In situ Transmission Electron Microscopy (TEM) provides powerful insights into the reaction mechanisms of Lithium-Sulfur (Li-S) batteries. However, distinguishing intrinsic electrochemical behaviors from artifacts induced by high-energy electron beam irradiation remains a critical challenge. Here, we systematically investigate the lithiation kinetics of sulfur nanoparticles triggered exclusively by electron beam irradiation, decoupling beam effects from electrochemical driving forces. We first conduct control experiments on pure lithium oxide (Li2O) and pure sulfur to assess their stability under electron irradiation, and then monitor lithiation behavior in a mixed system of sulfur and lithium oxide (Li2O), under varying irradiation times and temperatures. We report a striking "explosive" lithiation phenomenon, characterized by a massive volume expansion of up to 8300% and rapid kinetics (19312 nm2 s-1), which starkly contrasts with the ∼80% expansion observed in conventional electrochemical cycling. By conducting comparative experiments across a wide temperature range (25°C to -150°C), we identify the thermal effect of the electron beam as the dominant driving force; notably, the explosive reaction is completely suppressed at cryogenic temperatures (-150°C). Furthermore, we observe unique beam-induced artifacts, including directional cavity formation and rapid phase transitions from crystalline S to amorphous Li2S. This work establishes a critical baseline for distinguishing beam-induced damage from genuine electrochemical reactions in in situ TEM studies and provides nanoscopic insights into the thermal runaway mechanisms of sulfur cathodes under high-energy abuse conditions, underpinning accurate characterization of Li-S battery materials and development of advanced battery systems.

The self-assembly of block copolymers (BCPs) in solution is a primary method for creating functional nanostructures, however the real-time kinetic pathways—especially the formation of transient, metastable intermediates—remain difficult to observe. In this study, we use in-situ graphene liquid cell (GLC) transmission electron microscopy to directly visualize the phase separation dynamics of two vesicle-forming block copolymers, PS154-b-PAA49 and PS144-b-PAA22, in a DMF/water mixture. Our results reveal that the transition from spherical micelles to complex vesicles follows a three-stage kinetic pathway, rather than the traditional two-step model. We identify a critical transformation in which initial disordered aggregates undergo a “swallowing” phase followed by a “self-hollowing” stage. During this second stage, internal reorganization driven by interfacial energy minimization leads to the formation of metastable hollowed structures prior to reaching equilibrium. Molecular dynamics simulations and deep-learning-assisted image analysis support these observations, demonstrating that “self-hollowing” arises from the interplay between solvent-selective block interactions and local density fluctuations. By providing a high-resolution kinetic map of these morphological transitions, this work offers a clearer understanding of how to control BCP assembly to design precise porous nanomaterials.

This study constructed a coupled mechanical-electrochemical finite element model of Ti-6Al-4V dental implants considering surface micro-defects, and systematically analyzed the corrosion evolution under the combined effects of oral load and body fluid environment. The results show that preloading leads to stress concentration at the center of micro-defects, with the edges acting as anodes and preferentially dissolving, forming lateral corrosion propagation. A strong passivation film significantly inhibits the anodic reaction and reduces stress release efficiency. Oxygen concentration regulates passivation film formation, and a low-oxygen environment helps slow the overall corrosion rate. The model effectively reveals the corrosion mechanism of implants under complex environments, providing a theoretical tool for implant life prediction.

The pursuit of high-energy-density anode-free batteries (AFBs) has shifted the research focus toward the fundamental understanding of structural stability and interfacial chemistry. Layered cathode materials are central to this transition, yet their practical application in AFBs is hindered by complex failure mechanisms such as lattice strain and parasitic side reactions. This review systematically traces the evolution of advanced transmission electron microscopy (TEM) and its pivotal role in elucidating the structure-property relationships of these electrode materials. By integrating artificial intelligence (AI) and machine learning (ML) for high-throughput data processing, we highlight how modern characterization overcomes traditional limitations in image denoising and automated defect recognition. The discussion encompasses both lithium and sodium-ion systems, focusing on in situ and cryogenic TEM techniques that reveal real-time ion migration, phase transformations, and the evolution of fragile solid-electrolyte interphases. Furthermore, we emphasize the interdisciplinary synergy between electron microscopy and AI as a necessity for the “mechanism-driven” design of next-generation and high-stability batteries. This review provides critical insights into addressing the bottlenecks of layered cathode configurations. Furthermore, this review discusses the emerging role of AI in integrating fragmented research data into structured knowledge graphs. By organizing highly heterogeneous experimental findings into relational networks, AI can uncover latent structure-performance correlations, offering a data-driven roadmap for mechanism-guided material design and advanced characterization.

