Aggregation Problem Research Articles

Construction of copper-functionalized two-dimensional zeolitic imidazole framework-7 (ZIF-7) nanosheets for enhanced antibacterial and antibiofilm performance

Marine biological pollution restricts the sustainable development of marine economy. Cu2O stands as a predominant antifouling agent for developing marine resources engineering. However, the problems of easy aggregation, rapid failure, and explosive release of copper ions limit the practical application of Cu2O. In this work, a novel copper-functionalized two-dimensional zeolitic imidazolate framework-7 nanocomposites ZIF-7@Cu2O was successfully fabricated by in-situ growth methodology. The emergence of ZIF-7@Cu2O nanocomposites solves the above problems in the use of Cu2O. Due to the huge specific surface area of the 2D ZIF-7 nanosheets and the electrostatic interactions, the cubic Cu2O, with a diameter of 250 nm, can be uniformly and firmly anchored on the surface of 2D ZIF-7 nanosheets, thus effectively avoiding the rapid dissolution of cuprous oxide and reducing the release rate of copper ions. Antibacterial experiments demonstrate that, in comparison to ZIF-7, Cu2O, and ZIF-7/Cu2O (physical mixture of ZIF-7 and Cu2O), ZIF-7@Cu2O exhibits superior antibacterial properties with 99.99 % against E. coli and the minimum inhibitory concentration (MIC) of 32 μg/mL. Furthermore, the reactive oxygen species (ROS) assay confirms ZIF-7@Cu2O could promote the generation of ROS. Antibiofilm formation results reveal that ZIF-7@Cu2O nanocomposites are effective in preventing biofilm formation of E. coli and P. aeruginosa at a low concentration (50 μg/mL). Finally, ZIF-7@Cu2O nanocomposites are employed as fillers to prepare ZIF-7@Cu2O/EP composite coating, the bactericidal kinetics and bacterial adherence on the coating surface are investigated. We believe this work could provide novel insights into the rational design of 2D ZIF-based material in the field of antifouling.

Transforming clay minerals into solvent-free nanofluids via an interfacial interaction: An experimental and simulation study

The emergence of solvent-free nanofluids (SFNs) has solved the problem of aggregation of conventional nanoparticles, resulting in better compatibility and dispersion of nanoparticles, and has led to the rapid development of their applications in various fields. However, at present, clay mineral-based SFNs (Clay-F) are rarely reported, and the general preparation method of clay mineral-based SFNs has not been investigated. Therefore, we report a general strategy for the construction of Clay-F. Clay-F have good flow properties at room temperature, and have higher dispersion stability under the steric hindrance effect of the long chain of the corona-canopy species. We demonstrated the universality of this method by grafting a corona-canopy species onto various clay minerals (montmorillonite, kaolinite, and attapulgite). At the same time, based on the lack of current research on the synthesis mechanism of Clay-F by simulation, the interaction mechanism between montmorillonite and corona-canopy species was finally confirmed and verified at the molecular level by quantum chemistry and molecular dynamics simulation, and the formation mechanism of Clay-F was further determined. Finally, to verify the concept, the adsorption performance of Clay-F for CO2 was investigated. This work expands the family of solvent-free nanofluids and provides new ideas for the application of clay minerals.

Binder assisted graphene derivatives as lubricants in copper: Improved tribological performance for industrial application

Originally derived from graphite, high-quality single-layer graphene is an excellent anti-wear and -friction additive in metal matrix. Here, the tribological performance of 3 different commercialized graphene derivatives (e.g., graphene oxide [GO], reduced graphene oxide [RGO], and graphene nanoplatelet [GNP]) as additives in a Cu matrix, were investigated from an industrial perspective. To increase the interaction of graphene derivatives with Cu particles, and addressing the aggregation problem of the graphene derivatives, different binders (polyvinyl alcohol [PVA] and cellulose nanocrystals [CNC]) were introduced into the system. Benefiting from such a strategy, a uniform distribution of the graphene derivatives in Cu matrix was achieved with graphene loading up to 5 wt%. After high-temperature sintering, the graphene is preserved and well distributed in the Cu matrix. It was found that the GNP-containing sample shows the most stable friction coefficient behavior. However, GO and RGO also improve the tribological performance of Cu under different circumstances.

