Hollow Metal-Organic Framework/MXene/Nanocellulose Composite Films for Giga/Terahertz Electromagnetic Shielding and Photothermal Conversion

With the continuous advancement of communication technology,the escalating demand for electromagnetic shielding interference(EMI)materials with multifunctional and wideband EMI performance has become urgent.Controlling the electrical and magnetic components and designing the EMI material structure have attracted extensive interest,but remain a huge challenge.Herein,we reported the alternating electromagnetic structure composite films composed of hollow metal-organic frameworks/layered MXene/nanocellulose(HMN)by alternating vacuum-assisted filtration process.The HMN composite films exhibit excellent EMI shielding effectiveness performance in the GHz frequency(66.8 dB at Kaband)and THz frequency(114.6 dB at 0.1-4.0 THz).Besides,the HMN composite films also exhibit a high reflection loss of 39.7 dB at 0.7 THz with an effective absorption bandwidth up to 2.1 THz.Moreover,HMN composite films show remarkable photothermal conversion performance,which can reach 104.6℃under 2.0 Sun and 235.4℃under 0.8 W cm^(−2),respectively.The unique micro-and macrostructural design structures will absorb more incident electromagnetic waves via interfacial polarization/multiple scattering and produce more heat energy via the local surface plasmon resonance effect.These features make the HMN composite film a promising candidate for advanced EMI devices for future 6G communication and the protection of electronic equipment in cold environments.

All‑Covalent Organic Framework Nanofilms Assembled Lithium‑Ion Capacitor to Solve the Imbalanced Charge Storage Kinetics

Free-standing covalent organic framework(COFs)nanofilms exhibit a remarkable ability to rapidly intercalate/de-intercalate Li^(+) in lithium-ion batteries,while simultaneously exposing affluent active sites in supercapacitors.The development of these nanofilms offers a promising solution to address the persistent challenge of imbalanced charge storage kinetics between battery-type anode and capacitor-type cathode in lithium-ion capacitors(LICs).Herein,for the first time,custom-made COFBTMB-TP and COFTAPB-BPY nanofilms are synthesized as the anode and cathode,respectively,for an all-COF nanofilm-structured LIC.The COFBTMB-TP nanofilm with strong electronegative–CF3 groups enables tuning the partial electron cloud density for Li^(+) migration to ensure the rapid anode kinetic process.The thickness-regulated cathodic COFTAPB-BPY nanofilm can fit the anodic COF nanofilm in the capacity.Due to the aligned 1D channel,2D aromatic skeleton and accessible active sites of COF nanofilms,the whole COFTAPB-BPY//COFBTMB-TP LIC demonstrates a high energy density of 318 mWh cm^(−3) at a high-power density of 6 W cm^(−3),excellent rate capability,good cycle stability with the capacity retention rate of 77%after 5000-cycle.The COFTAPB-BPY//COFBTMB-TP LIC represents a new benchmark for currently reported film-type LICs and even film-type supercapacitors.After being comprehensively explored via ex situ XPS,7Li solid-state NMR analyses,and DFT calculation,it is found that the COFBTMB-TP nanofilm facilitates the reversible conversion of semi-ionic to ionic C–F bonds during lithium storage.COFBTMB-TP exhibits a strong interaction with Li^(+) due to the C–F,C=O,and C–N bonds,facilitating Li^(+) desolation and absorption from the electrolyte.This work addresses the challenge of imbalanced charge storage kinetics and capacity between the anode and cathode and also pave the way for future miniaturized and wearable LIC devices.