Soft-rigid interfaces in hydrogels often fail prematurely due to severe stress concentration caused by modulus mismatch. Traditional anti-peeling designs focus mainly on interfacial chemistry, overlooking the energy dissipation capacity of the soft adherend itself. Here we propose a hierarchical gradient-dissipative composite architecture for hydrogel systems that synergistically couples macroscopic stiffness modulation with microscopic molecular energy conversion. A through-thickness stiffness gradient is constructed in a polyacrylamide (PAAm) hydrogel by controlling crosslinker content, while microcrystalline cellulose (MCC) is uniformly dispersed to form a dynamic hydrogen-bond network. Under peeling, the gradient-softening structure progressively delocalizes stress and expands the process zone, while the MCC network dissipates energy through reversible bond rupture and fibril reorientation. This dual-scale mechanism yields an interfacial toughness of 1017 N/m-1.3- and 1.7-fold higher than uniform soft and stiff controls, respectively-as demonstrated by 90 degrees peeling tests and corroborated by finite-element simulations. The entire laminate is fabricated via rapid UV photo-curing in 30 min without plasma or surface treatment. This structure-driven strategy, combining tunable stiffness gradients with dynamic filler networks, offers a scalable platform for robust soft-rigid interfaces in flexible electronics, biomedical devices, and soft actuators.

Spent graphite (SG) anode materials are critical for achieving "carbon neutralization," but current recycling methods face challenges such as high energy consumption, environmental pollution, and limited practical applications. This study introduces a novel approach using Joule heating to construct an artificial solid-electrolyte interphase (SEI) layer with C-S-P bonds on the surface of SG in one pot. Characterizations via X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy confirmed the formation of C-S-P bonds and FeS nanoparticles. During cycling, these bonds facilitate the in-situ generation of a Li3P-based SEI layer, as verified by in-situ Raman spectroscopy and High-resolution transmission electron microscopy (HRTEM). This SEI layer improves Li+ transport and enhances fast-charging performance. The FeS nanoparticles and Li3PO4 coating layer, together with the in-situ formed Li3P-based SEI layer, formed a conductive network, thereby enhancing the conductivity and discharge performance of the graphite. The recycled graphite (RG) delivers a specific capacity of 101 mAh g-1 after 3000 cycles at 3 C, a nearly 2.5 times improvement over commercial graphite (CG). Full-cell and pouch-cell tests demonstrated superior performance under high-current conditions. This work offers a promising solution for high-value recycling of SG, advancing sustainable lithium-ion battery development.

Three-dimensional (3D) lattice structures exhibit unique mechanical properties, including a negative Poisson’s ratio and enhanced energy absorption, which make them superior to conventional materials. This study investigates the optimization mechanisms of three cross-scale design strategies—hierarchy, gradient, and disorder—on the mechanical performance of 3D lattices. By combining hierarchical topological reconstruction, gradient parameter adjustments, and disorder algorithms, 3D lattices significantly improve energy absorption, dynamic response, and multifunctional integration. These optimization strategies provide solutions for high-performance applications, such as impact protection and bone repair scaffolds, which are facilitated by advancements in additive manufacturing (AM) and intelligent optimization. However, challenges remain in multi-material AM and high-load integration, requiring further development to realize the full potential of 3D lattices. Future research will enhance their applicability, particularly in aerospace, biomedical, and energy absorption fields, thereby supporting the next generation of metamaterial systems.

