High-Quality Perovskite Film Preparations for Efficient Perovskite Solar Cells

Solar cells employing organolead halide perovskite films have caught tremendous attention, and their power conversion efficiencies were stunning from 3.9% to over 22% in only 6 years. Various research reports have shown that effective controls on perovskite crystallinity, homogeneity, and surface morphology are crucial to improving the power conversion efficiencies (PCE) of perovskite solar cells. Here, based on the typical one-step and two-step deposition methods, we would like to introduce the solvent treatment mechanisms of mixed-solvent-vapor annealing and polar solvent additive, investigate the growth mode and control means of perovskite films by physical characterizations, and discuss their effects on the photovoltaic performance improvements for perovskite solar cells

Interface Engineering and Electrode Engineering for Organic Solar Cells

Interface engineering and electrode engineering play important roles in the performance improvement for organic solar cells (OSCs). We here would investigate the effect of various cathode modifying layers and ITO-free electrodes on the device performance. First, for inverted organic solar cells (IOSCs) with a poly (3-hexylthiophene-2,5-diyl):[6,6]-phenyl C61 butyric acid methyl ester blend, an aqueous solution method using low temperatures is adopted to deposit a ZnO interlayer in IOSCs. When the ZnO annealing temperature is above 80°C, the corresponding IOSCs show senior PCEs over 3.5%. Meanwhile the flexible devices based on poly(ethylene terephthalate) substrate display a PCE of 3.26% and good flexibility. Second, the performance of IOSCs based on AZO cathode and Ca modifier are studied. The resulted IOSCs with an ultrathin Ca modifier (~1 nm) could achieve a senior PCE above 3%, and highly efficient electron transport at AZO/Ca/organic interface, which obviously weakens the light soaking issue. Third, by introducing a 2 nm MoO3 interlayer for Ag anode deposition, the obtained OSCs show an improved PCE of 2.71%, and the flexible device also achieves a comparable PCE of 2.50%. All these investigations may be instructive for further improvement of device performance and the possible commercialization in the future

Efficient Inverted ITO-Free Organic Solar Cells Based on Transparent Silver Electrode with Aqueous Solution-Processed ZnO Interlayer

Efficient inverted organic solar cells (OSCs) with the MoO3 (2 nm)/Ag (12 nm) transparent cathode and an aqueous solution ZnO electron extraction layer processed at low temperature are investigated in this work. The blend of low bandgap poly[[4,8-bis[(2-ethylhexyl)oxy]benzo[1,2-b:4,5-b′]dithiophene-2,6-diyl][3-fluoro-2-[(2-ethylhexyl)carbonyl]thieno[3,4-b]thiophenediyl]] (PTB7) and [6,6]-phenyl-C71-butyric acid methylester (PC71BM) is employed as the photoactive layer here. A power conversion efficiency (PCE) of 5.55% is achieved for such indium tin oxide- (ITO-) free OSCs under AM 1.5G simulated illumination, comparable to that of ITO-based reference OSCs (PCE of 6.11%). It is found that this ZnO interlayer not only slightly enhances the transparency of MoO3/Ag cathode but also obtains a lower root-mean-square (RMS) roughness on the MoO3/Ag surface. Meanwhile, ITO-free OSCs also show a good stability. The PCE of the devices still remains above 85% of the original values after 30 days, which is slightly superior to ITO-based reference OSCs where the 16% degradation in PCE is observed after 30 days. It may be instructive for further research of OSCs based on metal thin film electrodes

ITO-Free Semitransparent Organic Solar Cells Based on Silver Thin Film Electrodes

ITO-free semitransparent organic solar cells (OSCs) based on MoO3/Ag anodes with poly(3-hexylthiophene) and [6,6]-phenyl-C61-butyric acid methyl ester films as the active layer are investigated in this work. To obtain the optimal transparent (MoO3)/Ag anode, ITO-free reference OSCs are firstly fabricated. The power conversion efficiency (PCE) of 2.71% is obtained for OSCs based on the optimal MoO3 (2 nm)/Ag (9 nm) anode, comparable to that of ITO-based reference OSCs (PCE of 2.85%). Then based on MoO3 (2 nm)/Ag (9 nm) anode, ITO-free semitransparent OSCs with different thickness combination of Ca and Ag as the cathodes are investigated. It is observed from our results that OSCs with Ca (15 nm)/Ag (15 nm) cathode have the optimal transparency. Meanwhile, the PCE of 1.79% and 0.67% is obtained for illumination from the anode and cathode side, respectively, comparable to that of similar ITO-based semitransparent OSCs (PCE of 1.59% and 0.75% for illumination from the anode and cathode side, resp.) (Sol. Energy Mater. Sol. Cells, 95, pp. 877–880, 2011). The transparency and PCE of ITO-free semitransparent OSCs can be further improved by introducing a light couple layer. The developed method is compatible with various substrates, which is instructive for further research of ITO-free semitransparent OSCs