Research on the Legal Framework of Content Regulations for Network Platforms

In the era of the Internet,various network platforms have evolved into new hubs for information dissemination.Currently,China has established a platform-centered content regulation framework,wherein platforms proactively enforce content regulations in accordance with legal censorship obligations.Additionally,platform policies and user agreements augment their authority in content regulation.The platforms can achieve cost-effective and highly efficient content regulation by leveraging their strategic advantages enabled by their own technical capabilities and extensive coverage.The platform self-regulation model,however,still faces challenges.First,accurately evaluating content remains a formidable task;second,ensuring effective platform publicity through self-regulation poses difficulties;third,users may potentially face disadvantages due to the platform’s right of self-regulation;and fourth,digital copyright owners face challenges when defending digital copyright disputes under the safe harbor rule.Therefore,it is imperative to establish,review,and revise the legal framework for content regulation of network platforms in order to enhance the efficiency of their governance systems.The formulation of the legal framework for content regulation of network platforms may encompass the following aspects:rationalizing obligations pertaining to platform content regulations,enhancing supervision over platform self-regulation,and establishing a dual-track responsibility system for digital copyright content regulation.This will ensure a harmonious balance among public interests,users’personal rights and interests,and commercial benefits through regulating the content on network platforms.

Metal-organic frameworks and their composites for advanced lithium-ion batteries:Synthesis,progress and prospects

Metal-organic frameworks(MOFs)are among the most promising materials for lithium-ion batteries(LIBs)owing to their high surface area,periodic porosity,adjustable pore size,and controllable chemical composition.For instance,their unique porous structures promote electrolyte penetration,ions transport,and make them ideal for battery separators.Regulating the chemical composition of MOF can introduce more active sites for electrochemical reactions.Therefore,MOFs and their related composites have been extensively and thoroughly explored for LIBs.However,the reported reviews solely include the applications of MOFs in the electrode materials of LIBs and rarely involve other aspects.A systematic review of the application of MOFs in LIBs is essential for understanding the mechanism of MOFs and better designing related MOFs battery materials.This review systematically evaluates the latest developments in pristine MOFs and MOF composites for LIB applications,including MOFs as the main materials(anode,cathode,separators,and electrolytes)to auxiliary materials(coating layers and additives for electrodes).Furthermore,the synthesis,modification methods,challenges,and prospects for the application of MOFs in LIBs are discussed.

Synergistic catalysis of the N-hydroxyphthalimide on flower-like bimetallic metal-organic frameworks for boosting oxidative desulfurization

Synergic catalytic effect between active sites and supports greatly determines the catalytic activity for the aerobic oxidative desulfurization of fuel oils.In this work,Ni-doped Co-based bimetallic metal-organic framework(CoNi-MOF)is fabricated to disperse N-hydroxyphthalimide(NHPI),in which the whole catalyst provides plentiful synergic catalytic effect to improve the performance of oxidative desulfurization(ODS).As a bimetallic MOF,the second metal Ni doping results in the flower-like morphology and the modification of electronic properties,which ensure the exposure of NHPI and strengthen the synergistic effect of the overall catalyst.Compared with the monometallic Co-MOF and naked NHPI,the NHPI@CoNi-MOF triggers the efficient activation of molecular oxygen and improves the ODS performance without an initiator.The sulfur removal of dibenzothiophene-based model oil reaches 96.4%over the NHPI@CoNi-MOF catalyst in 8 h of reaction.Furthermore,the catalytic product of this aerobic ODS reaction is sulfone,which is adsorbed on the catalyst surface due to the difference in polarity.This work provides new insight and strategy for the design of a strong synergic catalytic effect between NHPI and bimetallic supports toward high-activity aerobic ODS materials.

A Tutorial on Federated Learning from Theory to Practice:Foundations,Software Frameworks,Exemplary Use Cases,and Selected Trends

