A gradient aligned domain adversarial network for unsupervised intelligent fault diagnosis of gearboxes.

Unsupervised domain adaptation alleviates the dependencies of conventional fault diagnosis methods on sufficient labeled data and strict data distributions. Nonetheless, the current domain adaptation methods only concentrate on the data distributions and ignore the feature gradient distributions, leading to some samples being misclassified due to large gradient discrepancies, thus affecting diagnosis performance. In this paper, a gradient aligned domain adversarial network (GADAN) is proposed. First, the discrepancies of the marginal and conditional distribution between the source and target domain are reduced by minimizing the joint maximum mean discrepancy. Then, a pseudo-labeling approach based on a clustering self-supervised strategy is utilized to attain high-quality pseudo-labels of target domains, and most importantly in the dimension of the data gradient, the feature gradient distributions are aligned by adversarial learning to further reduce the domain shift, even if the distributions of the two domains are close enough. Finally, experiments and engineering applications demonstrate the effectiveness and superiority of GADAN for transfer diagnosis between various working conditions or different machines.

Irreversible Bonding of Polydimethylsiloxane-Lithium Niobate using Oxygen Plasma Modification for Surface Acoustic Wave based Microfluidic Application: Theory and Experiment.

Acoustic microfluidic chips, fabricated by combining lithium niobate (LiNbO3 ) with polydimethylsiloxane (PDMS), practically find applications in biomedicine. However, high-strength direct bonding of LiNbO3 substrate with PDMS microchannel remains a challenge due to the large mismatching of thermal expansion coefficient at the interface and the lack of bonding theory. This paper elaborately reveals the bonding mechanisms of PDMS and LiNbO3 , demonstrating an irreversible bonding method for PDMS-LiNbO3 heterostructures using oxygen plasma modification. An in-situ monitoring strategy by using resonant devices is proposed for oxygen plasma, including quartz crystal microbalance (QCM) covered with PDMS and surface acoustic wave (SAW) fabricated by LiNbO3 . When oxygen plasma exposure occurs, surfaces are cleaned, oxygen ions are implanted, and hydroxyl groups (-OH) are formed. Upon interfaces bonding, the interface will form niobium-oxygen-silicon covalent bonds to realize an irreversible connection. A champion bonding strength is obtained of 1.1 MPa, and the PDMS-LiNbO3 acoustic microfluidic chip excels in leakage tests, withstanding pressures exceeding 60 psi, outperforming many previously reported devices. This work addresses the gap in PDMS-LiNbO3 bonding theory and advances its practical application in the acoustic microfluidic field.

Polarization-Sensitive, Self-Powered, and Broadband Semimetal MoTe2/MoS2 van der Waals Heterojunction for Photodetection and Imaging.

The emerging type II Weyl semimetal 1T' MoTe2 as a promising material in polarization-sensitive photodetectors has aroused much attention due to its narrow bandgap and intrinsic in-plane anisotropic crystal structure. However, the semimetal properties lead to a large dark current and a low response. Herein, we demonstrate for the first time an all-2D semimetal MoTe2/MoS2 van der Waals (vdWs) heterojunction to improve the performance of the photodetectors and realize polarization-sensitive, self-powered, and broadband photodetection and imaging. Owing to the built-in electric field of the heterojunction, the device achieves a self-powered photoresponse ranging from 520 to 1550 nm. Under 915 nm light illumination, the device demonstrates outstanding performance, including a high responsivity of 79 mA/W, a specific detectivity of 1.2 × 1010 Jones, a fast rise/decay time of 180/202 µs, and a high on/off ratio of 1.3 × 10.3 Wavelength-dependent photocurrent anisotropic ratio is revealed to vary from 1.10 at 638 nm to 2.24 at 1550 nm. Furthermore, we demonstrate the polarization imaging capabilities of the device in scattering surroundings, and the DoLP and AoLP images achieve 78% and 112% contrast enhancement, respectively, compared to the S0. This work opens up new avenues to develop anisotropic semimetals heterojunction photodetectors for high-performance polarization-sensitive photodetection and next-generation polarized imaging.

