Soft-hard zwitterionic additives for aqueous halide flow batteries.

Aqueous redox flow batteries with halide-based catholytes (where the halogen atom (X) is Br or I) are promising for sustainable grid energy storage. However, the formation of polyhalides during electrochemical charging and the associated phase separation into X2 limits the operable state of charge (SoC), results in vaporization and self-discharge inefficiencies, and spurs complete device failure1-3. Here we introduce soft-hard zwitterionic trappers (SH-ZITs) as complexing agents composed of a polyhalide-complexing 'soft' cationic motif and a water-soluble 'hard' anionic motif to enable homogeneous halide cycling. More than 300 structures were designed and 13 were characterized, showcasing the ability to complex polyhalides in homogeneous aqueous solution, to deter cation-exchange membrane crossover and to alter the electrochemical electrode mechanism. In flow battery cycling at a standard catholyte SoC of 66.6 per cent (stoichiometrically X3-), an average coulombic efficiency of more than 99.9 per cent at 40 milliamperes per square centimetre with no apparent decay was observed after more than 1,000 cycles over 2 months, with stability at elevated temperatures also demonstrated. Interestingly, SH-ZITs enable homogeneous cycling of the halide catholyte up to 90 per cent SoC at 2 moles per litre (47.7 ampere-hours per litre) for bromide, revealing previously unknown polyhalide regimes to be studied. Ultimately, SH-ZIT enables ultrahigh catholyte capacity utilization up to over 120 ampere-hours per litre at 80 per cent SoC with homogeneous cycling as well as the ability to pair with a zinc anode in a hybrid flow battery.

Ion transport mechanisms in covalent organic frameworks: implications for technology.

Covalent organic frameworks (COFs) have emerged as promising materials for ion conduction due to their highly tunable structures and excellent electrochemical stability. This review paper explores the mechanisms of ion conduction in COFs, focusing on how these materials facilitate ion transport across their ordered structures, which is crucial for applications such as solid electrolytes in batteries and fuel cells. We discuss the design strategies employed to enhance ion conductivity, including pore size optimization, functionalization with ionic groups, and the incorporation of solvent molecules and salts. Additionally, we examine the various applications of ion-conductive COFs, particularly in energy storage and conversion technologies, highlighting recent advancements and future directions in this field. This review paper aims to provide a comprehensive overview of the current state of research on ion-conductive COFs, offering insights into their potential to design highly ion-conductive COFs considering not only fundamental studies but also practical perspectives for advanced electrochemical devices.

Poly(2-vinylpyridine)/MCM-41 Composites with Micropores and Switchable Mesopores for the Removal of Cr(VI).

Porous structure design and reversible regulation of pore size during adsorption-desorption are crucial to the removal of pollutants in water such as Cr(VI). In this paper, micropores and switchable mesopores were constructed on MCM-41 to further improve adsorption-desorption performance of Cr(VI) via the confinement effect of micropores and opening and closing of mesopores. 2-Vinylpyridine was introduced and polymerized into the pores and on the pore mouth of MCM41 modified by C═C group (AM41) under the irradiation of ultraviolet light. The obtained samples (PM41) possessed mesopores (2.73 nm) and micropores (1.36 nm), where mesopores could open or close under different pH and micropores showed the confinement effect because their pore size is close to Cr(VI) diameter (0.87 nm). Compared with MCM-41, the introduction of poly(2-vinylpyridine) enhanced obviously its adsorptive ability and it trapped most of the Cr(VI) (99%) in solution, 12 times higher than that of the parent sample. The change of pore size is favorable to the cycle performance, and after 3 times recycling, the removal rate of Cr(VI) by PM41-20 remained above 88%. Langmuir isotherm showed a better data correlation than the Freundlich model. Cr(VI) in solution was removed by electrostatic interaction between the pyridine group and Cr(VI) and the confinement effect from micropores.

The impact of household wealth gap on individual's mental health.