When data privacy is imposed as a necessity,Federated learning(FL)emerges as a relevant artificial intelligence field for developing machine learning(ML)models in a distributed and decentralized environment.FL allows ML models to be trained on local devices without any need for centralized data transfer,thereby reducing both the exposure of sensitive data and the possibility of data interception by malicious third parties.This paradigm has gained momentum in the last few years,spurred by the plethora of real-world applications that have leveraged its ability to improve the efficiency of distributed learning and to accommodate numerous participants with their data sources.By virtue of FL,models can be learned from all such distributed data sources while preserving data privacy.The aim of this paper is to provide a practical tutorial on FL,including a short methodology and a systematic analysis of existing software frameworks.Furthermore,our tutorial provides exemplary cases of study from three complementary perspectives:i)Foundations of FL,describing the main components of FL,from key elements to FL categories;ii)Implementation guidelines and exemplary cases of study,by systematically examining the functionalities provided by existing software frameworks for FL deployment,devising a methodology to design a FL scenario,and providing exemplary cases of study with source code for different ML approaches;and iii)Trends,shortly reviewing a non-exhaustive list of research directions that are under active investigation in the current FL landscape.The ultimate purpose of this work is to establish itself as a referential work for researchers,developers,and data scientists willing to explore the capabilities of FL in practical applications.

Accelerating Oxygen Electrocatalysis Kinetics on Metal-Organic Frameworks via Bond Length Optimization

Metal-organic frameworks(MOFs)have been developed as an ideal platform for exploration of the relationship between intrinsic structure and catalytic activity,but the limited catalytic activity and stability has hampered their practical use in water splitting.Herein,we develop a bond length adjustment strategy for optimizing naphthalene-based MOFs that synthesized by acid etching Co-naphthalenedicarboxylic acid-based MOFs(donated as AE-CoNDA)to serve as efficient catalyst for water splitting.AE-CoNDA exhibits a low overpotential of 260 mV to reach 10 mA cm^(−2)and a small Tafel slope of 62 mV dec^(−1)with excellent stability over 100 h.After integrated AE-CoNDA onto BiVO_(4),photocurrent density of 4.3 mA cm^(−2)is achieved at 1.23 V.Experimental investigations demonstrate that the stretched Co-O bond length was found to optimize the orbitals hybridization of Co 3d and O 2p,which accounts for the fast kinetics and high activity.Theoretical calculations reveal that the stretched Co-O bond length strengthens the adsorption of oxygen-contained intermediates at the Co active sites for highly efficient water splitting.

Managing the surge:A comprehensive review of the entire disposal framework for retired lithium-ion batteries from electric vehicles

Anticipating the imminent surge of retired lithium-ion batteries(R-LIBs)from electric vehicles,the need for safe,cost-effective and environmentally friendly disposal technologies has escalated.This paper seeks to offer a comprehensive overview of the entire disposal framework for R-LIBs,encompassing a broad spectrum of activities,including screening,repurposing and recycling.Firstly,we delve deeply into a thorough examination of current screening technologies,shifting the focus from a mere enumeration of screening methods to the exploration of the strategies for enhancing screening efficiency.Secondly,we outline battery repurposing with associated key factors,summarizing stationary applications and sizing methods for R-LIBs in their second life.A particular light is shed on available reconditioning solutions,demonstrating their great potential in facilitating battery safety and lifetime in repurposing scenarios and identifying their techno-economic issues.In the realm of battery recycling,we present an extensive survey of pre-treatment options and subsequent material recovery technologies.Particularly,we introduce several global leading recyclers to illustrate their industrial processes and technical intricacies.Furthermore,relevant challenges and evolving trends are investigated in pursuit of a sustainable end-of-life management and disposal framework.We hope that this study can serve as a valuable resource for researchers,industry professionals and policymakers in this field,ultimately facilitating the adoption of proper disposal practices.

