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The fast penetration of electrification in rural areas calls for the development of competitive decentralized approaches. A promising solution is represented by low-cost and compact integrated solar flow batteries; however, obtaining high energy conversion performance and long device lifetime simultaneously in these systems has been challenging. Here, we use high-efficiency perovskite/silicon tandem solar cells and redox flow batteries based on robust BTMAP-Vi/N Me -TEMPO redox couples to realize a high-performance and stable solar flow battery device. Numerical analysis methods enable the rational design of both components, achieving an optimal voltage match. These efforts led to a solar-to-output electricity efficiency of 20.1% for solar flow batteries, as well as improved device lifetime, solar power conversion utilization ratio and capacity utilization rate. The conceptual design strategy presented here also suggests general future optimization approaches for integrated solar energy conversion and storage systems. Voltage matching and rational design of redox couples enable high solar-to-output electricity efficiency and extended operational lifetime in a redox flow battery integrated with a perovskite/silicon tandem solar cell.

The development of an efficient, stable, and low-cost hole-transporting material （HTM） is of great significance for perovskite solar cells （PSCs） from future commercialization point of view. Herein, we specifically synthesize a dicationic salt of X60 termed X60（TFSI）2, and adopt it as an effective and stable ＂doping＂ agent to replace the previously used lithium bis（trifluoromethanesulfonyl）imide （LiTFSI） for the low-cost organic HTM X60 in PSCs. The incorporation of this dicationic salt significantly increases the hole conductivity of X60 by two orders of magnitude from 10-6 to 10-4 S cm-1. The dramatic enhancement of the conductivity leads to an impressive power conversion efficiency （PCE） of 19.0% measured at 1 sun illumination （100 mW cm-2, AM 1.5 G）, which is comparable to that of the device doped with LiTFSI （19.3%） under an identical condition. More strikingly, by replacing LiTFSI, the PSC devices incorporating X60（TFSI）2 also show an excellent long-term durability under ambient atmosphere for 30 days, mainly due to the hydrophobic nature of the X60（TFSI）2 doped HTM layer,which can effectively prevent the moisture destroying the perovskite layer. The present work paves the way for the development of highly efficient, stable, and low-cost HTM for potential commercialization of PSCs.

The automated synthesis of small organic molecules from modular building blocks has the potential to transform our capacity to create medicines and materials 1 , 2 – 3 . Disruptive acceleration of this molecule-building strategy broadly unlocks its functional potential and requires the integration of many new assembly chemistries. Although recent advances in high-throughput chemistry 4 , 5 – 6 can speed up the development of appropriate synthetic methods, for example, in selecting appropriate chemical reaction conditions from the vast range of potential options, equivalent high-throughput analytical methods are needed. Here we report a streamlined approach for the rapid, quantitative analysis of chemical reactions by mass spectrometry. The intrinsic fragmentation features of chemical building blocks generalize the analyses of chemical reactions, allowing sub-second readouts of reaction outcomes. Central to this advance was identifying that starting material fragmentation patterns function as universal barcodes for downstream product analysis by mass spectrometry. Combining these features with acoustic droplet ejection mass spectrometry 7 , 8 we could eliminate slow chromatographic steps and continuously evaluate chemical reactions in multiplexed formats. This enabled the assignment of reaction conditions to molecules derived from ultrahigh-throughput chemical synthesis experiments. More generally, these results indicate that fragmentation features inherent to chemical synthesis can empower rapid data-rich experimentation. Mass spectrometry fragmentation patterns define analytical barcodes for the rapid, quantitative analysis of high-throughput chemical synthesis experiments.

