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Showing papers by "South China University of Technology published in 2021"


Journal ArticleDOI
TL;DR: The High-Resolution Network (HRNet) as mentioned in this paper maintains high-resolution representations through the whole process by connecting the high-to-low resolution convolution streams in parallel and repeatedly exchanging the information across resolutions.
Abstract: High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection. Existing state-of-the-art frameworks first encode the input image as a low-resolution representation through a subnetwork that is formed by connecting high-to-low resolution convolutions in series (e.g., ResNet, VGGNet), and then recover the high-resolution representation from the encoded low-resolution representation. Instead, our proposed network, named as High-Resolution Network (HRNet), maintains high-resolution representations through the whole process. There are two key characteristics: (i) Connect the high-to-low resolution convolution streams in parallel and (ii) repeatedly exchange the information across resolutions. The benefit is that the resulting representation is semantically richer and spatially more precise. We show the superiority of the proposed HRNet in a wide range of applications, including human pose estimation, semantic segmentation, and object detection, suggesting that the HRNet is a stronger backbone for computer vision problems. All the codes are available at https://github.com/HRNet .

1,162 citations


Journal ArticleDOI
TL;DR: In this article, the authors present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes.
Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

1,129 citations


Proceedings ArticleDOI
23 Aug 2021
TL;DR: Wang et al. as discussed by the authors proposed a strong baseline model SwinIR for image restoration based on the Swin Transformer, which consists of three parts: shallow feature extraction, deep feature extraction and high-quality image reconstruction.
Abstract: Image restoration is a long-standing low-level vision problem that aims to restore high-quality images from low-quality images (e.g., downscaled, noisy and compressed images). While state-of-the-art image restoration methods are based on convolutional neural networks, few attempts have been made with Transformers which show impressive performance on high-level vision tasks. In this paper, we propose a strong baseline model SwinIR for image restoration based on the Swin Transformer. SwinIR consists of three parts: shallow feature extraction, deep feature extraction and high-quality image reconstruction. In particular, the deep feature extraction module is composed of several residual Swin Transformer blocks (RSTB), each of which has several Swin Transformer layers together with a residual connection. We conduct experiments on three representative tasks: image super-resolution (including classical, lightweight and real-world image super-resolution), image denoising (including grayscale and color image denoising) and JPEG compression artifact reduction. Experimental results demonstrate that SwinIR outperforms state-of-the-art methods on different tasks by $\textbf{up to 0.14$\sim$0.45dB}$, while the total number of parameters can be reduced by $\textbf{up to 67%}$.

1,064 citations


Journal ArticleDOI
TL;DR: Li et al. as discussed by the authors showed that branched alkyl chains in non-fullerene acceptors allow favorable morphology in the active layer, enabling a certified device efficiency of 17.32% with a fill factor of 81.5% for single-junction organic solar cells.
Abstract: Molecular design of non-fullerene acceptors is of vital importance for high-efficiency organic solar cells. The branched alkyl chain modification is often regarded as a counter-intuitive approach, as it may introduce an undesirable steric hindrance that reduces charge transport in non-fullerene acceptors. Here we show the design and synthesis of a highly efficient non-fullerene acceptor family by substituting the beta position of the thiophene unit on a Y6-based dithienothiophen[3,2-b]-pyrrolobenzothiadiazole core with branched alkyl chains. It was found that such a modification to a different alkyl chain length could completely change the molecular packing behaviour of non-fullerene acceptors, leading to improved structural order and charge transport in thin films. An unprecedented efficiency of 18.32% (certified value of 17.9%) with a fill factor of 81.5% is achieved for single-junction organic solar cells. This work reveals the importance of the branched alkyl chain topology in tuning the molecular packing and blend morphology, which leads to improved organic photovoltaic performance. Molecular design of acceptor and donor molecules has enabled major progress in organic photovoltaics. Li et al. show that branched alkyl chains in non-fullerene acceptors allow favourable morphology in the active layer, enabling a certified device efficiency of 17.9%.

