Search Results (279)

Sophisticated energy-harvesting technologies have swiftly progressed, expanding energy supply distribution and leveraging advancements in self-sustaining electronic devices. Despite substantial advancements in friction nanomotors within the last decade, a considerable technical obstacle remains for their flawless incorporation using printed electronics and autonomous devices. Integrating advanced triboelectric nanogenerator (TENG) technology with the rapidly evolving field of composite material 3D printing with has resulted in the advancement of three-dimensionally printed TENGs. Triboelectric nanogenerators are an important part of the next generation of portable energy harvesting and sensing devices that may be used for energy harvesting and artificial intelligence tasks. This paper systematically analyzes the continual development of 3D-printed TENGs and the integration of composite materials. The authors thoroughly review the latest material combinations of composite materials and 3D printing techniques for TENGs. Furthermore, this paper showcases the latest applications, such as using a TENG device to generate energy for electrical devices and harvesting energy from human motions, tactile sensors, and self-sustaining sensing gloves. This paper discusses the obstacles in constructing composite-material-based 3D-printed TENGs and the concerns linked to research and methods for improving electrical output performance. The paper finishes with an assessment of the issues associated with the evolution of 3D-printed TENGs, along with innovations and potential future directions in the dynamic realm of composite-material-based 3D-printed TENGs. Full article

Liquid metals (LMs), with their unique combination of high electrical conductivity and mechanical deformability, have emerged as promising materials for stretchable electronics and biointerfaces. However, the practical application of bulk LMs in wearable sensors has been hindered by processing challenges and low stability. To overcome these limitations, liquid metal particles (LMPs) encapsulated by native oxide shells have gained attention as versatile and stable fillers for stretchable and conductive composites. Recent advances have focused on the development of LM-based hybrid composites that combine LMPs with metal, carbon, or polymeric fillers. These systems offer enhanced electrical and mechanical properties and can form conductive networks without the need for additional sintering processes. They also impart composites with multiple functions such as self-healing, electromagnetic interference shielding, and recyclability. Hence, the present review summarizes the fabrication methods and functional properties of LM-based composites, with a particular focus on their applications in wearable sensing. In addition, recent developments in the use of LM composites for physical motion monitoring (e.g., strain and pressure sensing) and electrophysiological signal recording (e.g., EMG and ECG) are presented, and the key challenges and opportunities for next-generation wearable platforms are discussed. Full article

This article presents a review on the applications of basalt fibers and their composites in infrastructures. The characteristics and advantages of high-performance basalt fibers and their composites are firstly introduced. Then, the article discusses strengthening using basalt fiber sheets and BFRP bars or grids, followed by concrete structures reinforced with BFRP bars, asphalt pavements, and cementitious composites reinforced with chopped basalt fibers in terms of mechanical behaviors and application examples. The load-bearing capacity of the strengthened structures can be increased by up to 60%, compared with those without strengthening. The lifespan of the concrete structures reinforced with BFRP can be extended by up to 50 years at least in harsh environments, which is much longer than that of ordinary reinforced concrete structures. In addition, the fatigue cracking resistance of asphalt can be increased by up to 600% with basalt fiber. The newly developed technologies including anchor bolts using BFRPs, self-sensing BFRPs, and BFRP–concrete composite structures are introduced in detail. Furthermore, suggestions are proposed for the forward-looking technologies, such as long-span bridges with BFRP cables, BFRP truss structures, BFRP with thermoplastic resin matrix, and BFRP composite piles. Full article