PLLA/(MWCNTs-ZnO)@PDA composite with NIR-light induced shape memory effect, antibacterial properties and 3D printability

PLLA based shape-memory polymer composites with multifunctions have attracted growing attention in biomedical applications. Generally, a single nanofiller has the problem of insufficient functionalization and easy aggregation. Therefore, we design and fabricate polydopamine (PDA) surface modified MWCNTs-ZnO hybrid nanostructure ((MWCNTs-ZnO)@PDA). The dispersion of (MWCNTs-ZnO)@PDA in PLLA is improved in comparison with the pristine MWCNTs or ZnO. The results indicate that the (MWCNTs-ZnO)@PDA nanosystem shows a synergistic effect on the mechanical properties and photothermal properties of the composites. Comparative analysis with neat PLLA demonstrates a remarkable 17% increase in tensile strength and a 19% increase in elongation at break for PLLA/(MWCNTs-ZnO)@PDA composite. Additionally, the composites exhibit excellent NIR light-induced shape memory effects with a shape recovery ratio reaching 100%. Moreover, PLLA/(MWCNTs-ZnO)@PDA composites show favorable antibacterial activity against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). Furthermore, the polymer composites display good 3D printability, and the 3D-printed porous scaffold possesses high compressive strength and modulus. Also, the PLLA/(MCNTs-ZnO)@PDA scaffold can be compressed into a compact size and recover its original shape under NIR light irradiation. This work provides an approach to prepare novel shape-memory polymer composites with multifunctions including high strength, light-induced shape-recovery, antibacterial properties and printability.

Porous Prussian Blue Analogs Decorated Electrospun Carbon Nanofibers as Efficient Electrocatalyst for Overall Water Splitting

Metal-organic frameworks are becoming increasingly important in electrocatalysis as the hydrogen production sector grows. However, their electrocatalytic capability is limited by their inclination to agglomerate and the insufficient exposure of active sites. In this work, a three-step strategy was used to develop a bifunctional electrocatalyst with porous Prussian blue analogs supported on carbon nanofibers. The use of electrospun carbon nanofibers as conductive substrates can successfully address the problem of easy aggregation. Moreover, the etching procedure with tannic acid creates a porous structure that effectively regulates the electrical structure and exposes additional active sites. The resulting catalyst performs well in both the hydrogen evolution reaction and the oxygen evolution reaction, and also exhibits good stability in overall water splitting. The findings of this study present new concepts for the design and fabrication of metal-organic frameworks-based materials in the realm of electrocatalysis.

A versatile non-precious metal based electrode material endowed by layer-on-layer structure for methanol oxidation and supercapacitor applications

A high-performance non-noble metal-based electrode is the need of the hour to resolve the challenge of huge energy demand. Energy conversion and storage devices are the two ways to tackle this challenge. In this context, porous and non-noble metal-based electrodes NiCo2O4 (NCO), NiCo2O4/NiO (CNO) and NiCo2O4/NiO/rGO (CNOG) are developed as a bifunctional electrode for supercapacitor and methanol fuel cell applications. The binary composite of NiCo2O4 with NiO increases the redox sites and enhances its electrochemical activity. The low conductivity and problem of aggregation of transition metal oxides are overcome by developing a hybrid nanocomposite of NiCo2O4/NiO with reduced graphene oxide (rGO). The layer-on-layer morphology of CNOG, and the interfacial interactions among NiCo2O4 nanoflakes, NiO nanoparticles and rGO nanosheets increase the specific surface area of the hybrid, which leads to enhanced ion penetration into the active sites. CNOG acts as a potential anode catalyst for methanol oxidation with excellent structural stability. It exhibits a high methanol oxidation current density with low onset potential and faster kinetics. Symmetric supercapacitor CNOG//CNOG delivers specific capacitance of 59.4989 F/g, energy and power density of 6.69 Wh/kg and 698 W/kg respectively at 3 M KOH aqueous electrolyte. The solid-state symmetric supercapacitor (SSSC) using PVA/KOH electrolyte allows broader potential window, thereby outperforming the aqueous electrolyte. The SSSC exhibits specific capacitance of 88.8 F/g, energy and power density 20.84 Wh/kg and 1003 W/kg respectively at the same current density.

