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.

High-throughput mechanistic study of highly selective hydrogen-bonded organic frameworks for electrochemical nitrate reduction to ammonia

Hydrogen-bonded organic frameworks(HOFs),an emerging porous macrocyclic materials linked by hydrogen-bond,hold potential for gas separation and storage,sensors,optical,and electrocatalysts.Here,HOF-based electrocatalysts are rationally developed for nitrates reduction to ammonia,allowing not only to regulate wastewater pollution but also to accomplish carbon-neutral ammonia(NH_(3))synthesis.We preform high-throughput computational screening of thirty-six HOFs with various metals as active sites,denoted as HOF-M1,for nitrate reduction reaction(NO_(3)RR)toward NH_(3).We have implemented a hierarchical four-step screening strategy,and ultimately,HOF-Ti1 was selected based on its exceptional catalytic activity and selectivity in the NO_(3)RR process.Through additional analysis,we discovered that the d band center of the active metal sites serves as an effective parameter for designing and predicting the performance of HOFs in NO_(3)RR.This research not only showcases the immense potential of electrocatalysis in transforming NO_(3)RR into NH_(3)but also provides researchers with a compelling incentive to undertake further experimental investigations.

One-Dimensional Hydrogen-bonded Double Chain Composed of a Copper(II) Complex with Chelidamic Acid

Complex [Cu（C7H3NO5）（DMF）（H2O）] was crystallized from the reaction of Cu（CH3COO）2·H2O with 2,6-dicarboxy-4-hydroxypyridine （chelidamic acid） in DMF solution and its structure was characterized by X-ray crystallography. The crystal is of triclinic, space group P1^- with a = 7.835（2）, b = 8.594（2）, c = 10.309（2） A, α = 84.16（3）, β= 77.94（3）, γ= 69.22（3）°, V = 634.4（2） A^3, Mr = 335.76, Z = 2, Dc = 1.758 g/cm^3, λ, = 0.71073 A,μ（MoKoα） = 1.756 mm^-1 and F（000） = 342. The structure was refined to R = 0.0367 and wR = 0.0805 for 2191 observed reflections with I 〉 2σ（I）. The crystal structure shows a distorted square pyramidal geometry around the copper（Ⅱ） ion, which is chelated by one nitrogen atom and two oxygen atoms of the chelidamic acid, one water molecule and one DMF molecule. The title, complex displays 1-D hydrogen-bonded double chains.

Chain Elongation Using Native Soil Inocula:Exceptional n-Caproate Biosynthesis Performance and Microbial Mechanisms

This study demonstrates the feasibility and effectiveness of utilizing native soils as a resource for inocula to produce n-caproate through the chain elongation(CE)platform,offering new insights into anaerobic soil processes.The results reveal that all five of the tested soil types exhibit CE activity when supplied with high concentrations of ethanol and acetate,highlighting the suitability of soil as an ideal source for n-caproate production.Compared with anaerobic sludge and pit mud,the native soil CE system exhibited higher selectivity(60.53%),specificity(82.32%),carbon distribution(60.00%),electron transfer efficiency(165.00%),and conductivity(0.59 ms∙cm^(-1)).Kinetic analysis further confirmed the superiority of soil in terms of a shorter lag time and higher yield.A microbial community analysis indicated a positive correlation between the relative abundances of Pseudomonas,Azotobacter,and Clostridium and n-caproate production.Moreover,metagenomics analysis revealed a higher abundance of functional genes in key microbial species,providing direct insights into the pathways involved in n-caproate formation,including in situ CO_(2)utilization,ethanol oxidation,fatty acid biosynthesis(FAB),and reverse beta-oxidation(RBO).The numerous functions in FAB and RBO are primarily associated with Pseudomonas,Clostridium,Rhodococcus,Stenotrophomonas,and Geobacter,suggesting that these genera may play roles that are involved or associated with the CE process.Overall,this innovative inoculation strategy offers an efficient microbial source for n-caproate production,underscoring the importance of considering CE activity in anaerobic soil microbial ecology and holding potential for significant economic and environmental benefits through soil consortia exploration.

