Cancers doi: 10.20517/microstructures.2026.20

Authors: Qi’an Zhang,Ziyi Fang,Mingzhi Wu,Yang Liu,Qidong Ma,Jiazhen Zhou,Shengqiang Liu,Dengfeng Peng

The development of high-performance self-recoverable near-infrared (NIR) mechanoluminescent materials is crucial for advancing applications. In this work, we presented a self-recoverable NIR mechanoluminescent material, platelike SrAl₁₂O₁₉, through singly doped with Cr³⁺ and co-doped with lanthanide ions (Nd³⁺, Yb³⁺, Er³⁺) in one step. By modulating the Cr³⁺ doping concentration, we achieved precise control over the mechanoluminescence (ML) intensity as well as the spectral tunability between characteristic R-line emission (~ 690 nm) and the broadband emission (750-950 nm). Moreover, energy transfer from Cr³⁺ to lanthanide ions enables multispectral ML emission extending into the NIR-II window (1,000-1,700 nm). The resultant material exhibits excellent ML self-recoverability and high chemical stability. The co-doped system was demonstrated with great potential in dynamic stress visualization, naked-eye-invisible information encryption and special identification under challenging conditions (e.g., underwater). We further demonstrated practical applications by fabricating dual-mode flexible NIR mechanoluminescent paper sheets and sprayable coatings. This work contributes to the advancement of new NIR mechanoluminescent materials with unique morphological features for various scenarios, including the advancement of intelligent sensing and multi-level anti-counterfeiting technologies.

Cancers doi: 10.20517/microstructures.2026.17

Authors: Wei Dai,Xiaochuan Sun,Kecheng Zhou,Yongkai Wang,Huamiao Wang,Yue Liu

Classical constitutive models explicitly couple macroscopic mechanical responses with underlying microstructural evolution, which is crucial for capturing complex deformation mechanisms across varying strain rates. However, current deep learning (DL) constitutive models predominantly focus on macroscopic stress-strain mapping, often neglecting these critical microstructural transitions. To bridge this gap, this work proposes a mechanics-informed deep learning constitutive model (MIDLCM) that integrates gated recurrent units and multi-head attention with a mechanics-informed layer and a mechanics-informed loss, enabling simultaneous prediction of stress response and microstructural descriptors. Trained on a CrFeNi FCC alloy dataset spanning strain rates from 10^-4 to 5,000 s^-1, MIDLCM accurately reproduces strain-rate-dependent stress-strain behavior and captures the associated evolution of dislocation density and twin volume fraction. Crucially, the model successfully represents the distinct dislocation accumulation regimes and the dynamic transition of plasticity mechanisms - from dislocation-dominated to twinning-assisted - across extreme dynamic loading, consistent with experimental trends and crystal-plasticity-based references. Ablation studies show that attention-based temporal encoding and mechanics-informed constraints contribute complementary improvements while preserving inference efficiency. By explicitly tracking these internal state variables, the proposed framework provides a mechanism-level interpretable and computationally efficient microstructure-mechanics coupled alternative for rate-dependent constitutive modeling and is readily extendable to other alloy systems and loading paths.

Cancers doi: 10.20517/microstructures.2025.177

Authors: Yanting Qin,Qingzhi Song,Linyu Bai,Qingshan Bao,Xiufeng Cheng,Lili Li,Yanlu Li,Xian Zhao

The dimensionless figure of merit ZT is the key metric for quantifying thermoelectric performance; however, its optimization is inherently limited by the intrinsic coupling between electrical and thermal transport properties. Herein, we perform first-principles calculations using the temperature-dependent effective potential method to investigate cation alloying in SnSe, where Sn²⁺ ions were randomly substituted by aliovalent cations - specifically Na⁺ and Sb³⁺ - a strategy that induces chemical bond synergy in NaSn₂SbSe₄, effectively decoupling electronic and phonon transport behaviors. Random cation occupation induces a mixed covalent-ionic bonding character, generating local bond-strength fluctuations that act as phonon-scattering centers. Furthermore, localized Sb-Se and Sn-Se antibonding states below the Fermi level correlate with the softening of low-frequency optical phonon branches. Combined with pronounced lattice anharmonicity, this phonon softening significantly enhances four-phonon scattering rates and suppresses the lattice thermal conductivity. Concurrently, aliovalent cation incorporation promotes electron delocalization between Sn-5p and Se-4p orbitals and strengthens covalent bonding character. This modified orbital hybridization alters band dispersion, reducing the hole effective mass while preserving high electrical conductivity in NaSn₂SbSe₄. The optimal balance between low lattice thermal conductivity and high power factor yields superior thermoelectric performance for NaSn₂SbSe₄ relative to SnSe across the entire temperature range, with a peak ZT of 0.88 at 800 K. This study establishes chemical bonding engineering as a promising strategy for enhancing thermoelectric performance and provides guidance for exploring high-performance high-entropy thermoelectric materials.

