Search Results (1,773)

Low-Dimensional Nanohybrids (LDNHs) have emerged as potent multifunctional platforms for neurosensing and neuromodulation, providing elevated spatial-temporal precision, versatility, and biocompatibility. This review examines the intersection of LDNHs with artificial intelligence, brain–computer interfaces (BCIs), and closed-loop neurotechnologies, highlighting their transformative potential in personalized neuro-nano-medicine. Utilizing stimuli-responsive characteristics, optical, thermal, magnetic, and electrochemical LDNHs provide real-time feedback-controlled manipulation of brain circuits. Their pliable and adaptable structures surpass the constraints of inflexible bioelectronics, improving the neuronal interface and reducing tissue damage. We also examined their use in less invasive neurological diagnostics, targeted therapy, and adaptive intervention systems. This review delineates recent breakthroughs, integration methodologies, and fundamental mechanisms, while addressing significant challenges such as long-term biocompatibility, deep-tissue accessibility, and scalable manufacturing. A strategic plan is provided to direct future research toward clinical use. Ultimately, LDNHs signify a transformative advancement in intelligent, tailored, and closed-loop neurotechnologies, integrating materials science, neurology, and artificial intelligence to facilitate the next era of precision medicine. Full article

The fatigue constitutive model under cyclic loading is of vital importance for studying the fatigue deformation characteristics of soft rocks. In this paper, based on the classical Bingham model, a modified Bingham fatigue model for describing the fatigue deformation characteristics of soft rocks under cyclic loading was developed. Firstly, the traditional constant-viscosity component was replaced by an improved nonlinear viscoelastic component related to the number of cycles. The elastic component was replaced by an improved nonlinear elastic component that decays as the number of cycle loads increases. Meanwhile, by decomposing the cyclic dynamic loads into static loads and alternating loads, a one-dimensional nonlinear viscoelastic-plastic Bingham fatigue model was developed. Furthermore, a rock fatigue yield criterion was proposed, and by using an associated flow rule compatible with this criterion, the one-dimensional fatigue model was extended to a three-dimensional constitutive formulation under complex stress conditions. Finally, the applicability of the developed Bingham fatigue model was verified through fitting with experimental data, and the parameters of the model were identified. The model fitting results show high consistency with experimental data, with correlation coefficients exceeding 0.978 and 0.989 under low and high dynamic stress conditions, respectively, and root mean square errors (RMSEs) below 0.028. Comparative analysis between theoretical predictions and existing soft rock fatigue test data demonstrates that the developed Bingham fatigue model more effectively captures the complete fatigue deformation process under cyclic loading, including the deceleration, constant velocity, and acceleration phases. With its simplified component configuration and straightforward combination rules, this model provides a valuable reference for studying fatigue deformation characteristics of rock materials under dynamic loading conditions. Full article

Strong coupling between plasmons and excitons in two-dimensional materials offers a powerful route for manipulating light–matter interactions at the nanoscale, with potential applications in quantum optics, nanophotonics, and polaritonic devices. Here, we design and numerically investigate a low-loss coupling platform composed of a silver nanocuboid dimer and monolayer of WS₂ using finite-difference time-domain (FDTD) simulations. The dimer supports a subradiant bonding plasmonic mode with a linewidth as narrow as 60 meV. This ultralow-loss feature enables strong coupling with monolayer WS₂ at relatively low coupling strengths. FDTD simulations combined with the coupled oscillator model reveal a Rabi splitting of ~60 meV and characteristic anticrossing behavior in the dispersion relations. Importantly, we propose and demonstrate two independent tuning mechanisms—loss engineering through nanocuboid tilt and coupling-strength modulation through the number of WS₂ layers—that enable transitions between weak and strong coupling regimes. This work provides a low-loss and tunable plasmonic platform for studying and controlling strong light–matter interactions in plasmon-two-dimensional material systems, with potential for room-temperature quantum and optoelectronic devices. Full article

Modern manufacturing is increasingly shaped by the paradigm of Industry 4.0 (Smart Manufacturing). As one of its nine pillars, additive manufacturing plays a crucial role, enabling high-quality final products with improved profitability in minimal time. Advances in this field have facilitated the emergence of diverse technologies—such as Fused Deposition Modelling (FDM), Stereolithography (SLA), and Selective Laser Sintering (SLS)—allowing the use of metallic, polymeric, and composite materials. Within this context, Klipper v.0.12, an open-source firmware for 3D printers, addresses the performance limitations of conventional consumer-grade systems. By offloading computationally intensive tasks to an external single-board computer (e.g., Raspberry Pi), Klipper enhances speed, precision, and flexibility while reducing prototyping time. The purpose of this study is twofold: first, to identify and analyze bottlenecks in low-cost 3D printers and second, to evaluate how these shortcomings can be mitigated through the integration of supplementary hardware and software (Klipper firmware, Raspberry Pi, additional sensors, and the Mainsail interface). The scientific contribution of this study lies in demonstrating that a consumer-grade FDM 3D printer can be significantly upgraded through this integration and systematic calibration, achieving up to a 50% reduction in printing time while maintaining dimensional accuracy and improving surface quality. Full article

Tungsten monophosphide (WP) has been reported to superconduct below 0.8 K, and theoretical work has predicted an unconventional Cooper pairing mechanism. Here we present data for WP single crystals grown by means of chemical vapor transport (CVT) of ${\mathrm{WO}}_3$, P, and ${\mathrm{I}}_2$. In comparison to synthesis using WP powder as a starting material, this technique results in samples with substantially decreased low-temperature scattering and favors a more three-dimensional morphology. We also find that the resistive superconducting transitions in these samples begin above 1 K. Variation in $T_c$ is often found in strongly correlated superconductors, and its presence in WP could be the result of influence from a competing order and/or a non-s-wave gap. Full article

