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Waste material classification is critical for efficient recycling and waste management. This study proposes a novel, low-cost material classification system based on a single, voltage-tunable Ge-on-Si photodetector operating across the visible and short-wave infrared (SWIR) spectral regions. Thanks to its tunability, the sensor is able to extract spectral information, and the system effectively distinguishes between seven different materials, including plastics, aluminum, glass, and paper. The system operates with a broadband illuminator, and material identification is obtained through the processing of the photocurrent signal at different bias voltages with classification algorithms. Here, we demonstrate the basic system functionality and near real-time classification of different waste materials.

Sensitive, accurate, and reliable detection of explosives has become one of the major needs for international security and environmental protection. Colloidal quantum dots, because of their unique chemical, optical, and electrical properties, as well as easy synthesis route and functionalization, have demonstrated high potential to meet the requirements for the development of suitable sensors, boosting the research in the field of explosive detection. Here, we critically review the most relevant research works, highlighting three different mechanisms for explosive detection based on colloidal quantum dots, namely photoluminescence, electrochemical, and chemoresistive sensing. We provide a comprehensive overview and an extensive discussion and comparison in terms of the most relevant sensor parameters. We highlight advantages, limitations, and challenges of quantum dot-based explosive sensors and outline future research directions for the advancement of knowledge in this surging research field.

Waste material classification is a challenging yet important task in waste management. The realization of low-cost waste classification systems and methods is critical to meet the ever-increasing demand for efficient waste management and recycling. In this paper, we demonstrate a simple, compact and low-cost classification system based on optical reflectance measurements in the short-wave infrared for the segregation of waste materials such as plastics, paper, glass, and aluminium. The system comprises a small set of LEDs and one single broadband photodetector. All devices are controlled through low-cost and low-power electronics, and data are gathered and managed via a computer interface. The proposed system reaches accuracy levels as high as 94.3% when considering seven distinct materials and 97.0% when excluding the most difficult to classify, thus representing a valuable proof-of-concept for future system developments.

A crucial yet difficult task for waste management is the identification of raw materials like plastic, glass, aluminum, and paper. Most previous studies use the diffused reflection spectroscopy for classification purposes. Despite the benefits in terms of speed and simplicity offered by modern compact spectrometers, their cost and the need for an external, wide-spectrum source of illumination create complications. To address this issue, the present paper proposes a discrete spectroscopy method that utilizes short-wave infrared (SWIR) reflectance to identify waste materials, exploiting a small set of selected wavelengths. This approach reduces the complexity of the classification data analysis and offers a more practical alternative to the conventional method. The proposed system comprises a single germanium photodetector and 10 different light emitting diodes (LEDs). The LED wavelengths are selected to maximize the system sensitivity towards a set of seven different waste materials. Using a classification strategy relying on support vector machines, the proposed methodology reaches a classification accuracy up to 98%.

We report on a sensor architecture for detection of hazardous gases. The proposed device is based on the integration of a solid-state quantum dot (QD) photoluminescent probe with a QD photodetector on the same substrate. The effectiveness of the approach is demonstrated by developing a compact optical sensor for trace detection of explosives in air. The proposed architecture is very simple and consists of a silicon substrate with both surfaces coated with QD films. The upper layer acts as photoluminescent probe, pumped by a blue LED. The change of photoluminescence intensity associated to the interaction between the QDs and the target analyte is measured by the QD photodetector fabricated on the opposite side of the substrate. The sensor is mounted into a small chamber provided with the LED and the front-end electronics. The device is characterized by using nitrobenzene as representative nitroaromatic compound. Extremely low concentrations (down to 0.1 ppm) can be detected by the proposed device, with a theoretical detection limit estimated to be as low as 2 ppb. Results are repeatable and no ageing effect is observed over a 70 d period. The proposed architecture may provide a promising solution for explosive detection in air as well as other sensing applications, thanks to its sensitivity, simple fabrication process, practical usability and cost effectiveness., (© 2022 IOP Publishing Ltd.)

