Articles in press have been peer-reviewed and accepted, which are not yet assigned to volumes/issues, but are citable by Digital Object Identifier (DOI).
Abstract: The diffusive behavior of nanoparticles in complex fluid environments is widely observed in natural and industrial processes. In contrast to classical Brownian diffusion, nanoparticles in complex fluids exhibit anomalous diffusion characteristics. Understanding its mechanisms and developing control approaches hold significant scientific importance and application value across fields such as biology, physics, medicine, and engineering. This article provides a systematic review of the research progress on anomalous diffusion of nanoparticles in complex fluid environments. First, the core features of anomalous diffusion that go beyond classical Brownian motion are elucidated, and the main theoretical frameworks and research methods are outlined. Second, mechanisms and models of three specific types anomalous diffusion, i.e., subdiffusion, superdiffusion, and Brownian yet non-Gaussian diffusion, are introduced in detail. The regulation mechanisms of diffusion behavior based on external field effects and intelligent design are also explored from the perspective of the coupling of mechanics and statistical physics. Finally, key challenges and future directions in modeling, experimental analysis, and applications in this field are summarized.
Xue C D, Zheng X, Hu G Q. Anomalous diffusion and manipulation of nanoparticles in complex fluid environments. AdvancesinMechanics, in press. doi: 10.6052/1000-0992-26-004.
Abstract: Touch, as one of the five primary human senses, carries crucial information related to environmental interaction, spatial perception and physical perception. In recent years, with the rapid advancement of human–machine interaction, how to efficiently and realistically reproduce haptic information has become a central challenge in building immersive interaction systems. However, traditional haptic devices are often limited by single functionality, complex structure, bulky size and weak integration, making it difficult to simultaneously achieve multimodal haptic reproduction and wearability. To overcome these bottlenecks, mechanical metamaterials, with their ultra-compact architectures, programmable mechanical properties and multifunctional integration capabilities, have demonstrated remarkable potential in haptic devices. This paper systematically reviews the mainstream functionalities of mechanical metamaterials and the practical integrability with corresponding haptic modalities, highlighting their potentials in haptic systems through programmable Poisson’s ratios, snap-through stabilities, various stiffness, and mode switching. Furthermore, typical haptic feedback application scenarios (VR/XR entertainment, medical rehabilitation, disability assistance and human–machine collaboration) are discussed from a system-level perspective in terms of enabling pathways and integration strategies. Finally, the challenges faced by mechanical metamaterials in haptic feedback are summarized, and future prospects are envisioned in the context of intelligent structural design, micro/nanoscale manufacturing and interdisciplinary convergence.
Zhang Z, Jia C, Jiang H Q. Mechanical metamaterials empowering haptic feedback. AdvancesinMechanics, in press. doi: 10.6052/1000-0992-25-030.
Abstract: Magnesium alloys, owing to their high specific strength and stiffness, offer significant potential for lightweight structural applications. However, corrosion fatigue remains a critical challenge that limits their reliable use in safety-critical load-bearing components. A comprehensive understanding of corrosion fatigue behavior, together with the development of robust life prediction models and effective protection strategies, is therefore essential to promote their broader engineering application. In this context, the present paper reviews the research progress on the macroscopic behavior, microscopic mechanisms, and life prediction of corrosion fatigue in magnesium alloys. First, it summarizes the effects of intrinsic factors of magnesium alloys, corrosive media, and loading conditions on their macroscopic evolution characteristics of corrosion fatigue. Second, the underlying damage mechanisms are discussed, with particular emphasis on insights gained from in situ and ex situ characterization techniques, as well as commonly employed numerical simulation approaches. Third, the current state of corrosion-fatigue life prediction models is systematically evaluated. Finally, the main findings are summarized, and key challenges and future research directions are highlighted.
Kang G Z, Ao N, Fu Z H, Li H, KAN Q H. Research progress on corrosion fatigue behavior and life prediction of magnesium alloys. AdvancesinMechanics, in press. doi: 10.6052/1000-0992-26-008.