966 citations


Journal ArticleDOI
TL;DR: A survey on recent advances of image super-resolution techniques using deep learning approaches in a systematic way, which can roughly group the existing studies of SR techniques into three major categories: supervised SR, unsupervised SR, and domain-specific SR.
Abstract: Image Super-Resolution (SR) is an important class of image processing techniqueso enhance the resolution of images and videos in computer vision. Recent years have witnessed remarkable progress of image super-resolution using deep learning techniques. This article aims to provide a comprehensive survey on recent advances of image super-resolution using deep learning approaches. In general, we can roughly group the existing studies of SR techniques into three major categories: supervised SR, unsupervised SR, and domain-specific SR. In addition, we also cover some other important issues, such as publicly available benchmark datasets and performance evaluation metrics. Finally, we conclude this survey by highlighting several future directions and open issues which should be further addressed by the community in the future.

837 citations


Journal ArticleDOI
21 Jan 2021-Cell
TL;DR: A comprehensive picture of the HCC ecosystem provides deeper insights into immune evasion mechanisms associated with tumor relapse, including those that dampen DC antigen presentation and recruit innate-like CD8+ T cells.

282 citations


Journal ArticleDOI
TL;DR: In this paper, a novel non-fullerene acceptor L8-BO-F is designed and incorporated into the PM6:BTP-eC9 blend, which shows complementary absorption spectra and cascade energy alignment.
Abstract: The ternary strategy, introducing a third component into a binary blend, opens a simple and promising avenue to improve the power conversion efficiency (PCE) of organic solar cells (OSCs). The judicious selection of an appropriate third component, without sacrificing the photocurrent and voltage output of the OSC, is of significant importance in ternary devices. Herein, highly efficient OSCs fabricated using a ternary approach are demonstrated, wherein a novel non-fullerene acceptor L8-BO-F is designed and incorporated into the PM6:BTP-eC9 blend. The three components show complementary absorption spectra and cascade energy alignment. L8-BO-F and BTP-eC9 are found to form a homogeneous mixed phase, which improves the molecular packing of both the donor and acceptor materials, and optimizes the ternary blend morphology. Moreover, the addition of L8-BO-F into the binary blend suppresses the non-radiative recombination, thus leading to a reduced voltage loss. Consequently, concurrent increases in open-circuit voltage, short-circuit current, and fill factor are realized, resulting in an unprecedented PCE of 18.66% (certified value of 18.2%), which represents the highest efficiency values reported for both single-junction and tandem OSCs so far.

279 citations


Journal ArticleDOI
TL;DR: In this paper, a stretchable conductor is fabricated by simply coating or printing liquid metal onto an electrospun elastomeric fiber mat, which self-organizes into a laterally mesh-like and vertically buckled structure, which offers simultaneously high permeability, stretchability, conductivity and electrical stability.
Abstract: Stretchable electronics find widespread uses in a variety of applications such as wearable electronics, on-skin electronics, soft robotics and bioelectronics. Stretchable electronic devices conventionally built with elastomeric thin films show a lack of permeability, which not only impedes wearing comfort and creates skin inflammation over long-term wearing but also limits the design form factors of device integration in the vertical direction. Here, we report a stretchable conductor that is fabricated by simply coating or printing liquid metal onto an electrospun elastomeric fibre mat. We call this stretchable conductor a liquid-metal fibre mat. Liquid metal hanging among the elastomeric fibres self-organizes into a laterally mesh-like and vertically buckled structure, which offers simultaneously high permeability, stretchability, conductivity and electrical stability. Furthermore, the liquid-metal fibre mat shows good biocompatibility and smart adaptiveness to omnidirectional stretching over 1,800% strain. We demonstrate the use of a liquid-metal fibre mat as a building block to realize highly permeable, multifunctional monolithic stretchable electronics.

271 citations


Journal ArticleDOI
TL;DR: In this paper, a comprehensive review of all-inorganic/organicinorganic hybrid metal halides is presented, focusing on the self-trapped excitons (STEs) model and PL regulation engineering.
Abstract: Zero-dimensional (0D) all-inorganic/organic-inorganic metal halides, as emerging luminescent materials, have attracted unparalleled interest from versatile perspectives due to their unique crystallographic/electronic structures with isolated building units and fascinating optical characteristics. However, significant challenges still exist for 0D metal halides, including their chemical molecular design, photoluminescence (PL) mechanism, PL modification and applications. In this review, we summarize the 0D metal halides through the classification of all-inorganic and organic-inorganic hybrid metal halides, and further emphasize the unique role of B-site cations with different electronic configurations in the PL process. Furthermore, the PL mechanisms focusing on the self-trapped excitons (STEs) model and PL regulation engineering are examined to explore their extraordinary PL properties and further reveal new application prospects. This review aims to provide in-depth insight into the structure-luminescence-application relationship of 0D metal halides and pave the way for the realization of next-generation high-performance luminescent materials.

