The incorporation of 2D materials into memristive devices has boosted advancements in non-volatile memory (NVM), and other related applications including brain inspired neuromorphic systems, artificial intelligence (AI)-machine learning (ML), optoelectronics, photonics, implementing arithmetic operations, and hybrid CMOS architectures. These advancements have taken place among limitations on silicon-based flash and surging data demands, stimulating the research of innovative materials and architectures, particularly for the next generation memory devices. This comprehensive review expands upon the cutting-edge developments in 2D material-based memristors, including their fabrication techniques, performance evaluation, fundamental properties, diverse applications, further challenges in their modernization, and future road map. By emphasizing the distinct characteristics of 2D materials, we reviewed their memristive behavior and highlighted the major contributions by leading researchers over the years. Focus of this review is on the incorporation of graphene (derivatives of graphene), transition metal dichalcogenides (TMDs), and other 2D materials (like MXenes and nanocomposites) in various memristive architectures. The review paper systematically explored the specific roles of graphene and other 2D materials in memristor devices including their use as electrodes, active layers, barrier layers, interfacial layers, and tunnel layers. The major challenges faced by the 2D material based memristor technology hindering their advancement have been critically reviewed including the scalability, yield, hardware implementation, performance enhancement, fabrication techniques, material/device engineering, and commercialization of these devices. Workable solutions to those problems along with the clear and comprehensive road map of future directions for addressing these hurdles have been recommended to unlock the full potential of this transitional technology. This review provides an authoritative resource and compelling rationale for researchers working towards metamorphic memristor solutions by emphasizing the imperative role of 2D materials.

Understanding competitive adsorption behaviors and pore-filling mechanisms of multicomponent gas mixtures in metal–organic frameworks (MOFs) is essential for advancing gas separation technologies. This study explores the adsorption dynamics of CO2, CH4, and N2 in MIL-101(Cr), demonstrating how its unique topological structure determines adsorption capacity and governs competitive interactions. Pure CO2 and N2 exhibit edge-to-center pore-filling sequences, while CH4 fills from the center outward. In mixed gas systems, CH4 dominates by reshaping the spatial distribution and filling sequence of CO2 and N2, while its own adsorption remains stable. Excess CO2 or CH4 inhibits competing gases from accessing adsorption sites, whereas excess N2 enhances CH4 adsorption, revealing a nuanced interplay of competitive effects. Furthermore, these interactions influence gas mobility, with excess molecules reducing the self-diffusion coefficients of other gases while increasing their own. This work also introduces a novel computational framework that integrates molecular-scale simulations with process-scale modelling to predict breakthrough curves of gas mixtures with high accuracy. The proposed two-stage adsorption process highlights MIL-101(Cr)’s exceptional potential for purifying CH4 from coal bed methane and biogas under ambient conditions. These findings underscore the utility of MIL-101(Cr) and computational innovations for sustainable energy applications and greenhouse gas mitigation.

Driven by the potential applications of ionic liquid (IL) flow for charging graphene-based surfaces in many emerging technologies, recent research efforts have focused on understanding ion dynamics and structuring at IL–graphene interfaces. Here, graphene colloid probe (GrP) atomic force microscopy (AFM) was used to probe the dynamics and ion structuring of 1-butyl-3-methylimidazolium tetrafluoroborate at graphene surfaces under various bias voltages. In particular, the AFM-measured nanofriction provides a good measure of the dynamic properties of the ILs at graphene surfaces. Compared with the IL at the unbiased graphene surface (0 V), the charged graphene surfaces with either negative (–1, –2 V) or positive (+1, +2 V) voltages favor a reduction in the friction coefficient by the IL. A higher magnitude of the bias voltage applied on the graphene surface with either sign (–2 or +2 V) results in a smaller friction coefficient than that at –1 and +1 V. In combination with the AFM-probed contact stiffness, adhesion forces, and ion structuring force curves with an ion orientational distribution according to molecular dynamics (MD) simulations, we discovered that the unbiased graphene surface (0 V) possesses randomly structured IL ions and that the graphene colloid probe is more likely to become stuck, resulting in more energy dissipation to contribute to a larger friction coefficient. Biasing of the graphene surface under either negative or positive voltages resulted in uniformly arranged ions, which produced a more ordered ion structure and, thus, a smoother sliding plane to reduce the friction coefficient. Electrochemical impedance spectroscopy (EIS) for the IL with graphene as an electrode demonstrated a greater ionic conductivity in the IL paired with the biased graphene than in the unbiased one, implying faster ion movement at the charged graphene, which is beneficial for reducing the friction coefficient.

