Inkjet-Printed Wearable E-nose with Liquid-Phase Ligand-Exchanged Quantum Dots for Human-Centered Gas/Odor Monitoring.

Ultrafast intraband Auger process in self-doped colloidal quantum dots

In a new E-nose development, the sensor array needs to be optimized to have enough sensitivity and selectivity for gas/odor classification in the application. The development process includes the preparation of gas sensitive materials, gas sensor fabrication, array optimization, sensor array package and E-nose system integration, which would take a long time to complete. A set of platforms including a gas sensing film parallel synthesis platform, high-throughput gas sensing unmanned testing platform and a handheld wireless E-nose system were presented in this paper to improve the efficiency of a new E-nose development. Inkjet printing was used to parallel synthesize sensor libraries (400 sensors can be prepared each time). For gas sensor selection and array optimization, a high-throughput unmanned testing platform was designed and fabricated for gas sensing measurements of more than 1000 materials synchronously. The structures of a handheld wireless E-nose system with low power were presented in detail. Using the proposed hardware platforms, a new E-nose development might only take one week.

As interests in air quality monitoring related to environmental pollution and industrial safety increase, demands for gas sensors are rapidly increasing. Among various gas sensor types, the semiconductor metal oxide (SMO)-type sensor has advantages of high sensitivity, low cost, mass production, and small size but suffers from poor selectivity. To solve this problem, electronic nose (e-nose) systems using a gas sensor array and pattern recognition are widely used. However, as the number of sensors in the e-nose system increases, total power consumption also increases. In this study, an ultra-low-power e-nose system was developed using ultraviolet (UV) micro-LED (μLED) gas sensors and a convolutional neural network (CNN). A monolithic photoactivated gas sensor was developed by depositing a nanocolumnar In2O3 film coated with plasmonic metal nanoparticles (NPs) directly on the μLED. The e-nose system consists of two different μLED sensors with silver and gold NP coating, and the total power consumption was measured as 0.38 mW, which is one-hundredth of the conventional heater-based e-nose system. Responses to various target gases measured by multi-μLED gas sensors were analyzed by pattern recognition and used as the training data for the CNN algorithm. As a result, a real-time, highly selective e-nose system with a gas classification accuracy of 99.32% and a gas concentration regression error (mean absolute) of 13.82% for five different gases (air, ethanol, NO2, acetone, methanol) was developed. The μLED-based e-nose system can be stably battery-driven for a long period and is expected to be widely used in environmental internet of things (IoT) applications.

Introduction The electronic nose (E-nose) is a device, which mimics the mammal olfactory, that can be widely used in food quality control, environmental monitoring, human exhaled breath monitoring, and etc. It consists of gas sampling, sensor arrays, and pattern recognition[1-2].Quantum dots (QDs) are generally spherical or quasi-spherical with diameters ranging from 2 to 20 nm, with remarkable surface activity attribute to the quantum effects. Furthermore, the QDs can be processed in solution with excellent thin film properties at room temperature, compatible with various rigid/flexible substrates, which is conducive to large-scale production and low-cost manufacturing[3-4]. In general, metal oxide semiconductor quantum dots have a large potential in gas sensing, especially in E-nose.The most common pattern recognition process used in E-nose is feature extraction, dimensionality reduction, and classification. In feature extraction, some features such as the response, response/recovery time and etc. are extracted from the response curves based on the basic understanding of the gas sensing mechanism. In dimensionality reduction, the Principal Components Analysis (PCA) is often used. While in the classification, Linear Discriminant Analysis (LDA) is often used for final discrimination. In nowadays, deep learning architectures have been widely applied to fields including computer vision, speech recognition, natural language processing, and etc. However, there is little literature introduces deep learning into the E-nose area. Unlike traditional machine learning methods needing to design features manually, deep learning algorithms attempt to learn high-level hierarchical features from mass data, and jointly optimize feature extractors and classifiers that seriously decreases the burden on users[5-7]. Thus, It is believed that with the help of machine learning, the accuracy of E-nose can be highly enhanced.In this work, the E-nose consists of 6 different metal oxide semiconductors such as SnO2 quantum dots, WO3 quantum dots, In2O3 quantum dots, SnO2 hieratical structure by spray pyrolysis, NiO nanoflake, and commercial SnO2 was fabricated. While the machine learning algorithm based on an end-to-end trained combination of deep convolutional and recurrent neural networks was introduced. Five different kinds of Chinese liquors were chosen for the demonstration of the classification. The high accuracy (99.6%) was achieved by this system, which is much better than the traditional pattern recognition method in the same condition. It can also be concluded that the quantum dots sensors contributed more accuracy than others. Method The solvothermal method was employed for the synthesis of colloidal metal oxide semiconductor quantum dots. WCl6 (Aladdin,0.68g) / SnCl4·5H2O (Aladdin,0.6g) / indium acetate (Aladdin,0.292g) / NiCl2·6H2O (Aladdin,0.238g) was dissolved in oleic acid and oleylamine. Before the mixture was transferred into the Teflon-lined stainless steel autoclave, 10 mL of ethanol was added in and stirred. The reaction was kept at 180 oC for 3 h, then the WO3 nanocrystals were centrifugated and washed with toluene and ethanol(1/5, v/v). Finally, the product was dispersed in toluene and N, N-Dimethylformamide (DMF).Gas sensing materials are coated on ceramic substrates(1.0×1.5 mm) with heater by dripping. The four electrodes of the substrate were then welded to the ase to form a single gas sensor element. Annealing was used to enhance the stability of each sensor.The E-nose consisted of gas inlet, sensor array chamber, micro pump, and data acquisition card (Fig. 1). Results and Conclusions We propose a novel machine learning architecture, specifically designed for metal oxide array-based odor recognition. Our algorithm is based on an end-to-end trained combination of deep convolutional and recurrent neural networks, which leverages a 1D Resnet-like network to automatically extract multi-scale features from multi-channel time-series signals, simultaneously, a high-level semantic branch is connected to LSTM to decode the extremely complex and long-term temporal dynamics. The concatenation of local spatial features and global temporal information extremely enhances the performance of multichannel time series recognition. We also integrate the 1D Convolutional Block Attention Module (CBAM) into Resnet-like architecture to further improve network performance. In contrast, we also built a set of experimental frameworks for traditional methods. Ten typical hand-crafted features were fed to PCA for dimensionality reduction and an LDA or Support Vector Machine (SVM) was used for classification.Five different Chinese liquors: ChunGuJiu (CGJ, Class 1), BaiYunBianJianXiang (BYBJX, Class 2), BaiYunBianNongXiang (BYBNX, Class 3), SiTeJiu (STJ, Class 4) and MaoTai (MT, Class 5) have been chosen for the benchmark. In the beginning, the E-nose was stabilized for 10s, then the sample was put in the inlet of the E-nose. After sensing for the 20s, the sample was removed. Each sample has been tested for 50 times in one month. The typical response curves of the sensors array were shown in Fig. 2.The algorithm achieves high recognition rates (accuracy 99.6%) on a challenging set of 5 fine-grained Chinese liquors with severe noise and sensor drift, outperform traditional methods by a large margin (Table 1).