Abstract: Rarefied gas transport is prevalent in critical fields such as aerospace, vacuum technology, micro- and nano-systems, and inertial confinement fusion. Particularly in extreme processes like spacecraft atmospheric reentry and near-space hypersonic flight, the flow exhibits prominent multiscale characteristics, accompanied by complex multiphysics coupling effects including molecular internal energy excitation, chemical reactions, and radiation. These features significantly increase the complexity of kinetic modeling, leading to severe computational bottlenecks for conventional numerical methods and restricting the accuracy and efficiency of large-scale engineering simulations. To address these challenges, this paper systematically introduces the general synthetic iterative scheme (GSIS), a multiscale numerical method characterized by both fast-convergence and asymptotic-preserving properties. The core of this method lies in the construction of macroscopic synthetic equations that are physically consistent with the kinetic equations. By leveraging the superior information propagation efficiency of parabolic macroscopic systems to guide the evolution of hyperbolic kinetic equations, GSIS breaks the inherent bottleneck where computational grids and time steps are constrained by the molecular collision scales, enabling unified and efficient simulation across all flow regimes. Theoretical analysis and numerical validation demonstrate that GSIS not only rigorously recovers the macroscopic fluid dynamics description in the continuum limit, but also exhibits exceptional iterative convergence efficiency across the entire range of Knudsen numbers. Furthermore, the GSIS framework possesses remarkable model compatibility and algorithmic extensibility. Through a variety of typical benchmarks, this paper highlights its high-precision and high-efficiency performance in problems involving polyatomic gases, high-temperature radiation, multi-component mixtures, and unsteady complex flows. Concurrently, the GSIS mechanism can be deeply integrated with stochastic particle algorithms, achieving significant acceleration of the Boltzmann and Enskog equations within the Direct Simulation Monte Carlo framework. Additionally, this paper presents the recent progress of GSIS in multiscale aerodynamic shape optimization, flow stability analysis, and turbulence-rarefaction interactions, showcasing its promising applications in frontier areas such as transition and turbulence in near-space hypersonic flight. Overall, GSIS provides an essential tool for multiscale numerical simulations of rarefied gas flows, and offers strong theoretical support and practical pathways for high-reliability, high-efficiency engineering simulations and optimization.
Zeng J N, Zhang Y B, Li Q, Su W, Wu L. General synthetic iterative scheme for the simulation of rarefied gas flows. AdvancesinMechanics, in press. doi: 10.6052/1000-0992-26-007.
Abstract: In complex unsteady wakes, the fluid–structure interaction (FSI) modes can differ significantly from those under uniform flows, often involving rich physical mechanisms. This paper reviews recent advances in three representative FSI phenomena: Vortex-induced vibration (VIV) of cylinders, flapping of flexible plates, and locomotion of swimming/flying organisms. These phenomena are widely observed in both nature and engineering applications and span self-excited, active, and hybrid FSI modes. First, we compare the response modes under uniform and unsteady wake inflows. Results show that incoming vortices can substantially amplify vibration amplitudes of cylinders and plates, potentially triggering new instabilities. In contrast, biological swimmers may actively exploit incoming vortices by modulating their motions to enhance propulsion efficiency. Furthermore, this paper discusses potential applications of such FSI modes in complex wake flows, including enhanced energy harvesting from flow-induced vibrations and the development of bioinspired robots with improved sensing and decision-making capabilities. Finally, the challenges and future research directions in this area are outlined to guide further exploration.
Han P, Zhang J D, Li Y R, Fan D X, Huang W X. Fluid–structure interaction modes under complex unsteady vortices: A review. AdvancesinMechanics, 2026, 56(3): 1-62. doi: 10.6052/1000-0992-25-022.