An End-To-End Hyperbolic Deep Graph Convolutional Neural Network Framework

Graph Convolutional Neural Networks(GCNs)have been widely used in various fields due to their powerful capabilities in processing graph-structured data.However,GCNs encounter significant challenges when applied to scale-free graphs with power-law distributions,resulting in substantial distortions.Moreover,most of the existing GCN models are shallow structures,which restricts their ability to capture dependencies among distant nodes and more refined high-order node features in scale-free graphs with hierarchical structures.To more broadly and precisely apply GCNs to real-world graphs exhibiting scale-free or hierarchical structures and utilize multi-level aggregation of GCNs for capturing high-level information in local representations,we propose the Hyperbolic Deep Graph Convolutional Neural Network(HDGCNN),an end-to-end deep graph representation learning framework that can map scale-free graphs from Euclidean space to hyperbolic space.In HDGCNN,we define the fundamental operations of deep graph convolutional neural networks in hyperbolic space.Additionally,we introduce a hyperbolic feature transformation method based on identity mapping and a dense connection scheme based on a novel non-local message passing framework.In addition,we present a neighborhood aggregation method that combines initial structural featureswith hyperbolic attention coefficients.Through the above methods,HDGCNN effectively leverages both the structural features and node features of graph data,enabling enhanced exploration of non-local structural features and more refined node features in scale-free or hierarchical graphs.Experimental results demonstrate that HDGCNN achieves remarkable performance improvements over state-ofthe-art GCNs in node classification and link prediction tasks,even when utilizing low-dimensional embedding representations.Furthermore,when compared to shallow hyperbolic graph convolutional neural network models,HDGCNN exhibits notable advantages and performance enhancements.

Unveiling the tailorable electrochemical properties of zeolitic imidazolate framework-derived Ni-doped LiCoO_(2) for lithium-ion batteries in half/full cells

As a prevailing cathode material of lithium-ion batteries(LIBs),LiCoO_(2)(LCO)still encounters the tricky problems of structural collapse,whose morphological engineering and cation doping are crucial for surmounting the mechanical strains and alleviating phase degradation upon cycling.Hereinafter,we propose a strategy using a zeolitic imidazolate framework(ZIF)as the self-sacrificing template to directionally prepare a series of LiNi_(0.1)Co_(0.9)O_(2)(LNCO)with tailorable electrochemical properties.The rational selection of sintering temperature imparts the superiority of the resultant products in lithium storage,during which the sample prepared at 700℃(LNCO-700)outperforms its counterparts in cyclability(156.8 mA h g^(-1)at 1 C for 200 cycles in half cells,1 C=275 mA g^(-1))and rate capability due to the expedited ion/electron transport and the strengthen mechanical robustness.The feasibility of proper Ni doping is also divulged by half/full cell tests and theoretical study,during which LNCO-700(167 mA h g^(-1)at 1 C for 100 cycles in full cells)surpasses LCO-700 in battery performance due to the mitigated phase deterioration,stabilized layered structu re,ameliorated electro nic co nductivity,a nd exalted lithium sto rage activity.This work systematically unveils tailorable electrochemical behaviors of LNCO to better direct their practical application.

A Study on the Explainability of Thyroid Cancer Prediction:SHAP Values and Association-Rule Based Feature Integration Framework

In the era of advanced machine learning techniques,the development of accurate predictive models for complex medical conditions,such as thyroid cancer,has shown remarkable progress.Accurate predictivemodels for thyroid cancer enhance early detection,improve resource allocation,and reduce overtreatment.However,the widespread adoption of these models in clinical practice demands predictive performance along with interpretability and transparency.This paper proposes a novel association-rule based feature-integratedmachine learning model which shows better classification and prediction accuracy than present state-of-the-artmodels.Our study also focuses on the application of SHapley Additive exPlanations(SHAP)values as a powerful tool for explaining thyroid cancer prediction models.In the proposed method,the association-rule based feature integration framework identifies frequently occurring attribute combinations in the dataset.The original dataset is used in trainingmachine learning models,and further used in generating SHAP values fromthesemodels.In the next phase,the dataset is integrated with the dominant feature sets identified through association-rule based analysis.This new integrated dataset is used in re-training the machine learning models.The new SHAP values generated from these models help in validating the contributions of feature sets in predicting malignancy.The conventional machine learning models lack interpretability,which can hinder their integration into clinical decision-making systems.In this study,the SHAP values are introduced along with association-rule based feature integration as a comprehensive framework for understanding the contributions of feature sets inmodelling the predictions.The study discusses the importance of reliable predictive models for early diagnosis of thyroid cancer,and a validation framework of explainability.The proposed model shows an accuracy of 93.48%.Performance metrics such as precision,recall,F1-score,and the area under the receiver operating characteristic(AUROC)are also higher than the baseline models.The results of the proposed model help us identify the dominant feature sets that impact thyroid cancer classification and prediction.The features{calcification}and{shape}consistently emerged as the top-ranked features associated with thyroid malignancy,in both association-rule based interestingnessmetric values and SHAPmethods.The paper highlights the potential of the rule-based integrated models with SHAP in bridging the gap between the machine learning predictions and the interpretability of this prediction which is required for real-world medical applications.

