Search

Abstract: We explore in this work the use of Cu as a cathode material in organic light-emitting devices (OLEDs) and find a dual electron–injection enhancement mechanism derived from the LiF layer. Different from what observed previously in Ag- and Au-cathode devices, the LiF buffer layer in the Cu-cathode OLEDs starts to play its role in performance improvement when it is much thinner than 3nm, the optimal value of buffer thickness, and in the case of optimal thickness, the device exhibits excellent performance comparable to conventional Al-cathode device. The phenomenon observed is ascribed to enhanced electron injection as a result of combined effect of interfacial reaction and tunneling barrier reduction mechanism: while chemical reaction plays a key role at the very beginning of interface formation, tunneling dominates in the subsequent stage leading to the tremendous improvement of the characteristics. [Copyright &y& Elsevier]

Excess sludge production from wastewater treatment plants has significantly increased, and sludge disposal has become a serious social and environmental problem. In this study, we constructed a microbial electrochemical hybrid system (MEHS) for simultaneous electricity generation, acid and alkali production, desalination, alkali pretreatment, and degradation of sludge. The alkaline solution generated in the MEHS was used for in situ sludge pretreatment. Owing to the efficiency in alkali pretreatment, a higher sludge degradation efficiency was obtained by the MEHS (Total chemical oxygen demand (TCOD) removal efficiency of 57.2%) than by the SMFC (TCOD removal efficiency of 51.7%). Moreover, the MEHS (0.165C) could recover more electricity from the sludge than a traditional single-chamber microbial fuel cell (SMFC, 0.133C). Additionally, the MEHS exhibited excellent performance in desalination (> 50%) and acid production. The system developed in this study provides a new solution for sludge degradation and multifunctional utilization. Unlabelled Image • MEHS utilized in-situ generated alkali for sludge treatment. • MEHS shows better sludge degradation performance than SMFC. • MEHS can collect more electricity than SMFC. • MEHS can achieve acid production and desalination. • This study provides a new way for sludge treatment and degradation in BES. [ABSTRACT FROM AUTHOR]

Hole transport materials (HTMs) play an essential role in obtaining efficient and stable perovskite solar cells (PSCs). In particular, PSCs based on dopant-free small molecule hole transport materials (SM-HTMs) have the unique advantages of reproducibility and long-term stability. In this work, we design and synthesis a small molecule, FIMPA-C11, with a D-A-D structure, to serve as a HTM. The corresponding inverted planar PSCs achieve a satisfying efficiency of 17.60%, equivalent to 17.01% of the NiO counterpart, with superior stability and much lower processing temperature. The property and morphology of FIMPA-C11 film make it a better substrate for the crystallization of perovskite absorbing layer. The work enriches the category of HTMs and provides innovation for high-performance dopant-free SM-HTMs in PSCs. [Display omitted] • A small-molecule with D-A-D structure and long alkyl chains was designed and synthesized as a dopant-free HTM for inverted PSCs. • FIMPA-C11 film can reduce the trap density at the HTL/perovskite interface, enhance the carrier migration and improve both efficiency and stability of device. • The device with lower process temperature shows higher PCE and better stability compared to the control device with NiO HTL. [ABSTRACT FROM AUTHOR]

A deep learning method is proposed to identify damages in jacket offshore platforms, which integrates the random decrement technique (RDT) and Transformer neural network. RDT is utilized to process the noisy strain response signals from various measurement points on the platform under random excitation, and the Transformer network is used to localize the damages and assess their severities. Numerical simulations and experimental studies are used to demonstrate that the proposed method is effective. The numerical model applied in this study is a jacket platform, including single and multiple damage cases in the entire section and partial section (two-fifths of the entire section) with minor severities (<5%), and different noise levels are considered. Additionally, the effect of measurement positions on identification accuracy of minor and major damage is discussed. Furthermore, the proposed method is validated by experimental studies using a jacket platform model fixed on a shaking table, where different severities of single and multiple damages are considered. Results of the numerical and experimental studies demonstrate that the proposed RDT-Transformer approach can accurately determine the location of structural damage and identify its severity. • Combine the RDT with Transformer for jacket offshore platforms damage identification under random excitation. • RDT can significantly improve the effectiveness of damage identification of Transformer under noise condition. • Validate the RDT-Transformer method through the numerical and experimental studies of jacket offshore platform. [ABSTRACT FROM AUTHOR]