Effect of polymethyl methacrylate on in situ patterning of perovskite quantum dots by inkjet printing.

The preparation of perovskite quantum dots (PQDs) using an in situ inkjet printing method is beneficial for improving the problems of aggregation and photoluminescence (PL) quenching during long-term storage. However, the stability of PQDs prepared using this method is still not ideal, and the morphology of in situ-printed patterns needs to be optimized. To address these problems, this study introduced polymethyl methacrylate (PMMA) into the process of in situ inkjet printing of PQDs and explored the effect of PMMA on the in situ patterning effect of PQDs. The results showed that using a mixed precursor solution containing a small amount of PMMA as the printing ink can slow down the shrinkage process of ink droplets and improve the uniformity of film formation. As the printing substrate, PMMA provided a suitable high-viscosity environment for the in situ growth of PQDs. This could effectively suppress the coffee ring effect. In addition, the interaction between the C=O=C group in PMMA and metal ion Pb2+ in the CsPbBr3 precursor molecules was favourable to enhancing the density of PQDs. The prepared PMMA-coated CsPbBr3 quantum dots (QDs) pattern had high stability and could maintain at 90.08% PL intensity after 1 week of exposure to air.

An adaptive large neighborhood search for the multi-point dynamic aggregation problem

An adaptive large neighborhood search for the multi-point dynamic aggregation problem

Modular relaxed indistinguishability and the aggregation problem

<p>The notion of indistinguishability operator plays a central role in a large number of problems that arise naturally in decision-making, artificial intelligence, and computer science. Among the different issues studied for these operators, the aggregation problem has been thoroughly explored. In some cases, the notion of indistinguishability operator can be too narrow and, for this reason, we can find two different extensions of such notion in the literature. On the one hand, modular indistinguishability operators make it possible to measure the degree of similarity or indistinguishability with respect to a parameter. On the other hand, relaxed indistinguishability operators delete the reflexivity condition of classical indistinguishability operators. In this paper, we introduced the notion of modular relaxed indistinguishability operator unifying under the same framework all previous notions. We focused our efforts on the study of the associated aggregation problem. Thus, we introduced the notion of modular relaxed indistinguishability operator aggregation function for a family of t-norms extending the counterpart formulated for classical non-modular relaxed indistinguishability operators. We provided characterizations of such functions in terms of triangle triplets with respect to a family of t-norms. Moreover, we addressed special cases where the operators fulfill a kind of monotony and a condition called small-self indistinguishability. The differences between the modular and the non-modular aggregation problem were specified and illustrated by means of suitable examples.</p>

Gelatin and sodium alginate derived carbon/silicon composites as high-performance anode materials for lithium-ion batteries.

The volume expansion and poor conductivity greatly limit the application of silicon as an anode for lithium-ion batteries. Although nanocrystallization of silicon and its surface carbon coating can be improved to some extent, the serious problems of particle aggregation and structural instability have not been effectively solved. In this paper, gelatin and sodium alginate (GE + SA) derived carbon/silicon composites are successfully prepared by a liquid-phase method, the freeze-drying technique, and heat treatment. Si nanoparticles (NPs) are uniformly encapsulated in a three-dimensional network of N-doped carbon that is enriched with a rich pore structure. The reversible capacity of the particular Si@C composite electrode was maintained at 580 mA h g-1 after 300 cycles at a current density of 1 A g-1, showing good cycling stability. Meanwhile, the anode also has excellent rate performance with reversible capacities of 2230, 1458, 1101, and 686.6 mA h g-1 at current densities of 0.1, 0.5, 1, and 2 A g-1, respectively. The GE + SA derived carbon/silicon composites effectively solve the problems of particle aggregation and an unstable carbon/silicon interface structure and can become candidates for anode materials in lithium-ion batteries.

