Houyang Chen

Graphene-based anodes often suffer from limited storage capacity and sluggish kinetics due to the chemical inertness of the pristine basal plane. Traditional activation strategies, such heteroatom doping or defect engineering, often compromise the superior mechanical integrity of materials. Herein we propose a nondestructive surface engineering strategy by demonstrating that mechanical buckling is not merely a physical deformation but also a potent chemical activator. Using first-principles calculations, we unravel the mechanism of curvature-induced rehybridization, where compressive strain disrupts the delocalized π-electron system, forcing a local transition from sp2 to partial sp3 character. We further identify three distinct activation mechanisms driven by the interplay between strain and metal adsorption. For weak compression, the graphene sheet remains planar until metal adsorption induces a reversible buckling, representing a dynamic active site mechanism where the structure recovers planarity upon desorption. For moderate compression (e.g., 5%), metal atom adsorption triggers a transition to a corrugated state that persists after desorption due to mechanical load, yet without π–σ orbital mixing. In contrast, under higher compression (e.g., 10% or 15%), the system undergoes an irreversible transition to a stable corrugated state where curvature is locked by both compressive force and π–σ coupling. This electronic modulation creates highly polarized active sites at the convex “ridges” and concave “valleys”, significantly enhancing the interfacial binding affinity for Li, Na, and K adatoms. Unlike planar graphene, the buckled architecture facilitates a multilayer adsorption mechanism, yielding exceptional theoretical specific capacities of ∼1675.1 mA h g–1 for a Li-ion battery and ∼744.5 mA h g–1 for a Na- and K-ion battery, far surpassing the commercial graphite anode. Furthermore, we identify anisotropic ion diffusion pathways, i.e., “ridge” and “valley”, where the valley channels exhibit ultralow energy barriers (<0.05 eV), acting as superionic highways for rapid kinetics. Our findings establish a robust structure–property relationship between geometric curvature and surface reactivity, providing a theoretical blueprint for designing next-generation flexible anodes via straintronics.

Effective monitoring of microcystin (MC)-LR toxin produced by blue-green algae is of great importance for water pollution and human health. Herein, a field-deployable (FiDe) photoelectrochemical (PEC) biosensor based on nitrogen vacancy-engineered Fe₂O₃@g-C₃N₄-6N_v was proposed for the sensitive and reliable detection of MC-LR. A critical insight was elucidated on atomic-level altered Fe-O/N coordination for an oriented built-in electric field in the composite, which thereby established a Z-scheme charge transfer for enhanced PEC responses. A thiolated aptamer, stably immobilized via Fe-S bonding, enabled specific MC-LR recognition with exceptional resilience. Synergistic integration of a defect-tailored Fe-N heterojunction and Fe-S aptamer immobilization precisely controlled interfacial charge dynamics through concentration-dependent target recognition, where MC-LR binding inhibited Fe-S/Fe-N electron transport to weaken PEC signals. Coupled with an in-house developed FiDe PEC device, the platform exhibited a log-linear detection range from 0.1 to 10000 ng·L^-1 with a detection limit of 0.034 ng·L^-1, significantly below the WHO safety threshold (1 μg·L^-1). It demonstrated exceptional robustness, pH tolerance, storage stability, and selectivity against MC-YR/RR/LA. Field validation across six representative sites along a small watershed of the Yangtze River Basin was conducted in complex matrices, with Bland-Altman analysis confirming statistical equivalence to HPLC. This work not only pioneers a defect-aptamer coengineering strategy to reconfigure Z-scheme charge dynamics but also develops a FiDe PEC device enabling on-site accurate quantification of MC-LR, ultimately empowering proactive water quality management and public health protection.

