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Multifunctional Nacre‑Like Nanocomposite Papers for Electromagnetic Interference Shielding via Heterocyclic Aramid/MXene Template‑Assisted In‑Situ Polypyrrole Assembly

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Nano-Micro Letters 2025年第3期17卷 37-54页

作者： Jinhua Xiong Xu Zhao Zonglin Liu He Chen Qian Yan Huanxin Lian Yunxiang Chen Qingyu Peng Xiaodong He National Key Laboratory of Science and Technology On Advanced Composites in Special Environments Center for Composite Materials and StructuresHarbin Institute of TechnologyHarbin 150080People’s Republic of China

Robust, ultra-flexible, and multifunctional MXene-basedelectromagnetic interference (EMI) shielding nanocomposite filmsexhibit enormous potential for applications in artificial intelligence,wireless telecommunication, and portable/wearable electronic *** this work, a nacre-inspired multifunctional heterocyclic aramid(HA)/MXene@polypyrrole (PPy) (HMP) nanocomposite paper withlarge-scale, high strength, super toughness, and excellent tolerance tocomplex conditions is fabricated through the strategy of HA/MXenehydrogel template-assisted in-situ assembly of PPy. Benefiting from the"brick-and-mortar" layered structure and the strong hydrogen-bondinginteractions among MXene, HA, and PPy, the paper exhibits remarkable mechanical performances, including high tensile strength (309.7 MPa),outstanding toughness (57.6 MJ m−3), exceptional foldability, and structural stability against ultrasonication. By using the template effect ofHA/MXene to guide the assembly of conductive polymers, the synthesized paper obtains excellent electronic conductivity. More importantly,the highly continuous conductive path enables the nanocomposite paper to achieve a splendid EMI shielding effectiveness (EMI SE) of 54.1 dBat an ultra-thin thickness (25.4 μm) and a high specific EMI SE of 17,204.7 dB cm2g−1. In addition, the papers also have excellent applicationsin electromagnetic protection, electro-/photothermal de-icing, thermal therapy, and fire safety. These findings broaden the ideas for developinghigh-performance and multifunctional MXene-based films with enormous application potential in EMI shielding and thermal management.

关键词： MXene Remarkable mechanical properties Heterocyclic aramid Electromagnetic interference shielding Polypyrrole Multifunctionality

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Machine learning-driven insights into biaxial strain-induced anomalous thermal conductivity enhancement of boron arsenide

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science China Technological sciences 2025年第5期68卷 5-18页

作者： Yikun LIU Yurong HE Tianqi TANG Jiaqi ZHU School of Energy Science and Engineering Harbin Institute of Technology Zhengzhou Research Institute Harbin Institute of Technology Heilongjiang Key Laboratory of New Energy Storage Materials and Processes National Key Laboratory of Science and Technology on Advanced Composites in Special Environments

Boron arsenide(BAs) is a promising integrated circuit thermal management material with ultra-high thermal conductivity(κ) and exceptional semiconductor properties. In practical devices, mechanical stress and strain caused by thermal expansion inevitably affect the thermodynamic properties of heat sink materials. Consequently, investigation of the effects of stress and strain on the κ of BAs is essential. Accurate assessment and regulation of the κ and phonon heat transport of BAs requires consideration of both three-phonon(3ph) and four-phonon(4ph) interactions. However, anharmonicity computation using density functional theory is computationally expensive, particularly for the fourth-order interatomic force constants. This work uses a machine learning-driven moment tensor potential method to evaluate higher-order anharmonicity and extends it to include fourth-order forces, accelerating the calculations significantly. Results show that the κ of BAs calculated using the moment tensor potential method when considering both 3ph and 4ph processes agrees well with experimental data. In contrast,considering the 3ph interaction alone causes κ to be overestimated. The machine learning approach reduces computational costs by approximately 94% while maintaining comparable accuracy to density functional theory. By solving the phonon Boltzmann transport equation, the thermal transport properties of BAs under biaxial tensile strains ranging up to 7% are evaluated. BAs shows an anomalous κ enhancement when including both 3ph and 4ph interactions, with a maximum enhancement of 15% at a small strain of 1%, primarily because of the weakening of the 3ph scattering. Beyond 2% strain, both the 3ph and 4ph scattering rates increase significantly, causing shorter phonon lifetimes and a monotonic reduction in κ. Additionally, the κ temperature dependence under strain is explored, highlighting temperature's role in modulating phonon scattering. This study provides machine learning-driven i