Abstract: With the global aging population and high incidence of chronic diseases, major intractable conditions such as cardiovascular diseases, tumors, and diabetes have become primary challenges to public health and socioeconomic development worldwide. Their pathological processes are often accompanied by abnormal remodeling of the extracellular matrix (ECM) and disruption of mechanical homeostasis, rendering traditional treatments ineffective in reversing these conditions. Recent studies reveal that actively modulating the mechanical properties of the ECM through principles of materials science and engineering to precisely mediate cellular behavior can effectively activate endogenous tissue repair, significantly promoting tissue regeneration. This research strategy, termed force-materials science, involves actively designing materials to leverage force−structure−function relationships for proactive control of the mechanical environment within biological systems. Based on this concept, this paper proposes: systematically identifying the molecular composition of the ECM from a matrixomics perspective and deconstructing its mechanical information encoding; utilizing matrix biomechanics to understand cell−ECM interaction mechanisms and decipher pathological ECM “re-encoding” processes; and, grounded in deep understanding of the ECM’s mechanical microenvironment, exploring matrix engineering technologies for “de-encoding” abnormal ECM and restoring function by integrating matrix biomechanics principles, ultimately achieving the goal of matrix therapy for endogenous tissue repair. Specifically, this paper introduces the composition and dynamic coding of the ECM, systematically summarizes the physiological/pathological changes in abnormal ECM mechanical microenvironments, and emphasizes the proposal and construction of novel matrix engineering and therapeutic strategies based on molecular targeting and material reconstruction. These efforts aim to provide new theoretical foundations and innovative approaches for the intervention of major intractable diseases and the advancement of regenerative medicine.
Xie Y Z, Liu Z X R, Xu F, Wei Z. Advances in matrix engineering and matrix therapy driven by extracellular matrix mechanics. AdvancesinMechanics, 2026, 56(3): 1-30. doi: 10.6052/1000-0992-25-029.
Abstract: Nanofluidics studies flow and mass transport in confined systems with characteristic dimensions ranging from about 100 nm down to the sub-nanometer scale. Nanofluidics is not simply a scaled-down version of macroscopic flow, where the predominant forces and boundary conditions are fundamentally different from the macroscopic flows, giving rise to new phenomena and enabling new applications. The development of nanotechnology enables the fabrication of nano- and even sub-nanometer structures, enabling to investigate the flow and transport in such small scales. This review summarizes the state-of-art in nanofluidics, including concepts, open questions, experiments advances, and examples of application. First, we outline the key scientific questions in nanofluidics, including boundary slip in nanochannels, coupling between flow and mass transport, two-phase flow in confinement, and the breakdown of continuum descriptions at the smallest scale. Second, we summarize key nanofabrication techniques and experimental methods used to probe flow and transport in such small confinement. Third, we describe multiscale simulation approaches used in nanofluidics—from continuum models to molecular dynamics and the ab initio simulations—and illustrate how they unvail the mechanisms of flow in nanoscale. Finally, we discuss emerging application areas in nanofluidics, such as drag reduction, energy conversion, chemical engineering, artificial intelligence, advanced manufacturing, and diagnosis. Overall, by bridging molecular-scale dynamics and macroscopic transport, nanofluidics has emerged as an important direction in fluid mechanics with broad interdisciplinary applications.
Yan M, Luan S Y, Shi D L, Gu Y W, Lu J J, Xie Y B. Nanofluidics: Flow and transport at nanoscale. AdvancesinMechanics, 2026, 56(3): 1-51. doi: 10.6052/1000-0992-25-034.