Machine learning has emerged as a powerful tool for analyzing scanning transmission electron microscopy (STEM) images, yet its widespread application remains constrained by the scarcity of annotated training data. While deep generative models offer a promising solution, they typically struggle to reproduce the complex high‐frequency components that define experimental STEM images. Here, STEMDiff, a conditional diffusion model that transforms simple binary labels derived from crystal structures into realistic STEM images through a physical information embedding strategy, is proposed. By developing a novel Discrete Wavelet Transform‐based skip‐connection architecture, the high‐frequency bias inherent in diffusion models are addressed, enabling the preservation of experimental noise characteristics. This approach generates images that are quantitatively nearly indistinguishable from experimental data (17 fold improvement over previous methods) while retaining ground truth structural information. Fully convolutional networks trained exclusively on these synthetic images achieve high‐precision atomic column detection in experimental STEM images of WSe ₂ and graphene, despite the presence of substantial background noise and contamination. This approach effectively eliminates the need for laborious manual annotation, providing a scalable solution to the data bottleneck in STEM image analysis. The principles underlying STEMDiff can extend to other scientific imaging modalities, accelerating advancements in materials design for water treatment.

A novel ternary synergistic photoelectrochemical (PEC) probe is presented utilizing metal–organic framework (MOF)-templated Pd/CdS@Co₃S₄ nanocages for sensing chlorpyrifos (CPF) using chronoamperometry under an applied bias of − 65 mV with 465-nm LED illumination. Derived from ZIF-67 via in situ sulfidation, the hollow nanocage architecture integrated CdS nanoparticles with Co₃S₄ to form a direct Z-scheme heterojunction, while decorating Pd quantum dots (QDs) created a Schottky barrier, implementing a crucial dual charge-transfer enhancement strategy. Density functional theory (DFT) simulations confirmed a 0.36-eV Fermi level difference at heterojunction interface, verifying a forced built-in electric field. The optimized Pd/CdS@Co₃S₄ nanocomposite exhibited a remarkable 4.63-fold photocurrent amplification over its pristine Co₃S₄, establishing a high-intensity signal baseline essential for accommodating wide-range concentration-dependent signal attenuation. Acetylcholinesterase (AChE)-immobilized biosensor quantified CPF via inhibition-triggered competitive electron consumption to attenuate photocurrent. The sensor demonstrated exceptional performance for CPF detection, most notably featuring a linear dynamic range spanning four orders of magnitude (0.1 ~ 2000 ng·mL⁻¹). Furthermore, it achieved a low detection limit (0.05 ng·mL⁻¹, S/N = 3), outstanding specificity against interfering species, excellent long-term stability, and reliable accuracy in complex real water samples (96.5 ~ 104.5%). This study proposes dual charge-transfer enhancement strategy and hollow architecture, addressing the broad-concentration-range in environmental pesticide detection with good sensitivity and adaptability to real-world matrices. Graphical Abstract

The depletion of fossil fuels and increasing greenhouse gas emissions underscore the urgent need for sustainable energy technologies. Herein, we present rC14, a novel two-dimensional (2D) carbon allotrope engineered by reconfiguring graphene through carbon–carbon bond rotation and defect introduction, which exhibits remarkable multifunctionality for energy storage and conversion applications under conventional and micro-strain conditions. Theoretical calculations indicate that rC14 exhibits excellent dynamical, thermal and mechanical stability. Its high porosity facilitates a theoretical Na-ion storage capacity of 1115 m Ah g⁻¹, approximately three times higher than that of conventional graphite, and this high capacity is retained under small compressive strains. It possesses a low ion diffusion barrier (0.22–0.54 eV) that promises rapid charge/discharge kinetics. Furthermore, the non-uniform charge distribution across rC14, particularly at C1 and C2 sites, renders it an effective metal-free catalyst for the hydrogen evolution reaction (HER). The application of small biaxial compressive strains further refines the electronic structure and adsorption properties of the metal-free catalyst, yielding near-optimal ΔG_H* values (|ΔG_H*| around 0.05 eV) that surpass the values of conventional catalysts such as the Pt(111) surface (−0.09 eV). This work establishes rC14 as a promising dual-function metal-free material for next-generation energy storage and conversion systems under conventional and micro-strain conditions and demonstrates the effectiveness of the designed strategies in advancing material performance.