Flexible hydrogel films are critical for flexible electronics and wearable devices, yet they face an inherent trade-off between interfacial peel resistance and structural integrity─an issue traditional methods (e.g., surface modification, uniform property tuning) cannot resolve. This study proposes a gradient-softening strategy to address this bottleneck. Hydrogel films with a through-thickness decreasing modulus gradient (0.24-0.034 MPa) were fabricated by adjusting cross-linker content (0.04-0.005 g) and water content (45-66 wt %): the surface layer maintained high stiffness for structural stability, while the substrate-adjacent layer softened to enable deformation and energy dissipation. Pure shear tests, multiangle (0°, 90°, 180°) peel tests, and finite element analysis (FEA) were conducted to characterize their performance and underlying mechanisms. The gradient-softening films exhibited a fracture toughness of 1253.5 J/m2, which significantly exceeded that of low-stiffness (526.1 J/m2) and high-stiffness (762.1 J/m2) uniform films. They also showed superior peel resistance: 914.6 N/m (90° average peel strength), 538.6 N/m (180° stick-slip amplitude), and 1544 N/m (0° maximum shear strength)─2.1-3.6 times higher than uniform films. Deformation observations and FEA show that the high fracture toughness of gradient-softening films is converted into superior interfacial peel resistance through "stiff-soft synergy": the stiff surface layer provides structural load-bearing capacity to avoid excessive deformation, while the soft substrate-adjacent layer enables strain redistribution and crack blunting to alleviate stress concentration, collectively increasing the energy required for peeling and thus realizing enhanced antipeeling performance; a quantitative correlation between gradient ratio and peel resistance was also revealed. The films remained stable after a 6 day sealed storage and 1000 cyclic bending tests. This strategy provides a novel solution for flexible electronics. It can be integrated with advanced manufacturing (e.g., multimaterial 3D bioprinting) to develop biomimetic interfaces, driving progress in wearable sensing and soft robotics.

The incorporation of metal nanoparticles (NPs) into the block copolymer (BCP) micelles has received considerable attention due to many potential applications as well as the variability in structures. One of the unsolved problems in this field is the incorporation mechanism of NPs into the desired position of controllable BCP micelles. In this paper, the procedure of polystyrene-block-poly(acrylic acid) (PS-b-PAA) deposition on Au NP surface has been captured by using an in situ graphene liquid cell. Attachment and direct deposition are the two pathways of polymer deposition that are decided by the surface chemistry of Au NPs. Additionally, three-dimensional electron tomography revealed that the NP morphology affects the volume and surface area of Au@PS-b-PAA core-shell NPs. This study offers new insights into polymer encapsulation and polymer imaging, which would benefit the design of core-shell NPs as well as their relative applications.

Porous current collectors (PCCs) exhibit enhanced electrochemical performance in terms of cyclic capacity, rate performance, and cycle life. However, the underlying chemo-mechanical coupled mechanisms are not yet fully understood. Here, lithium diffusion kinetics and the associated stress evolution in PCC-configured electrodes are systematically investigated through a one-way coupled theoretical framework. The symmetric PCC configuration induces a symmetric stress distribution relative to the midplane of active coatings along the thickness direction. This stress distribution is significantly influenced by the biaxial modulus and the thickness ratios of the PCC to the active coating. Compared to the traditional current collector (CC) at the equivalent average lithium concentration, the PCC electrode configuration can significantly lower stress levels, minimize the stress difference at the interface between the CC and the active coating, and decrease the energy release rate associated with interface delamination. These findings suggest that PCC-based electrode architectures can effectively mitigate mechanical failure and enhance structural integrity in symmetric electrode systems, highlighting the potential and critical importance of chemo-mechanical considerations in advanced battery engineering.

Solid electrolyte-free diffusion-dependent silicon (Si) is a highly promising anode for all-solid-state batteries (ASSBs), owing to its exceptional specific capacity and favorable lithiation potential. However, its practical implementation is significantly limited by rapid capacity degradation during cycling. To further elucidate the electrochemical failure mechanisms of Si anodes, this study systematically investigates the influence of particle size and mass loading on their electrochemical performances. The results indicate that mass loading of active material exerts a more pronounced impact on the performance degradation compared to particle size. Utilizing distribution of relaxation times (DRT) analysis derived from in situ electrochemical impedance spectroscopy (EIS), the kinetic behaviors of Si anodes were revealed across multiple time scales. Furthermore, capacity loss in the Si anode was quantified, demonstrating that nearly 50 % of the total capacity loss originates from lithium trapping within the Si anode. These findings provide critical insights into the electrochemical fading mechanisms of diffusion-dependent Si anode, offering valuable guidance for optimizing electrode design and enhancing the performance of Si-based ASSBs.