Merits and drawbacks of representative inorganic and organic redox active electrolytes used in aqueous redox flow batteries are discussed. Appropriate assessment and reporting methods of the cycling stability of electrolyte materials are recommended. Future directions in developing advanced electrolyte materials are presented. Redox flow batteries represent a viable technology for scalable energy storage. However, widespread market adoption of flow battery technologies is significantly impeded by the lack of robust, low-cost redox active electrolyte materials. In this perspective, we highlight the merits and drawbacks of representative inorganic and organic redox active electrolytes. We also provide a number of research strategies to develop high-performance redox active electrolytes to enable energy dense, durable, low-cost flow battery technologies. Graphical abstract

Ferrocyanide, such as K4[Fe(CN)6], is one of the most popular cathode electrolyte (catholyte) materials in redox flow batteries. However, its chemical stability in alkaline redox flow batteries has been debated. Mechanistic understandings at the molecular level are necessary to elucidate the cycling stability of K4[Fe(CN)6] and its oxidized state (K3[Fe(CN)6]) based electrolytes and guide their proper use in flow batteries for energy storage. Herein, we presented a suite of battery tests and spectroscopic studies to understand the chemical stability of K4[Fe(CN)6] and its charged state, K3[Fe(CN)6], at a variety of conditions. In a strong alkaline solution (pH 14), it was found that the balanced K4[Fe(CN)6]/K3[Fe(CN)6] half-cell experienced a fast capacity decay under dark conditions. Our studies revealed the chemical reduction of K3[Fe(CN)6] by a graphite electrode leads to the charge imbalance in the half-cell cycling and is the major cause of the observed capacity decay. In addition, at pH 14, K3[Fe(CN)6] undergoes a slow CN‒/OH‒ exchange reaction. The dissociated CN‒ ligand can chemically reduce K3[Fe(CN)6] to K4[Fe(CN)6], and it is converted to cyanate (OCN‒) and further, decompose into CO32‒ and NH3. Ultimately, the irreversible chemical conversion of CN‒ to OCN‒ leads to the irreversible decomposition of K4/K3[Fe(CN)6] at pH 14.

Modularized synthesis of small organic molecules is transforming our capacity to create medicines and materials. Disruptive acceleration of this molecule building strategy will broadly unlock its functional potential and requires integration of many new assembly chemistries. Recent advances in high-throughput chemistry stand to enable selection of appropriate chemical reaction conditions from the vast range of potential options. However, a disconnect between the rates of exploration and evaluation has limited progress. Here we report how intrinsic fragmentation features of chemical building blocks generalizes their analysis to yield sub-second readouts of reaction outcomes. Central to this advance was identifying that groups typically attached to boron, nitrogen, and oxygen atoms fragment in a specific and selective manner by mass spectrometry, enabling target agnostic analysis. Combining these features with acoustic droplet ejection mass spectrometry we could eliminate slow chromatographic steps and continuously evaluate chemical reaction outcomes in multiplexed formats. This allowed rapid assignment of reaction conditions to molecules derived from ultra-high throughput chemical synthesis experiments.

Compared with tedious per-pixel mask annotating, it is much easier to annotate data by clicks, which costs only several seconds for an image. However, applying clicks to learn video semantic segmentation model has not been explored before. In this work, we propose an effective weakly-supervised video semantic segmentation pipeline with click annotations, called WeClick, for saving laborious annotating effort by segmenting an instance of the semantic class with only a single click. Since detailed semantic information is not captured by clicks, directly training with click labels leads to poor segmentation predictions. To mitigate this problem, we design a novel memory flow knowledge distillation strategy to exploit temporal information (named memory flow) in abundant unlabeled video frames, by distilling the neighboring predictions to the target frame via estimated motion. Moreover, we adopt vanilla knowledge distillation for model compression. In this case, WeClick learns compact video semantic segmentation models with the low-cost click annotations during the training phase yet achieves real-time and accurate models during the inference period. Experimental results on Cityscapes and Camvid show that WeClick outperforms the state-of-the-art methods, increases performance by 10.24% mIoU than baseline, and achieves real-time execution.