Framework to Model User Request Access Patterns in the World Wide Web

In this paper, we present a novel approach to model user request patterns in the World Wide Web. Instead of focusing on the user traffic for web pages, we capture the user interaction at the object level of the web pages. Our framework model consists of three sub-models: one for user file access, one for web pages, and one for storage servers. Web pages are assumed to consist of different types and sizes of objects, which are characterized using several categories: articles, media, and mosaics. The model is implemented with a discrete event simulation and then used to investigate the performance of our system over a variety of parameters in our model. Our performance measure of choice is mean response time and by varying the composition of web pages through our categories, we find that our framework model is able to capture a wide range of conditions that serve as a basis for generating a variety of user request patterns. In addition, we are able to establish a set of parameters that can be used as base cases. One of the goals of this research is for the framework model to be general enough that the parameters can be varied such that it can serve as input for investigating other distributed applications that require the generation of user request access patterns.

Engineering Spin States of Isolated Copper Species in a Metal-Organic Framework Improves Urea Electrosynthesis

The catalytic activities are generally believed to be relevant to the electronic states of their active center, but understanding this relationship is usually difficult. Here, we design two types of catalysts for electrocatalytic urea via a coordination strategy in a metal–organic frameworks: Cu^(Ⅲ)-HHTP and Cu^(Ⅱ)-HHTP. Cu^(Ⅲ)-HHTP exhibits an improved urea production rate of 7.78 mmol h^(−1)g^(−1) and an enhanced Faradaic efficiency of 23.09% at-0.6 V vs. reversible hydrogen electrode, in sharp contrast to Cu^(Ⅱ)-HHTP.Isolated CuⅢspecies with S = 0 spin ground state are demonstrated as the active center in Cu^(Ⅲ)-HHTP, different from Cu^(Ⅱ) with S = 1/2 in Cu^(Ⅱ)-HHTP. We further demonstrate that isolated Cu^(Ⅲ)with an empty dx2-y20orbital in Cu^(Ⅲ)-HHTP experiences a single-electron migration path with a lower energy barrier in the C–N coupling process, while Cu^(Ⅱ)with a single-spin state( d_(x2-y2)^(1)) in Cu^(Ⅱ)-HHTP undergoes a two-electron migration pathway.

Recent Progress in Atmospheric Chemistry Research in China: Establishing a Theoretical Framework for the “Air Pollution Complex”

Atmospheric chemistry research has been growing rapidly in China in the last 25 years since the concept of the“air pollution complex”was first proposed by Professor Xiaoyan TANG in 1997.For papers published in 2021 on air pollution(only papers included in the Web of Science Core Collection database were considered),more than 24000 papers were authored or co-authored by scientists working in China.In this paper,we review a limited number of representative and significant studies on atmospheric chemistry in China in the last few years,including studies on(1)sources and emission inventories,(2)atmospheric chemical processes,(3)interactions of air pollution with meteorology,weather and climate,(4)interactions between the biosphere and atmosphere,and(5)data assimilation.The intention was not to provide a complete review of all progress made in the last few years,but rather to serve as a starting point for learning more about atmospheric chemistry research in China.The advances reviewed in this paper have enabled a theoretical framework for the air pollution complex to be established,provided robust scientific support to highly successful air pollution control policies in China,and created great opportunities in education,training,and career development for many graduate students and young scientists.This paper further highlights that developing and low-income countries that are heavily affected by air pollution can benefit from these research advances,whilst at the same time acknowledging that many challenges and opportunities still remain in atmospheric chemistry research in China,to hopefully be addressed over the next few decades.