Intelligent diagnosis of flip chip solder joints with resolution enhanced SAM image.

Scanning acoustic microscopy (SAM) technique has been applied to defect inspection in electronic devices. With the increase of packaging density, detection of the micro-defects in high density devices becomes more and more challenging. The SAM test is suffering from sacrificing the spatial resolution to reach a certain penetration depth of the ultrasonic waves. So it is necessary to enhance the resolution level of the SAM image. In this paper, a wavelet based resolution enhancement technique was investigated to reconstruct a high quality image for SAM test of the flip chip packages. The stationary wavelet transform was adopted to decompose the captured SAM image into four frequency subbands, and the high frequency subbands were enhanced by adding the difference matrix in the intermediate stage, and a super resolution SAM image was derived from combining all the subbands by using the Inverse Discrete Wavelet Transform. Then the solder joints segmented from the SR-SAM image were classified by using the SVM algorithm. The results validated that the proposed technique is effective to improve the detection accuracy of SAM test.

Tool Wear Monitoring in Milling Based on Fine-Grained Image Classification of Machined Surface Images.

Cutting tool wear state assessment during the manufacturing process is extremely significant. The primary purpose of this study is to monitor tool wear to ensure timely tool change and avoid excessive tool wear or sudden tool breakage, which causes workpiece waste and could even damage the machine. Therefore, an intelligent system, that is efficient and precise, needs to be designed for addressing these problems. In our study, an end-to-end improved fine-grained image classification method is employed for workpiece surface-based tool wear monitoring, which is named efficient channel attention destruction and construction learning (ECADCL). The proposed method uses a feature extraction module to extract features from the input image and its corrupted images, and adversarial learning is used to avoid learning noise from corrupted images while extracting semantic features by reconstructing the corrupted images. Finally, a decision module predicts the label based on the learned features. Moreover, the feature extraction module combines a local cross-channel interaction attention mechanism without dimensionality reduction to characterize representative information. A milling dataset is conducted based on the machined surface images for monitoring tool wear conditions. The experimental results indicated that the proposed system can effectively assess the wear state of the tool.

Embedded growth of colorful CsPbX3(X = Cl, Br, I) nanocrystals in metal-organic frameworks at Room Temperature.

Herein, we develop a novel strategy for preparing all-inorganic cesium lead halide (CsPbX3, X = Cl, Br, I) perovskite nanocrystals (NCs)@Zn-based metal-organic framework (MOF) composites through interfacial synthesis. The successful embedding of fluorescent perovskite NCs in Zn-MOFs is due to thein situconfined growth, which is attributed to the re-nucleation of water-triggered phase transformation from Cs4PbBr6to CsPbBr3. The controllable synthesis of mixed-halide based composites with various emission wavelength can be achieved by adding the desired amount of halide (Cl or I) salts in the re-nucleation process. More importantly, the anion exchange reaction is inhibited among various composites with different halogen atoms by being trapped in MOFs. Besides, a white light-emitting diode (WLED) is produced using a blue LED chip with the green-emitting and red-emitting composites, which has a color coordinate of (0.3291, 0.3272) and a wide color gamut. This work provides a novel route to achieving perovskite NCs growth in MOFs, which also can be extended to the other NCs embedded in frames as well.

Broadening the Spectral Response of Perovskite Photodetector to the Solar-Blind Ultraviolet Region through Phosphor Encapsulation.

