Naphthalene Diimide-Modified SnO2 Enabling Low-Temperature Processing for Efficient ITO-Free Flexible Perovskite Solar Cells.

A low-cost and indium-tin-oxide (ITO)-free electrode-based flexible perovskite solar cell (PSC) that can be fabricated by roll-to-roll processing shall be developed for successful commercialization. High processing temperatures present a challenge for the PSC fabrication on flexible substrates. The most efficient planar n-i-p PSC structures, which utilize a metal oxide as an electron transport layer (ETL), necessitate high annealing temperatures. In addition, the device performance deteriorates owing to the migration of halogen ions, which causes the oxidation of the metal electrodes. These drawbacks conflict with the development of highly efficient flexible PSCs fabricated on ITO-free transparent electrodes. Herein, an efficient ETL material that enables low-temperature processing is presented. Tin dioxide (SnO2) is modified by (sulfobetaine-N,N-dimethylamino)propyl naphthalene diimide (NDI-B) and used as an ETL. The NDI-B effectively reduces the interfacial nonradiative recombination between the ETL and perovskite and suppresses the ion migration by passivating oxygen-vacancy defects in SnO2 and strongly interacting with halogen ions, respectively. Based on the NDI-B-blended SnO2 ETL, a record PCE of 17.48% is achieved in the ITO-free flexible PSC fabricated at low temperature.

SCAE-Stacked Convolutional Autoencoder for Fault Diagnosis of a Hydraulic Piston Pump with Limited Data Samples.

Deep learning (DL) models require enormous amounts of data to produce reliable diagnosis results. The superiority of DL models over traditional machine learning (ML) methods in terms of feature extraction, feature dimension reduction, and diagnosis performance has been shown in various studies of fault diagnosis systems. However, data acquisition can sometimes be compromised by sensor issues, resulting in limited data samples. In this study, we propose a novel DL model based on a stacked convolutional autoencoder (SCAE) to address the challenge of limited data. The innovation of the SCAE model lies in its ability to enhance gradient information flow and extract richer hierarchical features, leading to superior diagnostic performance even with limited and noisy data samples. This article describes the development of a fault diagnosis method for a hydraulic piston pump using time-frequency visual pattern recognition. The proposed SCAE model has been evaluated on limited data samples of a hydraulic piston pump. The findings of the experiment demonstrate that the suggested approach can achieve excellent diagnostic performance with over 99.5% accuracy. Additionally, the SCAE model has outperformed traditional DL models such as deep neural networks (DNN), standard stacked sparse autoencoders (SSAE), and convolutional neural networks (CNN) in terms of diagnosis performance. Furthermore, the proposed model demonstrates robust performance under noisy data conditions, further highlighting its effectiveness and reliability.

Revolutionizing Robotic Depalletizing: AI-Enhanced Parcel Detecting with Adaptive 3D Machine Vision and RGB-D Imaging for Automated Unloading.

Detecting parcels accurately and efficiently has always been a challenging task when unloading from trucks onto conveyor belts because of the diverse and complex ways in which parcels are stacked. Conventional methods struggle to quickly and accurately classify the various shapes and surface patterns of unordered parcels. In this paper, we propose a parcel-picking surface detection method based on deep learning and image processing for the efficient unloading of diverse and unordered parcels. Our goal is to develop a systematic image processing algorithm that emphasises the boundaries of parcels regardless of their shape, pattern, or layout. The core of the algorithm is the utilisation of RGB-D technology for detecting the primary boundary lines regardless of obstacles such as adhesive labels, tapes, or parcel surface patterns. For cases where detecting the boundary lines is difficult owing to narrow gaps between parcels, we propose using deep learning-based boundary line detection through the You Only Look at Coefficients (YOLACT) model. Using image segmentation techniques, the algorithm efficiently predicts boundary lines, enabling the accurate detection of irregularly sized parcels with complex surface patterns. Furthermore, even for rotated parcels, we can extract their edges through complex mathematical operations using the depth values of the specified position, enabling the detection of the wider surfaces of the rotated parcels. Finally, we validate the accuracy and real-time performance of our proposed method through various case studies, achieving mAP (50) values of 93.8% and 90.8% for randomly sized and rotationally covered boxes with diverse colours and patterns, respectively.