关键词： boron arsenide machine learning potential biaxial strain thermal conductivity enhancement phonon transport

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An Approach to Optimize the Mechanical Properties of Cylindrical Negative Stiffness Structures

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ce/papers 2025年第2期8卷 1078-1086页

作者： Liu, Xin Tan, Xiaojun Wang, Bing National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of Technology Harbin150080 China School of Civil Aviation Northwestern Polytechnical University Xi'an710072 China

Negative stiffness (NS) structure, as a type of mechanical metamaterial, possess numerous excellent properties and has broad potential applications in areas such as impact energy absorption, vibration damping, and noise reduction. However, their energy absorption efficiency is not high. Typically, incorporating fillers into honeycomb structures proves to be an effective strategy for augmenting the mechanical properties of honeycomb materials. In this study, we propose a model for a filled cylindrical NS structure (CNS), where the fillers are treated as springs to facilitate finite element simulation. Subsequently, we further investigate the fundamental mechanical properties and energy dissipation capacity of unfilled CNS structures as well as filled CNS structures employing distinct types of fillers, including linear elastic and viscoelastic fillers. The results indicate that linear elastic fillers do not have a positive impact on improving the energy dissipation capacity of CNS structures but can be used to adjust the response curve. When viscoelastic fillers are filled inside the CNS structure, they can effectively enhance the strength and energy dissipation capacity of the CNS structure. Moreover, the approach presented in this investigation holds significant reference value for the design of various mechanical metamaterials based on NS structures. © 2025 Ernst & Sohn GmbH.

关键词： Honeycomb structures

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From Coils to Crawls: A Snake-Inspired Soft Robot for Multimodal Locomotion and Grasping

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Nano-Micro Letters 2025年第1期17卷 1-16页

作者： Chen, He Chen, Zhong Liu, Zonglin Xiong, Jinhua Yan, Qian Fei, Teng Zhao, Xu Xue, Fuhua Zheng, Haowen Lian, Huanxin Chen, Yunxiang Xu, Liangliang Peng, Qingyu He, Xiaodong National Key Laboratory of Science and Technology On Advanced Composites in Special Environments Center for Composite Materials and Structures Harbin Institute of Technology Harbin150080 China Dongfang Electric Academy of Science and Technology Co. Ltd Chengdu611731 China Suzhou Research Institute of HIT Suzhou215104 China

Currently, numerous biomimetic robots inspired by natural biological systems have been developed. However, creating soft robots with versatile locomotion modes remains a significant challenge. Snakes, as invertebrate reptiles, exhibit diverse and powerful locomotion abilities, including prey constriction, sidewinding, accordion locomotion, and winding climbing, making them a focus of robotics research. In this study, we present a snake-inspired soft robot with an initial coiling structure, fabricated using MXene-cellulose nanofiber ink printed on pre-expanded polyethylene film through direct ink writing technology. The controllable fabrication of initial coiling structure soft robot (ICSBot) has been achieved through theoretical calculations and finite element analysis to predict and analyze the initial structure of ICSBot, and programmable ICSBot has been designed and fabricated. This robot functions as a coiling gripper capable of grasping objects with complex shapes under near infrared light stimulation. Additionally, it demonstrates multi-modal crawling locomotion in various environments, including confined spaces, unstructured terrains, and both inside and outside tubes. These results offer a novel strategy for designing and fabricating coiling-structured soft robots and highlight their potential applications in smart and multifunctional robotics. (Figure presented.) © The Author(s) 2025.

关键词： Programmable robots

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Optimal Design of Composite Structures for Unmanned Aerial Vehicles Based on Deep Learning

Optimal Design of Composite Structures for Unmanned Aerial V...