Hybrid perovskite photodetectors generally exhibit brilliant performance for photodetecting in the visible spectrum but poor detectability in the solar-blind ultraviolet (UV) region. To break through the bottleneck, we demonstrate a novel strategy to broaden the spectral response of perovskite photodetectors to the solar-blind UV region through phosphor encapsulation. The high photoluminescence quantum yield trichromatic phosphor capping layer achieves an extended spectral response to the solar-blind UV region through effectively down-converting the incident UV light into visible light. In addition, an external quantum efficiency of up to 12.13%@265 nm is achieved without bias voltage, while the initial value is near zero. The corresponding spectral responsivity and detectivity are 0.0269 A/W and 7.52 × 1011 Jones, respectively. Thus, the photodetectors show a high photocurrent and on/off ratio, increasing by roughly 2 orders of magnitude. Moreover, the photodetectors exhibit a large linear dynamic range of 105 dB, fast response times of 50.16/51.99 µs, and excellent stability. The practical applications for flame detection and UV-based communication are further explored. This work provides a new way to achieve UV light detection based on perovskite photodetectors. Perhaps, it may also be a promising alternative for wide-band gap semiconductors to realize the urgent pursuit of UV detection.

Molecular Understanding of Electrochemical-Mechanical Responses in Carbon-Coated Silicon Nanotubes during Lithiation.

Carbon-coated silicon nanotube (SiNT@CNT) anodes show tremendous potential in high-performance lithium ion batteries (LIBs). Unfortunately, to realize the commercial application, it is still required to further optimize the structural design for better durability and safety. Here, the electrochemical and mechanical evolution in lithiated SiNT@CNT nanohybrids are investigated using large-scale atomistic simulations. More importantly, the lithiation responses of SiNW@CNT nanohybrids are also investigated in the same simulation conditions as references. The simulations quantitatively reveal that the inner hole of the SiNT alleviates the compressive stress concentration between a-LixSi and C phases, resulting in the SiNT@CNT having a higher Li capacity and faster lithiation rate than SiNW@CNT. The contact mode significantly regulates the stress distribution at the inner hole surface, further affecting the morphological evolution and structural stability. The inner hole of bare SiNT shows good structural stability due to no stress concentration, while that of concentric SiNT@CNT undergoes dramatic shrinkage due to compressive stress concentration, and that of eccentric SiNT@CNT is deformed due to the mismatch of stress distribution. These findings not only enrich the atomic understanding of the electrochemical-mechanical coupled mechanism in lithiated SiNT@CNT nanohybrids but also provide feasible solutions to optimize the charging strategy and tune the nanostructure of SiNT-based electrode materials.

A Novel End-To-End Fault Diagnosis Approach for Rolling Bearings by Integrating Wavelet Packet Transform into Convolutional Neural Network Structures.

Accidental failures of rotating machinery components such as rolling bearings may trigger the sudden breakdown of the whole manufacturing system, thus, fault diagnosis is vital in industry to avoid these massive economical costs and casualties. Since convolutional neural networks (CNN) are poor in extracting reliable features from original signal data, the time-frequency analysis method is usually called for to transform 1D signal into a 2D time-frequency coefficient matrix in which richer information could be exposed more easily. However, realistic fault diagnosis applications face a dilemma in that signal time-frequency analysis and fault classification cannot be implemented together, which means manual signal conversion work is also needed, which reduces the integrity and robustness of the fault diagnosis method. In this paper, a novel network named WPT-CNN is proposed for end-to-end intelligent fault diagnosis of rolling bearings. WPT-CNN creatively uses the standard deep neural network structure to realize the wavelet packet transform (WPT) time-frequency analysis function, which seamlessly integrates fault diagnosis domain knowledge into deep learning algorithms. The overall network architecture can be trained with gradient descent backpropagation algorithms, indicating that the time-frequency analysis module of WPT-CNN is also able to learn the dataset characteristics, adaptively representing signal information in the most suitable way. Two experimental rolling bearing fault datasets were used to validate the proposed method. Testing results showed that WPT-CNN obtained the testing accuracies of 99.73% and 99.89%, respectively, in two datasets, which exhibited a better and more reliable diagnosis performance than any other existing deep learning and machine learning methods.

Patterning Ag nanoparticles by selective wetting for fine size Cu-Ag-Cu bonding.

