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In this study, a sophisticated two-step methodology is proposed that incorporates the Kolarik and Hashin–Hansen models to precisely evaluate the effects of the interphase on the Young's modulus of nanodiamond (ND)-filled composites. Initially, the ND particles and their surrounding interphase were modeled as a core-shell structure, and the modulus of this structure was calculated. Subsequently, the core-shell particles were considered as a dispersed phase within a polymer matrix, leading to determination of the Young's modulus of the nanocomposite. The results obtained using the proposed method agreed well the experimental data of various nanocomposite samples. Furthermore, a robust correlation was indicated between the interphase properties and nanocomposite modulus. Notably, an interphase characterized by a thickness of 10 nm, modulus of 50 GPa, and a filler volume fraction of 0.02 increased the nanocomposite modulus to more than 3 GPa, assuming a matrix modulus of 1 GPa. Additionally, the findings revealed that ND particles with radii smaller than 4 nm had a remarkable influence on the nanocomposite modulus, whereas a high ND modulus had a minimal effect.

In this work, the depth of the interphase in graphene polymer systems is determined by the properties of graphene and interfacial parameters. Furthermore, the actual volume fraction and percolation onset of the nanosheets are characterized by the actual inverse aspect ratio, interphase depth, and tunneling distance. In addition, the dimensions of graphene, along with interfacial/interphase properties and tunneling characteristics, are utilized to develop the power-law equation for the conductivity of graphene-filled composites. Using the derived equations, the interphase depth, percolation onset, and nanocomposite conductivity are graphed against various ranges of the aforementioned factors. Moreover, numerous experimental data points for percolation onset and conductivity are presented to validate the equations. The optimal levels for interphase depth, percolation onset, and conductivity are achieved through high interfacial conductivity and large graphene nanosheets. In addition, increased nanocomposite conductivity can be attained with thinner nanosheets, a larger tunneling distance, and a thicker interphase. The calculations highlight the considerable impacts of interfacial/interphase factors and tunneling distance on the percolation onset. The highest nanocomposite conductivity of 0.008 S/m is acquired by the highest interfacial conduction of 900 S/m and graphene length (D) of 5 μm, while an insulated sample is observed at D< 1.2 μm. Therefore, higher interfacial conduction and larger nanosheets cause the higher nanocomposite conductivity, but the short nanosheets cannot promote the conductivity.

The prediction of electrical conductivity in MXene nanosheet –polymer composites is a complex task that lacks a straightforward model. In this study, a model is proposed to predict the conductivity for the samples filled with MXene. Our proposed method takes into account various factors that influence the overall conductivity of the samples. The factors include the dimensions of MXene, volume fraction of MXene, percolation onset, tunnel distance, network fraction, and interphase thickness. The validity of the expressed method is examined using experimental data for several samples. Furthermore, an analysis of the relationship between the predicted conductivity and the parameters is conducted to confirm the reliability of the proposed methodology. The calculated outcomes from the proposed model exhibit a high level of accordance with the experimented conductivity of the samples. The maximum electrical conductivity of 16.1 S/m is achieved by the minimum tunneling distance of 1 nm, but the conductivity becomes very weak when tunneling distance in more than 11 nm.

MEL-type zeolite was selected as a typical porous material to theoretically capture the purification scenario of a model landfill leachate comprising PbCl2and CuCl2varying the pressure (2.4–48 MPa). Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) was applied to simulate the equilibrium state (0.5 ns) and dynamics of Pb2+, Cu2+and Cl−and water molecules (4 ns). Overall, the flux through the MEL membrane was increased by the increase of pressure. Lennard-Jones potential was used to explain non-bonded interactions between the membrane and ions as well as water molecules, in terms of values of energy and snapshots were taken from the evolution of purification phenomenon. The molecular patterns of accumulation of ions in the vicinity of zeolitic membrane were also captured as functions of the energies of the interaction between the contaminants and porous membrane. Mean square displacement (MSD) variation was indicative of the effect of pressure on dynamics of heavy metal separation; higher energies obtained at higher pressures, as reflected in alteration of van der Waals (vdW) force between ions and water molecules. The membrane revealed rejection above 70% for Pb2+, and almost 100% against Cu2+and Cl−, respectively. Density of water remained almost 1 g cm3, but depending on population of water molecules decreased after passage into the zeolite membrane.