BACKGROUND: Improving the individual's mental health is important for sustainable economic and social development. Although some studies found that household wealth gap may affect individuals' mental health, few studies have clarified the causal relationship between household wealth gap between mental health in China. This study examines the impact of the household wealth gap on individuals' mental health using data from the 2012-2018 China Family Panel Survey. METHODS: This study first used the two-way fixed effects model to investigate the impact of household wealth gap on individuals' mental health. Considering the endogeneity, the two-stage least square and propensity score matching were employed to examine the impact of household wealth inequality on individuals' mental health. RESULTS: The results show that the household wealth gap has negative impact on individuals' mental health. A series of robustness tests support this conclusion. The results of heterogeneity analysis show that the impact of household wealth gap on mental health is more pronounced among middle-aged and elderly individuals, residents with lower education levels, and rural residents. The results of the mechanism analysis suggest that the household wealth gap may affect individuals' mental health by influencing the individual's health insurance investment and neighborhood relations. In addition, the household wealth gap not only significantly negatively affects individuals' mental health in the short term but also in the medium- to long-term. CONCLUSION: These findings suggest that the government should take various measures to narrow the wealth inequality between families, which may effectively improve the mental health of residents.

Self-supervised learning-based underwater acoustical signal classification via mask modeling.

The classification of underwater acoustic signals has garnered a great deal of attention in recent years due to its potential applications in military and civilian contexts. While deep neural networks have emerged as the preferred method for this task, the representation of the signals plays a crucial role in determining the performance of the classification. However, the representation of underwater acoustic signals remains an under-explored area. In addition, the annotation of large-scale datasets for the training of deep networks is a challenging and expensive task. To tackle these challenges, we propose a novel self-supervised representation learning method for underwater acoustic signal classification. Our approach consists of two stages: a pretext learning stage using unlabeled data and a downstream fine-tuning stage using a small amount of labeled data. The pretext learning stage involves randomly masking the log Mel spectrogram and reconstructing the masked part using the Swin Transformer architecture. This allows us to learn a general representation of the acoustic signal. Our method achieves a classification accuracy of 80.22% on the DeepShip dataset, outperforming or matching previous competitive methods. Furthermore, our classification method demonstrates good performance in low signal-to-noise ratio or few-shot settings.

Operando Elucidation of Electrocatalytic and Redox Mechanisms on a 2D Metal Organic Framework Catalyst for Efficient Electrosynthesis of Hydrogen Peroxide in Neutral Media.

The practical electrosynthesis of hydrogen peroxide (H2O2) is hindered by the lack of inexpensive and efficient catalysts for the two-electron oxygen reduction reaction (2e- ORR) in neutral electrolytes. Here, we show that Ni3HAB2 (HAB = hexaaminobenzene), a two-dimensional metal organic framework (MOF), is a selective and active 2e- ORR catalyst in buffered neutral electrolytes with a linker-based redox feature that dynamically affects the ORR behaviors. Rotating ring-disk electrode measurements reveal that Ni3HAB2 has high selectivity for 2e- ORR (>80% at 0.6 V vs RHE) but lower Faradaic efficiency due to this linker redox process. Operando X-ray absorption spectroscopy measurements reveal that under argon gas the charging of the organic linkers causes a dynamic Ni oxidation state, but in O2-saturated conditions, the electronic and physical structures of Ni3HAB2 change little and oxygen-containing species strongly adsorb at potentials more cathodic than the reduction potential of the organic linker (Eredox ∼ 0.3 V vs RHE). We hypothesize that a primary 2e- ORR mechanism occurs directly on the organic linkers (rather than the Ni) when E > Eredox, but when E < Eredox, H2O2 production can also occur through Ni-mediated linker discharge. By operating the bulk electrosynthesis at a low overpotential (0.4 V vs RHE), up to 662 ppm of H2O2 can be produced in a buffered neutral solution in an H-cell due to minimized strong adsorption of oxygenates. This work demonstrates the potential of conductive MOF catalysts for 2e- ORR and the importance of understanding catalytic active sites under electrochemical operation.