Metal nanoparticles (NPs) are promising bonding materials to replace Sn alloys in fine size Cu-Cu bonding. However, the method of rapidly patterning NPs on solder joints with sizes less than 30 µm is one of the main barriers that impede the practical applications of NPs in Cu-Cu bonding, especially in mass production. In this paper, a novel method of patterning Ag NPs on Cu pads by selective wetting was introduced. Cu pads with diameters down to 5 µm were coated with Ag NPs successfully. When sizes of Cu pads were larger than 10 µm, high density could be achieved and the ratio of diameters to pitches of Cu pads could reach 2/3. Furthermore, the thickness and the coverage of the Ag NPs layer could be raised by repeating coating. In the bonding test, the shear strength increased significantly with the increase of the bonding temperature and the bonding time. It could reach 22.92 MPa after sintering for 5 min at 250 °C under a bonding pressure of 20 MPa in N2. With the aforementioned advantages, patterning NPs by selective wetting will be one of the potential methods for applying NPs to Cu pads in Cu-NPs-Cu bonding.

Controllable Synthesis of All Inorganic Lead Halide Perovskite Nanocrystals with Various Appearances in Multiligand Reaction System.

All inorganic cesium lead halide (CsPbX3, X = Cl, Br, I) perovskite nanocrystals (PNCs) exhibit promising applications in light-emitting devices due to their excellent photophysical properties. Herein, we developed a low-cost and convenient method for the preparation of CsPbX3 PNCs in a multiligand-assisted reaction system where peanut oil is applied as a ligand source. The mixed-halide PNCs with tunable optical-band gap were prepared by mixing the single-halide perovskite solutions at room temperature. The resulting PNCs had good monodispersity, with dimensions of 8-10 nm, high photoluminescence quantum yield (96.9%), narrow emission widths (15-34 nm), and tunable emission wavelength (408-694 nm), covering the entire visible spectrum. Additionally, various morphologies of PNCs, such as nanospheres, nanocubes, and nanowires, were obtained by controlling reaction temperature and time, and the amount of oleamine with multiple ligands in peanut oil potentially playing a dominant role in the nucleation/growth processes of our PNCs. Finally, the resulting CsPbBr3 PNCs were employed to develop a white light-emitting diode (WLED), demonstrating the potential lighting applications for our method.

Ultrafast Self-Assembly MoS2/Cu(OH)2 Nanowires for Highly Sensitive Gamut Humidity Detection with an Enhanced Self-Recovery Ability.

Humidity sensors have attracted intense interest in various fields because of the importance of humidity detection. Different methods have been adopted to enhance sensing performances of humidity sensors, while it is challenging for researchers to avoid the invalidation of the sensors after being wet. Here, we, for the first time, introduce self-assembly MoS2/Cu(OH)2 nanowires fabricated by liquid self-spreading-coating-evaporating as sensing materials and present MoS2/Cu(OH)2 nanowire-based quartz crystal microbalance gamut humidity sensors with superior sensitivity and self-recovery ability. The sensors deliver a remarkable sensitivity (60.8 Hz/% RH) under a wide range (0-97% RH) with fast response (1.9 s)/recovery time (3.8 s) and upgrade self-recovery ability that can maintain their original performances even after being wet, frozen, and heated or immersed in water. The sensors are also employed to monitor water counting, dew alarming, and human breathing (within 4 s), further showing their ultrahigh sensitivity for water molecules. The underlying humidity-sensing mechanism is interpreted by density functional theory calculations and in-situ Fourier transform infrared spectra experiments adequately, revealing that the high sensing performances are attributed to abundant adsorption sites and physisorption of water molecules. Our work proposes a strategy for transferring materials to arbitrary nanostructures swiftly and demonstrates new perspectives for highly sensitive humidity detection as well as self-recovery ability.

In situ formation of metal-organic framework derived CuO polyhedrons on carbon cloth for highly sensitive non-enzymatic glucose sensing.