Triboelectric nanogenerators (TENGs) generate electricity through contact electrification. However, the output power is limited by several factors across materials, device design, and mechanical systems. This article aims to analyze several strategies for enhancing the outputs of TENGs across four key aspects: (1) The fundamentals of charge generation to establish effective strategies for designing or selecting tribo-materials, including recent practical approaches to surface and bulk modifications; (2) structural designs that maximize TENG output; (3) the output enhancement strategies tailored to different types of mechanical energy for practical applications; and (4) mechanical systems that effectively modulate external mechanical energy to increase TENG output. Finally, we provide a future outlook, highlighting open opportunities and remaining challenges for TENGs.

Traditional lubricating greases are mainly derived from petroleum, which poses major environmental challenges due to their non-biodegradability and pollution issues. This study attempts to synthesize lignin-based green thickeners and explore their potential for developing green and fossil-free greases. A lignin-based gelator was successfully synthesized by reacting malic acid with lignin and epoxidized soybean oil, in which malic acid participated in both the esterification reaction and the ring-opening of the epoxy group. This synthesized gelator was used as the thickener to prepare greases with several different oils, e.g., castor oil, epoxidized soybean oil, rapeseed oil, PAO 15, and paraffin oil. It was found that combining this lignin-based gelator with castor oil and epoxidized soybean oil can be successfully used for preparing greases, while it does not work with other oils. Rheological studied showed that the 35 % gelator-castor oil grease exhibited strong gel-like behaviour, with storage modulus (G', 400 Pa) exceeding loss modulus (G", 40 Pa) and shear-thinning viscosity reducing from 106 to 104 mPa·s under stress. Comprehensive tribological studies on the developed greases show that lignin-based gelators significantly improve lubricant performance (about 20 % lower friction and around 40 % lower wear under a contact pressure of 2.72 GPa, reciprocating speed 0.1 m/s, and 80 °C). XPS analysis further revealed the ability of the developed grease to form a protective film on metal surfaces. This study demonstrates the great potential of lignin as a green thickener and provides new ideas for developing high-performance, green, and fossil-free greases.

Corrosion and wear pose significant challenges to equipment operating in harsh environments. Thus, protective coatings are needed. Anti-corrosion and anti-wear coatings are traditionally fossil-based and often contain environmentally harmful additives. Achieving anti-corrosion and anti-wear coatings based on environmentally benign and sustainable materials is important and a significant challenge. This work focused on the development of organosolv lignin-based polyurethane (OS_lignin-PU) coatings. The coatings were synthesised and evaluated for corrosion protection using electrochemical impedance spectroscopy (EIS) and for wear properties using nanoindentation and nano scratch measurements. EIS revealed that the optimal lignin content for corrosion protection purposes in the OS_lignin-PU coatings was 15 wt%. Moreover, addition of 15 wt% lignin to the OS_lignin-PU coatings also enhanced their wear resistance, as evidenced by reduced thickness loss during tribometer tests. The nano scratch measurements revealed that OS_lignin-PU coatings containing 15 wt% lignin exhibited the lowest scratch depth and friction coefficient. It is found that the developed lignin-containing coating exhibits remarkable corrosion and wear resistance, making it a promising sustainable material in various applications for pursuing sustainable development.