254 citations


Journal ArticleDOI
TL;DR: A comprehensive review of the recent progress in hot exciton materials, which can effectively harness the non-radiative triplet excitons via reverse intersystem crossing (RISC) from high-lying triplet states to singlet states.
Abstract: According to Kasha's rule, high-lying excited states usually have little effect on fluorescence. However, in some molecular systems, the high-lying excited states partly or even mainly contribute to the photophysical properties, especially in the process of harvesting triplet excitons in organic electroluminescent devices. In the current review, we focus on a type of organic light-emitting diode (OLED) materials called “hot exciton” materials, which can effectively harness the non-radiative triplet excitons via reverse intersystem crossing (RISC) from high-lying triplet states to singlet states (Tn → Sm; n ≥ 2, m ≥ 1). Since Ma and Yang proposed the hot exciton mechanism for OLED material design in 2012, there have been many reports aiming at the design and synthesis of novel hot exciton luminogens. Herein, we present a comprehensive review of the recent progress in hot exciton materials. The developments of the hot exciton mechanism are reviewed, the fundamental principles regarding molecular design are discussed, and representative reported hot exciton luminogens are summarized and analyzed, along with their structure–property relationships and OLED applications.

251 citations


Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper fabricated a waterproof and breathable smart textile by construction of a multiple core-shell structure, i.e., MXene decoration onto the polydopamine (PDA) modified elastic textile followed by polydimethylsiloxane (PDMS) coating.

Journal ArticleDOI
TL;DR: A so-called DP-CRNN algorithm is developed with a newly designed neural network structure, to extract and highlight the combination of semantic and sequential features in terms of patient's inquiries in order to deal with the situation that patients’ online inquiries are usually not very long.
Abstract: The rapidly developed Health 2.0 technology has provided people with more opportunities to conduct online medical consultation than ever before. Understanding contexts within different online medical communications and activities becomes a significant issue to facilitate patients’ medical decision making process. As a subcategory of machine learning, neural networks have drawn increasing attentions in natural language processing applications. In this article, we focus on modeling and analyzing the patient-physician-generated data based on an integrated CNN-RNN framework, in order to deal with the situation that patients’ online inquiries are usually not very long. A so-called DP-CRNN algorithm is developed with a newly designed neural network structure, to extract and highlight the combination of semantic and sequential features in terms of patient's inquiries. An intelligent recommendation method is then proposed to provide patients with automatic clinic guidance and pre-diagnosis suggestions, in which a clustering mechanism is utilized to refine the learning process with more precise diagnosis scope and more representative features. Experiments based on the collected real world data demonstrate the effectiveness of our proposed model and method for intelligent pre-diagnosis service in online medical environments.

Journal ArticleDOI
TL;DR: A new framework for rotor-bearing system fault diagnosis under varying working conditions is proposed by using modified convolutional neural network (CNN) with transfer learning, which outperforms other cutting edge methods in fault diagnosis of rotor- bearing system.
Abstract: The existing intelligent fault diagnosis methods of rotor-bearing system mainly focus on vibration analysis under steady operation, which has low adaptability to new scenes In this article, a new framework for rotor-bearing system fault diagnosis under varying working conditions is proposed by using modified convolutional neural network (CNN) with transfer learning First, infrared thermal images are collected and used to characterize the health condition of rotor-bearing system Second, modified CNN is developed by introducing stochastic pooling and Leaky rectified linear unit to overcome the training problems in classical CNN Finally, parameter transfer is used to enable the source modified CNN to adapt to the target domain, which solves the problem of limited available training data in the target domain The proposed method is applied to analyze thermal images of rotor-bearing system collected under different working conditions The results show that the proposed method outperforms other cutting edge methods in fault diagnosis of rotor-bearing system