Metal-organic frameworks (MOFs) are considered promising templates for the fabrication of nanostructured materials with high porosities and high surface areas, which are important parameters for enhanced performance in sensing applications. Here, a facile in situ synthetic strategy to construct MOF-derived porous CuO polyhedrons on carbon cloth (CC) is reported. Uniform Cu(OH)2 nanorods are first synthesized on carbon cloth, followed by the conversion of Cu(OH)2 nanorods into porous CuO polyhedrons via a copper-based MOF, Cu-BTC, as the intermediate species. When evaluated as a glucose sensing electrode, the as-fabricated CuO polyhedrons/CC composite exhibits a high sensitivity of 13 575 µA mM-1 cm-2 with a fast response time (t90) of 2.3 s and a low detection limit of 0.46 µM. This work exemplifies the rational fabrication of porous nanostructures on conductive substrates for enhanced performance in glucose detection.

Three-dimensional MoS2/Graphene Aerogel as Binder-free Electrode for Li-ion Battery.

Hybrid MoS2/reduced graphene aerogels with rich micro-pore are fabricated through a hydrothermal method, followed by freeze-drying and annealing treatment. The porous structure could act as an electrode directly, free of binder and conductive agent, which promotes an improved electron transfer, and provides a 3D network for an enhanced ion transport, thus leading to an increased capacity and stable long cycle stability performance. Notably, the specific capacity of MoS2/reduced graphene aerogel is 1041 mA h g-1 at 100 mA g-1. Moreover, reversible capacities of 667 mA h g-1 with 58.6% capacity retention are kept after 100 cycles. The outstanding performance is beneficial from the synergistic effect of the MoS2 nanostructure and graphene conductive network, as well as the binder-free design. These results provide a route to integrate transition-metal-dichalcogenides with graphene to fabricate composites with rich micro-pores and a three-dimensional network for energy storage devices.

Size Distribution Control of Copper Nanoparticles and Oxides: Effect of Wet-Chemical Redox Cycling.

In this work, we studied the effect of liquid-phase redox cycling on the size of Cu nanoparticles and oxides. The mixed solution of sodium hydroxide and ammonium persulfate was applied as the oxidation system at room temperature, and ascorbic acid was used as reduction agent at 80 °C in the cycling process. It was found that pristine copper particles with average size of around 800 nm and wide distribution from 300 to 1300 nm could be turned into the resulting particles with the average size of around 162.3 nm with the distribution from 75 to 250 nm after 5 redox cycles. It was also observed that uniform copper oxide nanowires formed after 5 oxidation cycles could be easily reduced into fine copper nanoparticles. The critical tuning factors including the precursor size, morphology, defects, reaction time, and the way of adding oxidant were investigated. It was suggested that the synergetic driving effect of chemical reduction and nanostructure thermodynamic instability in solution accounted for the size reformation of the copper nanoparticles. This proposed method of size-shrinking could be developed as a general strategy for large-scale tuning the properties of copper nanoparticles for wide applications and extended to other metal particles as well.

One-Step Mask-Based Diffraction Lithography for the Fabrication of 3D Suspended Structures.

We propose a novel one-step exposure method for fabricating three-dimensional (3D) suspended structures, utilizing the diffraction of mask patterns with small line width. An optical model of the exposure process is built, and the 3D light intensity distribution in the photoresist is calculated based on Fresnel-Kirchhoff diffraction formulation. Several 3D suspended photoresist structures have been achieved, such as beams, meshes, word patterns, and multilayer structures. After the pyrolysis of SU-8 structures, suspended and free-standing 3D carbon structures are further obtained, which show great potential in the application of transparent electrode, semitransparent solar cells, and energy storage devices.

Efficient Carbon-Based CsPbBr3 Inorganic Perovskite Solar Cells by Using Cu-Phthalocyanine as Hole Transport Material.