Chemically Engineered Titanium Oxide Interconnecting Layer for Multijunction Polymer Solar Cells.

We report chemically tunable n-type titanium oxides using ethanolamine as a nitrogen dopant source. As the amount of ethanolamine added to the titanium oxide precursor during synthesis increases, the Fermi level of the resulting titanium oxides (ethanolamine-incorporated titanium oxides) significantly changes from -4.9 eV to -4.3 eV, and their free charge carrier densities are enhanced by two orders of magnitudes, reaching up to 5 × 1018 cm-3. Unexpectedly, a basic ethanolamine reinforces not only the n-type properties of titanium oxides, but also their basicity, which facilitates acid-base ionic junctions in contact with acidic materials. The enhanced charge carrier density and basicity of the chemically tuned titanium oxides enable multi-junction solar cells to have interconnecting junctions consisting of basic n-type titanium oxides and acidic p-type PEDOT:PSS to gain high open-circuit voltages of 1.44 V and 2.25 V from tandem and triple architectures, respectively.

C-Axis Aligned Composite InZnO via Thermal Atomic Layer Deposition for 3D Nanostructured Semiconductor.

Amorphous oxide semiconductors have been widely studied for various applications, including thin-film transistors (TFTs) for display backplanes and semiconductor memories. However, the inherent instability, limited mobility, and complexity of multicomponent oxide semiconductors for achieving high aspect ratios and conformality of cation distribution remain challenging. Indium-zinc oxide (IZO), known for its high mobility, also faces obstacles in instability resulting from high carrier doping density and low ionization energy. To address these issues and attain a balance between mobility and stability, adopting a highly aligned structure such as a c-axis aligned crystalline IGZO could be advantageous. However, limited studies have reported enhanced electrical performance using crystalline IZO, likely attributed to the high thermal stability of the individual components (In2O3 and ZnO). Here, we first propose a c-axis aligned composite (CAAC) IZO with superior TFT properties, including a remarkable performance of field-effect mobility (µFE) of 55.8 cm2/(V s) and positive-bias-temperature-stress stability of +0.16 V (2 MV/cm, 60 °C, 1 h), as well as a low subthreshold swing of 0.18 V/decade and hysteresis as 0.01 V, which could be obtained through optimization of growth temperature and composition using thermal atomic layer deposition. These results surpass those of TFTs based on nanocrystalline/polycrystalline/amorphous-IZO. We conducted a thorough investigation of CAAC-IZO and revealed that the growth temperature and cation distribution profoundly influence the crystal structure and device properties. Finally, we observed excellent compositional conformality and 97% step coverage of IZO on a high-aspect-ratio (HAR) structure with an aspect ratio reaching 40:1, which is highly promising for future applications. Our results include a detailed investigation of the influence of the crystal structure of IZO on the film and TFT performance and suggest an approach for future applications.

Microwave-Mediated, Catalyst-Free Synthesis of 1,2,4-Triazolo[1,5-a]pyridines from Enaminonitriles.

A catalyst-free, additive-free, and eco-friendly method for synthesizing 1,2,4-triazolo[1,5-a]pyridines under microwave conditions has been established. This tandem reaction involves the use of enaminonitriles and benzohydrazides, a transamidation mechanism followed by nucleophilic addition with nitrile, and subsequent condensation to yield the target compound in a short reaction time. The methodology demonstrates a broad substrate scope and good functional group tolerance, resulting in the formation of products in good-to-excellent yields. Furthermore, the scale-up reaction and late-stage functionalization of triazolo pyridine further demonstrate its synthetic utility. A plausible reaction pathway, based on our findings, has been proposed.