Cancers doi: 10.20517/microstructures.2026.13

Authors: Boya Wang,Valentina A. Bocharova,Jian Wang,Zhengwei Wang,Lin Gu

Single-phase optimization is increasingly insufficient to simultaneously satisfy the demands of rechargeable batteries for high energy density, fast rate capability, and long-term cycling stability. Growing evidence indicates that electrochemical performance is governed not only by chemical composition, but also by the spatial organization and dynamic evolution of multiple coexisting phases. Inspired by gene editing, this review introduces the concept of phase programming, in which crystalline phases, defect-ordered states, and interfacial phases are regarded as editable functional modules. By deliberately inserting, suppressing, reorganizing and spatially reprogramming these phases, electrode properties can be tuned in a programmable manner. Using energy density, rate performance, and cycling stability as guiding metrics, we reinterpret the interactions among functional modules under different modification strategies and their impacts on electrochemical behavior. On this basis, a phase programming design map is constructed, unifying gradient, core-shell, and multiphase architectures within a common physical framework. This framework establishes phase programming as a potentially transferable materials design language for next-generation battery electrodes.

Cancers doi: 10.20517/microstructures.2026.28

Authors: Yilin Zuo,Weijia Han,Guochao Wei,Kang Du,Yan Liu,Shengxiang Wang

Metamaterial absorbers have been extensively investigated for broadband light harvesting and narrowband sensing, but integrating both into one compact device still remains challenging. In this work, we propose a bifunctional metamaterial absorber (BMA) based on zirconium nitride (ZrN). The device consists of periodically arranged ZrN concentric-ring arrays on a silicon dioxide (SiO₂) spacer with an Au film underneath for broadband absorption, and ZrN-based four-by-four square-grid arrays on the opposite side of the Au substrate for narrowband refractive index sensing. Numerical simulations show that the broadband mode achieves an average absorptivity of 97.48% over the wavelength range of 800 to 2,300 nm, while the narrowband mode exhibits a near-perfect absorptivity at 948.1 nm with a bandwidth of 23.14 nm, delivering a sensitivity of 1,015.62 nm RIU^-1. Electric field distributions and impedance analyses indicate that the absorption behavior arises from the couplings of localized surface plasmon resonances, multipole resonances, and Rayleigh Anomalies (RAs). Parametric studies demonstrate that the broadband absorption maintains high absorptivity in a wide wavelength range, whereas the narrowband resonance systematically shifts as the varying structural parameters. These results not only highlight the importance of integrating light harvesting and refractive index sensing in a single design, but also pave the way for incorporating multiple functionalities into one compact device for broad applications.

Cancers doi: 10.20517/microstructures.2025.181

Authors: Feng Xu,Li-Long Zhang,Hu Li,Song Yang

Developing sustainable and atom-economical hydrogen transfer routes for constructing pharmacologically valuable quinoline scaffolds from abundant alcohol feedstocks remains a significant challenge. Herein, a tailored pyridinic-nitrogen-coordinated cobalt (Co) single-atom catalyst (Co-N/C-U) is showcased, enabling the efficient synthesis of quinoline derivatives from inexpensive and readily available 2-nitrobenzyl alcohol and various secondary or primary alcohols via a cascade hydrogen transfer process followed by annulation. Characterization confirmed that Co-N/C-U contains atomically dispersed Co centers and exhibits exceptional catalytic activity, accessing quinolines with up to 98% yield across a broad substrate scope (47 examples) with a turnover number of up to 30,808, outperforming state-of-the-art catalytic systems. This strategy demonstrates scalability to gram-scale reactions and enables the synthesis of the Cavosonstat derivative, while the pronounced stability and reusability of the catalyst further underscores its promising potential for practical implementation. Mechanistic studies revealed that the pyridinic-N-Co moiety plays a dual role, where the isolated Co sites facilitate efficient hydrogen transfer, and the neighboring pyridinic-N atoms act as basic sites to promote the key Friedländer cyclization step. Density functional theory calculations revealed that the enhanced catalytic performance of Co-N/C-U originates from its optimized pyridinic-N-Co coordination environment. This work establishes a sustainable route to a wide range of quinolines, providing a foundation for the precise design of next-generation SACs for complex organic transformations.