Journal of Materials Chemistry C最新文献

Conventional phase-transition ionic conductors (PTICs) based on ionic liquids (ILs) suffer from a fixed resistance-switching temperature (T_RS), intrinsically limited by the immutable melting point of ILs, which restricts their applications in scenarios requiring specific thermal triggers. Herein, we propose a general hierarchical strategy to achieve continuous and precise regulation of T_RS. This is accomplished by leveraging the well-defined relationship between the melting temperature (T_m) of polyethylene glycol (PEG) and its molecular weight (M_n) for coarse adjustment, followed by fine-tuning via blending with lower-M_n PEG or incorporating a plasticizer, succinonitrile (SN). The resulting PEG/PDES-Li-based PTICs enable wide-range tuning of T_m and T_RS from 37 to 59 °C with a precision of ∼1 °C. The optimized conductor (PTIC-4) demonstrates an ultrahigh negative temperature coefficient of resistance (TCR) of −7.64% °C⁻¹ within 30–40 °C, allowing for the detection of subtle temperature variations. Moreover, the material undergoes a reversible transparent-to-opaque transition at T_RS, facilitating intuitive visual thermometry. Beyond temperature sensing, the conductor also functions as a high-performance strain sensor for monitoring human joint motions and even Morse code communication. This work establishes a versatile platform and a general design principle for the development of intelligent wearable devices, medical monitoring systems, and human–computer interaction interfaces.

With the rapid development of emerging fields such as new energy vehicles, smart grids, and aerospace, the operating temperature and current density of power devices continue to increase, placing higher demands on the thermal conductivity, reliability, and high-temperature performance of joining materials. Owing to its excellent electrical and thermal conductivity, low-temperature joining capability, and high-temperature service reliability, metal paste sinter-joining technology has emerged as one of the most promising joining approaches for power electronics packaging. At present, this technology has achieved remarkable progress in small-area joining applications. However, when applied to large-area joining, issues such as delamination of the sintered joints and structural warpage readily arise, severely threatening the integrity and long-term stability of the packaging structure. This review provides a systematic summary of recent advances in large-area sinter-joining using metal pastes, clarifies the mechanisms underlying delamination and warpage, and highlights mainstream strategies for mitigating these issues, including solvent-free materials, incorporation of materials with different coefficients of thermal expansion (CTE), patterned printing, low-temperature sintering, and gradient porosity design. These insights offer theoretical support and technical guidance for further improving joint performance and service reliability. Additionally, the review summarizes the reliability evaluation methods for large-area sintered joints and discusses the key challenges and prospects for their practical applications.

Wearable devices in healthcare have garnered significant attention in recent years due to their flexibility, high biocompatibility, and small size, which enable them to predict and even modulate disease outcomes. This approach not only aligns with the principles of personalized medicine but also significantly reduces treatment costs. Among these, wound monitoring and healing promotion are of great significance for healthcare, especially for wounds that require special attention due to their unique characteristics. Consequently, the application of flexible wearable devices in the wound healing process, offering functions such as monitoring, treatment, and prediction, has become a focal point of contemporary research. This article analyzes the types and functionalities of wearable devices applied to various wounds in recent years and discusses the primary challenges and opportunities facing wearable devices in the future.

Mechanical flexibility and stretchability have become defining characteristics of next-generation electronics. As the core components for optical signal acquisition, infrared photodetectors are accordingly required to exhibit not only superior photodetection performance but also excellent mechanical compliance and durability. Recent advances have demonstrated promising pathways to transcend the limitations of conventional rigid devices through innovative material design and structural engineering. This review outlines key metrics for flexible inorganic infrared photodetectors, systematically summarizes advanced materials and their roles in core components (substrates, photoactive layers, and electrodes), and critically examines associated challenges. It concludes by discussing applications and future research directions, paving the way for technological advances in the field.