Research on Alliance Decision of Dual-Channel Remanufacturing Supply Chain Considering Bidirectional Free-Riding and Cost-Sharing

This study delves into the formation dynamics of alliances within a closed-loop supply chain(CLSC)that encom-passes a manufacturer,a retailer,and an e-commerce platform.It leverages Stackelberg game for this exploration,contrasting the equilibrium outcomes of a non-alliance model with those of three differentiated alliance models.The non-alliance model acts as a crucial benchmark,enabling the evaluation of the motivations for various supply chain entities to engage in alliance formations.Our analysis is centered on identifying the most effective alliance strategies and establishing a coordination within these partnerships.We thoroughly investigate the consequences of diverse alliance behaviors,bidirectional free-riding and cost-sharing,and the resultant effects on the optimal decision-making among supply chain actors.The findings underscore several pivotal insights:(1)The behavior of alliances within the supply chain exerts variable impacts on the optimal pricing and demand of its members.In comparison to the non-alliance(D)model,the manufacturer-retailer(MR)and manufacturer-e-commerce platform(ME)alliances significantly lower both offline and online resale prices for new and remanufactured goods.This adjustment leads to an enhanced demand for products via the MR alliance’s offline outlets and the ME alliance’s online platforms,thereby augmenting the profits for those within the alliance.Conversely,retailer-e-commerce platform(ER)alliance tends to increase the optimal retail price and demand across both online and offline channels.Under specific conditions,alliance behavior can also increase the profits of non-alliance members,and the profits derived through alliance channels also exceed those from non-alliance channels.(2)The prevalence of bidirectional free-riding behavior largely remains constant across different alliance configurations.Across these models,bidirectional free-riding typically elevates the equilibrium prices in offline channel while negatively affecting the equilibrium prices in other channel.(3)The effect of cost-sharing shows relative uniformity across the various alliance models.Across all configurations,cost-sharing tends to reduce the manufacturer’s profits.Nonetheless,alliances initiated by the manufacturer can counteract these negative impacts,providing a strategic pathway to bolster CLSC profitability.

Mathematical Modeling of Possibility Markov Chains by Possibility Theory

Statistical regression models are input-oriented estimation models that account for observation errors. On the other hand, an output-oriented possibility regression model that accounts for system fluctuations is proposed. Furthermore, the possibility Markov chain is proposed, which has a disidentifiable state (posterior) and a nondiscriminable state (prior). In this paper, we first take up the entity efficiency evaluation problem as a case study of the posterior non-discriminable production possibility region and mention Fuzzy DEA with fuzzy constraints. Next, the case study of the ex-ante non-discriminable event setting is discussed. Finally, we introduce the measure of the fuzzy number and the equality relation and attempt to model the possibility Markov chain mathematically. Furthermore, we show that under ergodic conditions, the direct sum state can be decomposed and reintegrated using fuzzy OR logic. We had already constructed the Possibility Markov process based on the indifferent state of this world. In this paper, we try to extend it to the indifferent event in another world. It should be noted that we can obtain the possibility transfer matrix by full use of possibility theory.

A Tutorial Review of the Solar Power Curve: Regressions, Model Chains, and Their Hybridization and Probabilistic Extensions

Owing to the persisting hype in pushing toward global carbon neutrality,the study scope of atmospheric science is rapidly expanding.Among numerous trending topics,energy meteorology has been attracting the most attention hitherto.One essential skill of solar energy meteorologists is solar power curve modeling,which seeks to map irradiance and auxiliary weather variables to solar power,by statistical and/or physical means.In this regard,this tutorial review aims to deliver a complete overview of those fundamental scientific and engineering principles pertaining to the solar power curve.Solar power curves can be modeled in two primary ways,one of regression and the other of model chain.Both classes of modeling approaches,alongside their hybridization and probabilistic extensions,which allow accuracy improvement and uncertainty quantification,are scrutinized and contrasted thoroughly in this review.

Durable poly(binaphthyl-co-p-terphenyl piperidinium)-based anion exchange membranes with dual side chains

Building well-developed ion-conductive highways is highly desirable for anion exchange membranes(AEMs).Grafting side chain is a highly effective approach for constructing a well-defined phaseseparated morphological structure and forming unblocked ion pathways in AEMs for fast ion transport.Fluorination of side chains can further enhance phase separation due to the superhydrophobic nature of fluorine groups.However,their electronic effect on the alkaline stability of side chains and membranes is rarely reported.Here,fluorine-containing and fluorine-free side chains are introduced into the polyaromatic backbone in proper configuration to investigate the impact of the fluorine terminal group on the stability of the side chains and membrane properties.The poly(binaphthyl-co-p-terphenyl piperidinium)AEM(QBNp TP)has the highest molecular weight and most dimensional stability due to its favorable backbone arrangement among ortho-and meta-terphenyl based AEMs.Importantly,by introducing both a fluorinated piperidinium side chain and a hexane chain into the p-terphenyl-based backbone,the prepared AEM(QBNp TP-QFC)presents an enhanced conductivity(150.6 m S cm^(-1))and a constrained swelling at 80℃.The electronic effect of fluorinated side chains is contemplated by experiments and simulations.The results demonstrate that the presence of strong electro-withdrawing fluorine groups weakens the electronic cloud of adjacent C atoms,increasing OH^(-)attack on the C atom and improving the stability of piperidinium cations.Hence QBNp TP-QFC possesses a robust alkaline stability at 80℃(95.3%conductivity retention after testing in 2 M Na OH for 2160 h).An excellent peak power density of 1.44 W cm^(-2)and a remarkable durability at 80℃(4.5%voltage loss after 100 h)can be observed.

