguide. This fully-integrated sensor allows high-sensitivity and high-resolution in a very small footprint and its readout is compatible with current commercial AFM systems., (Copyright © 2021. Published by Elsevier B.V.)

We propose a force sensor, with optical detection, based on a reconfigurable multi-cavity photonic molecule distributed over two parallel photonic crystal membranes. The system spectral behaviour is described with an analytical model based on coupled mode theory and validated by finite difference time domain simulations. The deformation of the upper photonic crystal membrane, due to a localized vertical force, is monitored by the relative spectral positions of the photonic molecule resonances. The proposed system can act both as force sensor, with pico-newton sensitivity, able to identify the position where the force is applied, and as torque sensor able to measure the torsion of the membrane along two perpendicular directions.

Random dielectrics defines a class of non-absorbing materials where the index of refraction is randomly arranged in space. Whenever the transport mean free path is sufficiently small, light can be confined in modes with very small volume. Random photonic modes have been investigated for their basic physical insights, such as Anderson localization, and recently several applications have been envisioned in the field of renewable energies, telecommunications, and quantum electrodynamics. An advantage for optoelectronics and quantum source integration offered by random systems is their high density of photonic modes, which span a large range of spectral resonances and spatial distributions, thus increasing the probability to match randomly distributed emitters. Conversely, the main disadvantage is the lack of deterministic engineering of one or more of the many random photonic modes achieved. This issue is solved by demonstrating the capability to electrically and mechanically control the random modes at telecom wavelengths in a 2D double membrane system. Very large and reversible mode tuning (up to 50 nm), both toward shorter or longer wavelength, is obtained for random modes with modal volumes of the order of few tens of (λ/n) 3 ., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Spectrometry is widely used for the characterization of materials, tissues, and gases, and the need for size and cost scaling is driving the development of mini and microspectrometers. While nanophotonic devices provide narrowband filtering that can be used for spectrometry, their practical application has been hampered by the difficulty of integrating tuning and read-out structures. Here, a nano-opto-electro-mechanical system is presented where the three functionalities of transduction, actuation, and detection are integrated, resulting in a high-resolution spectrometer with a micrometer-scale footprint. The system consists of an electromechanically tunable double-membrane photonic crystal cavity with an integrated quantum dot photodiode. Using this structure, we demonstrate a resonance modulation spectroscopy technique that provides subpicometer wavelength resolution. We show its application in the measurement of narrow gas absorption lines and in the interrogation of fiber Bragg gratings. We also explore its operation as displacement-to-photocurrent transducer, demonstrating optomechanical displacement sensing with integrated photocurrent read-out.