Joint-outcome prediction markets for climate risks.

Predicting future climate requires the integration of knowledge and expertise from a wide range of disciplines. Predictions must account for climate-change mitigation policies which may depend on climate predictions. This interdependency, or "circularity", means that climate predictions must be conditioned on emissions of greenhouse gases (GHGs). Long-range forecasts also suffer from information asymmetry because users cannot use track records to judge the skill of providers. The problems of aggregation, circularity, and information asymmetry can be addressed using prediction markets with joint-outcome spaces, allowing simultaneous forecasts of GHG concentrations and temperature. The viability of prediction markets with highly granular, joint-outcome spaces was tested with markets for monthly UK rainfall and temperature. The experiments demonstrate these markets can aggregate the judgments of experts with relevant expertise, and suggest similarly structured markets, with longer horizons, could provide a mechanism to produce credible forecasts of climate-related risks for policy making, planning, and risk disclosure.

What does it mean for consciousness to be multidimensional? A narrative review.

A recent development in the psychological and neuroscientific study of consciousness has been the tendency to conceptualize consciousness as a multidimensional phenomenon. This narrative review elucidates the notion of dimensionality of consciousness and outlines the key concepts and disagreements on this topic through the viewpoints of several theoretical proposals. The reviewed literature is critically evaluated, and the main issues to be resolved by future theoretical and empirical work are identified: the problems of dimension selection and dimension aggregation, as well as some ethical considerations. This narrative review is seemingly the first to comprehensively overview this specific aspect of consciousness science.

A Comparative Assessment and its Characterization of the Integrated Novel Water Pollution Index and its Statistical Approach for the Evaluation of Spatial Variations Using Factor Analysis: A Geospatial Approach in Mahanadi River, Odisha

Knowledge on water quality and its assessment, is necessary for both human health and environmental benefit. To account for spatial distribution, surface water quality parameters were analysed using integrated interpolation, geographical information systems (GIS) and multivariate analysis. A total of 19 locations and 13 water quality indicators were analysed, for a duration of six years (2018-2024). The study’s main objective was to assess the seasonal and regional variations in the water quality index (WQI) of Mahanadi River in Odisha using (N) pi, (S) pi, (O) pi, (C) pi, (E)y-WQI, Int w-WQI and Multivariate Statistical tools namely Factor Analysis (Fa). However, in the current investigation, pH, HCO3-, Na+, K+ and Mg2+ were within the permissible limits as per WHO standards. According to this study, the order of prevalence of ion concentrations is signified as follows: Mg2+ > Ca2+ > K+ > Na+ for cations and HCO3- > Cl- > SO42- for anions. The analysis of (N) pi indicated that about 15.79% of the sampled area, is affected by turbidity content, which is highly unsuitable for consumption. However, the remaining area (84.21%) is within the safe category of water. Classification of water based on (S) pi represents most of water samples falls between good water quality. Three unsuitable samples is noted as a result of excessive TDS and EC. In case of (O)pi, over 84.21% of the samples fell into categories of excellent, indicating the suitability for human activities. Using surface water quality results from (C) pi model, that reflects that out of 19 samples, 16 were suitable for drinking. Whereas 2 were polluted and 1 is seriously polluted, thus promotes unsuitability. Although there are several established techniques for calculating the WQI, the current study uses the quality index to consider a variety of water quality concerns in a cohesive manner. Meanwhile, in case of (E)y-WQI, 84.30% were excellent whereas 10% and 5% were poor and high polluted category. Over 42.11% of the samples fell into the categories of poor/very poor/not suitable, using the Int w-WQI diagram. Therefore, using these six approaches resembles a precise and comprehensive method to comprehend water quality in relation to pollution for human usage. In later stage, a factor analysis (Fa) can be applied to lessen the subjectivity and dimension of water quality characteristics. It reveals that the first five principal components explain almost 95.61% of dataset variation. This method removes the aggregation problems, weighting, opacity, and biases seen in traditional water quality evaluation techniques. The results of Fa suggested that turbidity, TKN, Ca2+ and Cl-, were the primary determinants of the water’s quality. The amount of organic pollution that was released into the river was influenced by anthropogenic activity in the vicinity of the river. In addition, the traditional dense habitation next to the river and the manufacturing waste that is transported from upstream to downstream are the sources of the high amount of TKN in urine and faeces. Therefore, given the high spatial distribution of geogenic turbidity and TKN occurrence, the study’s findings minimize uncertain causes and offer insights into surface water pollution regimes. They will also be useful to policy makers in helping to better plan, allocate resources, and manage the area’s potable water supply.

