Lingjie Zhang

High‑strength, tough hydrogels are urgently needed for biomedicine and soft robotics, yet single‑network architectures suffer from an inherent trade‑off between mechanical robustness and high water content. Herein, we propose a rectangular topological network (RN) composed of rectangular motifs in a single-network hydrogel via stoichiometric crosslinking of long and short polymer chains. This architecture achieves a high elastic modulus via dense intermolecular hydrogen bonds while maintaining large mesh sizes. Driven by a strain-induced hardening mechanism, the hydrogel achieves a simultaneous increase in strength and toughness. Successful fabrication using two crosslinkers demonstrates broad applicability. A representative PEG‑based RN hydrogel exhibits a Young’s modulus of 21.97 MPa, a toughness of 31.04 MJ·m⁻³, and a tensile strength of 7.72 MPa. Thus, we show that this facile and versatile RN strategy offers a route for high‑energy dissipation and can be extended to other platforms.

High-entropy materials (HEMs) have emerged as promising electrocatalyst platforms because compositional diversity enables tunable electronic structures and abundant active sites. With rising demands in energy conversion and environmental applications, theory now plays a central role in HEM design, in particular density functional theory (DFT), molecular dynamics (MD), and machine learning (ML). Recent advances in computational strategies for elucidating mechanisms and selecting optimal compositions are synthesized. The shift from experiment-driven studies to proactive, theory- and data-driven discovery is highlighted, enabled by the integration of high-throughput calculations with ML for efficient screening. Method limits and key challenges are assessed, including black-box interpretability, modeling of disorder and coverage, and gaps between theoretical models and experimental conditions, and directions in workflow standardization, open databases, and reproducible benchmarks are outlined. Building on these elements, a compact DFT-ML-MD closed-loop framework is proposed that links atomic-scale energetics to device-level metrics, with the aim of guiding the accelerated discovery and deployment of high-activity, durable high-entropy electrocatalysts for sustainable energy.

The development of high-strength, tough hydrogels is of profound importance for applications ranging from biomedicine to soft robotics. However, a longstanding challenge persists: reconciling mechanical robustness with essential attributes like transparency and biocompatibility. This dilemma stems from the fundamental absence of a structural motif capable of simultaneously supporting high load-bearing capacity, large extensibility, and high-water content. In this study, a novel strategy based on a rectangular topological motif is proposed. This architecture enables a high elastic modulus through a high density of intermolecular hydrogen bonds while maintaining large network mesh sizes. Meanwhile, the fracture strain and strength are significantly enhanced via a strain-induced hardening mechanism, leading to a simultaneous and remarkable improvement in both strength and toughness in single-network hydrogels. The rectangular topological network is constructed through stoichiometric crosslinking of equal amounts of long and short polymer chains. The successful fabrication of high-strength-toughness hydrogels using two different crosslinkers demonstrates the general applicability of the proposed strategy. FT-IR, NMR, and XRD confirmed the formation of the PEG-based rectangular single-network hydrogel with a Young’s modulus of 21.97 MPa, a toughness of 31.04 MJ/m³, and a tensile strength of 7.72 MPa. These values represent the highest mechanical performance reported to date for single-network hydrogels. This novel rectangular topological design strategy is facile and versatile, offering valuable guidance for the development of high-strength-toughness hydrogel materials.

A novel bio-based cardanol–phenol bisphenol, analogous to bisphenols A/F, with hormone receptor binding affinity nearly three orders of magnitude lower than that of bisphenol A, was designed, synthesized, and characterized. The synthetic strategy capitalizes on the differential reactivity at the ortho and para positions of phenol, induced by the cardanol side chain.

The oxygen evolution reaction (OER) plays a crucial role in water electrolysis and renewable energy conversion processes. Descriptors are utilized to elucidate the structure‐performance relationships of OER catalytic materials, yet each descriptor exhibits specificity to particular systems. Currently, there is a lack of effective descriptors to describe the relationship between electronic structure and OER performance in ionic systems. This study reveals for the first time that widely used OER descriptors, the d‐band center and charge transfer energy, are limited in their effectiveness for oxide systems dominated by ionic bonds, in which ionic interactions significantly enhance or suppress the catalytic activity. Furthermore, composite descriptors tailored for ionic systems are proposed, with findings extended to complex multi‐component and high‐entropy oxides. The results indicate that the metal d‐band unoccupied states parameter and the active states parameter can serve as effective OER descriptors for ionic catalytic materials. This work addresses the gap in OER descriptors for ionic systems, offering a new theoretical foundation and guidance for the development of efficient OER catalytic materials.

The oxygen evolution reaction (OER) plays a crucial role in water electrolysis and renewable energy conversion processes. Descriptors are utilized to elucidate the structure‐performance relationships of OER catalytic materials, yet each descriptor exhibits specificity to particular systems. Currently, there is a lack of effective descriptors to describe the relationship between electronic structure and OER performance in ionic systems. This study reveals for the first time that widely used OER descriptors, the d‐band center and charge transfer energy, are limited in their effectiveness for oxide systems dominated by ionic bonds, in which ionic interactions significantly enhance or suppress the catalytic activity. Furthermore, composite descriptors tailored for ionic systems are proposed, with findings extended to complex multi‐component and high‐entropy oxides. The results indicate that the metal d‐band unoccupied states parameter and the active states parameter can serve as effective OER descriptors for ionic catalytic materials. This work addresses the gap in OER descriptors for ionic systems, offering a new theoretical foundation and guidance for the development of efficient OER catalytic materials.

Silver (Ag) has difficult forming strong bonding with oxides due to its deep d band beneath the Fermi level and completely filled 4d orbital. Thus, it is difficult to fabricate silver-based composites with superior plasticity and processability because of the easy debonding at their interface. Herein, La₂Sn₂O₇ pyrochlore was used as a reinforcing phase for a silver matrix. The enhanced interfacial bonding strength of Ag-La₂Sn₂O₇ was confirmed both theoretically and experimentally, indicating that Ag could form more localized ionic bonding with La₂Sn₂O₇ than with SnO₂. The superior plasticity was further confirmed for the Ag-La₂Sn₂O₇ composite, as the uniform elongation (UE) of the Ag-La₂Sn₂O₇ composite was ~19%, i.e., ~14% higher than and 2.8 times that of the conventional Ag-SnO₂ composite. The plasticity enhancement mechanism was also unraveled by calculating the interfacial mobility. This work verified the usefulness of pyrochlore to fabricate silver-based composites with superior plasticity and also provides a new strategy for the construction of advanced silver-based composites for application in the electrical contact field.