Overcoming the Interfacial Photocatalytic Degradation of Nonfullerene Acceptor-Based Organic Photovoltaics by Introducing a UV-A-Insensitive Titanium Suboxide Layer.

Although recent dramatic advances in power conversion efficiencies (PCEs) have resulted in values over 19%, the poor photostability of organic photovoltaics (OPVs) has been a serious bottleneck to their commercialization. The photocatalytic effect, which is caused by incident ultraviolet-A (UV-A, 320-400 nm) light in the most commonly used zinc oxide (ZnOX) electron transport layer (ETL), significantly deteriorates the photostability of OPVs. In this work, we develop a new and facile method to enhance the photostability of nonfullerene acceptor-based OPVs by introducing UV-A-insensitive titanium suboxide (TiOX) ETL. Through an in-depth analysis of mass information at the interface between the ETL and photoactive layer, we confirm that the UV-A-insensitive TiOX suppresses the photocatalytic effect. The resulting device employing the TiOX ETL shows excellent photostability, obtaining 80% of the initial PCE for up to 200 h under 1 sun illumination, which is 10 times longer than that of the conventional ZnOX system (19 h).

The Effect of Fermented Grains (koji) on Physicochemical and Sensory Characteristics of Chicken Breasts.

This study investigated the tenderizing and flavor-enhancing effects of koji, a fermented grain cultured with a single microorganism, on chicken breasts during curing. Chicken breasts were cured with different ingredients, including 4% (w/w) curing agent (GC), 5% (w/w) Aspergillus oryzae with rice (FR), A. oryzae with soybean (FS), and Bacillus subtilis with soybean (BS) for 4 h at 4 °C prior to cooking. After the superheated steam procedure, all samples were cooked in a convection oven, and their physicochemical properties were analyzed. Koji-treated samples exhibited significantly higher expressible moisture due to the degradation of the protein matrix (p < 0.05). Texture profile analysis showed that the tenderness of koji-treated samples was significantly higher than that of GC (p < 0.05). Furthermore, koji-treated samples were regarded as tenderer, and they were preferred over GC (p < 0.05) in the sensory evaluation. Principal attributes analysis revealed that the overall preference for koji-treated samples was highly correlated with umami, juiciness, and tenderness (p < 0.05). Overall, this study provides insights into applying koji as a potential curing treatment to improve the eating quality of chicken breasts. Koji can be used as a novel technology in the food industry to improve taste and tenderness simultaneously.

In Situ Doping of the PEDOT Top Electrode for All-Solution-Processed Semitransparent Organic Solar Cells.

The development of an ideal solution-processable transparent electrode has been a challenge in the field of all-solution-processed semitransparent organic solar cells (ST-OSCs). We present a novel poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS) top electrode for all-solution-processed ST-OSCs through in situ doping of PEDOT:PSS. A strongly polarized long perfluoroalkyl (n = 8) chain-anchored sulfonic acid effectively eliminates insulating PSS and spontaneously crystallizes PEDOT at room temperature, leading to outstanding electrical properties and transparency of PEDOT top electrodes. Doped PEDOT-based ST-OSCs yield a high power conversion efficiency of 10.9% while providing an average visible transmittance of 26.0% in the visible range. Moreover, the strong infrared reflectivity of PEDOT enables ST-OSCs to reject 62.6% of the heat emitted by sunlight (76.7% from infrared radiation), outperforming the thermal insulation capability of commercial tint films. This light management approach using PEDOT enables ST-OSCs to simultaneously provide energy generation and energy savings, making it the first discovery toward sustainable energy in buildings.

Device-Algorithm Co-Optimization for an On-Chip Trainable Capacitor-Based Synaptic Device with IGZO TFT and Retention-Centric Tiki-Taka Algorithm.