Enabling a scalable composite solid electrolyte via cathode-supported scale-up processing

The designed composite solid electrolytes (CSEs) address the aggregation problems of inorganic particles and the issue of difficult reproduction of 3D porous oxide electrolyte frameworks, providing a new pathway for the scale-up of CSE synthesis.

Preparation of AC-TiO2 by One-Step Activation Method and the Degradation Properties of Tetracycline Hydrochloride

A one-step activation technique for preparing activated carbon/titanium dioxide (AC-TiO2) photocatalyst was developed in this study, which achieved the expansion of activated carbon and the crystallization transition of titanium dioxide in one step. The properties of the generated materials were examined utilizing photocatalytic degradation of tetracycline hydrochloride (TC). The optimized sample (10%AC-TiO2) has a photocatalytic efficiency of 99.8% in 60 minutes and a degradation efficiency of more than 90% after 5 cycles. According to the experiment results, the combination of AC with TiO2 at high temperatures can induce a considerable number of oxygen vacancies in TiO2, hence increasing the reaction activation site, resulting in improved photocatalytic performance. A strong C-Ti chemical bond can be formed between AC and TiO2. Simultaneously, using AC as the substrate decreases the aggregation problem induced by the small nano size of TiO2 and increases dispersion uniformity. The unique carbon structure with a amount of pore structure can considerably improve the catalystand#39;s adsorption efficacy. Because of the synergistic effect of adsorption-degradation and the perfect photocatalytic activity of TiO2, the composite photocatalyst has exceptional photocatalytic efficiency, opening new possibilities for TiO2 modification.

Embracing fairness within a cross-efficiency hierarchical network DEA system

Several scholars have utilized hierarchical network Data Envelopment Analysis modeling techniques to assess the performance of complex structures. However, there has been limited consideration given to the integration of a peer-appraisal setting within a self-evaluation hierarchical context. This aims to enhance discriminatory power and mitigate the issue of unrealistic weighting scheme. To this end, our study extends the single-stage hierarchical additive self-evaluation model of Kao (Omega 51:121–127, 2015. https://doi.org/10.1016/j.omega.2014.09.008), by integrating the well-established cross-efficiency method. An original combination of a maxmin secondary goal model and the Criteria Importance Through Inter-criteria Correlation (CRITIC) method is proposed, to expand the basic hierarchical self-evaluation model. The maxmin model addresses the issue of the non-unique optimal multipliers obtained from the self-evaluation model, ensuring a more realistic weight scheme. The CRITIC method, that tackles the aggregation problem by objectively determining weights of criteria, rewards the minority and is conducive to a fairer evaluation. Results indicate that the proposed approach is more likely to obtain a unique efficiency and ranking score for the units under consideration. This study entails a numerical experimentation aimed at evaluating the efficiency of a set of 20 universities while validating the applicability of our proposed approach. To conclude, the practical applications of this methodological framework could encompass assessing services within the higher education sector or fostering sustainable development across various operations within a hierarchical structure.

Synthesis of three-dimensional porous ZIF-67/Bi2S3 heterojunctions with improved photocatalytic activity under visible-light irradiation

