Rational design of new in situ reduction of Ni(II)catalytic system for low-cost and large-scale preparation of porous aromatic frameworks

Porous aromatic framework 1(PAF-1)is an extremely representative nanoporous organic framework owing to its high stability and exceptionally high surface area.Currently,the synthesis of PAF-1 is catalyzed by the Ni(COD)2/COD/bpy system,suffering from great instability and high cost.Herein,we developed an in situ reduction of the Ni(II)catalytic system to synthesize PAF-1 in low cost and high yield.The active Ni(0)species produced from the NiCl_(2)/bpy/NaI/Mg catalyst system can effectively catalyze homocoupling of tetrakis(4-bromophenyl)methane at the room temperature to form PAF-1 with high Brunauer-Emmett-Teller(BET)-specific surface area up to 4948 m^(2) g^(−1)(Langmuir surface area,6785 m2 g−1).The possible halogen exchange and dehalogenation coupling mechanisms for this new catalytic process in PAF's synthesis are discussed in detail.The efficiency and universality of this innovative catalyst system have also been demonstrated in other PAFs'synthesis.This work provides a cheap,facile,and efficient method for scalable synthesis of PAFs and explores their application for high-pressure storage of Xe and Kr.

Challenges and Opportunities in Preserving Key Structural Features of 3D-Printed Metal/Covalent Organic Framework

Metal-organic framework(MOF)and covalent organic framework(COF)are a huge group of advanced porous materials exhibiting attractive and tunable microstructural features,such as large surface area,tunable pore size,and functional surfaces,which have significant values in various application areas.The emerging 3D printing technology further provides MOF and COFs(M/COFs)with higher designability of their macrostructure and demonstrates large achievements in their performance by shaping them into advanced 3D monoliths.However,the currently available 3D printing M/COFs strategy faces a major challenge of severe destruction of M/COFs’microstructural features,both during and after 3D printing.It is envisioned that preserving the microstructure of M/COFs in the 3D-printed monolith will bring a great improvement to the related applications.In this overview,the 3D-printed M/COFs are categorized into M/COF-mixed monoliths and M/COF-covered monoliths.Their differences in the properties,applications,and current research states are discussed.The up-to-date advancements in paste/scaffold composition and printing/covering methods to preserve the superior M/COF microstructure during 3D printing are further discussed for the two types of 3D-printed M/COF.Throughout the analysis of the current states of 3D-printed M/COFs,the expected future research direction to achieve a highly preserved microstructure in the 3D monolith is proposed.

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.

Systematic Security Guideline Framework through Intelligently Automated Vulnerability Analysis

This research aims to propose a practical framework designed for the automatic analysis of a product’s comprehensive functionality and security vulnerabilities,generating applicable guidelines based on real-world software.The existing analysis of software security vulnerabilities often focuses on specific features or modules.This partial and arbitrary analysis of the security vulnerabilities makes it challenging to comprehend the overall security vulnerabilities of the software.The key novelty lies in overcoming the constraints of partial approaches.The proposed framework utilizes data from various sources to create a comprehensive functionality profile,facilitating the derivation of real-world security guidelines.Security guidelines are dynamically generated by associating functional security vulnerabilities with the latest Common Vulnerabilities and Exposure(CVE)and Common Vulnerability Scoring System(CVSS)scores,resulting in automated guidelines tailored to each product.These guidelines are not only practical but also applicable in real-world software,allowing for prioritized security responses.The proposed framework is applied to virtual private network(VPN)software,wherein a validated Level 2 data flow diagram is generated using the Spoofing,Tampering,Repudiation,Information Disclosure,Denial of Service,and Elevation of privilege(STRIDE)technique with references to various papers and examples from related software.The analysis resulted in the identification of a total of 121 vulnerabilities.The successful implementation and validation demonstrate the framework’s efficacy in generating customized guidelines for entire systems,subsystems,and selected modules.

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.

Three-dimensional porous bimetallic metal–organic framework/gelatin aerogels: A readily recyclable peroxymonosulfate activator for efficient and continuous organic dye removal