Applications of Metal–Organic Frameworks and Their Derivatives in Electrochemical CO_(2)Reduction

Electrochemically reducing CO_(2)to more reduced chemical species is a promising way that not only enables the conversion of intermittent energy resources to stable fuels,but also helps to build a closed-loop anthropogenic carbon cycle.Among various electrocatalysts for electrochemical CO_(2)reduction,multifunctional metal–organic frameworks(MOFs)have been employed as highly efficient and selective heterogeneous electrocatalysts due to their ultrahigh porosity and topologically diverse structures.Up to now,great progress has been achieved in the design and synthesis of highly active and selective MOF-related catalysts for electrochemical CO_(2)reduction reaction(CO_(2)RR),and their corresponding reaction mechanisms have been thoroughly studied.In this review,we summarize the recent progress of applying MOFs and their derivatives in CO_(2)RR,with a focus on the design strategies for electrocatalysts and electrolyzers.We first discussed the reaction mechanisms for different CO_(2)RR products and introduced the commonly applied electrolyzer configurations in the current CO_(2)RR system.Then,an overview of several categories of products(CO,HCOOH,CH_(4),CH_(3)OH,and multi-carbon chemicals)generated from MOFs or their derivatives via CO_(2)RR was discussed.Finally,we offer some insights and perspectives for the future development of MOFs and their derivatives in electrochemical CO_(2)reduction.We aim to provide new insights into this field and further guide future research for large-scale applications.

Research progress on the substrate for metal-organic framework(MOF) membrane growth for separation

During the last decade, metal-organic frameworks(MOFs) have been applied in various fields due to their unique chemical and functional advantages. One of the widespread research hotspots is MOF-based membranes for separations, specifically continuous defect-free MOF membranes, which are usually grown on porous substrates. The substrate not only serves as the MOF layer support but also has a great influence on the membrane fabrication process and the final separation performance of the resultant membrane. In this review, we mainly introduce the progress focused on the substrates for MOF membranes fabrication. The substrate modifications and seeding methods aimed at synthesizing highquality MOF membranes are also summarized systematically.

A Comprehensive Evaluation Framework of Water-Energy-Food System Coupling Coordination in the Yellow River Basin,China

For mankind’s survival and development,water,energy,and food(WEF)are essential material guarantees.In China,however,the spatial distribution of WEF is seriously unbalanced and mismatched.Here,a collaborative governance mechanism that aims at nexus security needs to be urgently established.In this paper,the Yellow River Basin in China with a representative WEF system,was selected as a case.Firstly,a comprehensive framework for WEF coupling coordination was constructed,and the relationship and mechanism between them were analyzed theoretically.Then,we investigated the spatiotemporal characteristics and driving mechanisms of the coupling coordination degree(CCD)with a composite evaluation method,coupling coordination degree model,spatial statistical analysis,and multiscale geographic weighted regression.Finally,policy implications were discussed to promote the coordinated development of the WEF system.The results showed that:1)WEF subsystems showed a significant imbalance of spatial pattern and diversity in temporal changes;2)the CCD for the WEF system varied little and remained at moderate coordination.Areas with moderate coordination have increased,while areas with superior coordination and mild disorder have decreased.In addition,the spatial clustering phenomenon of the CCD was significant and showed obvious characteristics of polarization;and 3)the action of each factor is self-differentiated and regionally variable.For different factors,GDP per capita was of particular importance,which contributed most to the regional development’s coupling coordination.For different regions,GDP per capita,average yearly precipitation,population density,and urbanization rate exhibited differences in geographical gradients in an east-west direction.The conclusion can provide references for regional resource allocation and sustainable development by enhancing WEF system utilization efficiency.