Due to close contact between various components, the volume change of active materials during lithiation or delithiation leads to inevitable constraint-induced stresses. This is particularly prominent in all-solid-state batteries, which impose relatively high external pressure on electrode particles. To date, the effects of this additional external pressure on chemo-mechanical coupled behaviors are not fully understood. To address these issues, this study develops a chemo-mechanical coupled model of electrode particles in Li-based batteries that incorporates the effects of surface stress and external pressure. The theoretical results indicate that lithiation kinetics and stress evolution within electrode particles are size-dependent, varying from bulk to nanoscale sizes. As particle size decreases, Li ions increasingly tend to accumulate near-surface storage sites, which is aggravated by external pressure due to the growing compressive stress and a resultant reduction in stress-dependent diffusivity. Moreover, the low-porosity surrounding matrix can exacerbate this tendency by amplifying the external pressure. The work enhances our understanding of capacitor-like behaviors of some nanosized electrode materials, which may arise from the combined effects of surface stress and external pressure. It also emphasizes the importance of interactions between neighboring components in chemo-mechanical coupled performance.

Despite polyethylene's (PE) inherent thermal stability, its mechanical performance deteriorates above 80 degrees C, leading to material failure in high-temperature applications or solvents. While commercial cross-linked polyethylene (XLPE) technologies-gamma-irradiation and peroxide-mediated cross-linking-address these issues partially, they suffer from uncontrolled network architectures, incomplete gelation, and performance compromises due to the introduction of additives or the formation of byproducts. Here, we report a benzocyclobutene (BCB)-based cross-linking strategy that eliminates the need for additives and the formation of byproducts while preserving PE's non-polar integrity. A norbornene-derived BCB monomer was rationally designed and incorporated into polyethylene via two pathways including ring-opening metathesis polymerization and coordination-insertion copolymerization. Thermal activation triggered a quantitative BCB [4 + 4] cycloaddition, achieving complete gelation and forming robust eight-membered ring networks. The cross-linked materials exhibited exceptional thermal stability, structural stability at high temperature, and intrinsic hydrophobicity. This methodology overcomes conventional challenges-residual catalysts and toxic byproducts-enabling the development of upgrading XLPE for potential applications. By combining molecular design with industrially viable thermal processing, this work establishes BCB chemistry as a platform for next-generation polyolefin thermosets.

Soft materials that can dynamically reconfigure its morphology upon interaction with environment or perceptions of information is currently thriving. Among these materials, magnetic hydrogels offer great opportunities for novel applications, particularly within biomedical field. However, the design of magnetic hydrogels is rather complicated since (i) it concurrently combines large deformation, magneto-active response and solvent diffusion, and (ii) the relationship remains unclear between the hydrogel performance and various magnetic field types, including uniform, nonuniform, and low-frequency alternating magnetic fields. Herein, a multiphysics model is developed to characterize the coupled processes of hydrogel magnetization, solvent diffusion and large deformation of the hydrogel, based on a general thermodynamically consistent framework. In particular, the magnetic boundary conditions are specified by solving the Laplace’s equation for the magnetic scalar potential if a nonuniform magnetic field is imposed. Various case studies are conducted to investigate the influences of magnetic permeability, field distribution coefficients, and hydrogel-magnet distance on the hydrogel performance. The numerical results show that the morphology of the hydrogel can be rapidly tailored and the way it deforms changes significantly depending on the magnetic field type used. Additionally, the hydrogel elongates along the field direction under a uniform magnetic field, while it shrinks when a nonuniform magnetic field is applied. The present multiphysics model may provide theoretical guidance for optimal design and control of the magnetic hydrogel system.

Correctly assessing overturning resistance of tree root systems is vital to designing sustainable and resilient urban forestry. In previous numerical modelling to investigate root anchorage behaviour, none of the root–soil contact models employed was able to capture slipping at the root–soil interface of complex root system architectures efficiently. This study proposed, derived and implemented a novel, computationally efficient, three-dimensional root–soil contact model that can capture interfacial strain-softening shearing behaviour for an arbitrary root system architecture independent from the spatial discretisation of the surrounding soil within a 3D finite-element model. Validation against existing pull-out test and centrifuge data revealed that the model well captured root pull-out and tree overturning behaviours. The validated model was subsequently used to investigate the transfer mechanisms of artificially generated root system architectures when growing with and without the presence of underground walls. Windward root segments that were more closely aligned with the lateral push provided the most contribution to resisting overturning. The presence of underground walls made the root system architecture highly asymmetric, forming a taproot complex that ‘interlocked’ the surrounding soil to provide overturning resistance. The walls also restricted the relative root–soil displacement, reducing the variability in the overturning moment.