As promising catalysts for the degradation of organic pollutants,metal–organic frameworks(MOFs)often face limitations due to the particle agglomeration and challenging recovery in liquid-catalysis application,stemming from their powdery nature.Engineering macroscopic structures from pulverous MOF is thus of great importance for broadening their practical applications.In this study,three-dimensional porous MOF aerogel catalysts were successfully fabricated for degrading organic dyes by activating peroxymonosulfate(PMS).MOF/gelatin aerogel(MOF/GA)catalysts were prepared by directly integrating bimetallic FeCo-BDC with gelatin solutions,followed by freeze-drying and low-temperature calcination.The FeCo-BDC-0.15/GA/PMS system exhibited remarkable performance in degrading various organic dyes,eliminating 99.2%of rhodamine B within a mere 5 min.Compared to the GA/PMS system,there was over a 300-fold increase in the reaction rate constant.Remarkably,high removal efficiency was maintained across varying conditions,including different solution pH,co-existing inorganic anions,and natural water matrices.Radical trapping experiments and electron paramagnetic resonance analysis revealed that the degradation involved radical(SO_(4)^(-)·)and non-radical routes(^(1)O_(2)),of which ^(1)O_(2) was dominant.Furthermore,even after a continuous 400-min reaction in a fixed-bed reactor at a liquid hourly space velocity of 27 h^(-1),the FeCo-BDC/GA composite sustained a degradation efficiency exceeding 98.7%.This work presents highly active MOF-gelatin aerogels for dye degradation and expands the potential for their large-scale,continuous treatment application in organic dye wastewater management.

Advances of Electrochemical and Electrochemiluminescent Sensors Based on Covalent Organic Frameworks

Covalent organic frameworks(COFs),a rapidly developing category of crystalline conjugated organic polymers,possess highly ordered structures,large specific surface areas,stable chemical properties,and tunable pore microenvironments.Since the first report of boroxine/boronate ester-linked COFs in 2005,COFs have rapidly gained popularity,showing important application prospects in various fields,such as sensing,catalysis,separation,and energy storage.Among them,COFs-based electrochemical(EC)sensors with upgraded analytical performance are arousing extensive interest.In this review,therefore,we summarize the basic properties and the general synthesis methods of COFs used in the field of electroanalytical chemistry,with special emphasis on their usages in the fabrication of chemical sensors,ions sensors,immunosensors,and aptasensors.Notably,the emerged COFs in the electrochemiluminescence(ECL)realm are thoroughly covered along with their preliminary applications.Additionally,final conclusions on state-of-the-art COFs are provided in terms of EC and ECL sensors,as well as challenges and prospects for extending and improving the research and applications of COFs in electroanalytical chemistry.

Parallel Light Fields: A Perspective and A Framework

Dear Editor,Light fields give relatively complete description of scenes from perspective of angles and positions of rays. At present time, most of the computer vision algorithms take 2D images as input which are simplified expression of light fields with depth information discarded. In theory, computer vision tasks may achieve better performance as long as complete light fields are acquired.

Recent advances in core-shell organic framework-based photocatalysts for energy conversion and environmental remediation

Direct conversion of solar energy into chemical energy in an environmentally friendly manner is one of the most promising strategies to deal with the environmental pollution and energy crisis.Among a variety of materials developed as photocatalysts,the core-shell metal/covalent-organic framework(MOF or COF)photocatalysts have garnered significant attention due to their highly porous structure and the adjustability in both structure and functionality.The existing reviews on core-shell organic framework photocatalytic materials have mainly focused on core-shell MOF materials.However,there is still a lack of indepth reviews specifically addressing the photocatalytic performance of core-shell COFs and MOFs@COFs.Simultaneously,there is an urgent need for a comprehensive review encompassing these three types of core-shell structures.Based on this,this review aims to provide a comprehensive understanding and useful guidelines for the exploration of suitable core-shell organic framework photocatalysts towards appropriate photocatalytic energy conversion and environmental governance.Firstly,the classification,synthesis,formation mechanisms,and reasonable regulation of core-shell organic framework were summarized.Then,the photocatalytic applications of these three kinds of core-shell structures in different areas,such as H_(2)evolution,CO_(2)reduction,and pollutants degradation are emphasized.Finally,the main challenges and development prospects of core-shell organic framework photocatalysts were introduced.This review aims to provide insights into the development of a novel generation of efficient and stable core-shell organic framework materials for energy conversion and environmental remediation.

Porous framework materials for energy&environment relevant applications:A systematic review

Carbon peaking and carbon neutralization trigger a technical revolution in energy&environment related fields.Development of new technologies for green energy production and storage,industrial energy saving and efficiency reinforcement,carbon capture,and pollutant gas treatment is in highly imperious demand.The emerging porous framework materials such as metal–organic frameworks(MOFs),covalent organic frameworks(COFs)and hydrogen-bonded organic frameworks(HOFs),owing to the permanent porosity,tremendous specific surface area,designable structure and customizable functionality,have shown great potential in major energy-consuming industrial processes,including sustainable energy gas catalytic conversion,energy-efficient industrial gas separation and storage.Herein,this manuscript presents a systematic review of porous framework materials for global and comprehensive energy&environment related applications,from a macroscopic and application perspective.

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.

