This article reviews wood microstructure and component features, analyzes modification mechanisms, explores applications of modified wood, and suggests optimizing technologies and lowering costs to promote sustainable wood industry development.

Low-dielectric polyimides (PIs) have emerged as essential materials for next-generation microelectronics and communication technologies, yet traditional experimental and theoretical calculation methods for acquiring dielectric constant data face challenges in cost, accuracy, and scalability. This study presents a machine learning (ML) framework that combines polymer domain knowledge with advanced data-driven modeling techniques for accurate prediction of PI dielectric constants at 1 kHz. A dataset of 439 PIs was constructed, and 208 molecular descriptors were derived from SMILES-encoded structures. Through rigorous feature engineering—variance filtering, correlation analysis, and recursive feature elimination—10 key descriptors were identified, capturing electronic and polar interaction, surface area, and structural complexity. Five ML algorithms were evaluated, with Gaussian Process Regression (GPR) achieving superior predictive accuracy (test set: R² = 0.90, RMSE = 0.10). Shapley additive explanations (SHAP) analysis quantifies the contribution of molecular descriptors to PI dielectric constants. By means of SHAP values, it discloses the positive or negative impacts of descriptors on the predictions. Three novel PIs were synthesized for experimental validation, showing strong agreement between predicted and measured dielectric constants (mean percentage deviation: 2.24%). The model demonstrates robust predictions for other structurally similar polymers but reveals a 40% accuracy reduction (R² = 0.60) in 10 GHz cross-frequency predictions, emphasizing the requirement for multi-frequency training datasets to enhance model generalizability. This work advances the research paradigm of polymer dielectric materials and provides a pathway for the rational design of materials guided by machine learning.

Fluorinated polyimide (FPI), renowned for its exceptional low-dielectric properties, colorless transparency, high-temperature resistance, and flexibility, has emerged as an ideal material for addressing challenges in 5G/6G high-frequency signal transmission and flexible electronic substrates. Nevertheless, the structure–property relationship between molecular architectures and the dielectric characteristics of FPI films remains insufficiently understood, necessitating urgent elucidation of the underlying mechanisms. In this study, a diamine monomer containing bis-amide bonds, 4-amino-N-{4-[(4-aminobenzoyl)amino]phenyl}benzamide (PABA), was synthesized. Subsequently, six FPI films (FPAIs, FPEIs, and FPEsIs) with distinct structural features were prepared through homopolymerization of PABA and five other diamines (containing amide bonds, ether, and ester groups) with fluorinated dianhydride (6FDA). Systematic characterization of thermal, mechanical, optical, and dielectric properties revealed that these films exhibit excellent thermal stability (T_g: 296–388 °C), mechanical strength (σ: 152.5–248.1 MPa, E: 2.1–3.4 GPa), and optical transparency (T_{550 nm}: 82–86%). Notably, they demonstrated a low dielectric constant (D_k as low as 2.8) and dielectric loss (D_f down to 0.002) under both low- and high-frequency electric fields. Furthermore, molecular dynamics simulations and quantum chemical were employed to calculate critical physical parameters and HOMO–LUMO energy levels of the six FPIs. This computational analysis provides deeper insights into the structure–performance correlations governing dielectric behavior and optical transparency in FPIs. The findings establish valuable theoretical guidance for designing advanced PI films with tailored dielectric properties and high transparency.

Polyimides (PIs), recognized for their exceptional thermal stability, are extensively employed in advanced applications, including aerospace, flexible displays, flexible solar cells, flame-retardant materials, and high-temperature filtration materials. However, with the continuous advancements in science and technology, the demand for improved thermal performance of PIs in these application areas has increased significantly. In this study, four spirobis(indene)-bis(benzoxazole) diamine monomers (5a, 5aa, 5b and 5bb) were designed and synthesized. These monomers were copolymerized with pyromellitic dianhydride (PMDA) and 4,4-diaminodiphenylmethane (ODA) to develop Kapton-type PIs. By varying the copolymerization molar ratios of the different diamines, a series of novel ultrahigh-temperature-resistant PI films were successfully prepared, and it was found that incorporating a highly rigid and twisted spirobis(indene)-bis(benzoxazole) structure into the PI matrix enhances the rigidity of the polymer chains and restricts their mobility, thereby significantly improving the thermal performance of the PI films. When 5a and ODA were copolymerized at molar ratios of 1:9 and 4:6, the glass transition temperature (T_g) of Kapton-type films significantly increased from 396 °C to 467 °C and >520 °C, respectively. These PI films also exhibit exceptional mechanical properties, with the modulus increasing from 1.6 GPa to 4.7 GPa, while demonstrating low dielectric performance, as evidenced by a decrease in the dielectric constant (D_k) from 3.51 to 3.08 under a 10 GHz high-frequency electric field. Additionally, molecular dynamics simulations were employed to further explore the relationships between polymer molecular structure, condensed states, and film properties, providing theoretical guidance for the development of polymers with ultrahigh thermal resistance and superior overall performance.