The effect of venture capital on green innovation: Is environmental regulation an institutional guarantee?

Venture capital (VC) may play a role in urban green innovation (GI) by providing long-term financial support. Based on panel data from 150 cities in China, this study analyzes the impact of VC on urban GI and the underlying mechanism. The research conclusions are as follows. VC significantly promotes urban GI, and we find micro-level evidence for this conclusion. The results of a quantile regression show that with an improvement in a city's GI level, the positive effect of VC shows an increasing trend. A mechanism analysis shows that VC promotes urban GI by enhancing urban investment and innovative talent agglomeration and that the accumulation of high-quality human capital brought by VC is the main reason for its positive impact on urban GI. In addition, the influence of VC on urban GI exhibits a threshold effect based on environmental regulations. There is an optimal range of environmental regulation intensity that maximizes the effect of VC on GI. This study confirms the important role of VC in regional GI activities, enriching the research on the innovation effect of VC and providing a theoretical and practical reference for promoting green economic development.

A Porphyrinic Zirconium Metal-Organic Framework for Oxygen Reduction Reaction: Tailoring the Spacing between Active-Sites through Chain-Based Inorganic Building Units.

The oxygen reduction reaction (ORR) is central in carbon-neutral energy devices. While platinum group materials have shown high activities for ORR, their practical uses are hampered by concerns over deactivation, slow kinetics, exorbitant cost, and scarce nature reserve. The low cost yet high tunability of metal-organic frameworks (MOFs) provide a unique platform for tailoring their characteristic properties as new electrocatalysts. Herein, we report a new concept of design and present stable Zr-chain-based MOFs as efficient electrocatalysts for ORR. The strategy is based on using Zr-chains to promote high chemical and redox stability and, more importantly, tailor the immobilization and packing of redox active-sites at a density that is ideal to improve the reaction kinetics. The obtained new electrocatalyst, PCN-226, thereby shows high ORR activity. We further demonstrate PCN-226 as a promising electrode material for practical applications in rechargeable Zn-air batteries, with a high peak power density of 133 mW cm-2. Being one of the very few electrocatalytic MOFs for ORR, this work provides a new concept by designing chain-based structures to enrich the diversity of efficient electrocatalysts and MOFs.

Multistructure-Based Collaborative Online Distillation.

Recently, deep learning has achieved state-of-the-art performance in more aspects than traditional shallow architecture-based machine-learning methods. However, in order to achieve higher accuracy, it is usually necessary to extend the network depth or ensemble the results of different neural networks. Increasing network depth or ensembling different networks increases the demand for memory resources and computing resources. This leads to difficulties in deploying depth-learning models in resource-constrained scenarios such as drones, mobile phones, and autonomous driving. Improving network performance without expanding the network scale has become a hot topic for research. In this paper, we propose a cross-architecture online-distillation approach to solve this problem by transmitting supplementary information on different networks. We use the ensemble method to aggregate networks of different structures, thus forming better teachers than traditional distillation methods. In addition, discontinuous distillation with progressively enhanced constraints is used to replace fixed distillation in order to reduce loss of information diversity in the distillation process. Our training method improves the distillation effect and achieves strong network-performance improvement. We used some popular models to validate the results. On the CIFAR100 dataset, AlexNet's accuracy was improved by 5.94%, VGG by 2.88%, ResNet by 5.07%, and DenseNet by 1.28%. Extensive experiments were conducted to demonstrate the effectiveness of the proposed method. On the CIFAR10, CIFAR100, and ImageNet datasets, we observed significant improvements over traditional knowledge distillation.

Highly Tunable and Facile Synthesis of Uniform Carbon Flower Particles.