Federated Learning on Internet of Things:Extensive and Systematic Review

The proliferation of IoT devices requires innovative approaches to gaining insights while preserving privacy and resources amid unprecedented data generation.However,FL development for IoT is still in its infancy and needs to be explored in various areas to understand the key challenges for deployment in real-world scenarios.The paper systematically reviewed the available literature using the PRISMA guiding principle.The study aims to provide a detailed overview of the increasing use of FL in IoT networks,including the architecture and challenges.A systematic review approach is used to collect,categorize and analyze FL-IoT-based articles.Asearch was performed in the IEEE,Elsevier,Arxiv,ACM,and WOS databases and 92 articles were finally examined.Inclusion measures were published in English and with the keywords“FL”and“IoT”.The methodology begins with an overview of recent advances in FL and the IoT,followed by a discussion of how these two technologies can be integrated.To be more specific,we examine and evaluate the capabilities of FL by talking about communication protocols,frameworks and architecture.We then present a comprehensive analysis of the use of FL in a number of key IoT applications,including smart healthcare,smart transportation,smart cities,smart industry,smart finance,and smart agriculture.The key findings from this analysis of FL IoT services and applications are also presented.Finally,we performed a comparative analysis with FL IID(independent and identical data)and non-ID,traditional centralized deep learning(DL)approaches.We concluded that FL has better performance,especially in terms of privacy protection and resource utilization.FL is excellent for preserving privacy becausemodel training takes place on individual devices or edge nodes,eliminating the need for centralized data aggregation,which poses significant privacy risks.To facilitate development in this rapidly evolving field,the insights presented are intended to help practitioners and researchers navigate the complex terrain of FL and IoT.

Covalent Organic Framework with 3D Ordered Channel and Multi-Functional Groups Endows Zn Anode with Superior Stability

Achieving a highly robust zinc(Zn)metal anode is extremely important for improving the performance of aqueous Zn-ion batteries(AZIBs)for advancing“carbon neutrality”society,which is hampered by the uncontrollable growth of Zn dendrite and severe side reactions including hydrogen evolution reaction,corrosion,and passivation,etc.Herein,an interlayer containing fluorinated zincophilic covalent organic framework with sulfonic acid groups(COF-S-F)is developed on Zn metal(Zn@COF-S-F)as the artificial solid electrolyte interface(SEI).Sulfonic acid group(-SO_(3)H)in COF-S-F can effectively ameliorate the desolvation process of hydrated Zn ions,and the three-dimensional channel with fluoride group(-F)can provide interconnected channels for the favorable transport of Zn ions with ion-confinement effects,endowing Zn@COF-S-F with dendrite-free morphology and suppressed side reactions.Consequently,Zn@COF-S-F symmetric cell can stably cycle for 1,000 h with low average hysteresis voltage(50.5 m V)at the current density of 1.5 m A cm^(-2).Zn@COF-S-F|Mn O_(2)cell delivers the discharge specific capacity of 206.8 m Ah g^(-1)at the current density of 1.2 A g^(-1)after 800 cycles with high-capacity retention(87.9%).Enlightening,building artificial SEI on metallic Zn surface with targeted design has been proved as the effective strategy to foster the practical application of high-performance AZIBs.

Hydrogen-bonded organic framework modified separator for simultaneously enhancing the safety and electrochemical performance of Ni-rich lithium-ion battery

Nickel-rich layered oxide cathode(LiNi_(x)Co_(y)Mn_(1−x−y)O_(2),x>0.5,NCM)shows substantial potential for applications in longer-range electrical vehicles.However,the rapid capacity decay and serious safety concerns impede its practical viability.This work provides a hydrogen-bonded organic framework(HOF)modification strategy to simultaneously improve the electrochemical performance,thermal stability and incombustibility of separator.Melamine cyanurate(MCA),as a low-cost and reliable flame-retardant HOF,was implemented in the separator modification layer,which can prevent the battery short circuit even at a high temperature.In addition,the supermolecule properties of MCA provide unique physical and chemical microenvironment for regulating ion-transport behavior in electrolyte.The MCA coating layer enabled the nickel-rich layered oxide cathode with a high-capacity retention of 90.3%after 300 cycles at 1.0 C.Collectively,the usage of MCA in lithium-ion batteries(LIBs)affords a simple,low-cost and efficient strategy to improve the security and service life of nickel-rich layered cathodes.