The overturning resistance of trees under lateral loads depends on the interaction between their root system and the surrounding soil, with leeward lateral roots being particularly important. This study presents a parametric investigation into the behaviour of leeward lateral roots during tree overturning using the finite element method (FEM) based on a beam-on-nonlinear-Winkler-foundation (BNWF) approach. The model efficiently simulates large root–soil deformations using non-linear p-y connectors, the properties of which were calibrated against 2D plane-strain continuum FEM simulations and validated against analytical solutions for pipeline bearing capacity (an analogous problem). Simulations varied in root diameter, length, and material properties. A critical root length was identified, beyond which further increases in length do not enhance the root’s contribution to tree moment capacity, defining an optimal root length for peak resistance. The study further demonstrates that moment capacity is profoundly more sensitive to root diameter than to length. Initial rotational stiffness, which is highly relevant to non-destructive field-based winching tests, was also found to be primarily controlled by diameter and independent of length for most practical cases. A direct comparison between leeward and windward roots under specified rotation conditions confirmed the greater mechanical contribution of leeward roots to anchorage, which is consistent with field observations.

The surface morphology and shape of crystalline nanowires significantly influence their functional properties, including phonon transport, electrocatalytic performance, to name but a few. However, the kinetic pathways driving these morphological changes remain underexplored due to challenges in real-space and real-time imaging at single-particle and atomic resolutions. This study investigates the dynamics of shell (Au, Pd, Pt, Fe, Cu, Ni) deposition on AuAg alloy seed nanowires during core-shell formation. By using chiral/non-chiral seed nanowires, advanced imaging techniques, including liquid-phase transmission electron microscopy (LPTEM), cryogenic TEM, and three-dimensional electron tomography, a three-step deposition process is revealed: heterogeneous nucleation, nanoparticle attachment, and coalescence. It is found that colloidal Ostwald ripening, metal reactivity, and deposition amount modulate nanoparticle size and surface roughness, shaping final morphologies. Noble metal nanoparticles (Au, Ag, Pd, Pt) coalesce with seed nanowire along the 〈111〉 direction, distinct from that of other metals. These findings are consistent across different metals, including Ru, Cu, Fe, and Ni, highlighting the hypothesis of these processes in nanowire formation. These findings enhance traditional crystallographic theories and provide a framework for designing nanowire morphology. Additionally, our imaging techniques may be applied to investigate phenomena like electrodeposition, dendrite growth in batteries, and membrane deformation.

In various domains spanning materials synthesis, chemical catalysis, life sciences, and energy materials, in situ transmission electron microscopy (TEM) methods exert a profound influence. These methodologies enable the real-time observation and manipulation of gas-phase and liquid-phase reactions at the nanoscale, facilitating the exploration of pivotal reaction mechanisms. Fundamental research areas like crystal nucleation, growth, etching, and self-assembly have greatly benefited from these techniques. Additionally, their applications extend across diverse fields such as catalysis, batteries, bioimaging, and drug delivery kinetics. However, the intricate nature of 'soft matter' presents a challenge due to the unique molecular properties and dynamic behavior of these substances that remain insufficiently understood. Investigating soft matter within in situ liquid-phase TEM settings demands further exploration and advancement compared to other research domains. This research harnesses the potential of in situ liquid-phase TEM technology while integrating deep learning methodologies to comprehensively analyze the quantitative aspects of soft matter dynamics. This study centers on diverse phenomena, encompassing surfactant molecule nucleation, block copolymer behavior, confinement-driven self-assembly, and drying processes. Furthermore, deep learning techniques are employed to precisely analyze Ostwald ripening and digestive ripening dynamics. The outcomes of this study not only deepen the understanding of soft matter at its fundamental level but also serve as a pivotal foundation for developing innovative functional materials and cutting-edge devices.