Even though the perovskite solar cell has been so popular for its skyrocketing power conversion efficiency, its further development is still roadblocked by its overall performance, in particular ...long-term stability, large-area fabrication and stable module efficiency. In essence, the soft component and ionic-electronic nature of metal halide perovskites usually chaperonage large number of anion vacancy defects that act as recombination centers to decrease both the photovoltaic efficiency and operational stability. Herein, we report a one-stone-for-two-birds strategy in which both anion-fixation and associated undercoordinated-Pb passivation are in situ achieved during crystallization by using a single amidino-based ligand, namely 3-amidinopyridine, for metal-halide perovskite to overcome above challenges. The resultant devices attain a power conversion efficiency as high as 25.3% (certified at 24.8%) with substantially improved stability. Moreover, the device without encapsulation retained 92% of its initial efficiency after 5000 h exposure in ambient and the device with encapsulation retained 95% of its initial efficiency after >500 h working at the maximum power point under continuous light irradiation in ambient. It is expected this one-stone-for-two-birds strategy will benefit large-area fabrication that desires for simplicity.
A new method for feature subset selection in machine learning, FSS-MGSA (Feature Subset Selection by Modified Gravitational Search Algorithm), is presented. FSS-MGSA is an evolutionary, stochastic ...search algorithm based on the law of gravity and mass interactions, and it can be executed when domain knowledge is not available. A wrapper approach, over Naive-Bayes, ID3, K-Nearest Neighbor and Support Vector Machine learning algorithms, is used to evaluate the goodness of each visited solution. The key to the success of the MGSA is to utilize the piecewise linear chaotic map for increasing its diversity of species, and to use sequential quadratic programming for accelerating local exploitation. Promising results are achieved in a variety of tasks where domain knowledge is not available. The experimental results show that the proposed method has the ability of selecting the discriminating input features correctly and can achieve high accuracy of classification, which is comparable to or better than well-known similar classifier systems. Furthermore, the MGSA is tested on ten functions provided by CEC 2005 special session and compared with various modified Gravitational Search Algorithm, Particle Swarm Optimization, and Genetic Algorithm. The obtained results confirm the high performance of the MGSA in solving various problems in optimization.
The flexible pressure sensor is expected to be applied in the new generation of sports wearable electronic devices. Developing flexible pressure sensors with a wide linear range and great ...sensitivity, however, remains a significant barrier. In this work, we propose a hybrid conductive elastomeric film oxide-based material with a concave-shape micro-patterned array (P-HCF) on the surface that sustainably shows the necessary sensing qualities. To enhance sensing range and sensitivity, one-dimensional carbon fibers and two-dimensional MXene are incorporated into the polydimethylsiloxane matrix to form a three-dimensional conductive network. Micro-patterns with a curved shape in P-HCFs can be able to linear sensitivity across the sensing range by controlling the pressure distribution inside the material. Besides, the sensitivity of P-HCF pressure sensor can reach 31.92 kPa
−1
, and meanwhile, the linear band of P-HCF pressure sensor can arrive at 24 Pa–720 kPa, which makes it a good choice for sports monitoring. The designed pressure sensor can be used to monitor the foot pressure during running. By analyzing the gait information during running, it can provide data support and strategy improvement for running. This new dual working mode pressure P-HCF sensor will provide a new way for the development of intelligent sports.
The simultaneous cooling in the dehumidification of an internally-cooled process is quite different from an adiabatic process that uses liquid desiccant. In the present study, the operating ...performance of an internally-cooled process was examined through both experimental tests and simulation analysis. An internally-cooled dehumidifier made of stainless steel was designed, and experimental results in different working conditions were analyzed using a lithium bromide (LiBr) aqueous solution. The moisture removal rate, dehumidifying efficiency, and volume mass transfer coefficient were adopted as indices to evaluate the performance. The effects of the inlet parameters on these performance indices were investigated. The predicted results by the numerical model agreed well with the experimental results. The validated model was then utilized to predict the performance of the entire internally-cooled/heated air handling system, in which low regeneration temperature could be realized. An internally-cooled/heated system driven by the exhaust heat of heat pump was then proposed, and COP was in the range of 4.2–6.5.
► Experiments on an internally-cooled dehumidifier are carried out using LiBr. ► Effects of tw,in, m˙wandm˙s on the dehumidifying performance are investigated. ► Theoretical model for an internal cooled/heated system is built and validated. ► An internally-cooled/heated system driven by the heat pump is analyzed.
New structural type of 2D AA′n−1MnX3n+1 type halide perovskites stabilized by symmetric diammonium cations has attracted research attention recently due to the short interlayer distance and better ...charge‐transport for high‐performance solar cells (PSCs). However, the distribution control of quantum wells (QWs) and its influence on optoelectronic properties are largely underexplored. Here effective phase‐alignment is reported through dynamical control of film formation to improve charge transfer between quantum wells (QWs) for 2D perovskite (BDA)(MA)n‐1PbnI3n+1 (BDA = 1,4‐butanediamine, 〈n〉 = 4) film. The in situ optical spectra reveal a significantly prolonged crystallization window during the perovskite deposition via additive strategy. It is found that finer thickness gradient by n values in the direction orthogonal to the substrate leads to more efficient charge transport between QWs and suppressed charge recombination in the additive‐treated film. As a result, a power conversion efficiency of 14.4% is achieved, which is not only 21% higher than the control one without additive treatment, but also one of the high efficiencies of the low‐n (n ≤ 4) AA′n−1MnX3n+1 PSCs. Furthermore, the bare device retains 92% of its initial PCE without any encapsulation after ambient exposure for 1200 h.