Abstract: Uncertainty quantification (UQ) and uncertainty-based design optimization (UBDO), as an emerging design paradigm for flight vehicles, provide a systematic methodological framework for addressing the precise characterization, propagation, and design optimization of uncertainties. This paper reviews the core concepts and key technologies in this field. It summarizes the uncertainty challenges associated with critical systems and significant environmental conditions of flight vehicles. Based on the latest research progress, five key research directions are identified: (1) High-dimensional uncertainty quantification and efficient propagation: Constructing an adaptive high-dimensional UQ framework by integrating techniques such as dimensionality reduction, compressed sensing, and low-rank tensor decomposition to effectively address the “curse of dimensionality”. (2) Hybrid uncertainty quantification and efficient propagation: A unified framework is established to accommodate various types of uncertainties—including probabilistic, interval, fuzzy, and evidence theory. The computational efficiency for complex, multi-source uncertainty problems is further enhanced by incorporating surrogate modeling and active learning strategies. (3) Multi-level and multi-fidelity UQ framework: Achieving dynamic and optimal allocation of computational resources across models of varying fidelities by integrating techniques like generalized approximate control variates and adaptive multi-index stochastic collocation. (4) Uncertainty-based design optimization algorithms and frameworks: Unifying probabilistic constraints and robustness metrics within a multi-objective optimization and decision-making framework under uncertainty, enabling trade-off optimization among performance, reliability, and robustness through single-loop and decoupled optimization strategies. (5) Uncertainty design and analysis based on artificial intelligence techniques: Centered on physics-informed neural networks, this direction incorporates physical knowledge and multi-source data to establish intelligent frameworks for uncertainty quantification and optimization.
Zhang H R, Wang Y, Hong D P. Research advances in uncertainty quantification and design optimization for flight vehicles. AdvancesinMechanics, 2026, 56(3): 1-35. doi: 10.6052/1000-0992-25-032.
Abstract: Metal laser additive manufacturing technology exhibits the capability for precision forming of complex components in high-end fields such as the aerospace, defense, and medicine. However, its broader application in advanced engineering fields remains constrained by manufacturing defects; fluctuations in power density and cooling rate during processing can readily induce defects such as thermally induced porosity and high-stress cracking, thereby posing interdisciplinary challenges for in-situ monitoring and quality control. This paper reviews the establishment of a multi-dimensional detection technology system and systematizes the advancements in key testing methods and technologies. Specifically, mainstream sensing technologies, including optical and acoustic sensing, when integrated with advanced intelligent algorithms, facilitate dynamic identification of surface defects and extraction of internal defect characteristics. Multi-source data fusion further establishes a collaborative analysis framework linking microscopic molten pool behavior to macroscopic geometric accuracy. Additionally, emerging techniques, such as high-speed synchrotron radiation imaging, offer accurate cross-scale online observation tools for investigating the initiation and evolution mechanisms of defects. Current technologies are constrained by challenges such as multi-source noise interference and low synchronization efficiency of multi-physics field data. Future research should focus on the in-depth integration of multi-sensor detection technology with machine learning, explore online intelligent detection approaches, and develop full-process quality prediction models driven by digital twins. This study intends to provide theoretical synthesis and technical pathway analysis to address the common challenges of defect monitoring and forming accuracy control in the additive manufacturing process.
Jiang C, Feng W, Long Z Y, Wang P X, Zhao J Z, Zheng B, Xie H M, Liu Z W. Research progress on online monitoring technology for metal laser additive manufacturing. AdvancesinMechanics, 2026, 56(3): 1-39. doi: 10.6052/1000-0992-25-027.
Abstract: Through structural design, architected materials can achieve extraordinary properties and therefore have found broad applications across biomedical, aerospace, energy, and environmental domains. Incorporating non-periodicity into structural design helps mitigate the brittleness arising from localized failure in conventional periodic materials, leading to improved toughness, damage tolerance, and defect insensitivity. However, the added complexity imposes computational and manufacturing challenges, calling for the development of new theoretical frameworks and design methodologies. Spinodoid materials/spinodal-like materials, characterized by spinodal topology, represent a class of non-periodic architected materials, and the research paradigm established for these materials can be generalized to predict mechanical performance and guide structural design of various complex non-periodic architectures. This review focuses on spinodoid structures as a representative example, introducing their modeling principles, effective mechanical properties, design and manufacturing methods, and typical applications. We summarize the current research and propose future research directions, with the aim of charting a roadmap for non-periodic architected materials based on the advanced methods across the integrated “modeling–design–manufacturing–application" pipeline.
Zhang J, Yan Z M, Zhuang Z, Liu Z L. Spinodoid non-periodic architected materials: Mechanical performance prediction, design, and applications. AdvancesinMechanics, in press. doi: 10.6052/1000-0992-26-001.