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15th Asia Conference on Mechanical and Aerospace Engineering, ACMAE 2024

作者： Xiang, Zijian Ma, Zhenyu Yang, Xixiang Deng, Xiaolong Lin, Guochang College of Aerospace Science and Engineering National University of Defense Technology Changsha410073 China National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9781643685892

Composite materials are characterized by their lightweight and high-strength properties. Modern drone bodies predominantly utilize laminate structures made from composite materials. This article explores the application of deep learning methods in the design process of drone composite material structures, aiming to achieve weight reduction while maintaining structural strength and stiffness. To this end, we first conducted a study on the mechanical properties of composite laminates and employed a generative adversarial network (GAN) model to perform an inversion analysis of the single-layer parameters of the laminate. Subsequently, we executed a finite element simulation study of the UAV composite structure and applied the GAN model for inversion analysis. The laminate layering parameters were optimized and analyzed. The results indicate that the deep learning approach significantly enhances the accuracy of parameter inversion and the efficiency of layering design for composite laminate structures, demonstrating substantial application value for the optimal design of UAV composite material structures. © 2025 The Authors.

关键词： Laminated composites

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Material response model with artificial neural networks for ablation analysis of lightweight silicone-modified phenolic matrix nanocomposites

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composites science and technology 2025年 267卷

作者： Xiao, Jie Fang, Guodong Zhang, Yisheng Qin, Xiaoqiang Wang, Hongyue Hong, Changqing Meng, Songhe National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of Technology Harbin150001 China

Polymer matrix thermal protection materials are developing towards lightweight, better thermal insulation and oxidation resistance to satisfy the requirements of planetary entry vehicles, which have a strong gas-solid interaction in the aerodynamic heating environment. A material response model with an artificial neural network (ANN) is developed to study the thermochemical responses of the lightweight silicone-modified phenolic matrix nanocomposites. The ANN is designed to determine the real-time dimensionless char blowing rate and wall enthalpy for the material response model. A constant offset of the dimensionless char blowing rate is added to account for the contribution of multiple constituents of the material surface to the ablation wall. The material response model is validated against three plasma heating test cases in terms of surface temperature, in-depth temperature, and recession. A three-step ablation mechanism is revealed through molecular dynamics simulations, comprising thermal decomposition of the polymer, phase separation/rearrangement, and an enhancement in crystallinity. The effect of ambient pressure on the ablation response is further investigated and found that the lower pressures can lead to higher surface material consumption and higher recession rate due to the reduced blowdown flux of pyrolysis gases. © 2025

关键词： Thermal insulation

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key materials for extreme high-temperature environments: Ultra-high-temperature ceramics and their composites

Extreme Materials

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Extreme Materials 2025年第1期1卷 38-66页

作者： Yuxuan Liu Hui Wang Jianchao Hao Yuan Cheng Shun Dong Ping Hu Wenbo Han Xinghong Zhang National Key Laboratory of Science and Technology on Advanced Composites in Special Environments and Center for Composite Materials and Structures Harbin Institute of Technology Harbin 150001 China

With the advancement of hypersonic vehicles, extreme high temperature environments have imposed increasingly stringent requirements on the performance of thermal protection systems. Consequently, the development of high-performance thermal protection materials capable of withstanding extreme conditions has become a primary focus of current research. Ultra-high temperature ceramics (UHTCs) and their composites, known for their excellent oxidation resistance and ablation performance, are regarded as highly promising non-ablative thermal protection materials. This paper provides a systematic review of recent research progress on UHTC composites in several key areas, including innovations and optimizations in fabrication processes, exploration of toughening strategies and mechanisms, in-depth studies on oxidation and ablation resistance mechanisms, and the development and potential applications of high-entropy ceramics. Furthermore, the paper discusses the practical application prospects of UHTCs and their composites in extreme environments, analyzes the current technical challenges, and proposes future research directions and priorities.