Colloidal quantum dots (CQDs) have been recently investigated as promising building blocks for low-cost and high-performance gas sensors due to their large effective surface-to-volume ratio and their suitability for versatile functionalization through surface chemistry. In this work we report on lead sulphide CQDs based sensors for room temperature NO 2 detection. The sensor response has been measured for different pollutant gases including NO 2 , CH 4 , CO and CO 2 and for different concentrations in the 2.8-100 ppm range. For the first time, the influence of the QDs film thickness on the sensor response has been investigated and optimized. Upon 30 ppm NO 2 release, the best room temperature gas response is about 14 Ω/Ω, with response and recovery time of 12 s and 26 min, respectively. A detection limit of about 0.15 ppb was estimated from the slope of the sensor response and its electric noise. The gas sensors exhibit high sensitivity to NO 2 , remarkable selectivity, repeatability and full recovery after exposure.

High performance photodetectors based on colloidal quantum dots have been demonstrated in a wide spectral range spanning from the visible to the mid infrared. Quantum dot photodetectors typically show a low-pass type spectral response with a tunable cutoff wavelength. In this paper, we propose a method for the realization of narrowband photodetectors based on the combination of photoconductors and optical filters, both realized with colloidal PbS quantum dots. We demonstrate that an array of such narrowband photodetectors can be effectively employed for the realization of a compact wavemeter operating in the visible and near-infrared spectral range.

Designs and results for a low-power and economical fingerprint visible light positioning (VLP) system are discussed in this paper. A system using four white LEDs and one photodiode was deployed. The LEDs are independently controlled and modulated by individual transmitter circuits, removing the requirement for a large, expensive signal generator. The receiver circuit filters and converts the received signal to DC, allowing a simple microcontroller to save the received signal. We propose the creation of a fingerprint database by recording signal data, fitting a two-dimensional Gaussian distribution to the data, and then generating the fingerprint database for all positions in the evaluation system. System positioning accuracy of 13.44+/-0.36  mm was observed, corresponding to a relative error of 2.8% with respect to the system dimensions. This result presents an improvement on positioning accuracy for fingerprint positioning VLP systems, which build their own transmitters.

We demonstrated an optical method to evaluate the state of asphalt due to the presence of atmospheric agents using the measurement of the polarization/depolarization state of near infrared radiation. Different sensing geometries were studied to determine the most efficient ones in terms of performance, reliability and compactness. Our results showed that we could distinguish between a safe surface and three different dangerous surfaces, demonstrating the reliability and selectivity of the proposed approach and its suitability for implementing a sensor.

Colloidal quantum dots have recently attracted lot of interest in the fabrication of optoelectronic devices due to their unique optical properties and their simple and low cost fabrication. PbS nanocrystals emerged as the most advanced colloidal material for near infrared photodetectors. In this work we report on the fabrication and characterization of PbS colloidal quantum dot photoconductors. In order to make devices suitable for the monolithic integration with silicon electronics, we propose a simple and low cost process for the fabrication of photodetectors and investigate their operation at very low voltage bias. Our photoconductors feature high responsivity and detectivity at 1.3 μm and 1 V bias with maximum values of 30 A/W and 2·10 10 cmHz 1/2 W -1 , respectively. Detectivity close to 10 11  cmHz 1/2 W -1 has been obtained resorting to bridge sensor readout.

Combining reverse proton exchange and uniform periodic poling in LiNbO3 planar waveguides, we demonstrate low-energy spatial optical solitons by second-harmonic generation at room temperature, with a threshold as low as 23 pJ/microm at 1.5 microm.

With second-harmonic generation in surface and buried planar waveguides achieved by direct and reverse proton exchange in lithium niobate, we demonstrate a novel kind of quadratic spatial simulton: The transverse-electric fundamental input and the transverse-magnetic second-harmonic waves nonlinearly couple two superimposed planar waveguides, permitting transverse localization of light at room temperature and at excitations as low as 340 nJ in 20-ps pulses.