Abstract: Injury biomechanics primarily investigates human responses and injury outcomes based on mechanical principles. A thorough understanding of specific injury mechanisms and associated tolerance limits is essential for improving human protection. Crash test dummies, serving as anthropomorphic substitutes that replicate human biomechanical responses during impact, are widely applied in automotive safety, sports rehabilitation, forensic analysis, military protection, and aerospace engineering. In the field of automotive safety, crash test dummies constitute essential tools for injury assessment and are generally categorized into physical dummies and computational human surrogates. This paper reviews the development history of both physical and virtual dummies, with a particular focus on parametric design methodologies used in automotive crash dummy development. Moreover, the paper discusses future trends in injury assessment techniques, with the aim of contributing to the advancement of injury biomechanics and supporting technological progress in automotive safety.
Tian T F, Liu Z X, Wang L Z. Advances in automotive crash test dummies based on injury biomechanics. AdvancesinMechanics, in press. doi: 10.6052/1000-0992-25-033.
Abstract: The rise of artificial intelligence (AI), particularly its transformative advance in algorithm and large-scale data processing, has provided a new path for humanity to address the energy crisis. As the ultimate form of future energy, nuclear fusion has advanced from basic research to the commercialization threshold after more than 70 years of development. This paper systematically elaborates on the current development status and key challenges of global nuclear fusion research, deeply analyzes the application scenarios and practical achievements of AI technology in key fields such as nuclear fusion device control, data processing, model optimization, and risk management, discusses the transformative impact of the integration of AI and nuclear fusion on the global energy pattern, and finally looks forward to the future development direction and industrial layout of this field, providing a reference for promoting the energy revolution and scientific and technological progress.
Liang Y F. AI+ nuclear fusion: A crucial opportunity for the transformation of the global energy pattern. AdvancesinMechanics, in press. doi: 10.6052/1000-0992-25-045.
Abstract: Energetic composites constitute a class of architected material systems whose mechanical, thermal, and safety-related properties can be tailored over a broad design space through multiscale structural design. However, their overall performance is often constrained by degradation mechanisms originating at the particle/matrix interface, including thermal mismatch, stress concentration, and interfacial debonding. These effects are further amplified under extreme service conditions, thereby undermining structural reliability and operational safety. Fundamentally, this challenge reflects a highly coupled multi-objective optimization problem involving mechanical, thermal, and safety performance. Interfacial engineering offers an effective pathway to address this challenge. By introducing functionalized coatings at the particle scale, stress transfer and heat-transport behaviors can be synergistically regulated, enabling energetic composites to access performance regimes in which mechanical robustness and thermal stability coexist. Despite rapid advances in experimental characterization, theoretical modeling, and data-driven approaches, a unified framework that systematically links interfacial architectural design with mechano–thermal synergy remains lacking. This review provides a comprehensive survey of recent progress in interfacial coating strategies for energetic composites. Emphasis is placed on coating material systems, fabrication routes, and microstructural descriptors, together with their influences on macroscopic mechanical and thermal properties. The interfacial coupling mechanisms responsible for coordinated enhancements in stiffness, strength, thermal conductivity, and thermal expansion behavior are further elucidated. On this basis, an integrated “materials–microstructure–process–characterization–model–artificial intelligence (AI)” framework is outlined to guide the rational design and scalable manufacture of multifunctional energetic composites and structural components.
Zeng X, He R Q, Guan W F, Lu Q S, Ma W B, Zhao Z Y, Lu T J. Cross-scale mechanisms of interfacial coating-enabled synergistic regulation of mechano–thermal properties in energetic composites. AdvancesinMechanics, in press. doi: 10.6052/1000-0992-25-040.