Journal ArticleDOI
TL;DR: In this article, a synergetic dual-additive strategy is adopted to prepare perovskite films with low defect density and high environmental stability by using 18-crown-6 and poly(ethylene glycol) methyl ether acrylate (MPEG-MAA) as the additives.
Abstract: Quasi-2D perovskites have long been considered to have favorable "energy funnel/cascade" structures and excellent optical properties compared with their 3D counterparts. However, most quasi-2D perovskite light-emitting diodes (PeLEDs) exhibit high external quantum efficiency (EQE) but unsatisfactory operating stability due to Auger recombination induced by high current density. Herein, a synergetic dual-additive strategy is adopted to prepare perovskite films with low defect density and high environmental stability by using 18-crown-6 and poly(ethylene glycol) methyl ether acrylate (MPEG-MAA) as the additives. The dual additives containing COC bonds can not only effectively reduce the perovskite defects but also destroy the self-aggregation of organic ligands, inducing the formation of perovskite nanocrystals with quasi-core/shell structure. After thermal annealing, the MPEG-MAA with its CC bond can be polymerized to obtain a comb-like polymer, further protecting the passivated perovskite nanocrystals against water and oxygen. Finally, state-of-the-art green PeLEDs with a normal EQE of 25.2% and a maximum EQE of 28.1% are achieved, and the operating lifetime (T50 ) of the device in air environment is over ten times increased, providing a novel and effective strategy to make high efficiency and long operating lifetime PeLEDs.

Journal ArticleDOI
TL;DR: New insight is provided into constructing highly efficient ternary OPVs with well compatible Y6 and its derivative as acceptor and the JSC and FF improvement of ternARY OPVs should be ascribed to comprehensively optimal photon harvesting, exciton dissociation and charge transport in Ternary active layers.
Abstract: A series of ternary organic photovoltaics (OPVs) are fabricated with one wide bandgap polymer D18-Cl as donor, and well compatible Y6 and Y6-1O as acceptor. The open-circuit-voltage (VOC ) of ternary OPVs is monotonously increased along with the incorporation of Y6-1O, indicating that the alloy state should be formed between Y6 and Y6-1O due to their excellent compatibility. The energy loss can be minimized by incorporating Y6-1O, leading to the VOC improvement of ternary OPVs. By finely adjusting the Y6-1O content, a power conversion efficiency of 17.91% is achieved in the optimal ternary OPVs with 30 wt% Y6-1O in acceptors, resulting from synchronously improved short-circuit-current density (JSC ) of 25.87 mA cm-2, fill factor (FF) of 76.92% and VOC of 0.900 V in comparison with those of D18-Cl : Y6 binary OPVs. The JSC and FF improvement of ternary OPVs should be ascribed to comprehensively optimal photon harvesting, exciton dissociation and charge transport in ternary active layers. The more efficient charge separation and transport process in ternary active layers can be confirmed by the magneto-photocurrent and impedance spectroscopy experimental results, respectively. This work provides new insight into constructing highly efficient ternary OPVs with well compatible Y6 and its derivative as acceptor.

Journal ArticleDOI
TL;DR: In this article, the adaptive dynamic programming (ADP) with applications in control is reviewed, and the use of ADP to solve game problems, mainly nonzero-sum game problems is elaborated.
Abstract: This article reviews the recent development of adaptive dynamic programming (ADP) with applications in control. First, its applications in optimal regulation are introduced, and some skilled and efficient algorithms are presented. Next, the use of ADP to solve game problems, mainly nonzero-sum game problems, is elaborated. It is followed by applications in large-scale systems. Note that although the functions presented in this article are based on continuous-time systems, various applications of ADP in discrete-time systems are also analyzed. Moreover, in each section, not only some existing techniques are discussed, but also possible directions for future work are pointed out. Finally, some overall prospects for the future are given, followed by conclusions of this article. Through a comprehensive and complete investigation of its applications in many existing fields, this article fully demonstrates that the ADP intelligent control method is promising in today’s artificial intelligence era. Furthermore, it also plays a significant role in promoting economic and social development.


Journal ArticleDOI
TL;DR: The results indicate that less urbanized districts were generally more sensitive to the synergies, and stronger HW-UHI synergies indicate the necessity to develop specific urban heat emergency response plans, able to capture and intervene on the underlying mechanisms.

