RESUMEN
Apples are one of the most widely planted fruits in the world, with an extremely high annual production. Several issues should be addressed to avoid the damaging of samples during the quality grading process of apples (e.g., the long detection period and the inability to detect the internal quality of apples). In this study, an electronic nose (e-nose) detection system for apple quality grading based on the K-nearest neighbor support vector machine (KNN-SVM) was designed, and the nasal cavity structure of the e-nose was optimized by computational fluid dynamics (CFD) simulation. A KNN-SVM classifier was also proposed to overcome the shortcomings of the traditional SVMs. The performance of the developed device was experimentally verified in the following steps. The apples were divided into three groups according to their external and internal quality. The e-nose data were pre-processed before features extraction, and then Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were used to reduce the dimension of the datasets. The recognition accuracy of the PCA-KNN-SVM classifier was 96.45%, and the LDA-KNN-SVM classifier achieved 97.78%. Compared with other commonly used classifiers, (traditional KNN, SVM, Decision Tree, and Random Forest), KNN-SVM is more efficient in terms of training time and accuracy of classification. Generally, the apple grading system can be used to evaluate the quality of apples during storage.
Asunto(s)
Malus , Máquina de Vectores de Soporte , Algoritmos , Análisis Discriminante , Nariz Electrónica , HidrodinámicaRESUMEN
Narrowband photodetectors have wide application potential in high-resolution imaging and encrypted communication, due to their high-precision spectral resolution capability. In this work, we report a fast response, high spectral rejection ratio, and self-filtered ultranarrowband photodetector with a new mechanism, which introduces bulk recombination by doping Bi3+ and cooperates with surface recombination for further quenching photogenerated charges generated by short-wavelength-light excitation in perovskite single-crystal. A perovskite film focused on collecting charges is fabricated on the single crystal by a lattice-matched solution-processed epitaxial growth method. Due to the formation of PN heterojunctions, a narrowband photodetector in this mechanism has remarkable spectral selectivity and detection performance with an ultranarrow full width at half-maximum (FWHM) of 7.7 nm and a high spectral rejection ratio of 790, as well as a high specific detectivity up to 1.5 × 1010 Jones, a fast response speed with a rise time and fall time of â¼8 and 137 µs. The ultrafast and ultranarrow spectra response of self-filtered narrowband photodetector provides a new strategy in high-precision and high-resolution photoelectric detection.
RESUMEN
Toward next-generation electroluminescent quantum dot (QD) displays, inkjet printing technique has been convinced as one of the most promising low-cost and large-scale manufacturing of patterned quantum dot light-emitting diodes (QLEDs). The development of high-quality and stable QD inks is a key step to push this technology toward practical applications. Herein, a universal ternary-solvent-ink strategy is proposed for the cesium lead halides (CsPbX3 ) perovskite QDs and their corresponding inkjet-printed QLEDs. With this tailor-made ternary halogen-free solvent (naphthene, n-tridecane, and n-nonane) recipe, a highly dispersive and stable CsPbX3 QD ink is obtained, which exhibits much better printability and film-forming ability than that of the binary solvent (naphthene and n-tridecane) system, leading to a much better qualitied perovskite QD thin film. Consequently, a record peak external quantum efficiency (EQE) of 8.54% and maximum luminance of 43 883.39 cd m-2 is achieved in inkjet-printed green perovskite QLEDs, which is much higher than that of the binary-solvent-system-based devices (EQE = 2.26%). Moreover, the ternary-solvent-system exhibits a universal applicability in the inkjet-printed red and blue perovskite QLEDs as well as cadmium (Cd)-based QLEDs. This work demonstrates a new strategy for tailor-making a general ternary-solvent-QD-ink system for efficient inkjet-printed QLEDs as well as the other solution-processed electronic devices in the future.
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Special radiation-hard and ultralow-power complementary metal-oxide-semiconductor (CMOS) integrated circuits (ICs) are used in the fields of deep space, nuclear energy, and medical X-ray imaging. In this work, we first constructed radiation-hard, repairable, and sub-1 V-driven printed hybrid CMOS field-effect transistors (FETs) and ICs, which integrate printed carbon nanotube (CNT) (band gap â¼ 0.65 eV) p-type FETs and indium oxide (In2O3) (band gap â¼3.64 eV) n-type FETs on glass substrates using a printed PS-PMMA/[EMIM][TFSI] mixture as the gate dielectric layer. The PS-PMMA/[EMIM][TFSI] mixture gate dielectric layer not only lowered the supply voltage (VDD) by providing ultrahigh gate efficiency but also improved the anti-irradiation ability of the hybrid CMOS FETs and ICs. Specifically, the hybrid CMOS inverters exhibited rail-to-rail output with a high voltage gain and high noise margins at a low VDD that could be scaled down to 0.4 V. Furthermore, the hybrid CMOS FETs and ICs showed excellent radiation hardness, that is, withstanding a 3 Mrad (Si) total irradiation dose (TID) at a dose rate of 560 rad s-1 (Si), which is an exceptional result for CMOS transistors and ICs. Furthermore, the radiation-damaged CMOS FETs could be fully recovered by removing and reprinting the PS-PMMA/[EMIM][TFSI] mixture gate dielectric layer, indicating the ability to repair irradiation damage. This work provides an in-space IC fabrication technology.
RESUMEN
Artificial synapses/neurons based on electronic/ionic hybrid devices have attracted wide attention for brain-inspired neuromorphic systems since it is possible to overcome the von Neumann bottleneck of the neuromorphic computing paradigm. Here, we report a novel photoneuromorphic device based on printed photogating single-walled carbon nanotube (SWCNT) thin film transistors (TFTs) using lightly n-doped Si as the gate electrode. The drain currents of the printed SWCNT TFTs can gradually increase to over 3000 times of their starting value after being pulsed with light stimulation, and the electrical signals can maintain for over 10 min. These characteristics are similar to the learning and memory functions of brain-inspired neuromorphic systems. The working mechanism of the light-stimulated neuromorphic devices is investigated and described here in detail. Important synaptic characteristics, such as low-pass filtering characteristics and nonvolatile memory ability, are successfully emulated in the printed light-stimulated artificial synapses. It demonstrates that the printed SWCNT TFT photoneuromorphic devices can act as the nonvolatile memory units and perform photoneuromorphic computing, which exhibits potential for future neuromorphic system applications.