Electrospun nanofiber-based triboelectric nanogenerators (TENGs) have emerged as a highly promising class of self-powered sensors for a broad range of applications, particularly in intelligent sensing technologies. By combining the advantages of electrospinning and triboelectric nanogenerators, these sensors offer superior characteristics such as high sensitivity, mechanical flexibility, lightweight structure, and biocompatibility, enabling their integration into wearable electronics and biomedical interfaces. This review presents a comprehensive overview of recent progress in electrospun nanofiber-based TENGs, covering their working principles, operating modes, and material composition. Both pure polymer and composite nanofibers are discussed, along with various electrospinning techniques that enable control over morphology and performance at the nanoscale. We explore their practical implementations in both contact-type and non-contact-type sensing, such as human–machine interaction, physiological signal monitoring, gesture recognition, and voice detection. These applications demonstrate the potential of TENGs to enable intelligent, low-power, and real-time sensing systems. Furthermore, this paper points out critical challenges and future directions, including durability under long-term operation, scalable and cost-effective fabrication, and seamless integration with wireless communication and artificial intelligence technologies. With ongoing advancements in nanomaterials, fabrication techniques, and system-level integration, electrospun nanofiber-based TENGs are expected to play a pivotal role in shaping the next generation of self-powered, intelligent sensing platforms across diverse fields such as healthcare, environmental monitoring, robotics, and smart wearable systems. Full article

Owing to high electrical conductivity, layered structure, and abundant surface functional groups, transition metal carbides/nitrides (MXenes) have received enormous interest in the field of gas sensors at room temperature. In this work, we synthesize a heterostructured nanocomposite with indium oxide (In₂O₃) decorated on titanium carbide (Ti₃C₂T_x) nanosheets by electrostatic self-assembly and develop it for high-selectivity NO₂ gas sensing at room temperature. Self-assembly formation of multiple heterojunctions in the In₂O₃/Ti₃C₂T_x composite provide abundant NO₂ gas adsorption sites and high electron transfer activity, which is conducive to improving the gas-sensing response of the In₂O₃/Ti₃C₂T_x gas sensor. Assisted by rich adsorption sites and hetero interface, the as-fabricated In₂O₃/Ti₃C₂T_x gas sensor exhibits the highest response to NO₂ among various interference gases. Meanwhile, a detection limit of 0.3 ppm, and response/recovery time (197.62/93.84 s) is displayed at room temperature. Finally, a NO₂ sensing mechanism of In₂O₃/Ti₃C₂T_x gas sensor is constructed based on PN heterojunction enhancement and molecular adsorption. This work not only expands the gas-sensing application of MXenes, but also demonstrates an avenue for the rational design and construction of NO₂-sensing materials. Full article

This work presents a high-performance novel photodetector based on two-dimensional boron nitride (BN) nanosheets functionalized with gold nanoparticles (Au NPs), offering ultra-broadband photoresponse from 0.25 to 5.9 μm. Operating in both photovoltaic and photoconductive modes, the device features rapid response times (<0.5 ms), high responsivity (up to 1015 mA/W at 250 nm and 2.5 V bias), and thermal stability up to 100 °C. The synthesis process involved CO₂ laser exfoliation of hexagonal boron nitride, followed by gold NP deposition via RF sputtering and thermal annealing. Structural and compositional analyses confirmed the formation of a three-dimensional network of atomically thin BN nanosheets decorated with uniformly distributed gold nanoparticles. This architecture facilitates plasmon-enhanced absorption and efficient charge separation via heterojunction interfaces, significantly boosting photocurrent generation across the deep ultraviolet (DUV), visible, near-infrared (NIR), and mid-infrared (MIR) spectral regions. First-principles calculations support the observed broadband response, confirming bandgap narrowing induced by defects in h-BN and functionalization by gold nanoparticles. The device’s self-driven operation, wide spectral response, and durability under elevated temperatures underscore its strong potential for next-generation broadband, self-powered, and wearable sensing and optoelectronic applications. Full article

Simulation experiments are a crucial method for investigating overburden failure, strata movement, and strata control during coal mining. However, traditional similar materials struggle to effectively monitor internal damage, fracturing, and dynamic development processes within the strata during mining. To address this issue, carbon fibers were introduced into the field of similar material simulation experiments for mining. Leveraging the excellent conductivity and the sensitive feedback of resistivity changes in response to damage of this composite material enabled real-time monitoring of internal damage and fracture patterns within the mining strata during similar simulation experiments, leading to the development of a carbon fiber similar simulation composite material with damage self-sensing properties. This study found that as the carbon fiber content increased, the evolution patterns of the electrical resistance change rate and the damage coefficient of the similar material tended to coincide. When the carbon fiber content in the similar material exceeded 2%, the electrical resistance change rate and the damage coefficient consistently exhibited synchronized growth with identical increments. A similar simulation experiment revealed that after the completion of workface mining, the thick sandstone aquifer did not develop significant cracks and remained stable. In the early stages of mining, damage rapidly accumulated at the bottom of the thick aquifer, approaching the failure threshold. In the middle layers, a step-like increase in the damage coefficient occurred after mining reached a certain width, while the top region was less affected by mining activities, resulting in less significant damage development. The research findings offer new experimental insights into rock layer movement and control studies, providing theoretical guidance for the prediction, early warning, and prevention of dynamic disasters in mines with thick key layers. Full article