Analog in-memory computing synaptic devices are widely studied for efficient implementation of deep learning. However, synaptic devices based on resistive memory have difficulties implementing on-chip training due to the lack of means to control the amount of resistance change and large device variations. To overcome these shortcomings, silicon complementary metal-oxide semiconductor (Si-CMOS) and capacitor-based charge storage synapses are proposed, but it is difficult to obtain sufficient retention time due to Si-CMOS leakage currents, resulting in a deterioration of training accuracy. Here, a novel 6T1C synaptic device using only n-type indium gaIlium zinc oxide thin film transistor (IGZO TFT) with low leakage current and a capacitor is proposed, allowing not only linear and symmetric weight update but also sufficient retention time and parallel on-chip training operations. In addition, an efficient and realistic training algorithm to compensate for any remaining device non-idealities such as drifting references and long-term retention loss is proposed, demonstrating the importance of device-algorithm co-optimization.

Photopically Transparent Organic Solar Cells with Tungsten Oxide-Based Multilayer Electrodes.

The tailoring of the average photopic transmittance (APT) of transparent organic solar cells (T-OSCs) has been the greatest challenge in building-integrated photovoltaic applications for future smart solar windows to regulate indoor brightness, maintain a human circadian rhythm, and positively impact human emotions by allowing the observation of the external environment. However, a notorious trade-off exists between the APT and power conversion efficiency (PCE) of T-OSCs, mainly due to the absence of highly conductive and transparent top electrodes, which are a key building block determining the PCE and APT. Herein, we demonstrate a new tungsten oxide (WO3)-based multilayer as a highly conductive and transparent top electrode that provides an excellent APT while maintaining a high PCE in T-OSCs. With the assistance of optical simulation based on a transfer matrix method to calculate the optimum thicknesses of the multilayer electrodes, we achieve the best-performing T-OSC with a PCE of 7.0% and a full device APT of 46.7%, resulting in a high light utilization efficiency of 3.27%, which is superior to that of T-OSCs based on the same photoactive system. Furthermore, superior thermal stability at 85 °C in an N2 atmosphere is observed in WO3-based T-OSCs, maintaining 98% of the initial PCE after about 231 h. Our findings provide new insights into the development of T-OSCs with high efficiency and transparency.

Efficient and Stable Quasi-2D Ruddlesden-Popper Perovskite Solar Cells by Tailoring Crystal Orientation and Passivating Surface Defects.

Solar cells (PSCs) with quasi-2D Ruddlesden-Popper perovskites (RPP) exhibit greater environmental stability than 3D perovskites; however, the low power conversion efficiency (PCE) caused by anisotropic crystal orientations and defect sites in the bulk RPP materials limit future commercialization. Herein, a simple post-treatment is reported for the top surfaces of RPP thin films (RPP composition of PEA2 MA4 Pb5 I16 = 5) in which zwitterionic n-tert-butyl-α-phenylnitrone (PBN) is used as the passivation material. The PBN molecules passivate the surface and grain boundary defects in the RPP and simultaneously induce vertical direction crystal orientations of the RPPs, which lead to efficient charge transport in the RPP photoactive materials. With this surface engineering methodology, the optimized devices exhibit a remarkably enhanced PCE of 20.05% as compared with the devices without PBN (≈17.53%) and excellent long-term operational stability with 88% retention of the initial PCE under continuous 1-sun irradiation for over 1000 h. The proposed passivation strategy provides new insights into the development of efficient and stable RPP-based PSCs.

New Ternary Blend Strategy Based on a Vertically Self-Assembled Passivation Layer Enabling Efficient and Photostable Inverted Organic Solar Cells.

