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1. Correlating electronic properties with M-site composition in solid solution Ti _y Nb _{2- y} CT _x MXenes

   https://doi.org/10.1088/2053-1583/ac9e68  

   Yang, Yizhou; Han, Meikang; Shuck, Christopher E; Sah, Raj K; Paudel, Jay R; Gray, Alexander X; Gogotsi, Yury; May, Steven J (November 2022, 2D Materials)

   Abstract High electrical conductivity is desired in MXene films for applications such as electromagnetic interference shielding, antennas, and electrodes for electrochemical energy storage and conversion applications. Due to the acid etching-based synthesis method, it is challenging to deconvolute the relative importance that factors such as chemical composition and flake size contribute to resistivity. To understand the intrinsic and extrinsic contributions to the macroscopic electronic transport properties, a systematic study controlling compositional and structural parameters was conducted with eight solid solutions in the Ti y Nb 2− y CT x system. In particular, we investigated the different roles played by metal (M)-site composition, flake size, and d -spacing on macroscopic transport. Hard x-ray photoemission spectroscopy and spectroscopic ellipsometry revealed changes to electronic structure induced by the M-site alloying. Consistent with the spectroscopic results, the low- and room-temperature conductivities and effective carrier mobility are correlated with the Ti content, while the impact of flake size and d -spacing is most prominent in low-temperature transport. The results provide guidance for designing and engineering MXenes with a wide range of conductivities. 

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2. Insights in emerging Ti3C2Tx MXene-enriched polymeric coatings for metallic surface protection: Advancements in microstructure, anti-aging, and electrochemical performance

   https://doi.org/10.1016/j.porgcoat.2024.108606  

   Wang, Xingyu; Koirala, Sampada; Xu, Luyang; Li, Qiaobin; Lin, Zhibin; Qi, Xiaoning; Huang, Ying; Yang, Zhongyu; Wang, Danling (September 2024, Progress in Organic Coatings)

   This study provides new insights into the development of high-performance MXene-reinforced coatings to strengthen polymeric nanocomposites by enhancing microstructure, anti-aging properties, corrosion resistance, and robustness. MXene nanoparticles, labeled 25C and 80C, were synthesized using two different methods and incorporated at concentrations ranging from 0.1 to 2.0 wt.% into epoxy composites. The results demonstrated that 80C MXene, characterized by its finer morphology and superior dispersion, significantly improved the composite's performance compared to 25C. Electrochemical Impedance Spectroscopy (EIS) tests, along with long-term exposure assessments, suggested that incorporating both types of MXene nanoparticles enhances the corrosion protection performance of epoxy coatings over time. Micro-CT analysis revealed that both types of MXene substantially reduced defects and voids in the polymeric matrix, resulting in enhanced protective performance. This void reduction confirms that the incorporation of both 25C and 80C MXene improves microstructural integrity by filling voids and creating a more continuous, uniform structure, particularly in samples with 0.1% to 1.0% MXene flakes. The findings also highlighted MXene's potential in modifying the anti-aging properties of epoxy by inhibiting free radical generation and enhancing the composite's resistance against corrosion. Both 25C and 80C MXene-epoxy groups exhibited a clear trend of diminishing free radical intensity with increasing MXene concentration up to 1.0%, with free radical intensity reduced by over 40% compared to neat epoxy. The relationship between MXene concentration and reinforcement was also investigated, revealing superior corrosion protection properties at concentrations of 0.5-1.0 wt.%. This research offers a profound understanding of MXene's potential in polymer-based composites, laying a foundation for future investigations aimed at utilizing MXene to achieve superior material properties for a wide range of applications, particularly in the realm of metallic surface protection. 