Three-dimensional hierarchical porous carbon materials with flower-like superstructures are of great interest for energy applications since their unique shape not only provides high accessible surface area and consequently more exposed active sites but also facilitates ion transport for high-rate capability. However, finding a controllable way to make porous carbons with such specific shapes has been challenging. Herein, we report a tunable and simple method for one-pot synthesis of polyacrylonitrile and its copolymer nanostructured particles with various superstructures (flower, pompom, hairy leave, and petal shapes) controlled by employing various solvents or by the incorporation of different co-monomers. The correlation between polymer particle shapes and solvent properties has been identified through Hansen solubility parameters analysis. The obtained uniform polyacrylonitrile particles could be readily converted into porous carbons by high-temperature gas treatment while maintaining the original shape of the polymer precursor structures. The resulting carbon materials have high nitrogen-doping concentration (7-15 at%) and tunable porous structures. This novel synthetic method provides a simple way to make porous carbons with controllable morphology and potentially advantageous properties for a variety of potential energy and environmental applications, such as electrochemical energy conversion and wastewater treatment.

Stabilization of Hexaaminobenzene in a 2D Conductive Metal-Organic Framework for High Power Sodium Storage.

Redox-active organic materials have gained growing attention as electrodes of rechargeable batteries. However, their key limitations are the low electronic conductivity and limited chemical and structural stability under redox conditions. Herein, we report a new cobalt-based 2D conductive metal-organic framework (MOF), Co-HAB, having stable, accessible, dense active sites for high-power energy storage device through conjugative coordination between a redox-active linker, hexaaminobenzene (HAB), and a Co(II) center. Given the exceptional capability of Co-HAB for stabilizing reactive HAB, a reversible three-electron redox reaction per HAB was successfully demonstrated for the first time, thereby presenting a promising new electrode material for sodium-ion storage. Specifically, through synthetic tunability of Co-HAB, the bulk electrical conductivity of 1.57 S cm-1 was achieved, enabling an extremely high rate capability, delivering 214 mAh g-1 within 7 min or 152 mAh g-1 in 45 s. Meanwhile, an almost linear increase of the areal capacity upon increasing active mass loading up to 9.6 mg cm-2 was obtained, demonstrating 2.6 mAh cm-2 with a trace amount of conducting agent.

Synthetic Routes for a 2D Semiconductive Copper Hexahydroxybenzene Metal-Organic Framework.

Conductive metal-organic frameworks (c-MOFs) have shown outstanding performance in energy storage and electrocatalysis. Varying the bridging metal species and the coordinating atom are versatile approaches to tune their intrinsic electronic properties in c-MOFs. Herein we report the first synthesis of the oxygen analog of M3(C6X6)2 (X = NH, S) family using Cu(II) and hexahydroxybenzene (HHB), namely Cu-HHB [Cu3(C6O6)2], through a kinetically controlled approach with a competing coordination reagent. We also successfully demonstrate an economical synthetic approach using tetrahydroxyquinone as the starting material. Cu-HHB was found to have a partially eclipsed packing between adjacent 2D layers and a bandgap of approximately 1 eV. The addition of Cu-HHB to the family of synthetically realized M3(C6X6)2 c-MOFs will enable greater understanding of the influence of the organic linkers and metals, and further broadens the range of applications for these materials.

Deep Convolutional Neural Network-Based Early Automated Detection of Diabetic Retinopathy Using Fundus Image.

The automatic detection of diabetic retinopathy is of vital importance, as it is the main cause of irreversible vision loss in the working-age population in the developed world. The early detection of diabetic retinopathy occurrence can be very helpful for clinical treatment; although several different feature extraction approaches have been proposed, the classification task for retinal images is still tedious even for those trained clinicians. Recently, deep convolutional neural networks have manifested superior performance in image classification compared to previous handcrafted feature-based image classification methods. Thus, in this paper, we explored the use of deep convolutional neural network methodology for the automatic classification of diabetic retinopathy using color fundus image, and obtained an accuracy of 94.5% on our dataset, outperforming the results obtained by using classical approaches.

Size-Controlled Synthesis of Porphyrinic Metal-Organic Framework and Functionalization for Targeted Photodynamic Therapy.