All-inorganic α-CsPbBr x I 3- x perovskites featuring nano-sized crystallites show great potential for pure-red light-emitting diode (LED) applications. Currently, the CsPbBr x I 3– x LEDs based on nano-sized α-CsPbBr x I 3- x crystallites have been fabricated mainly via the classical colloidal route including a tedious procedure of nanocrystal synthesis, purification, ligand or anion exchange, film casting, etc. With the usually adopted conventional LED device structure, only high turn-on voltages (> 2.7) have been achieved for CsPbBr x I 3- x LEDs. Moreover, this mix-halide system may suffer from severe spectra-shift under bias. In this report, CsPbBr x I 3- x thin films featuring nano-sized crystallites are prepared by incorporating multiple ammonium ligands in a one-step spin-coating route. The multiple ammonium ligands constrain the growth of CsPbBr x I 3- x nanograins. Such CsPbBr x I 3- x thin films benefit from quantum confinement. The corresponding CsPbBr x I 3- x LEDs, adopting a conventional LED structure of indium-doped tin oxide (ITO)/poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS)/CsPbBr x I 3- x /[6, 6]-phenyl C61 butyric acid methyl ester (PCBM)/bathocuproine (BCP)/Al, emit pure-red color at Commission Internationale de l’éclairage (CIE) coordinates of (0.709, 0.290), (0.711, 0.289), etc., which represent the highest color-purity for reported pure-red perovskite LEDs and meet the Rec. 2020 requirement at CIE (0.708, 0.292) very well. The CsPbBr x I 3- x LED shows a low turn-on voltage of 1.6 V, maximum external quantum efficiency of 8.94%, high luminance of 2,859 cdm −2 , and good color stability under bias.

The upscaling of perovskite solar cells to module scale and long-term stability have been recognized as the most important challenges for the commercialization of this emerging photovoltaic technology. In a perovskite solar module, each interface within the device contributes to the efficiency and stability of the module. Here, we employed a holistic interface stabilization strategy by modifying all the relevant layers and interfaces, namely the perovskite layer, charge transporting layers and device encapsulation, to improve the efficiency and stability of perovskite solar modules. The treatments were selected for their compatibility with low-temperature scalable processing and the module scribing steps. Our unencapsulated perovskite solar modules achieved a reverse-scan efficiency of 16.6% for a designated area of 22.4 cm 2 . The encapsulated perovskite solar modules, which show efficiencies similar to the unencapsulated one, retained approximately 86% of the initial performance after continuous operation for 2,000 h under AM1.5G light illumination, which translates into a T 90 lifetime (the time over which the device efficiency reduces to 90% of its initial value) of 1,570 h and an estimated T 80 lifetime (the time over which the device efficiency reduces to 80% of its initial value) of 2,680 h. The upscaling of layer treatments and processing that afford high efficiency and stability in small-area perovskite solar cells remains challenging. Liu et al. show how the efficiency and stability of perovskite modules can be improved using an integrated approach to interface and layer engineering.

With the rapid advancement of artificial intelligence (AI) technologies, AI has evolved from an exploratory technology into a critical component of the design process. This study develops an extended model utilizing the Big Five Personality (BFP) framework, the Technology Acceptance Model (TAM), and Perceived Risk Theory (PRT) to examine the influence of BFP traits on Generation Z designers’ willingness to subscribe to paid AI drawing tools. Structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) were employed to analyze data from 477 valid responses. The SEM results demonstrate that Openness (OPE) and Extraversion (EXT) positively affect Perceived Ease of Use (PEU) and Willingness to Pay for Subscription (WPS), while negatively influencing Perceived Risk (PR). EXT and Agreeableness (AGR) enhance Perceived Usefulness (PU). Neuroticism (NEU) adversely affects PU, PEU, and WPS but enhances PR. Moreover, WPS is positively affected by PEU and PU, yet negatively by PR, with PEU, PU, and PR acting as mediators in certain paths. The fsQCA findings exhibit the complex interplay of BFP traits, revealing four configurations that influence WPS among Generation Z designers, distinctly contrasting with the SEM results. This research systematically explores for the first time the impact of personality traits on technology acceptance behaviors among Generation Z designers, contributing theoretical developments and fresh insights into personality psychology and technology acceptance studies. It also offers practical implications for technology development, marketing, education, and human resource management.