Abstract: The problem of elastoplastic crack propagation in isothermal or room temperature environments, typified by the failure of thin-walled aircraft metallic structures, poses a severe challenge to the applicability of linear elastic fracture mechanics (LEFM) and J-integral theory due to characteristics such as large-scale yielding and stable crack growth. Despite the successive proposal of various parameters—including fracture strain, crack tip opening angle/displacement (CTOA/D), essential work of fracture (EWF), and incremental crack-tip integrals—the distinct physical interpretations, ambiguous interrelationships, and questionable “transferability” of these parameters have severely hindered the development of a unified theory and its engineering applications. To address this dilemma, this paper constructs a unified theoretical framework for elastoplastic fracture, adopting the fracture process zone (FPZ) as the core perspective under the simplifying assumptions of neglecting thermal source effects and body forces. This framework not only offers a unified and self-consistent explanation for historical conundrums such as the Rice paradox but also systematically demonstrates that mainstream parameters, including incremental integrals, CTOA/D, fracture strain, and EWF, are intrinsically equivalent to the driving force on “steady FPZ”, thereby revealing the inherent unity among existing elastoplastic fracture parameters. Furthermore, by elucidating the thermodynamic significance of the power balance laws for a body with an extending crack, the framework establishes the FPZ as an independent thermodynamic system possessing “autonomy”, providing a solid theoretical foundation for the “transferability” of fracture parameters. This paper aims to systematically elaborate on the construction process, core arguments, and academic significance of this theoretical framework.
Lu L K. Mode I elastic-plastic fracture theory from the perspective of fracture process zone. AdvancesinMechanics, in press. doi: 10.6052/1000-0992-25-041.
Abstract: With their uniquely three-dimensional, wavy whiskers, harbor seals (Phoca vitulina) exhibit exceptional underwater sensing capabilities. Studies have shown that harbor seals can detect weak vortices with flow velocities as low as 245 μm·s−1 and can track hydrodynamic trails left by targets up to 180 m away and as long as 35 s earlier. These abilities highlight the remarkable advantages of harbor seal whiskers in underwater vortex sensing and hydrodynamic trail tracking. Bio-inspired sensor designs based on harbor seal whiskers have thus become a research hotspot in biomimetic science and engineering, demonstrating promising applications in underwater target detection and recognition. This paper first reviews research progress on the morphological characteristics and geometric modeling of harbor seal whiskers, summarizing and comparing the strengths and limitations of different simplified models. It then provides an overview of advances in the hydrodynamic characteristics of biomimetic whisker models, covering wake features and vibration responses of such models in uniform and wake flows, the sensing mechanisms of harbor seal whiskers, interactions within whisker arrays, and applications of artificial intelligence methods in sensing-signal recognition. Finally, based on the shortcomings and key open questions in existing research, the paper outlines several research directions that warrant attention for advancing biomimetic science and engineering applications of harbor seal whiskers.
Zhao H H, Ji C N, Li X H, Zhang Z M, Yuan D K, Zhang J F, Chen W L. A review of morphology characteristics and sensing mechanisms of harbor seal whiskers. AdvancesinMechanics, in press. doi: 10.6052/1000-0992-25-037.
Abstract: A dynamic multiscale topology optimization method based on equivalent static load method (ESLM) and structural genome databases (SGD) is proposed in this paper. This method transforms the complex transient dynamics optimization problem into a multi-condition static optimization problem by ESLM, and replaces the asymptotic homogenization analysis with the pre-trained graph convolutional neural networks (GCNN) model in the structural genome databases, which significantly improves the computational efficiency. In the optimization framework, the moving morphable component (MMC) method is used to describe the macro and micro structures, and the collaborative optimization design between the two scales is realized. The effectiveness of the proposed method is verified by a numerical example of MBB beam structure under transient load. The results show that the maximum strain energy of the optimized structure is reduced by about 20.80%, the average strain energy is reduced by 51.44%, and the maximum displacement amplitude of the load point is reduced by 72.31%. It shows the superior performance and engineering application potential of this method in multi-scale structural topology optimization and impact resistance design under dynamic conditions.
Lin X J, Xu Z A, Guo T T, Bian H W, Guo X, Du Z L. Dynamic multiscale topology optimization based on equivalent static load method and structural genome databases. AdvancesinMechanics, in press. doi: 10.6052/1000-0992-26-002.
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