KOH-assisted aqueous synthesis of bimetallic metal-organic frameworks and their derived selenide composites for efficient lithium storage

To solve low efficiency,environmental pollution,and toxicity for synthesizing zeolitic imidazolate frameworks(ZIFs)in organic solvents,a KOH-assisted aqueous strategy is proposed to synthesize bimetallic ZIFs polyhedrons,which are used as precursors to prepare bimetallic selenide and N-doped carbon(NC)composites.Among them,Fe–Co–Se/NC retains the three-dimensional(3D)polyhedrons with mesoporous structure,and Fe–Co–Se nanoparticles are uniform in size and evenly distributed.When assessed as anode material for lithium-ion batteries,Fe–Co–Se/NC achieves an excellent initial specific capacity of 1165.9 m Ah·g^(-1)at 1.0 A·g^(-1),and the reversible capacity of Fe–Co–Se/NC anode is 1247.4 m Ah·g^(-1)after 550 cycles.It is attributed to that the uniform composite of bimetallic selenides and N-doped carbon can effectively tune redox active sites,the stable 3D structure of Fe–Co–Se/NCs guarantees the structural stability and wettability of the electrolyte,and the uniform distribution of Fe–Co–S nanoparticles in size esuppresses the volume expansion and accelerates the electrochemical reaction kinetics.

A novel strategy of constructing 2D supramolecular organic framework sensor for the identification of toxic metal ions

Two novel two-dimensional(2D)supramolecular organic frameworks were fabricated in water based on the encapsulation-enhanced donor-acceptor interaction between the methyl viologen(MV)units,methoxy naphthyl(MN)units,and CB[8].The tetraphenylethylene(TPE)derivatives 1 with four MV units were employed as rigid building blocks and the two MN units modified oligoethylene glycol derivatives 2 and 3 served as flexible edges,respectively.The obtained two SOFs have obvious sheet-like structures and exhibit fluorescence emission at 350-500 nm.In addition,these two SOFs were employed for the luminescent detection of Cr(Ⅵ)and Mn(Ⅶ)in aqueous solutions,and the detection limits of CrO_(4)^(2-),Cr_(2)_(O)_(7)^(2-),and MnO_(4)
were calculated in a very low concentration range,indicating that these two SOFs can serve as a potential sensor for Cr(Ⅵ)and Mn(Ⅶ)detection in water.This work constructs two SOFs in an aqueous solution through a facile method and further enriches the applications of SOFs.

Tuning the electronic structure of a metal-organic framework for an efficient oxygen evolution reaction by introducing minor atomically dispersed ruthenium

The establishment of efficient oxygen evolution electrocatalysts is of great value but also challenging.Herein,a durable metal–organic framework(MOF)with minor atomically dispersed ruthenium and an optimized electronic structure is constructed as an efficient electrocatalyst.Significantly,the obtained NiRu_(0.08)-MOF with doping Ru only needs an overpotential of 187 mV at 10 mA cm^(-2) with a Tafel slop of 40 mV dec^(-1) in 0.1M KOH for the oxygen evolution reaction,and can work continuously for more than 300 h.Ultrahigh Ru mass activity is achieved,reaching 56.7 Ag^(-1)_(Ru) at an overpotential of 200 mV,which is 36 times higher than that of commercial RuO_(2).X-ray adsorption spectroscopy and density function theory calculations reveal that atomically dispersed ruthenium on metal sites in MOFs is expected to optimize the electronic structure of nickel sites,thus improving the conductivity of the catalyst and optimizing the adsorption energy of intermediates,resulting in significant optimization of electrocatalytic performance.This study could provide a new avenue for the design of efficient and stable MOF electrocatalysts.