Herein, a new ternary strategy to fabricate efficient and photostable inverted organic photovoltaics (OPVs) is introduced by combining a bulk heterojunction (BHJ) blend and a fullerene self-assembled monolayer (C60 -SAM). Time-of-flight secondary-ion mass spectrometry - analysis reveals that the ternary blend is vertically phase separated with the C60 -SAM at the bottom and the BHJ on top. The average power conversion efficiency - of OPVs based on the ternary system is improved from 14.9% to 15.6% by C60 -SAM addition, mostly due to increased current density (Jsc ) and fill factor -. It is found that the C60 -SAM encourages the BHJ to make more face-on molecular orientation because grazing incidence wide-angle X-ray scattering - data show an increased face-on/edge-on orientation ratio in the ternary blend. Light-intensity dependent Jsc data and charge carrier lifetime analysis indicate suppressed bimolecular recombination and a longer charge carrier lifetime in the ternary system, resulting in the enhancement of OPV performance. Moreover, it is demonstrated that device photostability in the ternary blend is enhanced due to the vertically self-assembled C60 -SAM that successfully passivates the ZnO surface and protects BHJ layer from the UV-induced photocatalytic reactions of the ZnO. These results suggest a new perspective to improve both performance and photostability of OPVs using a facial ternary method.

New Non-Fullerene Acceptor with Extended Conjugation of Cyclopenta [2,1-b:3,4-b'] Dithiophene for Organic Solar Cells.

Herein, we design and characterize 9-heterocyclic ring non-fullerene acceptors (NFAs) with the extended backbone of indacenodithiophene by cyclopenta [2,1-b:3,4-b'] dithiophene (CPDT). The planar conjugated CPDT donor enhances absorption by reducing vibronic transition and charge transport. Developed NFAs with different end groups shows maximum absorption at approximately 790-850 nm in film. Because of the electronegative nature of the end-group, the corresponding acceptors showed deeper LUMO energy levels and red-shifted ultraviolet absorption. We investigate the crystallinity, film morphology, surface energy, and electronic as well as photovoltaic performance. The organic photovoltaic cells using novel NFAs with the halogen end groups fluorine or chlorine demonstrate better charge collection and faster exciton dissociation than photovoltaic cells using NFAs with methyl or lacking a substituent. Photovoltaic devices constructed from m-Me-ITIC with various end groups deliver power conversion efficiencies of 3.6-11.8%.

Efficient and Stable Perovskite Solar Cells with a High Open-Circuit Voltage Over 1.2 V Achieved by a Dual-Side Passivation Layer.

Suppressing nonradiative recombination at the interface between the organometal halide perovskite (PVK) and the charge-transport layer (CTL) is crucial for improving the efficiency and stability of PVK-based solar cells (PSCs). Here, a new bathocuproine (BCP)-based nonconjugated polyelectrolyte (poly-BCP) is synthesized and this is introduced as a "dual-side passivation layer" between the tin oxide (SnO2 ) CTL and the PVK absorber. Poly-BCP significantly suppresses both bulk and interfacial nonradiative recombination by passivating oxygen-vacancy defects from the SnO2 side and simultaneously scavenges ionic defects from the other (PVK) side. Therefore, PSCs with poly-BCP exhibits a high power conversion efficiency (PCE) of 24.4% and a high open-circuit voltage of 1.21 V with a reduced voltage loss (PVK bandgap of 1.56 eV). The non-encapsulated PSCs also show excellent long-term stability by retaining 93% of the initial PCE after 700 h under continuous 1-sun irradiation in nitrogen atmosphere conditions.

Total Synthesis of Isohericerinol A and Its Analogues to Access Their Potential Neurotrophic Effects.

The secondary metabolites from Hericium erinaceus are well-known to have neurotrophic and neuroprotective effects. Isohericerinol A (1), isolated by our colleagues from its fruiting parts has a strong ability to increase the nerve growth factor secretion in C6 glioma cells. The current work describes the total synthesis of 1 and its regioisomer 5 in a few steps. We present two different approaches to 1 and a regiodivergent approach for both 1 and 5 by utilizing easily accessible feedstocks. Interestingly, the natural product 1, regioisomer 5, and their intermediates exhibited potent neurotrophic activity in in vitro experimental systems. Thus, these synthetic strategies provide access to a systematic structure-activity relationship study of natural product 1.