Global Industrial and Supply Chain Restructuring:Background,Characteristics and Development Trends

The restructuring of global industrial and supply chains is a hot issue in today’s world,and as a result of the once-in-a-century changes and intensified geopolitical and economic competition,the demand for global industrial and supply chain security has risen sharply,with government departments and transnational corporations(TNCs)becoming the most critical stakeholders.Governments carefully calibrate industrial and trade policies from the perspective of national strategies to create industrial chains that support national competitive advantages,and multinational corporations respond to geopolitical risks by prioritizing industrial and supply chain security and sustainability over capital and efficiency.Against the backdrop of changes unseen in a century,decelerating globalization and global economic downturn,the characteristics and future trends of global industrial and supply chain restructuring are worth paying attention to.

International Supply Chain Cooperation and China’s Role

In recent years,the challenges facing the development of international supply chains have been increasing.Major country competition,COVID pandemic and geopolitical conflicts have impacted the development of international supply chains and continue to have negative effects.Against this background,the international community should cooperate to deal with the risks and challenges.

A Proposed Feature Selection Particle Swarm Optimization Adaptation for Intelligent Logistics--A Supply Chain Backlog Elimination Framework

The diversity of data sources resulted in seeking effective manipulation and dissemination.The challenge that arises from the increasing dimensionality has a negative effect on the computation performance,efficiency,and stability of computing.One of the most successful optimization algorithms is Particle Swarm Optimization(PSO)which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search task.This research proposes an effective enhancement of PSO that tackles the challenge of randomness search which directly enhances PSO performance.On the other hand,this research proposes a generic intelligent framework for early prediction of orders delay and eliminate orders backlogs which could be considered as an efficient potential solution for raising the supply chain performance.The proposed adapted algorithm has been applied to a supply chain dataset which minimized the features set from twenty-one features to ten significant features.To confirm the proposed algorithm results,the updated data has been examined by eight of the well-known classification algorithms which reached a minimum accuracy percentage equal to 94.3%for random forest and a maximum of 99.0 for Naïve Bayes.Moreover,the proposed algorithm adaptation has been compared with other proposed adaptations of PSO from the literature over different datasets.The proposed PSO adaptation reached a higher accuracy compared with the literature ranging from 97.8 to 99.36 which also proved the advancement of the current research.

Global Supply Chain Governance and the Future of Globalization

Over the past 30 years or so,globalization has been underpinned by ever-evolving supply chains.The heightened attention to supply chain issues in recent years has been due to a series of global events in the world that have had a significant and profound impact.Factors such as the COVID pandemic,the Ukraine Crisis and increased geopolitical tensions have led to supply chain crises globally or regionally.

Production Chain Length and PPI-CPI Divergence:Analysis Based on the Global Input-output Price Model

Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production chains.The question is how the changing length of production chains will affect CPI and PPI,as well as CPI-PPI correlation?By constructing a global input-output price model,this paper offers a theoretical discussion on the impact of production chain length on the CPI-PPI divergence.Our findings suggest that the price shock of international bulk commodities has a greater impact on China’s PPI than that on CPI.The effects on both China’s PPI and CPI estimated by using the single-country input-output model are higher than the results estimated with the global input-output model.However,the difference between CPI and PPI variations estimated with the global input-output model is greater than the result estimated with the single-country input-output model,which supports the view that the lengthening of production chains,especially international production chains,leads to a divergence between CPI and PPI.Empirical results based on cross-national panel data also suggest that the lengthening of production chains has reduced the CPI-PPI correlation for countries,i.e.the lengthening of production chains has increased the PPI-CPI divergence.That is to say,policymakers should target not just CPI in maintaining price stability,but instead focus on the stability of both PPI and CPI.Efforts can be made to proactively adjust the price index system,and formulate the industrial chain price index.