This paper presents a comparative study examining the effects of carbon nanotubes (CNTs) and expanded graphite (EG) on the thermal, mechanical, morphological, electrical, and piezoresistive properties of poly(ethylene-co-methacrylic acid) (EMAA) nanocomposites. To this end, different amounts of carbonaceous fillers (EG and CNTs separately) were added to the EMAA thermoplastic matrix, and the relative electrical percolation thresholds (EPTs) were determined. The effect of filler concentration on thermo-oxidative degradation and the EMAA crystallinity was investigated via thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), respectively. Dynamic mechanical analysis (DMA) demonstrated that both fillers enhance the Young’s and storage moduli, as well as the glass transition temperature, with a greater improvement for the bidimensional nanofiller, most likely due to the cumulative effect of more extensive EG-matrix interactions. In tensile tests, a very relevant difference was detected in the Gauge Factor (G.F.) and the elongation at break of the two typologies of nanocomposites. The G.F. of EMAA 10% CNT and EMAA 15% EG were found to be 0.5 ± 0.08 and 165 ± 14, respectively, while elongation at break was about 68% for EMAA 10% CNT and 8% for EMAA 15% EG. Emission Scanning Electron Microscopy (FESEM) and Tunneling Atomic Force Microscopy (TUNA) have contributed to explaining the differences between EG- and CNT-based nanocomposites from a morphological point of view, underlying the pivotal role of the filler aspect ratio and its structural features in determining different mechanical and piezoresistive performance. The comprehensive analysis of EMAA-EG and EMAA-CNT nanocomposites provides a guide for selecting the best self-sensing system for the specific application. More specifically, EMAA-CNT nanocomposites with high elongation at break and lower sensitivity to small strains are suitable for movement sensors in the soft robotic field, where high deformation has to be detected. On the other hand, the high sensitivity at a low strain of EMAA-EG systems makes them suitable for integrated sensors in more rigid composite structures, such as aeronautical and automotive components or wind turbines. Full article

Resistive gas sensors have attracted significant attention due to their simple architecture, low cost, and ease of integration, with widespread applications in environmental monitoring, industrial safety, and healthcare diagnostics. This review provides a comprehensive overview of recent advances in resistive gas sensors, focusing on their fundamental working mechanisms, sensing material design, device architecture optimization, and intelligent system integration. These sensors primarily operate based on changes in electrical resistance induced by interactions between gas molecules and sensing materials, including physical adsorption, charge transfer, and surface redox reactions. In terms of materials, metal oxide semiconductors, conductive polymers, carbon-based nanomaterials, and their composites have demonstrated enhanced sensitivity and selectivity through strategies such as doping, surface functionalization, and heterojunction engineering, while also enabling reduced operating temperatures. Device-level innovations—such as microheater integration, self-heated nanowires, and multi-sensor arrays—have further improved response speed and energy efficiency. Moreover, the incorporation of artificial intelligence (AI) and Internet of Things (IoT) technologies has significantly advanced signal processing, pattern recognition, and long-term operational stability. Machine learning (ML) algorithms have enabled intelligent design of novel sensing materials, optimized multi-gas identification, and enhanced data reliability in complex environments. These synergistic developments are driving resistive gas sensors toward low-power, highly integrated, and multifunctional platforms, particularly in emerging applications such as wearable electronics, breath diagnostics, and smart city infrastructure. This review concludes with a perspective on future research directions, emphasizing the importance of improving material stability, interference resistance, standardized fabrication, and intelligent system integration for large-scale practical deployment. Full article