A Zero-Shot Learning Method Using Artificial Neural Network for Drift Calibration of Gas Sensor Array

Quantum dots (QDs) ink from Mn2+-doped ZnS (ZnS:Mn2+) quantum dots with poly(vinyl alcohol) (PVA) as stabilizer has been synthesized by two steps. First, ZnS:Mn2+ quantum dots were prepared by chemical co-precipitation method at room temperature and second, the powder of ZnS:Mn2+ quantum dots was dispersed in a solution of poly(vinyl alcohol) (PVA), de-ionized water, and alcohol to achieve a stable ink formulation. The ZnS:Mn2+ quantum dots exhibited both blue trap-state emission at around 430 nm and a strong orangered emission at about 600 nm with an excitation wavelength of 325 nm. The structural and optical properties of the ZnS:Mn2+ quantum dots were characterized by X-Ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-Visible absorption spectrum and photoluminescence (PL) spectroscopy. XRD analysis showed the formation of cubic ZnS:Mn2+ particles with average sizes from 2.0 to 2.53 nm while the particle size was estimated to be 10 nm from transmission electron microscopy (TEM). The ZnS:Mn2+ quantum dots ink was printed on photographic paper using screen technique. The studied result indicated that the ZnS:Mn2+ quantum dots can be used in the ink printing of security documents and labels, light – emitting diodes (LEDs), in novel photoluminescent display and advertising.

A novel periodic array CdSe nanowire is prepared on a substrate of the porous titanium dioxide by using a self-assembly method of the colloidal CdSe quantum dots (QDs). The experimental results show that the colloidal CdSe QDs have renewedly assembled on its space scale and direction in process of losing background solvent and form the periodic array nanowire. The main peak wavelength of Photoluminescence (PL) spectra, which is measured by using a 100-nm aperture laser beam spot on a scanning near-field optics microscopy, has shifted 60 nm with compared to the colloidal CdSe QDs. Furthermore, we have measured smaller ordered nanometer structure in thin QDs area as well, a 343-nm periodic nanowire in thick QDs area and the colloidal QDs in edge of well-ordered nanowire.

High performance pixelated quantum dots array on Micro-LED by inkjet printing

The inkjet printing method is a promising deposition method to fabricate multicolor quantum dot display, multicolor micro-LED display, and solar cells. This paper presents a method to inkjet print uniform quantum dots (QDs) polymer films for multicolor QLED display applications. The challenge is to obtain uniform polymer QDs dots from the dilute polymer solution without affecting the optical properties of QDs. Polydimethylsiloxane (PDMS) was used as the base polymer combining with phenyl group-based inks as the QDs polymer ink. PDMS is one of the most widely used polymers for microlectronics due to its optical properties of high transparency and high refractive index. Furthermore, PDMS is also biocompatible, inflammable and flexible. All of these properties make PDMS very popular in wearable and flexible electronic devices. The emission peak and full width half maximum (FWHM) of polymer QDs ink are the same as those of the pure QDs ink. This reveals that the optical properties of polymer QDs ink is the same as those of pure QDs ink. The size of the printed QDs was around 19 gm without the coffee ring effect that may be due to the establishment of a solvent composition gradient. By reducing the drop spacing of printed dots, a 5x5 mm uniform polymer QDs thin film could be achieved. The thickness of the polymer QDs film can be optimized by the layer-by-layer printing structure. The luminance intensity increased with the increase of printing layers. The color coordinate value could also be optimized with the layer-by-layer printing structure. The printed QDs film proved its potential use in the multicolor display applications.