One stone two birds:electrochemical and colorimetric dual-mode biosensor based on copper peroxide/covalent organic framework nanocomposite for ultrasensentive norovirus detection

Norovirus(NoV)is regarded as one of the most common causes of foodborne diarrhea in the world.It is urgent to identify the pathogenic microorganism of the diarrhea in short time.In this work,we developed an electrochemical and colorimetric dual-mode detection for NoV based on the excellent dual catalytic properties of copper peroxide/COF-NH_(2)nanocomposite(CuO_(2)@COF-NH_(2)).For the colorimetric detection,NoV can be directly detected by the naked eye based on CuO_(2)@COF-NH_(2)as a laccase-like nonazyme using“peptide-NoV-antibody”recognition mode.The colorimetric assay displayed a wide and quality linear detection range from 1 copy/mL to 5000 copies/mL of NoV with a low limit of detection(LOD)of 0.125 copy/mL.For the electrochemical detection of NoV,CuO_(2)@COF-NH_(2)showed an oxidation peak of copper ion from Cu^(+)to Cu^(2+)using“peptide-NoV-antibody”recognition mode.The electrochemical assay showed a linear detection range was 1-5000 copies/mL with a LOD of 0.152 copy/mL.It's worthy to note that this assay does not need other electrical signal molecule,which provide the stable and sensitive electrochemial detection for NoV.The electrochemical and colorimetric dual-mode detection was used to detect NoV in foods and faceal samples,which has the potential for improving food safety and diagnosing of NoV-infected diarrhea.

A layered multifunctional framework based on polyacrylonitrile and MOF derivatives for stable lithium metal anode

Composite Li metal anodes based on three-dimensional(3D) porous frameworks have been considered as an effective material for achieving stable Li metal batteries with high energy density.However,uneven Li deposition behavior still occurs at the top of 3D frameworks owing to the local accumulation of Li ions.To promote uniform Li deposition without top dendrite growth,herein,a layered multifunctional framework based on oxidation-treated polyacrylonitrile(OPAN) and metal-organic framework(MOF) derivatives was proposed for rationally regulating the distribution of Li ions flux,nucleation sites,and electrical conductivity.Profiting from these merits,the OPAN/carbon nano fiber-MOF(CMOF) composite framework demonstrated a reversible Li plating/stripping behavior for 500 cycles with a stable Coulombic efficiency of around 99.0% at the current density of 2 mA/cm~2.Besides,such a Li composite anode exhibited a superior cycle lifespan of over 1300 h under a low polarized voltage of 18 mV in symmetrical cells.When the Li composite anode was paired with LiFePO_(4)(LFP) cathode,the obtained full cell exhibited a stable cycling over 500 cycles.Moreover,the COMSOL Multiphysics simulation was conducted to reveal the effects on homogeneous Li ions distribution derived from the above-mentioned OPAN/CMOF framework and electrical insulation/conduction design.These electrochemical and simulated results shed light on the difficulties of designing stable and safe Li metal anode via optimizing the 3D frameworks.

Enhancing competency of clinical research nurses:A comprehensive training and evaluation framework

The Sun et al's training program for clinical research nurses(CRNs)in the World Journal of Clinical Cases is a comprehensive and scientific approach.It includes structured frameworks for CRN training,aiming to improve CRN competency.This program emphasizes practical abilities,updates training content,and improves evaluation methods.The cultivation of CRN talents focuses on enhancing the training system,establishing a multifaceted evaluation framework,and continuously refining the training programs.Regular feedback and evalua-tion are essential to improve CRNs'competency in practical settings.

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.

Juxtapose of System Performance for Food Calorie Estimation Using IoT and Web-based Indagation

A rudimentary aspect of human life is the health of an individual,and most commonly the wellbeing is impacted in a colossal manner through the consumption of food. The intake of calories therefore is a crucial aspect that must be meticulously monitored. Various health gremlins can be largely circumvented when there is a substantial balance in the number of calories ingested versus the quantity of calories expended.The food calorie estimation is a popular domain of research in recent times and is meticulously analyzed through various image processing and machine learning techniques. However,the need to scrutinize and evaluate the calorie estimation through various platforms and algorithmic approaches aids in providing a deeper insight on the bottlenecks involved,and in improvising the bariatric health of an individual. This paper pivots on comprehending a juxtaposed approach of food calorie estimation through the use of employing Convolution Neural Network(CNN)incorporated in Internet of Things(IoT),and using the Django framework in Python,along with query rule-based training to analyze the subsequent actions to be followed post the consumption of food calories in the constructed webpage. The comparative analysis of the food calorie estimate implemented in both platforms is analyzed for the swiftness of identification,error rate and classification accuracy to appropriately determine the optimal method of use. The simulation results for IoT are carried out using the Raspberry Pi4B model,while the Anaconda prompt is used to run the server holding the web page.

ETSI & CEN Workshop on EU Digital Identity Framework Standards

Regulation(EU)2024/1183 amending Regulation(EU)910/2014 on electronic identities,authentication and signatures(eIDAS 2)was published in the Official Journal of the European Union this spring 2024.This amendment establishes an ambitious European Digital Identity Framework with digital identity wallets and a number of new trust services.This will bring about a major transformation of security of the European digital infrastructure facilitating cross border transactions,supporting seamless access to financial,governmental and commercial services across Europe with a high level of accountability.