Attention-Based Temporal-Frequency Aggregation for Speaker Verification

Convolutional neural networks (CNNs) have significantly promoted the development of speaker verification (SV) systems because of their powerful deep feature learning capability. In CNN-based SV systems, utterance-level aggregation is an important component, and it compresses the frame-level features generated by the CNN frontend into an utterance-level representation. However, most of the existing aggregation methods aggregate the extracted features across time and cannot capture the speaker-dependent information contained in the frequency domain. To handle this problem, this paper proposes a novel attention-based frequency aggregation method, which focuses on the key frequency bands that provide more information for utterance-level representation. Meanwhile, two more effective temporal-frequency aggregation methods are proposed in combination with the existing temporal aggregation methods. The two proposed methods can capture the speaker-dependent information contained in both the time domain and frequency domain of frame-level features, thus improving the discriminability of speaker embedding. Besides, a powerful CNN-based SV system is developed and evaluated on the TIMIT and Voxceleb datasets. The experimental results indicate that the CNN-based SV system using the temporal-frequency aggregation method achieves a superior equal error rate of 5.96% on Voxceleb compared with the state-of-the-art baseline models

Neural Network-Based Autonomous Search Model with Undulatory Locomotion Inspired by Caenorhabditis Elegans

Caenorhabditis elegans (C. elegans) exhibits sophisticated chemotaxis behavior with a unique locomotion pattern using a simple nervous system only and is, therefore, well suited to inspire simple, cost-effective robotic navigation schemes. Chemotaxis in C. elegans involves two complementary strategies: klinokinesis, which allows reorientation by sharp turns when moving away from targets; and klinotaxis, which gradually adjusts the direction of motion toward the preferred side throughout the movement. In this study, we developed an autonomous search model with undulatory locomotion that combines these two C. elegans chemotaxis strategies with its body undulatory locomotion. To search for peaks in environmental variables such as chemical concentrations and radiation in directions close to the steepest gradients, only one sensor is needed. To develop our model, we first evolved a central pattern generator and designed a minimal network unit with proprioceptive feedback to encode and propagate rhythmic signals; hence, we realized realistic undulatory locomotion. We then constructed adaptive sensory neuron models following real electrophysiological characteristics and incorporated a state-dependent gating mechanism, enabling the model to execute the two orientation strategies simultaneously according to information from a single sensor. Simulation results verified the effectiveness, superiority, and realness of the model. Our simply structured model exploits multiple biological mechanisms to search for the shortest-path concentration peak over a wide range of gradients and can serve as a theoretical prototype for worm-like navigation robots

Enhanced Performance of Inverted Non-Fullerene Organic Solar Cells by Using Metal Oxide Electron- and Hole-Selective Layers with Process Temperature ≤150 °C

In this work, an efficient inverted organic solar cell (OSC) based on the non-fullerene PBDB-T:IT-M blend system is demonstrated by using an aqueous solution processed ZnO electron-selective layer with the whole process temperature ≤150 °C and a thermally evaporated MoO3 hole-selective layer The ZnO selective layer is deposited by aqueous solution and prepared in a low-temperature process, so that it can be compatible with the roll-to-roll process. The proposed device achieves an enhanced power conversion efficiency (PCE) of 9.33% compared with the device based on the high-temperature sol-gel-processed ZnO selective layer, which achieves a PCE of 8.62%. The inverted device also shows good stability, keeping more than 82% of its initial PCE after being stored under ambient air conditions and a humidity of around 40% without any encapsulation for 240 h. The results show the potential for the fabrication of efficient non-fullerene OSCs with low-temperature metal oxide selective layers

Predicting the Risk of Alzheimer’s Disease and Related Dementia in Patients with Mild Cognitive Impairment Using a Semi-Competing Risk Approach

Alzheimer’s disease (AD) and AD-related dementias (AD/ADRD) are a group of progressive neurodegenerative diseases. The progression of AD can be conceptualized as a continuum in which patients progress from normal cognition to preclinical AD (i.e., no symptoms but biological changes in the brain) to mild cognitive impairment (MCI) due to AD (i.e., mild symptoms but not interfere with daily activities), followed by increasing severity of dementia due to AD. Early detection and prediction models for the transition of MCI to AD/ADRD are needed, and efforts have been made to build predictions of MCI conversion to AD/ADRD. However, most existing studies developing such prediction models did not consider the competing risks of death, which may result in biased risk estimates. In this study, we aim to develop a prediction model for AD/ADRD among patients with MCI considering the competing risks of death using a semi-competing risk approach