Journal ArticleDOI
TL;DR: In this article, a dimensionally graded perovskite formation approach was proposed to reduce the photovoltage loss through the simultaneous passivation of internal bulk defects and dimensional graded two-dimensional pervskite interface defects.
Abstract: Metal halide perovskite solar cells have demonstrated a high power conversion efficiency (PCE), and further enhancement of the PCE requires a reduction of the bandgap-voltage offset (WOC) and the non-radiative recombination photovoltage loss (ΔVOC,nr). Here, we report an effective approach for reducing the photovoltage loss through the simultaneous passivation of internal bulk defects and dimensionally graded two-dimensional perovskite interface defects. Through this dimensionally graded perovskite formation approach, an open-circuit voltage (VOC) of 1.24 V was obtained with a champion PCE of 21.54% in a 1.63 eV perovskite system (maximum VOC = 1.25 V, WOC = 0.38 V and ΔVOC,nr = 0.10 V); we further decreased the WOC to 0.326 V in a 1.53 eV perovskite system with a VOC of 1.21 V and a PCE of 23.78% (certified 23.09%). This approach is equally effective in achieving a low WOC (ΔVOC,nr) in 1.56 eV and 1.73 eV perovskite solar cell systems, and further leads to the substantially improved operational stability of perovskite solar cells. The use of a dimensionally graded 2D perovskite interface and passivation results in perovskite solar cells with very low photovoltage loss.

Journal ArticleDOI
TL;DR: This review summarizes the recent advances of AIE light-up probes for PDT and discusses the strategies and principles to design AIE photosensitizers and light- up probes in photodynamic antitumor and antibacterial applications.
Abstract: As a new non-invasive treatment method, photodynamic therapy (PDT) has attracted great attention in biomedical applications. The advantages of possessing fluorescence for photosensitizers have made it possible to combine imaging and diagnosis together with PDT. The unique features of aggregation-induced emission (AIE) fluorogens provide new opportunities for facile design of light-up probes with high signal-to-noise ratios and improved theranostic accuracy and efficacy for image-guided PDT. In this review, we summarize the recent advances of AIE light-up probes for PDT. The strategies and principles to design AIE photosensitizers and light-up probes are firstly introduced. The application of AIE light-up probes in photodynamic antitumor and antibacterial applications is further elaborated in detail, from binding/targeting-mediated, reaction-mediated, and external stimuli-mediated light-up aspects. The challenges and future perspectives of AIE light-up probes in the PDT field are also presented with the hope to encourage more promising developments of AIE materials for phototheranostic applications and translational research.

Journal ArticleDOI
TL;DR: In this paper, a kind of multifunctional ionogels with a combination of desirable properties, including transparency, high stretchability, solvent and temperature resistance, recyclability, high conductivity, underwater self-healing ability, and underwater adhesiveness is reported.
Abstract: Ionogels have gained increasing attentions as a flexible conductive material. However, it remains a big challenge to integrate multiple functions into one gel that can be widely applied in various complex scenes. Herein, a kind of multifunctional ionogels with a combination of desirable properties, including transparency, high stretchability, solvent and temperature resistance, recyclability, high conductivity, underwater self-healing ability, and underwater adhesiveness is reported. The ionogels are prepared via one-step photoinitiated polymerization of 2,2,2-trifluoroethyl acrylate and acrylamide in a hydrophobic ionic liquid. The abundant noncovalent interactions including hydrogen bonding and ion-dipole interactions endow the ionogels with excellent mechanical strength, resilience, and rapid self-healing capability at room temperature, while the fluorine-rich polymeric matrix brings in high tolerance against water and various organic solvents, as well as tough underwater adhesion on different substrates. Wearable strain sensors based on the ionogels can sensitively detect and differentiate large body motions, such as bending of limbs, walking and jumping, as well as subtle muscle movements, such as pronunciation and pulse. It is believed that the designed ionogels will show great promises in wearable devices and ionotronics.

Journal ArticleDOI
TL;DR: In this article, an intelligent reflecting surface (IRS) is employed to enhance the performance of UAV-aided air-ground networks, where the UAV trajectory, the transmit beamforming and the RIS passive beamforming are jointly optimized.
Abstract: Thanks to their flexibility and mobility, unmanned aerial vehicles (UAVs) have been widely applied in wireless networks. However, UAV communications may suffer from blockage and eavesdropping in practical scenarios due to the complex environment. Taking the recent advances in intelligent reflecting surface (IRS) to reconfigure the propagation environments, in this article, we employ IRS to enhance the performance of UAV-aided air-ground networks. First, we overview the combination of UAV and IRS, by introducing the diverse applications of IRS and the appealing advantages of UAV, and highlighting the benefits of combining them. Then, we investigate two case studies where the UAV trajectory, the transmit beamforming and the IRS passive beamforming are jointly optimized. In the first case study, by equipping the IRS on a UAV, the average achievable rate of the relaying network is maximized. In the second one, the IRS is deployed to assist the UAV-ground communication while combating the adversarial eavesdropper. Simulation results are provided to demonstrate the performance enhancement resulting from combining UAV and IRS in air-ground networks. Finally, we shed light on some challenging issues to be resolved for practical implementations in this direction.