关键词： Extreme environments materials Ultra-high temperature ceramics (UHTCs) Toughening and strengthening Oxidation and ablation Hypersonic vehicles

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An SPH model reconstruction framework with fragment mapping method for multiplate structure hypervelocity impact simulation

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Advances in Space Research 2025年第11期75卷 8140-8157页

作者： Cao, Xu Zhou, Jianqiu Xu, Huadong Song, Di Miao, Changqing National Key Laboratory of Science and Technology on Advanced Composites in Special Environment Harbin Institute of Technology Harbin150001 China School of Basic Medical Sciences Harbin Medical University Harbin150001 China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan Chengdu611731 China

Smoothed Particle Hydrodynamics (SPH) method is widely used in hypervelocity impact analysis, but it is computationally inefficient for common multiplate structures, such as multi-shock, mesh double-bumper, and stuffed shields. To improve the efficiency and accuracy of the SPH method, a reconstruction framework is proposed, including a fragment identification method, a fragment mapping method, and a sequential modeling and simulation approach. In the reconstruction framework, the total impact simulation of a multiplate structure consisting of n plates is decomposed into n individual impacts on each plate. To reduce the computation for each impact, a fragment identification method and a fragment mapping method are developed. Fragments generated from the impact with the i-th plate (i © 2025 COSPAR

关键词： 3D reconstruction

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Acoustic Emission Behavior of Carbon Fiber Bundle Under Tensile Load

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Experimental Mechanics 2025年 1-11页

作者： Yang, Z. Fang, G. School of Mechanical Engineering Yancheng Institute of Technology Yancheng China Science and Technology On Advanced Composites in Special Environments Key Laboratory Harbin Institute of Technology Harbin People’s Republic of China

Acoustic emission (AE) is widely used to study the progressive damage of composite materials. Traditionally, the AE method focuses on assessing structural damage by experimentally testing AE signals. However, the application of mechanical methods to theoretically predict AE signals during the progressive damage process of dry fiber bundles has been limited. The primary objective of this study is to establish a theoretical method for predicting AE signals during the tensile fracture process of dry fiber bundles. This model comprises three key components: (1) Single Fiber Fracture Dynamics Model: This component analyzes the motion of the fracture cross-section at the moment of fiber breakage. (2) Point Sound Source Model: Utilizing the motion of fiber cross-sections as a source, this model analyzes the acoustic signals generated during one single fiber fractures. (3) Monte Carlo Model: This model simulates the progressive fracture of the dry fiber bundle by aggregating the AE signals from individual fiber fractures. It generates a comprehensive time-domain signal profile by summing the contributions from each fracture event. To validate the model's effectiveness and accuracy, a comparison was made with existing prediction models and available experimental data. The experimental results were found to be in good agreement with the theoretical predictions. This theoretical model has been thoroughly validated and can be applied to analyze AE signals in other brittle dry fiber bundles, providing valuable insights into their fracture behaviors.

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Residual tensile behavior of carbon fiber/phthalonitrile composites after isothermal and anisothermal heating

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composites Communications 2025年 57卷

作者： Yang, Jinchuan Wang, Dongqing Hu, Jiqiang Ji, Chunming Wang, Bing National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of Technology Harbin 150001 China

The residual mechanical properties of resin-based composite materials exposed to high-temperature environments will significantly decrease. Phthalonitrile has great potential to serve as the matrix for new-generation lightweight resin-based thermal protection composite material, while the residual mechanical properties of phthalonitrile composites after thermal effect have not been fully studied and are pressing. In this study, the residual tensile behavior of unidirectional carbon fiber-reinforced phthalonitrile composites after isothermal and anisothermal heating are investigated. The strength attenuation of carbon fibers in high-temperature environments is the main factor causing the decrease in the tensile strength of carbon fiber reinforced phthalonitrile composites, while the thermal decomposition of phthalonitrile resin has a relatively small impact. The residual tensile strength prediction models with high fitting accuracies based on pyrolysis degree and mass loss are constructed for materials subjected to isothermal and anisothermal heating, respectively. Unidirectional carbon fiber reinforced phthalonitrile composites have higher tensile strength retention after isothermal and anisothermal heating compared to those with quasi-isotropic layup. © 2025

关键词： Flame exposure Phthalonitrile Polymer-matrix composites (PMCs) Strength prediction

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