Firstly, Bi2S3 material was prepared by hydrothermal synthesis method, and the ZIF-67/Bi2S3 composite photocatalyst material was obtained by adding different contents of Bi2S3 in the synthesis process of ZIF-67. Three-dimensional porous ZIF-67/Bi2S3 heterojunction has a high specific surface area and provides a large number of reaction sites, which can be fully in contact with organic molecules, thereby improving light capture and photocatalytic reaction activity. The Bi2S3 semiconductor has a bandgap of about 1.3 eV and has strong light absorption in the visible region. ZIF-67 has a band gap of about 1.98 eV, which is not only porous but also has a good band structure. The combination of Bi2S3 and ZIF-67 can not only expand the spectral absorption range, but also ZIF-67 can be used as Bi2S3 carrier, which is conducive to photogenic carrier separation, solving the problem of Bi2S3 easy aggregation, and improving the processing efficiency. The morphology and elemental composition of ZIF-67/Bi2S3 were studied by XRD, SEM and XPS, and the synthesis of ZIF-67/Bi2S3 was successful. The absorption capacity of visible light was studied by UV–Vis DRS, and it was confirmed that ZIF-67/Bi2S3 composite photocatalytic material has extensive absorption of light. The results show that the prepared ZIF-67/Bi2S3-40 % heterojunction has good photocatalytic performance. Under visible light irradiation, the degradation rate of tetracycline hydrochloride (TCH) by ZIF-67/ Bi2S3-40 % was 91.1 % within 90 min, which was 1.25 times and 4.6 times of the absorption efficiency of naked ZIF-67 and Bi2S3, respectively (72.4 % for ZIF-67 and 19.8 % for Bi2S3). Then the valence band and conduction band values of semiconductor materials were calculated by M−S curve, and finally the degradation mechanism of ZIF-67/Bi2S3 composite photocatalyst was deduced.

Liberalism, polarization, and the aggregation problem

Liberalism, polarization, and the aggregation problem

Heuristic Search for Rank Aggregation with Application to Label Ranking

Rank aggregation combines the preference rankings of multiple alternatives from different voters into a single consensus ranking, providing a useful model for a variety of practical applications but posing a computationally challenging problem. In this paper, we provide an effective hybrid evolutionary ranking algorithm to solve the rank aggregation problem with both complete and partial rankings. The algorithm features a semantic crossover based on concordant pairs and an enhanced late acceptance local search method reinforced by a relaxed acceptance and replacement strategy and a fast incremental evaluation mechanism. Experiments are conducted to assess the algorithm, indicating a highly competitive performance on both synthetic and real-world benchmark instances compared with state-of-the-art algorithms. To demonstrate its practical usefulness, the algorithm is applied to label ranking, a well-established machine learning task. We additionally analyze several key algorithmic components to gain insight into their operation. History: Accepted by Erwin Pesch, Area Editor for Heuristic Search & Approximation Algorithms. Funding: This work was supported by the National Natural Science Foundation of China [Grant 72371157] and Shanghai Pujiang Programme [Grant 23PJC069]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0019 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2022.0019 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Platform for the Immobilizing of Ultrasmall Pd Clusters for Carbonylation: In Situ Self-Templating Fabrication of ZIF-8 on ZnO.

Incorporating metal clusters into the confined cavities of metal-organic frameworks (MOFs) to form MOF-supported catalysts has attracted considerable research interest with regard to carbonylation reactions. Herein, a self-templating method is used to prepare the zinc oxide (ZnO)-supported core-shell catalyst ZnO@Pd/ZIF-8. This facile strategy controls the growth of metal sources on the ZIF-8 shell layer and avoids the metal diffusion or aggregation problems of the conventional synthesis method. The characteristics of the catalysts show that the palladium (Pd) clusters are highly dispersed with an average particle size of ≈1.2nm, making them excellent candidates as a catalyst for carbonylation under mild conditions. The optimal catalyst (1.25-ZnO@Pd/ZIF-8) exhibits excellent activity in synthesizing α, β-alkynyl ketones under 1 atm of carbon monooxide (CO), and the conversion rate of 1, 3-diphenylprop-2-yn-1-one is 3.09 and 3.87 times more than those of Pd/ZIF-8 and Pd2+, respectively, for the first 2h. Moreover, the 1.25-ZnO@Pd/ZIF-8 is recyclable, showing negligible metal leaching, and, under the conditions used in this investigation, can be reused at least five times without considerable loss in its catalytic efficiency. This protocol can also be applied with other nucleophile reagents to synthesize esters, amides, and acid products.