In recent years, sulfite (S(Ⅳ)), as an alternative to persulfates, has played a crucial role in eliminating antibiotics in wastewater, so there is an urgent need to develop a cheap, environmentally friendly, and effective catalyst. Zero-valent iron (ZVI) has great potential for activated S(Ⅳ) removal of organic pollutants, but its reactivity in water is reduced due to passivation. In this study, a micron-scale iron-carbon composite(mZVI@C-800) prepared via high-temperature calcination was coupled with S(Ⅳ) to degrade metronidazole (MNZ). Under the optimized reaction conditions of mZVI@C-800 dosage of 0.2 g/L and S(Ⅳ) concentration of 0.1 g/L, the MNZ removal rate was up to 81.5 % in acidic and neutral environments. The surface chemical properties of the catalysts were characterized by different analytical techniques, and the corresponding catalytic mechanism was analyzed based on these analytical results. As a result, Fe2+ is the main active site, and ·OH and SO 4 ·- were the dominant active species. The increase in efficiency was attributed to the introduction of carbon to enhance the corrosion of mZVI further releasing more Fe2+. Additionally proposed were the potential response mechanism, the degradation path, and the toxicity change rule. These results demonstrate that the catalytic breakdown of antibiotics in wastewater treatment can be accelerated by the use of the outstanding catalytic material mZVI@C-800. [Display omitted] • A novel mZVI@C-T composites were developed for removal of MNZ. • MNZ could be effectively removed at the pH range of 3–7. • The enhanced mechanism of mZVI@C-T was explored. • The degradation pathways and ecotoxicity of the intermediates of MNZ were proposed. [ABSTRACT FROM AUTHOR]

Two perylene diimide (PDI) based polymeric acceptors, PFPDIBT-TT2F and PFPDIT-TT2F, which consist of fused-PDI moieties (FPDIBT and FPDIT) and 3,3′-difluoro-2,2′-bithiophene (TT2F) units, has been designed and synthesized. Compared with the unfused-PDI polymer (PPDI-TT2F) as the control molecule, the influence of structural conformation and π-conjugation extension on the performance of all-polymer solar cells has been investigated. Due to both the extended π-conjugation and the torsional polymer skeleton, the device adopting PFPDIT-TT2F achieved an obviously improved PCE of 5.11% comparing with the devices using the other two polymeric acceptors. This study demonstrates that the fused PDIs bridged by a thiophene enables both extended π-conjugation and twisted molecular conformation, and the latter plays a dominant role in the improvement of device performance. [Display omitted] • Two fused PDI based polymeric acceptors for all-PSCs are designed and synthesized. • Fused PDIs bridged by a thiophene enables both extended π-conjugation and twisted molecular conformation. • Twisted structure plays a dominant role comparing with expansion of π-conjugation. • A rule on the design and selection of the fusing unit for PDI-based polymeric acceptors are proposed as reference. [ABSTRACT FROM AUTHOR]

Machine learning methods for damage detection of thermoplastic composite pipes (TCPs) under noise conditions are presented, which combine the random decrement technique (RDT) with random forest (RF) and long and short-term memory (LSTM) networks. RDT is applied first to process the measured noisy strain response data of the TCP under random excitation. Then the RF or LSTM method is used to conduct the damage localization and severity estimation of the pipe. The applicability of the proposed methods is verified by means of numerical and experimental studies. The numerical example consists of a TCP subjected to internal pressure and random wave excitation considering several noise levels. The damages are simulated as circular holes on different layers of the pipe and varying severity, characterized by their radii and depths. The damage detection is carried out using RDT-RF and RDT-LSTM methods. The experimental studies consist of laboratory tests of a TCP model using Fiber Bragg Grating sensors. The damage cases, simulated as cracks with different lengths and depths on the reinforcement layer, are discussed. Both the numerical simulation and experimental tests show that the proposed RDT-RF and RDT-LSTM methods have an excellent performance in damage detection of TCPs. • Propose machine learning methods, RF and LSTM combined with RDT for damage detection of thermoplastic composite pipes. • RDT can remarkably improve the capability of damage detection of RF and LSTM methods under noise conditions. • Validate RDT-RF and RDT-LSTM through the numerical simulation and experimental test of thermoplastic composite pipes. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To investigate the prevalence of depression and anxiety symptoms and their influence factors in women during menopausal transition and postmenopause. Methods: A cross-sectional investigation was conducted with a composed questionnaire on general conditions, social support scoring, the Zung self-evaluating depression and anxiety scoring. All of the parameters were input into a database and analyzed with t-test, χ 2 and logistic regression using SPSS. Results: A total of 1280 women aged 45–59 in Beijing city were interviewed with the questionnaire mentioned above. The prevalence of depression symptoms and anxiety in these women was 306 (23.9%) and 131 (10.2%), respectively. Risk factors associated with depression included strait financial status, social support, dyspareunia and dry vagina, hot flashes and sweating, satisfaction with family, children fail college or job and divorced or separated. Risk factors associated with anxiety included history of premenstrual dysphoric disorder (PMDD), hot flashes, vaginal dryness or dyspareunia and some negative life events. Conclusions: Depression and anxiety were common symptoms in Chinese women during menopausal transition and postmenopause. Some psycho-social factors may play a role in the prevalence of them. [Copyright &y& Elsevier]