Sensitive H2S gas sensors employing colloidal zinc oxide quantum dots

Tunable-band-gap colloidal QDs are a potential building block to harvest the wide-energy solar spectrum. The solution-phase surface passivation with lead halide-based halometallate ligands has remarkably simplified the processing of quantum dots (QDs) and enabled the proficient use of materials for the development of solar cells. It is, however, shown that the hallometalate ligand passivated QD ink allows the formation of thick crystalline shell layer, which limits the carrier transport of the QD solids. Organic thiols have long been used to develop QD solar cells using the solid-state ligand exchange approach. However, their use is limited in solution-phase passivation due to poor dispersity of thiol-treated QDs in common solvents. In this report, a joint passivation strategy using thiol and halometallate ligand is developed to prepare the QD ink. The mutually passivated QDs show a 50% reduction in shell thickness, reduced trap density, and improved monodispersity in their solid films. These improvements lead to a 4 times increase in carrier mobility and doubling of the diffusion length, which enable the carrier extraction from a much thicker absorbing layer. The photovoltaic devices show a high efficiency of 10.3% and reduced hysteresis effect. The improvement in surface passivation leads to reduced oxygen doping and improved ambient stability of the solar cells.

The direct‐synthesis of conductive PbS quantum dot (QD) ink is facile, scalable, and low‐cost, boosting the future commercialization of optoelectronics based on colloidal QDs. However, manipulating the QD matrix structures still is a challenge, which limits the corresponding QD solar cell performance. Here, for the first time a coordination‐engineering strategy to finely adjust the matrix thickness around the QDs is presented, in which halogen salts are introduced into the reaction to convert the excessive insulating lead iodide into soluble iodoplumbate species. As a result, the obtained QD film exhibits shrunk insulating shells, leading to higher charge carrier transport and superior surface passivation compared to the control devices. A significantly improved power‐conversion efficiency from 10.52% to 12.12% can be achieved after the matrix engineering. Therefore, the work shows high significance in promoting the practical application of directly synthesized PbS QD inks in large‐area low‐cost optoelectronic devices.

Novel optoelectronic systems based on ensembles of semiconductor nanocrystals are addressed in this paper. Colloidal semiconductor quantum dots and related quantum-wire structures have been characterized optically; these optical measurements include those made on self-assembled monolayers of DNA molecules terminated on one end with a common substrate and on the other end with TiO₂ quantum dots. The electronic properties of these structures are modeled and compared with experiment. The characterization and application of ensembles of colloidal quantum dots with molecular interconnects are considered. The chemically-directed assembly of ensembles of colloidal quantum dots with biomolecular interconnects is demonstrated with quantum dot densities in excess of 10⁺¹⁷ cm^-3. A number of novel photodetectors have been designed based on the combined use of double-barrier quantum-well injectors, colloidal quantum dots, and conductive polymers. Optoelectronic devices including photodetectors and solar cells based on threedimensional ensembles of quantum dots are considered along with underlying phenomena such as miniband formation and the robustness of minibands to displacements of quantum dots in the ensemble.

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 43883.39cdm-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.

Control of composition, stoichiometry, and defects in colloidal quantum dots (QDs) of III-V semiconductors has proven to be difficult due to their covalent character. Whereas the synthesis of colloidal indium pnictides such as InP, InAs, and InSb has made significant progress, gallium-containing colloidal III-V QDs still remain largely elusive. Gallium pnictides represent an important class of semiconductors due to their excellent optoelectronic properties in the bulk; however, the difficulty with the synthesis of gallium-containing colloidal III-V QDs has largely prohibited their exploration as solution-processed semiconductors. Here we introduce molten inorganic salts as high-temperature solvents for the synthesis and manipulation of III-V QDs. We demonstrate cation exchange reactions on presynthesized InP and InAs QDs to form In1- xGa xP and In1- xGa xAs QDs at temperatures above 380 °C. This approach produces novel ternary alloy QDs with controllable compositions that show size- and composition-dependent absorption and emission features. Emission quantum yields of up to ∼50% can be obtained for In1- xGa xP/ZnS core-shell QDs. A comparison of the optical properties of InP/ZnS core-shells with In1- xGa xP/ZnS core-shells reveals that Ga incorporation leads to significant improvement in the optical properties of III-V/II-VI core-shell emitters which is of great importance for quantum dot-based lighting and display applications. This work also demonstrates the potential of molten inorganic salts as versatile solvents for the synthesis and processing of colloidal nanomaterials at temperatures inaccessible for traditional solvents.