Hydrogen-bonded Three-Dimensional Networks Encapsulating One-dimensional Covalent Chains: [Cu(3-ampy)(H_2O)_4](SO_4)·(H_2O) (3-ampy = 3-Aminopyridine)

A three-dimensional complex [Cu（3-ampy）（HEO）4]（SO4）·（H2O） （3-ampy = 3-amino- pyridine） has been synthesized. Crystallographic data： C5H16CuN2O9S, Mr = 343.80, triclinic, space group P1, a = 7.675（2）, b = 8.225（3）, c = 10.845（3）A, α= 86.996（4）, β = 76.292（4）, γ= 68.890（4）°, V = 620.0（3）A^3, Z = 2, Dc = 1.841 g/cm^3, F（000） = 354 and μ = 1.971 mm^-1. The structure was refined to R = 0.0269 and wR = 0.0659 for 1838 observed reflections （I 〉 2a（/））. The structure consists of [Cu（3-ampy）（H2O）4]^2＋ cations, SO4^2- anions and lattice water molecules. 3-Ampy acting as a bidentate bridging ligand generates a 1D covalent chain. A supramolecular 2D framework is formed through π-π stacking of pyridine rings. The lattice water molecules and SO4^2- anions are located between the adjacent 2D frameworks. The hydrogen bonding interactions from lattice water molecules and SO4^2- anions to coordinate water extend the 2D framework into a 3D network.

Hepatomegaly and jaundice as the presenting symptoms of systemic light-chain amyloidosis: A case report

BACKGROUND Light chain(AL)amyloidosis is a plasma cell dyscrasia characterized by the pathologic production and extracellular tissue deposition of fibrillar proteins derived from immunoglobulin AL fragments secreted by a clone of plasma cells,which leads to progressive dysfunction of the affected organs.The two most commonly affected organs are the heart and kidneys,and liver is rarely the dominant affected organ with only 3.9%of cases,making them prone to misdia-gnosis and missed diagnosis.CASE SUMMARY A 65-year-old woman was admitted with a 3-mo history of progressive jaundice and marked hepatomegaly.Initially,based on enhanced computed tomography scan and angiography,Budd-Chiari syndrome was considered and balloon dilatation of significant hepatic vein stenoses was performed.However,addi-tional diagnostic procedures,including liver biopsy and bone marrow-exami-nation,revealed immunoglobulin kapa AL amyloidosis with extensive liver involvement and hepatic vascular compression.The disease course was progre-ssive and fatal,and the patient eventually died 5 mo after initial presentation of symptoms.CONCLUSION AL amyloidosis with isolated liver involvement is very rare,and can be easily misdiagnosed as a vascular disease.

Alkyl chain modulation of asymmetric hexacyclic fused acceptor synergistically with wide bandgap third component for high efficiency ternary organic solar cells

Herein,two asymmetric hexacyclic fused small molecule acceptors(SMAs),namely BP4F-HU and BP4F-UU,were synthesized.The elongated outside chains in the BP4F-UU molecule played a crucial role in optimizing the morphology of blend film,thereby improving charge mobility and reducing energy loss within the corresponding film.Notably,the PM6:BP4F-UU device exhibited a higher open-circuit voltage(V_(oc))of 0.878 V compared to the PM6:BP4F-HU device with a V_(oc)of 0.863 V.Further,a new wide bandgap SMA named BTP-TA was designed and synthesized as the third component to the PM6:BP4F-UU host binary devices,which showed an ideal complementary absorption spectrum in PM6:BP4F-UU system.In addition,BTP-TA can achieve efficient intermolecular energy transfer to BP4F-UU by fluorescence resonance energy transfer(FRET)pathway,due to the good overlap between the photoluminescence(PL)spectrum of BTP-TA and the absorption region of BP4F-UU.Consequently,ternary devices with 15wt%BTP-TA exhibits broader photon utilization,optimal blend morphology,and reduced charge recombination compared to the corresponding binary devices.Consequently,PM6:BP4F-UU:BTP-TA ternary device achieved an optimal power conversion efficiency(PCE)of 17.83%with simultaneously increased V_(oc)of 0.905 V,short-circuit current density(J_(sc))of 26.14 mA/cm^(2),and fill factor(FF)of 75.38%.

Study on the force chain characteristics with coal dust layer and the three-body contact stiffness