The understanding of nanomaterials for targeted cancer therapy is of great importance as physical parameters of nanomaterials have been shown to be strong determinants that can promote cellular responses. However, there have been rare platforms that can vastly tune the core of nanoparticles at a molecular level despite various nanomaterials employed in such studies. Here we show targeted photodynamic therapy (PDT) with Zr(IV)-based porphyrinic metal-organic framework (MOF) nanoparticles. Through a bottom-up approach, the size of MOF nanoparticles was precisely tuned in a broad range with a designed functional motif, built upon selection of building blocks of the MOF. In particular, molecular properties of the porphyrinic linker are maintained in the MOF nanoparticles regardless of their sizes. Therefore, size-dependent cellular uptake and ensuing PDT allowed for screening of the optimal size of MOF nanoparticles for PDT while MOF nanoparticle formulation of the photosensitizer showed better PDT efficacy than that of its small molecule. Additionally, Zr6 clusters in the MOF enabled an active targeting modality through postsynthetic modification, giving even more enhanced PDT efficacy. Together with our finding of size controllability covering a broad range in the nano regime, we envision that MOFs can be a promising nanoplatform by adopting advanced small molecule systems into the tunable framework with room for postsynthetic modification.

Seed-Mediated Synthesis of Metal-Organic Frameworks.

The synthesis of phase-pure metal-organic frameworks (MOFs) is of prime importance but remains a significant challenge because of the flexible and diversified coordination modes between metal ions and organic linkers. In this work, we report the synthesis of phase-pure MOFs via a facile seed-mediated approach. For several "accompanying" pairs of Zr-porphyrinic MOFs that are prone to yield mixtures, by fixing all reaction parameters except introducing seed crystals, MOFs in phase-pure forms have been obtained because the stage of MOF nucleation, which generates mixed nuclei, is bypassed. In addition, phase-pure MOF isomers with distinct pore structures have also been prepared through such an approach, revealing its versatility. To the best of our knowledge, this is an initial report on seed-assisted synthesis of phase-pure MOFs.

Pyrazolate-Based Porphyrinic Metal-Organic Framework with Extraordinary Base-Resistance.

Guided by a top-down topological analysis, a metal-organic framework (MOF) constructed by pyrazolate-based porphyrinic ligand, namely, PCN-601, has been rationally designed and synthesized, and it exhibits excellent stability in alkali solutions. It is, to the best of our knowledge, the first identified MOF that can retain its crystallinity and porosity in saturated sodium hydroxide solution (∼ 20 mol/L) at room temperature and 100 °C. This almost pushes base-resistance of porphyrinic MOFs (even if MOFs) to the limit in aqueous media and greatly extends the range of their potential applications. In this work, we also tried to interpret the stability of PCN-601 from both thermodynamic and kinetic perspectives.

Highly Stable Zr(IV)-Based Metal-Organic Frameworks for the Detection and Removal of Antibiotics and Organic Explosives in Water.

Antibiotics and organic explosives are among the main organic pollutants in wastewater; their detection and removal are quite important but challenging. As a new class of porous materials, metal-organic frameworks (MOFs) are considered as a promising platform for the sensing and adsorption applications. In this work, guided by a topological design approach, two stable isostructural Zr(IV)-based MOFs, Zr6O4(OH)8(H2O)4(CTTA)8/3 (BUT-12, H3CTTA = 5'-(4-carboxyphenyl)-2',4',6'-trimethyl-[1,1':3',1″-terphenyl]-4,4″-dicarboxylic acid) and Zr6O4(OH)8(H2O)4(TTNA)8/3 (BUT-13, H3TTNA = 6,6',6″-(2,4,6-trimethylbenzene-1,3,5-triyl)tris(2-naphthoic acid)) with the the-a topological structure constructed by D4h 8-connected Zr6 clusters and D3h 3-connected linkers were designed and synthesized. The two MOFs are highly porous with the Brunauer-Emmett-Teller surface area of 3387 and 3948 m(2) g(-1), respectively. Particularly, BUT-13 features one of the most porous water-stable MOFs reported so far. Interestingly, these MOFs represent excellent fluorescent properties, which can be efficiently quenched by trace amounts of nitrofurazone (NZF) and nitrofurantoin (NFT) antibiotics as well as 2,4,6-trinitrophenol (TNP) and 4-nitrophenol (4-NP) organic explosives in water solution. They are responsive to NZF and TNP at parts per billion (ppb) levels, which are among the best performing luminescent MOF-based sensing materials. Simultaneously, both MOFs also display high adsorption abilities toward these organic molecules. It was demonstrated that the adsorption plays an important role in the preconcentration of analytes, which can further increase the fluorescent quenching efficiency. These results indicate that BUT-12 and -13 are favorable materials for the simultaneous selective detection and removal of specific antibiotics and organic explosives from water, being potentially useful in monitoring water quality and treating wastewater.

