Guangdong Institute of New Materials

Abstract In pathological microenvironments of diabetes, neuroinflammation, arthritis and other chronic diseases marked by oxidative stress, chronic inflammation, and bacterial infection, severely disrupt cellular physiological functions leading to failure of tissue regeneration. Existing therapeutic strategies are difficult to achieve simultaneous pathological causative factor removal and tissue regeneration due to the cascading pathological reactions triggered by endogenous enzyme insufficiency. Biomimetic artificial enzymes have been used to remodel pathological microenvironments, but the lack of precise structural design and unclear structure‐performance relationships limit their catalytic activities. As a new generation of enzyme‐like materials, atomically precise metal cluster enzymes (MCEs) can mimic the spatial hierarchical structure of natural enzymes and significantly enhance the enzyme‐like activity by regulating the configuration of the metal core and ligand, which is expected to enable pathological microenvironment repair. This review summarizes the design and controllable synthesis of atomically precise MCEs. The precise regulatory mechanisms of cluster enzymes are systematically analyzed for their mechanism of action in tissue repair microenvironments. In addition, the application of atomically precise MCEs for tissue regeneration in pathological microenvironments is discussed in detail. Finally, the future potential of atomically precise MCEs in pathological tissue regeneration is envisioned as perspectives.

ABSTRACT M CrAl X coatings are widely used as bond coats in thermal barrier coating systems to protect turbine blades from high‐temperature oxidation. However, their oxidation resistance is often restricted by uncontrolled microstructures, surface roughness, and aggregation of reactive elements (REs). In this study, high‐repetition‐rate femtosecond laser remelting (HRR‐FLR) is introduced as an advanced surface modification technique to overcome these limitations. Owing to its ultrafast self‐quenching and polishing effects, HRR‐FLR enables precise control of surface morphology, microstructural reconstruction, and REs redistribution. As a result, a uniform and periodic distribution of REs is achieved, which promotes the rapid nucleation and compact growth of α‐Al 2 O 3 and helps maintain the stability of the oxide scale under long‐term exposure. The HRR‐FLR‐treated coatings show remarkable performance, with the TGO growth rate reduced by approximately 80% and the oxidation lifetime extended to about 300 h compared with the untreated ones. Moreover, REs exhibit a dual function during oxidation: They act as preferential nucleation sites for Al 2 O 3 in the initial stage and segregate at TGO grain boundaries during growth, thereby suppressing outward cation diffusion. Overall, HRR‐FLR provides a novel and effective femtosecond‐laser‐based approach to tailor REs’ behavior and enhance the long‐term oxidation resistance of M CrAl X coatings, offering practical insights for the design of high‐temperature protective systems.

Thermomechanical Metamaterials The cold spray technique, primarily meant for component repair applications, preserves the original material properties owing to non-melting, producing dense, well-adhered coatings with minimal oxidation or thermal distortion. The image illustrates the powder metals being deposited on the substrate from a spray gun, with a magnified inset showing the jetting behavior of individual particle during high-energy impact. The orientation maps of the powders in-flight and after coating, highlights the microstructural evolution in each impacted particle viz-a viz the whole coating. More information can be found in the Research Article by Malar Vadani, Sabeur Msolli, Ayan Bhowmik, and co-workers (10.1002/adem.202501848).

Rapid bottom-up fabrication via additive manufacturing (AM) unlocks unprecedented design freedom for geometrically complex and lightweight titanium (Ti) alloys, a critical material for next-generation aerospace systems and 3C (computer, communication and consumer electronics) products. However, conventional AM Ti alloys face a persistent dilemma: achieving yield strengths above 1 GPa catastrophically degrades work hardening (typically < 2 GPa) and uniform ductility (< 5%). Here, we harness a strengthening-metastability synergy strategy via AM to demonstrate the powerful CoCrNi additive-strengthened Ti alloy with an outstanding combination of loss-free yield strength and drastically enhanced work hardening. Unlike traditional metastable alloys with incomplete phase transformation (β → β/α'), our design triggers a complete two-step martensitic transformation (β → β/α' → α'/α' twin) during deformation, without residual matrix and forming hierarchically mutual twin structures. This unique transformation pathway sustains a successive work hardening, achieving a record work hardening rate of 5.7 GPa and uniform elongation of 9.3% (triple that of base alloy), while maintaining 1030 MPa yield strength. The dual emphasis on synergy strategy and mechanistic innovation via the non-equilibrium AM process directly addresses the structural sector’s urgent need for high-performance yet sustainable metallic solutions.

This paper addresses the challenges of perceptual error propagation and limited decision reliability during mobile robot exploration. A novel autonomous exploration method is proposed, aiming to reduce the discrepancy between the robot's perception and the actual environment. The method begins with a boundary point detection mechanism based on feature richness, which directs the robot to prioritize exploration of structurally informative areas. Next, a time-varying covariance propagation model is developed to dynamically estimate pose confidence, thereby enabling more reliable decision-making. Finally, a deep reinforcement learning (DRL) strategy is integrated to learn optimal exploration behaviors that balance immediate gains with long-term benefits. Simulation and real-world experiments demonstrate that the proposed method outperforms mainstream approaches in terms of exploration coverage and localization accuracy, exhibiting strong generalization and practical applicability.