In the current era of big data, it is crucial to develop advanced optoelectronic devices that integrate sensing, storage, computing, and other functions to meet the diverse needs of information processing systems for high energy efficiency, high performance, and emerging functions of electronic devices. Gallium oxide (Ga₂O₃) stands out in fields such as photodetectors, field effect transistors, and gas sensors due to its advantages of ultra-wide bandgap (4.8–5.4 eV), high breakdown field strength (8 MV cm⁻¹) and high dielectric constant, becoming the preferred material for the next generation of high-power devices. To overcome the size limitation of transistor performance in the Moore era, two-dimensional (2D) materials have received widespread attention in the field of electronic devices due to their advantages such as atomic thickness, no dangling bonds, and large specific surface area. Here, we provide a comprehensive review of the growth, integration and application of Ga₂O₃/2D heterojunctions in optoelectronic devices. This review summarizes their innovative applications in logic functional transistors, ultraviolet detectors, memory storage, optoelectronic synapse devices and flexible electronic devices, aiming to promote the practical application of Ga₂O₃-based devices and provide new ideas for the development of multifunctional integrated devices.

Correction for ‘Electronic structures and magnetic properties of the rare-earth-free permanent magnet α″-Fe₁₆N₂: first-principles calculations’ by Peirun Duan et al., J. Mater. Chem. C, 2025, 13, 6728–6735, https://doi.org/10.1039/D4TC04934A.

In recent years, innovations in functional hydrogel technology have led to significant breakthroughs in the healthcare sector. Polyvinyl alcohol (PVA) hydrogels, owing to their multiple properties, have become ideal materials for biomedical applications. Although previous studies and reviews have summarized the preparation methods and applications of PVA hydrogels, most of these works remain largely descriptive and lack systematic analysis of the relationships between crosslinking strategies, network structures, multifunctional properties, and application requirements. To address these issues, this review comparatively analyzes how different crosslinking strategies influence the network structure and performance of PVA hydrogels. It reveals the roles of crosslinking mechanisms in regulating key properties such as conductivity, mechanical properties, self-healing capability, and anti-swelling resistance. Based on application demands, this review systematically analyzes the specific combinations of properties required for PVA-based hydrogels in biomarker detection, rehabilitation monitoring, wound dressings, drug delivery, and physiological signal monitoring. It further reveals design strategies for achieving performance matching through structural design. By linking crosslinking strategies, functional properties, and biomedical applications, this review provides guidance for the rational design of multifunctional PVA-based hydrogels for smart medical systems.

Purely organic room-temperature phosphorescence (RTP) materials are a new kind of triplet emitters characterized by long emission lifetimes and high exciton utilization, offering great potential in a wide range of applications. To achieve efficient RTP emission, a deep understanding of the structure–property relationship is urgently needed. To date, most of the studies have focused on the effect of single molecular structures and molecular packing on RTP properties, while the molecular conformation, although very important, is often ignored. In this review, we highlight the significant influence of molecular conformation on RTP effects, including the conformation-dependent RTP phenomenon, the precise control of molecular conformation through rational molecular design and the dynamic regulation of molecular conformation with external stimulus.

The widespread adoption of organic light-emitting diodes (OLEDs) in high-end electronics is due to their superior contrast, color accuracy, and flexible form factors. Despite these advancements, significant challenges remain, which limit overall device lifetime and efficiency. Traditional materials discovery methods are often slow, costly, and inefficient in exploring the vast chemical space, while conventional computational approaches are resource-intensive. The availability of materials databases and sophisticated algorithms has propelled machine learning to reshape OLED research. This review highlights machine learning's pivotal role throughout the entire OLED research and development process—from accelerating materials design and discovery through accurate property prediction, de novo molecular design, and high-throughput virtual screening to predicting device performance metrics such as external quantum efficiency and lifetime. Furthermore, machine learning is improving OLED characterization and analysis, enabling advanced spectroscopic data interpretation and image analysis for automated defect detection and manufacturing process control. Looking ahead, the future of machine learning-driven OLED innovation will focus on overcoming data ecosystem challenges, improving model interpretability using explainable artificial intelligence (XAI) techniques, expanding applicability to emerging OLED technologies (e.g., perovskite and quantum dot OLEDs) via transfer learning and physics-informed machine learning and deploying advanced methods for smart manufacturing. Ultimately, a collaborative effort between humans and artificial intelligence is set to accelerate scientific progress toward next-generation OLEDs.

We report a new class of photo-responsive polar nanostructured liquid crystals. Controlled aromatic core fluorination directs self-assembly into a novel tetragonal mesophase with co-existing columns and micelles. These unique nanostructured materials enable tunable charge transport, providing a design model for functional organic semiconductors.