Controlled Generation of Singlet Oxygen in Living Cells with Tunable Ratios of the Photochromic Switch in Metal-Organic Frameworks.

Development of a photosensitizing system that can reversibly control the generation of singlet oxygen ((1) O2 ) is of great interest for photodynamic therapy (PDT). Recently several photosensitizer-photochromic-switch dyads were reported as a potential means of the (1) O2 control in PDT. However, the delivery of such a homogeneous molecular dyad as designed (e.g., optimal molar ratio) is extremely challenging in living systems. Herein we show a Zr-MOF nanoplatform, demonstrating energy transfer-based (1) O2 controlled PDT. Our strategy allows for tuning the ratios between photosensitizer and the switch molecule, enabling maximum control of (1) O2 generation. Meanwhile, the MOF provides proximal placement of the functional entities for efficient intermolecular energy transfer. As a result, the MOF nanoparticle formulation showed enhanced PDT efficacy with superior (1) O2 control compared to that of homogeneous molecular analogues.

An In Situ One-Pot Synthetic Approach towards Multivariate Zirconium MOFs.

Chemically highly stable MOFs incorporating multiple functionalities are of great interest for applications under harsh environments. Herein, we presented a facile one-pot synthetic strategy to incorporate multiple functionalities into stable Zr-MOFs from mixed ligands of different geometry and connectivity. Via our strategy, tetratopic tetrakis(4-carboxyphenyl)porphyrin (TCPP) ligands were successfully integrated into UiO-66 while maintaining the crystal structure, morphology, and ultrahigh chemical stability of UiO-66. The amount of incorporated TCPP is controllable. Through various combinations of BDC derivatives and TCPP, 49 MOFs with multiple functionalities were obtained. Among them, MOFs modified with FeTCPPCl were demonstrated to be catalytically active for the oxidation of ABTS. We anticipate our strategy to provide a facile route to introduce multiple functionalities into stable Zr-MOFs for a wide variety of potential applications.

Dual Exchange in PCN-333: A Facile Strategy to Chemically Robust Mesoporous Chromium Metal-Organic Framework with Functional Groups.

A facile preparation of a mesoporous Cr-MOF, PCN-333(Cr) with functional group, has been demonstrated through a dual exchange strategy, involving a sequential ligand exchange and metal metathesis process. After optimization of the exchange system, the functionalized PCN-333(Cr), N3-PCN-333(Cr) shows well maintained crystallinity, porosity, as well as much improved chemical stability. Because of the exceptionally large pores (∼5.5 nm) in PCN-333(Cr), a secondary functional moiety, Zn-TEPP with a size of 18 Å × 18 Å, has been successfully clicked into the framework. In this article, we have also analyzed kinetics and thermodynamics during dual exchange process, showing our attempts to interpret the exchange event in the PCN-333. Our findings not only provide a highly stable mesoporous Cr-MOF platform for expanding MOF-based applications, but also suggest a route to functionalized Cr-MOF which may have not been achievable through conventional approaches.