To explore the influence of the meso-mechanical behaviors of the wet coal dust layers on the contact stiffness of mechanical bonding surfaces,a three-body contact model incorporating an interface with wet coal dust was constructed based on breakage theory.The model considered the mechanical surface morphology and contact characteristics of the wet coal dust.The force chain evolution laws of the wet coal dust layer were elucidated under the effects of gap filling and the cover layer,and the bearing characteristics of the three-body contact bonding surfaces were revealed by quantitative analyses of the number,length,collimation coefficient,and coordination number of the force chains within the wet coal dust layer.Finally,the three-body normal contact stiffness under various preload forces was computed and experimentally validated.The results demonstrate that the external load transfer path of the three-body contact bonding surfaces was from mechanical surface(macroscopic stress)to wet coal dust layer(mesoscopic force chains)and then to mechanical surface(peaks and valleys).The interactions among these three elements contributed to transforming the distributions of the macroscopic stresses and mesoscopic force chains to the locations at the peaks and valleys of the mechanical surface.Among them,the proportion of short force chains in the wet coal dust layer increased from approximately 0.8%–91%,while the proportion of long force chains exhibited an opposite changing trend.The force chain collimation coefficient initially increased and subsequently stabilized,reaching a maximum value of 0.93.A large number of broken,small particles in the wet coal dust layer mainly served to fill the gaps among large particles.The maximum relative error between the experimental and simulated values on the three-body contact stiffness is 7.26%,indicating that the simulation results can be an approximate substitute for the experimental results with a certain degree of accuracy and practicality.The research results are of great significance for understanding the contact characteristics of mechanical surfaces containing particulate media.

Establishment of Regional Green Innovation Value Chains:A Case Study on Tackling the Impeded Diffusion of Green Products

The green innovation value chain is a key step in transforming green,innovative scientific,and technological achievements into productive forces.The establishment of green innovation value chains based on value distribution rather than technical conditions can effectively overcome the common bottleneck faced by different nations during their green innovation endeavors,namely,the substitution of conventional products with green alternatives.This study investigates the impeded diffusion of green products and their underlying causes,analyzes the internal structure and mechanism of the green innovation value chain,and explores the establishment of regional green innovation value chains and the models available for value chain upgrading.

Service Function Chain Deployment Algorithm Based on Multi-Agent Deep Reinforcement Learning

Aiming at the rapid growth of network services,which leads to the problems of long service request processing time and high deployment cost in the deployment of network function virtualization service function chain(SFC)under 5G networks,this paper proposes a multi-agent deep deterministic policy gradient optimization algorithm for SFC deployment(MADDPG-SD).Initially,an optimization model is devised to enhance the request acceptance rate,minimizing the latency and deploying the cost SFC is constructed for the network resource-constrained case.Subsequently,we model the dynamic problem as a Markov decision process(MDP),facilitating adaptation to the evolving states of network resources.Finally,by allocating SFCs to different agents and adopting a collaborative deployment strategy,each agent aims to maximize the request acceptance rate or minimize latency and costs.These agents learn strategies from historical data of virtual network functions in SFCs to guide server node selection,and achieve approximately optimal SFC deployment strategies through a cooperative framework of centralized training and distributed execution.Experimental simulation results indicate that the proposed method,while simultaneously meeting performance requirements and resource capacity constraints,has effectively increased the acceptance rate of requests compared to the comparative algorithms,reducing the end-to-end latency by 4.942%and the deployment cost by 8.045%.

Sustainability Assessment of Banana (Musa spp.) Yield Gap Reduction through Value Chain Development Interventions in Smallholder Farming Systems in Manicaland, Zimbabwe

This study evaluated the effectiveness of donor supported agricultural value chain development projects in sustainably narrowing yield gaps for banana smallholder farmer producers in Manicaland, Zimbabwe. The study used a mixed methods research design that relied on farmers records for the quantitative analysis and focus group discussion and in-depth interviews for key experts for the qualitative aspects. A mix of regression analysis, t-tests, Pearsons’s correlation and analysis of variance statistical methods were used for the quantitative analysis while thematic response analysis was used for the qualitative engagements. The findings showed that by the end of the activity, the project had successfully narrowed the banana yield gaps to 18.66 tons per hectare working with a potential yield base of 40 tons. However, 5 years after the project closure the yield gap had fallen to 24.7 tons indicating a lack of sustainability of yield gap reduction. However, the yield gap slump does not override the fact that farmers on average were still able to sell approximately 5 tons per every 6 months after 5 years from the project closure which is beyond any poverty threshold. This suggests genuine upward economic mobility. Additionally, in analyzing what factors had the greatest influence on yield gap reduction, the access to fertilizer ranked highest where genetics, irrigation and improved agronomy followed in that respective order. The study further showed that farmers who receive value chain development support whilst at an already commercialized state tend to maintain productivity thresholds higher in comparison to those who are at a pre commercial state. This is evidenced by the fact that the pre commercial farmers had a yield reduction of 30.83 percent after 5 years of the project closure whereas the former realized a productivity growth of 7.84%. In conclusion, whilst the intervention was successful in transitioning farmers out of poverty, more investment should be made towards transitioning smallholder farmers to integrated soil fertility management practices and improvement of agronomic efficiency through stronger on field collaboration between research institutions, the government and development institutions.