Synthesis and photophysical properties of N-alkyl dithieno[3,2-b:2',3'-d]pyrrole based donor/acceptor-π-conjugated copolymers for solar-cell application.

Two kinds of donor-acceptor π-conjugated copolymer based on poly{[N-hexyl-dithieno(3,2-b:2',3'-d)pyrrole-2,6-diyl]alt-[isoindigo]} (PDTP-IID) and poly{[N-hexyl-dithieno(3,2-b:2',3'-d)pyrrole-2,6-diyl]alt-[thiazol-2,5-diyl]} (PDTP-Thz) were investigated. These copolymers were synthesized via a Stille coupling reaction. The results showed the structure-property relationships of different donor-acceptor (D-A) combinations. The polymer structures and photophysical properties were characterized by 1H NMR, TGA, DSC, UV-vis absorption spectroscopy, AFM, CV, and XRD measurement. Through UV-vis absorption and cyclic voltammetry (CV) measurements, it showed that the copolymers exhibit not only a low bandgap of 1.29 eV and 1.51 eV but also a deep highest occupied molecular orbital (HOMO) of -5.49 and -5.11 eV. Moreover, photovoltaic properties in combination with the fullerene derivatives were investigated. The device based on the copolymers with PC71BM exhibited higher maximum power conversion efficiency and higher maximum short-circuit current density of 0.23% with 1.64 mA cm-2 of PDTP-IID:PC71BM and 0.13% with 1.11 mA cm-2 of PDTP-Thz:PC71BM than those of the copolymers with PC61BM. Measurements performed for N-hexyl-dithieno(3,2-b:2',3'-d)pyrrole-based copolymers proved the potential of these polymers to be applied in optoelectronic applications.

A New General Fatigue Limit Diagram and Its Application of Predicting Die Fatigue Life during Cold Forging.

Traditional fatigue fracture theory and practice focus principally on structural design. It is thus too conservative and inappropriate when used to predict the high-cycle fatigue life of dies used for metal forming, especially cold forging. We propose a novel mean stress correction model and diagram to predict the high-cycle fatigue lives of cold forging dies, which focuses on the upper part of the equivalent fatigue strength curve. Considering the features of die materials characterized by high yield strength and low ductility, a straight line is assumed for the tensile yield line. To the contrary, a general curve is used to represent the fatigue strength. They are interpolated, based on the distance ratio, when finding an appropriate equivalent fatigue strength curve at the mean stress and stress amplitude between the line and curve. The approach is applied to a well-defined literature example to verify its validity and shed light on the characteristics of die fatigue life. The approach is also applied to practical forging and useful qualitative results are obtained.

Vibration-Based Loosening Detection of a Multi-Bolt Structure Using Machine Learning Algorithms.

Since artificial intelligence (AI) was introduced into engineering fields, it has made many breakthroughs. Machine learning (ML) algorithms have been very commonly used in structural health monitoring (SHM) systems in the last decade. In this study, a vibration-based early stage of bolt loosening detection and identification technique is proposed using ML algorithms, for a motor fastened with four bolts (M8 × 1.5) to a stationary support. First, several cases with fastened and loosened bolts were established, and the motor was operated in three different types of working condition (800 rpm, 1000 rpm, and 1200 rpm), in order to obtain enough vibration data. Second, for feature extraction of the dataset, the short-time Fourier transform (STFT) method was performed. Third, different types of classifier of ML were trained, and a new test dataset was applied to evaluate the performance of the classifiers. Finally, the classifier with the greatest accuracy was identified. The test results showed that the capability of the classifier was satisfactory for detecting bolt loosening and identifying which bolt or bolts started to lose their preload in each working condition. The identified classifier will be implemented for online monitoring of the early stage of bolt loosening of a multi-bolt structure in future works.