Journal ArticleDOI
26 Jan 2021-ACS Nano
TL;DR: This assay involves confining the RNA-triggered Cas13a catalysis system in cell-like-sized reactors to enhance local concentrations of target and reporter simultaneously, via droplet microfluidics, and achieves >10 000-fold enhancement in sensitivity when compared to the bulk Cas 13a assay and enables absolute digital single-molecule RNA quantitation.
Abstract: Existing methods for RNA diagnostics, such as reverse transcription PCR (RT-PCR), mainly rely on nucleic acid amplification (NAA) and RT processes, which are known to introduce substantial issues, including amplification bias, cross-contamination, and sample loss. To address these problems, we introduce a confinement effect-inspired Cas13a assay for single-molecule RNA diagnostics, eliminating the need for NAA and RT. This assay involves confining the RNA-triggered Cas13a catalysis system in cell-like-sized reactors to enhance local concentrations of target and reporter simultaneously, via droplet microfluidics. It achieves >10 000-fold enhancement in sensitivity when compared to the bulk Cas13a assay and enables absolute digital single-molecule RNA quantitation. We experimentally demonstrate its broad applicability for precisely counting microRNAs, 16S rRNAs, and SARS-CoV-2 RNA from synthetic sequences to clinical samples with excellent accuracy. Notably, this direct RNA diagnostic technology enables detecting a wide range of RNA molecules at the single-molecule level. Moreover, its simplicity, universality, and excellent quantification capability might render it to be a dominant rival to RT-qPCR.

Journal ArticleDOI
TL;DR: In this article, a comprehensive summary of the recent progress in the field of the electrochemical nitrogen reduction reaction and related catalysts is provided, including the operational procedures of the E-NRR, the acquisition of key metrics, the challenges faced, and the most suitable solutions.
Abstract: The electrochemical method of combining N2 and H2 O to produce ammonia (i.e., the electrochemical nitrogen reduction reaction [E-NRR]) continues to draw attention as it is both environmentally friendly and well suited for a progressively distributed farm economy. Despite the multitude of recent works on the E-NRR, further progress in this field faces a bottleneck. On the one hand, despite the extensive exploration and trial-and-error evaluation of E-NRR catalysts, no study has stood out to become the stage protagonist. On the other hand, the current level of ammonia production (microgram-scale) is an almost insurmountable obstacle for its qualitative and quantitative determination, hindering the discrimination between true activity and contamination. Herein i) the popular theory and mechanism of the NRR are introduced; ii) a comprehensive summary of the recent progress in the field of the E-NRR and related catalysts is provided; iii) the operational procedures of the E-NRR are addressed, including the acquisition of key metrics, the challenges faced, and the most suitable solutions; iv) the guiding principles and standardized recommendations for the E-NRR are emphasized and future research directions and prospects are provided.

Journal ArticleDOI
TL;DR: In this paper, a semi-asynchronous federated learning (SAFA) protocol is proposed to mitigate the impacts of straggglers, crashes and model staleness in order to boost efficiency and improve the quality of the global model.
Abstract: Federated learning (FL) has attracted increasing attention as a promising approach to driving a vast number of end devices with artificial intelligence. However, it is very challenging to guarantee the efficiency of FL considering the unreliable nature of end devices while the cost of device-server communication cannot be neglected. In this article, we propose SAFA, a semi-asynchronous FL protocol, to address the problems in federated learning such as low round efficiency and poor convergence rate in extreme conditions (e.g., clients dropping offline frequently). We introduce novel designs in the steps of model distribution, client selection and global aggregation to mitigate the impacts of stragglers, crashes and model staleness in order to boost efficiency and improve the quality of the global model. We have conducted extensive experiments with typical machine learning tasks. The results demonstrate that the proposed protocol is effective in terms of shortening federated round duration, reducing local resource wastage, and improving the accuracy of the global model at an acceptable communication cost.