In the face of increasingly complex urban challenges, a critical question arises: can urban ecosystems maintain resilience, vitality, and sustainability when confronted with external threats and pressures? Taking Kunming—a plateau-mountainous city in China—as a case study, this research constructs an urban ecosystem resilience (UER) assessment model based on the DPSIR (Driving forces, Pressures, States, Impacts, and Responses) framework. A total of 25 indicators were selected via questionnaire surveys, covering five dimensions: driving forces such as natural population growth, annual GDP growth, urbanization level, urban population density, and resident consumption price growth; pressures including per capita farmland, per capita urban construction land, land reclamation and cultivation rate, proportion of natural disaster-stricken areas, and unit GDP energy consumption; states measured by Evenness Index (EI), Shannon Diversity Index (SHDI), Aggregation Index (AI), Interspersion and Juxtaposition Index (IJI), Landscape Shape Index (LSI), and Normalized Vegetation Index (NDVI); impacts involving per capita GDP, economic density, per capita disposable income growth, per capita green space area, and per capita water resources; and responses including proportion of natural reserve areas, proportion of environmental protection investment to GDP, overall utilization of industrial solid waste, and afforestation area. Based on remote sensing and other data, indicator values were calculated for 2006, 2011, and 2016. The entire-array polygon indicator method was used to visualize indicator interactions and derive composite resilience index values, all of which remained below 0.25—indicating a persistent low-resilience state, marked by sustained economic growth, frequent natural disasters, and declining ecological self-recovery capacity. Forecasting results suggest that, under current development trajectories, Kunming’s UER will remain low over the next decade. This study is the first to integrate the DPSIR framework, entire-array polygon indicator method, and Grey System Forecasting Model into the evaluation and prediction of urban ecosystem resilience in plateau-mountainous cities. The findings highlight the ecosystem’s inherent capacities for self-organization, adaptation, learning, and innovation and reveal its nested, multi-scalar resilience structure. The DPSIR-based framework not only reflects the complex human–nature interactions in urban systems but also identifies key drivers and enables the prediction of future resilience patterns—providing valuable insights for sustainable urban development. Full article

With the rapid rise in Internet of Things (IoT) and artificial intelligence (AI) technologies, there is an increasing need for portable, wearable, and self-powered flexible sensing devices. In such scenarios, self-powered nanogenerators have emerged as promising energy harvesters capable of converting ambient mechanical stimuli into electrical energy, enabling the development of autonomous flexible sensors and sustainable systems. This review highlights recent advances in nanogenerator technologies—particularly those based on piezoelectric and triboelectric effects—with a focus on soft, flexible, and gel-based polymer materials. Key mechanisms of energy conversion are discussed alongside strategies to enhance performance through material innovation, structural design, and device integration. Special attention is given to the role of gel-type composites, which offer unique advantages such as mechanical tunability, self-healing ability, and biocompatibility, making them highly suitable for next-generation wearable, biomedical, and environmental sensing applications. We also explore the evolving landscape of energy applications, from microscale sensors to large-area systems, and identify critical challenges and opportunities for future research. By synthesizing progress across materials, mechanisms, and application domains, this review aims to guide the rational design of high-performance, sustainable nanogenerators for the next era of energy technologies. Full article

In recent years, the rapid development of three-dimensional (3D)-printed continuous fiber-reinforced polymer (CFRP) technology has provided novel strategies for customized manufacturing of high-performance composites. This review systematically summarizes research advancements in material systems, processing methods, mechanical performance regulation, and functional applications of this technology. Material-wise, the analysis focuses on the performance characteristics and application scenarios of carbon fibers, glass fibers, and natural fibers, alongside discussions on the processing behaviors of thermoplastic matrices such as polyetheretherketone (PEEK). At the process level, the advantages and limitations of fused deposition modeling (FDM) and photopolymerization techniques are compared, with emphasis on their impact on fiber–matrix interfaces. The review further examines the regulatory mechanisms of fiber orientation, volume fraction, and other parameters on mechanical properties, as well as implementation pathways for functional designs, such as electrical conductivity and self-sensing capabilities. Application case studies in aerospace lightweight structures and automotive energy-absorbing components are comprehensively analyzed. Current challenges are highlighted, and future directions proposed, including artificial intelligence (AI)-driven process optimization and multi-material hybrid manufacturing. This review aims to provide a comprehensive assessment of the current achievements in 3D printing CFRP technology and a forward-looking analysis of existing challenges, offering a systematic reference for accelerating the transformation of 3D printing CFRP technology from laboratory research to industrial-scale implementation. Full article