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3. Bridged structures in ultrathin 2D materials for high toughness.

   https://doi.org/10.1016/j.mechmat.2024.104932  

   Paul, Kamalendu; Zhang, Chang-Jun; Yu, Chi-Hua; Qin, Zhao (April 2024, Mechanics of Materials)

   2D materials such as graphene, monolayer MoS2 and MXene are highly functional for their unique mechanical, thermal and electrical features and are considered building blocks for future ultrathin, flexible electronics. However, they can easily fracture from flaws or defects and thus it is important to increase their toughness in applications. Here, inspired by natural layered composites and architected 3D printed materials of high toughness, we introduce architected defects to the 2D materials and study their fracture in molecular dynamics simulations. We find that the length of the defects in the shape of parallel bridges is crucial to fracture toughness, as long bridges can significantly increase the toughness of graphene and MoS2 but decrease the toughness of MXene, while short bridges show opposite effects. This strategy can increase the toughness of 2D materials without introducing foreign materials or altering the chemistry of the materials, providing a general method to improve their mechanics. 

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4. Thermosensitive P(AAc‐co‐NIPAm) Hydrogels Display Enhanced Toughness and Self‐Healing via Ion–Ligand Interactions

   https://doi.org/10.1002/marc.202200320  

   Xu, Lin; Fu, Yu; Wagner, Robert J.; Zou, Xiang; He, Qingrui; Li, Tao; Pan, Wenlong; Ding, Jianning; Vernerey, Franck J. (July 2022, Macromolecular Rapid Communications)

   Abstract Hydrogels containing thermosensitive polymers such as poly(N‐isopropylacrylamide) (P(NIPAm)) may contract during heating and show great promise in fields ranging from soft robotics to thermosensitive biosensors. However, these gels often exhibit low stiffness, tensile strength, and mechanical toughness, limiting their applicability. Through copolymerization of P(NIPAm) with poly(Acrylic acid) (P(AAc)) and introduction of ferric ions (Fe³⁺) that coordinate with functional groups along the P(AAc) chains, here a thermoresponsive hydrogel with enhanced mechanical extensibility, strength, and toughness is introduced. Using both experimentation and constitutive modeling, it is found that increasing the ratio of m(AAc):m(NIPAm) in the prepolymer decreases strength and toughness but improves extensibility. In contrast, increasing Fe³⁺concentration generally improves strength and toughness with little decrease in extensibility. Due to reversible coordination of the Fe³⁺bonds, these gels display excellent recovery of mechanical strength during cyclic loading and self‐healing ability. While thermosensitive contraction imbued by the underlying P(NIPAm) decreases slightly with increased Fe³⁺concentration, the temperature transition range is widened and shifted upward toward that of human body temperature (between 30 and 40 °C), perhaps rendering these gels suitable as in vivo biosensors. Finally, these gels display excellent adsorptive properties with a variety of materials, rendering them possible candidates in adhesive applications. 

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5. Machine Learning‐Guided Discovery of Factors Governing Deformation Twinning in Mg–Y Alloys

   https://doi.org/10.1002/adem.202402485  

   Mastracco, Peter; Yu, Kehang; Wang, Xin; Murillo, Crystal; Melchor, Carlos; Belcher, Calvin_H; Schoenung, Julie_M; Lavernia, Enrique_J; Copp, Stacy_M (April 2025, Advanced Engineering Materials)

   Magnesium (Mg) alloys are promising lightweight structural materials whose limited strength and room‐temperature ductility limit applications. Precise control of deformation‐induced twinning through microstructural alloy design is being investigated to overcome these deficiencies. Motivated by the need to understand and control twin formation during deformation in Mg alloys, a series of magnesium‐yttrium (Mg–Y) alloys are investigated using electron backscatter diffraction (EBSD). Analysis of EBSD maps produces a large dataset of microstructural information for >40000 grains. To quantitatively determine how processing parameters and microstructural features are correlated with twin formation, interpretable machine learning (ML) is employed to statistically analyze the individual effects of microstructural features on twinning. An ML classifier is trained to predict the likelihood of twin formation, given inputs including grain microstructural information and synthesis and deformation conditions. Then, feature selection is used to score the relative importance of these inputs for twinning in Mg–Y alloys. It is determined that using information only about grain size, grain orientation, and total applied strain, the ML model can predict the presence of twinning and that other parameters do not significantly contribute to increasing the model's predictive accuracy. Herein, the utility of ML for gaining new fundamental insights into materials processing is illustrated. 

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