Metal halide perovskite solar cells (PSCs) have attracted extensive research interest for next-generation solution-processed photovoltaic devices because of their high solar-to-electric power conversion efficiency (PCE) and low fabrication cost. Although the world's best PSC successfully achieves a considerable PCE of over 20% within a very limited timeframe after intensive efforts, the stability, high cost, and up-scaling of PSCs still remain issues. Recently, inorganic perovskite material, CsPbBr3, is emerging as a promising photo-sensitizer with excellent durability and thermal stability, but the efficiency is still embarrassing. In this work, we intend to address these issues by exploiting CsPbBr3 as light absorber, accompanied by using Cu-phthalocyanine (CuPc) as hole transport material (HTM) and carbon as counter electrode. The optimal device acquires a decent PCE of 6.21%, over 60% higher than those of the HTM-free devices. The systematic characterization and analysis reveal a more effective charge transfer process and a suppressed charge recombination in PSCs after introducing CuPc as hole transfer layer. More importantly, our devices exhibit an outstanding durability and a promising thermal stability, making it rather meaningful in future fabrication and application of PSCs.

Leaf Vein-Inspired Hierarchical Wedge-Shaped Tracks on Flexible Substrate for Enhanced Directional Water Collection.

Water collection has been extensively researched due to its potential for mitigating the water scarcity in arid and semiarid regions. Numerous structures mimicking the fog-harvesting strategy of organisms have been fabricated for improving water-collecting efficiency. In this contribution, we demonstrate four-level wedge-shaped tracks inspired by leaf vein for enhancing directional water collection. Superhydrophilic Cu(OH)2 nanowires are introduced and prepared on flexible hydrophobic polyethylene terephthalate (PET) substrates by alkali-assisted surface oxidation at room temperature. They provide abundant capillary paths for promoting droplet absorption and forming water film tracks. Then, the hierarchical wedge-shaped tracks enable the water to be transported to a certain accumulation region spontaneously owing to the continuous Young-Laplace pressure difference. As a result, the four-level wedge-shaped tracks on PET substrate achieve the highest water-collecting efficiency, increasing by nearly 1150 and 510% compared to the bare PET and Cu(OH)2 nanowires on PET, respectively. After being bent for 105 cycles at a radius of 10 mm, the samples can still preserve high efficiency, indicating that the synthetic structures possess outstanding durability. Our approach provides a novel strategy for water collection and paves ways for directional liquid transportation and microfluidic devices.

Microscopic Three-Dimensional Measurement Based on Telecentric Stereo and Speckle Projection Methods.

Three-dimensional (3D) measurement of microstructures has become increasingly important, and many microscopic measurement methods have been developed. For the dimension in several millimeters together with the accuracy at sub-pixel or sub-micron level, there is almost no effective measurement method now. Here we present a method combining the microscopic stereo measurement with the digital speckle projection. A microscopy experimental setup mainly composed of two telecentric cameras and an industrial projection module is established and a telecentric binocular stereo reconstruction procedure is carried out. The measurement accuracy has firstly been verified by performing 3D measurements of grid arrays at different locations and cylinder arrays with different height differences. Then two Mitutoyo step masters have been used for further verification. The experimental results show that the proposed method can obtain 3D information of the microstructure with a sub-pixel and even sub-micron measuring accuracy in millimeter scale.

Fitting an Optical Fiber Background with a Weighted Savitzky-Golay Smoothing Filter for Raman Spectroscopy.

The Raman background arising from optical fiber materials poses a critical problem for fiber optic surface-enhanced Raman spectroscopy (SERS). A novel filter is developed to fit the optical fiber background from the measured SERS spectrum of the target sample. The general model of the filter is built by incorporating a weighted term of matching the similarity between the estimated background spectrum and the measured background spectrum into the classic Savitzky-Golay (SG) smoothing filter model. Through respectively selecting Euclidean cosine coefficient (ECos) and Pearson correlation coefficient (PCor) as the similarity index, two different models of the weighted SG smoothing filter are derived and named as SG-ECos and SG-PCor accordingly. Furthermore, the algorithm is presented, implemented, successfully applied to experimentally measured SERS spectra of rhodamine 6G and crystal violet, and validated with mathematically simulated Raman spectra. Experimental and simulation results show that the SG-ECos filter is effective, fast, flexible, and of certain anti-noise capability in background fitting. It is suggested that the proposed filter may be also applicable for other Raman spectra measurements to remove spectral contaminants originated from sampling substrates such as glass slides.