Since 2015, research on liquid–solid triboelectric nanogenerators (L-S TENGs) has shown steady growth, with the primary focus on application domains such as engineering, physics, materials science, and chemistry. These applications have underscored the significant attention L-S TENGs have garnered in areas like human–nature interaction, energy harvesting, data sensing, and enhancing living conditions. Presently, doping composite dielectric materials and surface modification techniques are the predominant methods for improving the power generation capacity of TENGs, particularly L-S TENGs. However, studies exploring the combined effects of these two approaches to enhance the power generation capacity of TENGs remain relatively scarce. Following a review of existing literature on the use of composite material doping and surface modification to improve the power generation performance of L-S TENGs, this paper proposes an experimental framework termed “self-assembled surface TENG@carbonyl iron particle doping (SAS-TENG@CIP)” to investigate the integrated power generation effects of L-S TENGs when combining these two methods. Research cases and data results indicate that, for TENGs exhibiting capacitor-like properties, the enhancement of power generation performance through composite material doping and superhydrophobic surface modification is not limitless. Each process possesses its own inherent threshold. When these thresholds are surpassed, the percolation of current induced by material doping and electrostatic breakdown (EB) triggered by surface modification can lead to a notable decline in the power output capacity of L-S TENGs. Consequently, in practical applications moving forward, fully realizing the synergistic potential of these methods necessitates a profound understanding of the underlying scientific mechanisms. The conclusions and insights presented in this paper may facilitate their complex integration and contribute to enhancing power generation efficiency in future research. Full article

Tomatoes (Solanum lycopersicum) and potatoes (Solanum tuberosum) are vital staple crops. They are prone to diseases from pathogens like Ralstonia and Fusarium, which cause significant agricultural losses. Detecting volatile organic compounds (VOCs) emitted by plants under stress offers a promising approach for advanced monitoring of crop health. This study examines sensing materials for wearable plant sensors targeting VOCs as biomarkers under abiotic and biotic stress. Key questions addressed include the specific VOC emission profiles of potato and tomato cultivars, how materials and sensing mechanisms influence sensor performance, and material considerations for agricultural use. The analysis reveals cultivar-specific VOC profiles under stress, challenging the identification of universal biomarkers for specific diseases. Through a literature review, this study reviews VOC responses to fungi, bacteria, and viruses, and compares non-composite and hybrid chemiresistive and electrochemical sensors based on sensitivity, selectivity, detection limits, response time, robustness, cost-effectiveness, and biocompatibility. A superstructure bridging materials science, plant pathology, AI, data science, and manufacturing is proposed, emphasizing three strategies: sensitivity, flexibility, and sustainability. This study identifies recent research trends that involve developing biodegradable wearable sensors for precision agriculture, leveraging flexible biocompatible materials, multi-parameter monitoring, self-healing properties, 3D-printed designs, advanced nanomaterials, and energy-harvesting technologies. Full article

Steel fibers (SFs) can form stable conductive networks in coal gangue-cemented composites (CGCCs), endowing CGCCs with excellent mechanical, electrical and self-sensing properties. Meanwhile, electrochemical impedance spectroscopy (EIS) provides a potential approach to evaluate the damage situation of SF-reinforced CGCC. In this paper, EIS responses of CGCCs with different SF content and damage levels were determined. An equivalent circuit was then explored, and the effect of the SF content and damage levels on its parameters was investigated. It was observed that CGCC with 0.8% SFs yielded the best result in terms of mechanical and self-sensing ability. In addition, damage such as microcracks primarily affects the conductive pathways induced by pores rather than those induced by SFs. More importantly, as a non-destructive method, the EIS technique is practical and promising for monitoring damage conditions of SF-reinforced CGCC in underground engineering. Full article