Journal ArticleDOI
20 Jan 2021-Joule
TL;DR: In this paper, the authors proposed DTB-FL, a low-cost and efficient hole transport materials (HTM) for the commercialization of perovskite solar cells (PSCs), featuring facile synthesis and excellent optoelectronic properties.

Journal ArticleDOI
TL;DR: In this paper, a MOF-in-COF concept was proposed for the confined growth of metal-organic framework (MOFs) inside a supported COF layer to prepare MOF in COF membranes, which exhibited an excellent hydrogen permeance (>3000 GPU) together with a significant enhancement of hydrogen over other gases.
Abstract: Covalent organic frameworks (COFs) are promising materials for advanced molecular-separation membranes, but their wide nanometer-sized pores prevent selective gas separation through molecular sieving. Herein, we propose a MOF-in-COF concept for the confined growth of metal-organic framework (MOFs) inside a supported COF layer to prepare MOF-in-COF membranes. These membranes feature a unique MOF-in-COF micro/nanopore network, presumably due to the formation of MOFs as a pearl string-like chain of unit cells in the 1D channel of 2D COFs. The MOF-in-COF membranes exhibit an excellent hydrogen permeance (>3000 GPU) together with a significant enhancement of separation selectivity of hydrogen over other gases. The superior separation performance for H2/CO2 and H2/CH4 surpasses the Robeson upper bounds, benefiting from the synergy combining precise size sieving and fast molecular transport through the MOF-in-COF channels. The synthesis of different combinations of MOFs and COFs in robust MOF-in-COF membranes demonstrates the versatility of our design strategy.

Journal ArticleDOI
TL;DR: The mechanisms and beneficial roles of these strategies in intracellular Cas9 RNP delivery were reviewed and examples in the development of stimuli-responsive and targeted carriers for R NP delivery are highlighted.
Abstract: CRISPR/Cas9 genome editing has gained rapidly increasing attentions in recent years, however, the translation of this biotechnology into therapy has been hindered by efficient delivery of CRISPR/Cas9 materials into target cells. Direct delivery of CRISPR/Cas9 system as a ribonucleoprotein (RNP) complex consisting of Cas9 protein and single guide RNA (sgRNA) has emerged as a powerful and widespread method for genome editing due to its advantages of transient genome editing and reduced off-target effects. In this review, we summarized the current Cas9 RNP delivery systems including physical approaches and synthetic carriers. The mechanisms and beneficial roles of these strategies in intracellular Cas9 RNP delivery were reviewed. Examples in the development of stimuli-responsive and targeted carriers for RNP delivery are highlighted. Finally, the challenges of current Cas9 RNP delivery systems and perspectives in rational design of next generation materials for this promising field will be discussed.

Journal ArticleDOI
TL;DR: In this article, asymmetric side-chain engineering can effectively tune the properties of NFSMAs and improve the power conversion efficiency (PCE) for binary non-fullerene polymer solar cells.
Abstract: Side-chain engineering has been considered as one of the most promising strategies to optimize non-fullerene small-molecule acceptors (NFSMAs). Previous efforts were focused on the optimization of alkyl-chain length, shape, and branching sites. In this work, we propose that asymmetric side-chain engineering can effectively tune the properties of NFSMAs and improve the power conversion efficiency (PCE) for binary non-fullerene polymer solar cells (NFPSCs). Specifically, by introducing asymmetric side chains into the central core, both of the absorption spectra and molecule orientation of NFSMAs are efficiently tuned. When blended with polymer donor PM6, NFPSCs with EH-HD-4F (2-ethylhexyl and 2-hexyldecyl side chains) demonstrate a champion PCE of 18.38% with a short-circuit current density (JSC) of 27.48 mA cm−2, an open circuit voltage (VOC) of 0.84 V, and a fill factor (FF) of 0.79. Further studies manifest that the proper asymmetric side chains in NFSMAs could induce more favorable face-on molecule orientation, enhance carrier mobilities, balance charge transport, and reduce recombination losses.

Journal ArticleDOI
TL;DR: In this paper, the authors developed nitrogen-doped fluorescent carbon dots (NCDs) as a multi-mechanism detection for iodide and curcumin in actual complex biological and food samples, which was prepared by a one-step solid phase synthesis using tartaric acid and urea as precursors without adding any other reagents.