In this work, ultralow friction (0.054) of graphene was achieved under high contact pressure (1.03 GPa) and atmosphere environment via the operando formation of PbS quantum dots (QDs)/graphene heterojunction at the frictional interface. It is found that PbS QDs are trapped in graphene nanosheets via shear-induced rearrangement for obtaining the PbS QDs/graphene heterojunctions, which provide an excellent rolling effect to lower friction. It is also found that the heterogeneous PbS QDs/graphene tribofilms have a strong Pb-enriched function and heterojunction nanorod phase. Our objective is to uncover the physical and chemical mechanisms governing the friction of 0D/1D nanostructures within PbS QDs/graphene heterostructures through our studies. This research will enhance our comprehension of nanomaterials' frictional behavior while offering valuable guidance and optimization strategies for their application in mechanical engineering and functional nanomaterials. Consequently, our efforts aim to foster the advancement of nanoscience and technology, leading to additional scientific and technological breakthroughs.

The long-term intelligent machine condition monitoring system is essential in improving maintenance costs and decision-making. Triboelectric nanogenerator (TENG) has a great advantage in developing self-powered machine condition monitoring. The main issues preventing TENG for such applications are poor integration to machine components, limited operational range, and weak durability. In this work, durable non-contact TENG energy harvester adaptive is designed to mechanical shafts for harvesting rotational energy. The harvester is designed to automatically switch to the non-contact mode by using centrifugal force to avoid manual switching while operating over a wide range of speeds of 0–2000 rpm. The designed TENG generates a high output of up to 25 mW with excellent stability for >20 days of continuous operation and exhibits a high-power density of 286 W m−3. Moreover, a self-powered long-term continuous condition monitoring system is developed from a TENG sensor, energy harvester, and wireless module. The developed system successfully sends possible machine fault frequency every 74 min to the cloud and accessible anywhere. This is the only TENG design reported in the literature that can fully power a Wi-Fi module to send data. Hence, the result promises the practical application of the system in developing internet of things (IoT) in the Industry.

Unwanted ice build-up is a ubiquitous phenomenon in nature, which creates a series of catastrophic impacts on a wide range of human activities. Various anti/de-icing materials have been proposed for dealing with icing issues. Superhydrophobic anti/de-icing coatings have been widely reported since it has high efficiency and can be achieved in different ways. The surface functional groups have a significant influence on surface energy which is related to surface wettability. However, the influence of the coating surfaces functional groups on the anti-/de-icing properties is still not well studied. To investigate this influence, different groups with different hydrophilicity have been introduced to 3,3,4,4,5,5,6,6,7,7,8,8,8-Tridecafluorooctyl acrylate (TFOA) to fabricate several branch copolymer ice-phobic coatings. The anti-icing performance and the influence of group radius and interaction were studied. The acrylic acid TFOA showed a great superhydrophobic property (over 150° water contact angle), lower ice adhesion strength (<50 kPa), and lower wear depth compared with other copolymer coatings. The mechanism was studied via the molecular dynamic calculation carried out in ChemDraw software. The interaction between hydrophobic and hydrophilic groups and the steric length of the hydrophilic groups influence the surface structure and surface element distribution, further influencing the ice adhesion strength.

Intelligent machine condition monitoring is desirable to enable Industry 4.0 and 5.0 to create sustainable products and services via the integration of automation, data exchange, and human–machine interface. In the past decades, huge progress has been achieved in establishing sustainable machine condition monitoring systems via various sensing technologies. Yet, the dependence on external power sources or batteries for sensing and data communication remains a challenge. In addition, energy harvesting and sensing are dynamically growing research fields introducing various working mechanisms and designs for improved performance, flexibility, and integrability. Recently, triboelectric nanogenerators (TENG) have been applied as a new technology for energy harvesting and sensing to monitor machine performance. This manuscript presents the potential application of TENG for self-powered sensors and energy harvesting technology for machine condition monitoring, where the developmental aspects of TENG-based devices including the robustness of design and device integration to machine elements are reviewed. For better comparison, the performance of various reported devices is summarized. Simultaneously, the advanced results achieved in employing TENGs for various condition analysis techniques and self-powered wireless communication for machine condition monitoring are discussed. Finally, the challenges, and key strategies for utilizing TENGs for machine condition monitoring in the future, are presented.