Patchy interactions and heterogeneous charge distribution make nanoclay (NC) a promising biomaterial to interact with different biomolecules, polymers, and biological components. Many researchers have studied the polymer/clay nanocomposites in recent years. However, some deficiencies, such as poor impact strength, limit the application of polymer/clay nanocomposites in different fields. As a result, many attempts have been made to resolve this problem. Also, researchers have developed calcium carbonate (CaCO3) nanoparticles as biomedical materials. The nontoxic properties and biocompatibility of both CaCO3and NC make their nanocomposites ideal for biomedical applications. In this article, a detailed review of the ternary polymer nanocomposites containing NC and CaCO3is presented. The morphological, thermal, mechanical, and rheological characteristics, in addition to the modeling of behavior and foam properties, are studied in this article. In addition, the potential challenges for ternary nanocomposites and their biomedical applications are discussed.

In this study, a multi-scale method is developed using simple equations and meaningful factors to estimate the effective conductivity of carbon nanofiber (CNF) polymer composites, referred to PCNFs. The interphase around the networked nanofibers is considered in Step I, while the tunneling zone near the CNF/interphase is addressed in Step II. Finally, the effective conductivity of PCNFs, comprising CNFs, interphase, and tunnels, is estimated in Step III. The calculations of the multi-step method are validated by plotting the impacts of all factors and comparing them with experimental data from numerous CNF-filled samples. The minimum ranges of percolating onset (ϕp) and polymer resistivity in the tunnel (ρ) maximize the effective conductivity of system, but an insulative sample is observed at ρ> 60 Ω.m and ϕp> 0.015. Additionally, a tunneling distance (λ) of 1 nm and a contact diameter (d) of 60 nm yield the uppermost effective conductivity of 0.45 S/m, though d< 20 nm results in an insulative PCNF. Consequently, lower percolation onset, smaller polymer tunneling resistivity, narrower tunnels, and larger contact diameters enhance the effective conductivity in PCNFs. Furthermore, the sample with the lowest tunneling resistance demonstrates the highest effective conductivity. This evidence reveals the key role of electron tunneling in PCNFs, validating the multi-scale methodology.

The shift towards a renewable energy future requires the development of sustainable energy storage technologies. The pulp and paper industry generates large quantities of waste black liquor, containing mostly lignin, that is incinerated to generate heat and electricity to meet the energy demand of pulp and paper mills. This article aims to explore potential of converting waste black liquor lignin into valuable and high-performance carbon materials for use in the energy storage systems, such as batteries, supercapacitors, and fuel cells. The article compares the properties and performance of lignin-derived carbon materials to other carbon materials used in energy storage and discusses various synthesis methods. The article also addresses the challenges and opportunities associated with development and application of lignin-derived carbon materials, as well as their economic and environmental impacts. The article evaluates the technology and societal readiness levels for lignin-derived carbon materials and presents successful commercial case studies. In conclusion, lignin-derived carbon materials have potential for energy storage due to lower cost, sustainability, and less environmental impact compared to other materials. However, such methods currently represent a low technology readiness level (TRL) and face challenges such as low performance and scaling up production. To address such challenges, future research should focus on optimizing synthesis methods, tailoring properties, using composite materials, promoting sustainable production, conducting application-specific research, and standardizing testing protocols. The current study builds knowledge on the lignin-derived carbon materials for energy storage to key stakeholders and contributes to understanding their potential for sustainable and environmentally friendly energy storage solutions.

•Real-time product release and process control challenges in the dairy industry.•The dairy milk powder industry has unique characteristics.•Unique features of dairy industry need to be considered before PAT implementation.•An explicit focus on process control for real-time release testing is needed.