The in situ optical spectra reveal a significantly prolonged crystallization window during the perovskite deposition via additive strategy. Finer thickness gradient by n values in the direction orthogonal to the substrate leads to more efficient charge transport between quantum wells and suppressed charge recombination in the additive‐treated film. Finally, the power conversion efficiency of 14.4% is obtained.
A new chaotic secure communication scheme based on a gravitational search algorithm (GSA) filter is proposed. In this scheme, useful signals are delivered via an encoder, a chaotic transmitter, a ...GSA-based filter, a chaotic receiver, and a decoder. The security of such a communication system is promoted due to the unpredictable features of the chaotic map and the unknown encoding-modulation scheme. By using a GSA filter technique the resistance of the system to noise is enhanced. To verify the effectiveness of the proposed scheme, it is compared with the current state-of-the-art schemes in simulations. At the same time, comparisons with a genetic algorithm (GA) filter and a particle swarm optimization (PSO) filter are made. Numerical simulations confirm that the proposed method is better in estimating the states and information symbols, and has a lower bit error rate than other schemes.
Research in recent years has seen the development of chaotic systems for secure communication. However, most chaotic systems fail to compensate for channel noise which often degrades the performance ...of chaos-based secure communication systems. In this work, we propose a chaotic secure communication scheme based on the Modified Gravitational Search Algorithm (MGSA), which minimizes premature convergence of Gravitational Search Algorithm (GSA). Here, we apply the MGSA-based filter to the proposed communication scheme to reduce channel noise. Computer simulations with the unified chaotic map are done to verify the feasibility of the proposed secure communication scheme. The results show that the proposed new scheme accurately estimates the states and information symbols, and provides a lower bit error rate (BER) than existing secure communication schemes. Furthermore, the MGSA is tested on the nonlinear filter modeling and compared with GSA and particle swarm optimization (PSO). The results confirm the high performance of the MGSA-based filter in parameters estimation of nonlinear filter modeling. In other words, the more accurately the MGSA estimates the parameters, the more noise the filter reduces.
•We examine the predictability of time-varying risk aversion on stock volatility.•We use a simple linear autoregressive model to capture predictive relationships.•In-sample results show time-varying ...risk aversion has significant predictability.•It is statistically and economically significant for out-of-sample performance.
In this paper, we predict realized volatility of stock return by utilizing time-varying risk aversion based on a simple linear autoregressive model. Our in-sample results suggest that time-varying risk aversion have significant impact for stock return volatility. In terms of out-of-sample forecasting performance, the empirical results indicate that the incorporation of time-varying risk aversion in the benchmark model can yield more accurate stock return volatility forecasts. Notably, the out-of-sample forecasting results confirm that our conclusions are robust when we apply alternative lag orders and alternative prediction evaluation periods. Finally, we study links between the prediction ability of time-varying risk aversion and the volatility of other stock indices and two kinds of crude oil, and find that the new predictor can effectively strengthen forecasting performance in most case. In view of the importance of volatility risk in the asset pricing process, our research is of great significance for financial asset participants.
Time series observed in real world is often nonlinear, even chaotic. However, observed data is often contaminated by noise of various types. To effectively extract desired information from observed ...data, it is vital to preprocess data to reduce noise for both the analysis of dynamical systems and many potential applications of these systems. In this paper, we present a noise reduction approach to the problem of additive source separation characterized by wide band power spectra when one of the sources is chaotic. The algorithm is based on a Center-Based Genetic Algorithm (CBGA) in lifting wavelet framework, in which the CBGA is used for threshold optimization. This method intelligently adapts itself to various types of noise, and it weighs preservation of dynamics and denoising through Signal-to-Noise Ratio (SNR) and Root-Mean-Square Error (RMSE). Computer simulations show that the approach is very effective in diminishing different kinds of noise, and performs better in terms of visual quality as well as quantitative metrics than existing algorithms.
Eco-friendly printing is important for mass manufacturing of thin-film photovoltaic (PV) devices to preserve human safety and the environment and to reduce energy consumption and capital expense. ...However, it is challenging for perovskite PVs due to the lack of eco-friendly solvents for ambient fast printing. In this study, we demonstrate for the first time an eco-friendly printing concept for high-performance perovskite solar cells. Both the perovskite and charge transport layers were fabricated from eco-friendly solvents
scalable fast blade coating under ambient conditions. The perovskite dynamic crystallization during blade coating investigated using
grazing incidence wide-angle X-ray scattering (GIWAXS) reveals a long sol-gel window prior to phase transformation and a strong interaction between the precursors and the eco-friendly solvents. The insights enable the achievement of high quality coatings for both the perovskite and charge transport layers by controlling film formation during scalable coating. The excellent optoelectronic properties of these coatings translate to a power conversion efficiency of 18.26% for eco-friendly printed solar cells, which is on par with the conventional devices fabricated
spin coating from toxic solvents under inert atmosphere. The eco-friendly printing paradigm presented in this work paves the way for future green and high-throughput fabrication on an industrial scale for perovskite PVs.
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