Rapid population growth and accelerating urbanization are intensifying the demand for construction materials, particularly concrete, which is predominantly produced with Portland cement and natural aggregates. This reliance imposes substantial environmental burdens through resource depletion and greenhouse gas emissions. Within the framework of sustainable construction, recycled aggregates and industrial by-products such as fly ash, slags, crushed glass, and other secondary raw materials have emerged as viable substitutes in concrete production. At the same time, three-dimensional concrete printing (3DCP) offers opportunities to optimize material use and minimize waste, yet it requires tailored mix designs with controlled rheological and mechanical performance. This review synthesizes current knowledge on the use of recycled construction and demolition waste, industrial by-products, and geopolymers in concrete mixtures for 3D printing applications. Particular attention is given to pozzolanic activity, particle size effects, mechanical strength, rheology, thermal conductivity, and fire resistance of recycled-based composites. The environmental assessment is considered through life-cycle analysis (LCA), emphasizing carbon footprint reduction strategies enabled by recycled constituents and low-clinker formulations. The analysis demonstrates that recycled-based 3D printable concretes can maintain or enhance structural performance while mix-level (cradle-to-gate, A1–A3) LCAs of printable mixes report CO₂ reductions typically in the range of ~20–50% depending on clinker substitution and recycled constituents—with up to ~48% for fine recycled aggregates when accompanied by cement reduction and up to ~62% for mixes with recycled concrete powder, subject to preserved printability. This work highlights both opportunities and challenges, outlining pathways for advancing durable, energy-efficient, and environmentally responsible 3D-printed construction materials. Full article

Neuromorphic computing, inspired by the human brain’s architecture, offers a transformative approach to overcoming the limitations of traditional von Neumann systems by enabling highly parallel, energy-efficient information processing. Among emerging materials, MXenes—a class of two-dimensional transition metal carbides and nitrides—have garnered significant attention due to their exceptional electrical conductivity, tunable surface chemistry, and mechanical flexibility. This review comprehensively examines recent advancements in MXene-based optoelectronic synapses and neurons, focusing on their structural properties, device architectures, and operational mechanisms. We emphasize synergistic electrical–optical modulation in memristive and transistor-based synaptic devices, enabling improved energy efficiency, multilevel plasticity, and fast response times. In parallel, MXene-enabled optoelectronic neurons demonstrate integrate-and-fire dynamics and spatiotemporal information integration crucial for biologically inspired neural computations. Furthermore, this review explores innovative neuromorphic hardware platforms that leverage multifunctional MXene devices to achieve programmable synaptic–neuronal switching, enhancing computational flexibility and scalability. Despite these promising developments, challenges remain in device stability, reproducibility, and large-scale integration. Addressing these gaps through advanced synthesis, defect engineering, and architectural innovation will be pivotal for realizing practical, low-power optoelectronic neuromorphic systems. This review thus provides a critical roadmap for advancing MXene-based materials and devices toward next-generation intelligent computing and adaptive sensory applications. Full article

Since the 1930s, polyamides (PAs) have become increasingly vital across industries like automotive, textiles, electronics, and packaging, owing to their exceptional properties. However, they also have notable limitations, including a tendency to absorb water, low dimensional stability, poor solubility, and the resulting processing challenges. From an environmental perspective, the reliance on fossil-based monomers for traditional PAs and the accumulation of post-consumer waste, due to their resistance to (bio)degradation, are key concerns. In recent decades, significant advancements have been made in synthesizing PAs from bio-based monomers, primarily sourced from inedible lignocellulosic materials. Some of these bio-based PAs exhibit properties comparable to their fossil-derived counterparts, with benefits like enhanced solubility, which simplifies processing. Moreover, certain bio-based variants have shown improved biodegradability, facilitating the potential recovery of monomers for the production of new virgin polymers and reducing waste accumulation. This review highlights the progress in developing PAs from commonly used bio-based sources, including lignin-derived aromatic compounds, terpenes, fatty acids, and furan derivatives, with a focus on the improvements made over their fossil-based analogs. Full article

Mechanical exfoliation remains the most common method for producing high-quality two-dimensional (2D) materials, but its inherently low yield requires screening large numbers of samples to identify usable flakes. Efficient optimization of the exfoliation process demands scalable methods to analyze deposited material across extensive datasets. While machine learning clustering techniques have demonstrated ~95% accuracy in classifying 2D material thicknesses from optical microscopy images, current tools are limited by slow processing speeds and heavy reliance on manual user input. This work presents an open-source, GPU-accelerated software platform that builds upon existing classification methods to enable high-throughput analysis of 2D material samples. By leveraging parallel computation, optimizing core algorithms, and automating preprocessing steps, the software can quantify flake coverage and thickness across uncompressed optical images at scale. Benchmark comparisons show that this implementation processes over 200× more pixel data with a 60× reduction in processing time relative to the original software. Specifically, a full dataset of2916 uncompressed images can be classified in 35 min, compared to an estimated 32 h required by the baseline method using compressed images. This platform enables rapid evaluation of exfoliation results across multiple trials, providing a practical tool for optimizing deposition techniques and improving the yield of high-quality 2D materials. Full article

In this study, a new hybrid hydrogel based on PAM (polyacrylamide)-Ag-g/WS₂/Ti₃C₂T_x was synthesized by radical polymerization using a conductive heterostructural nanocomposite WS₂/Ti₃C₂T_x. The synergy between the polymer matrix and the interface between two-dimensional nanomaterials ensured the production of a hydrogel with high extensibility and conductivity, as well as sensory characteristics. The composite hydrogel exhibited excellent strain-sensing capabilities, with gauge factors of 1.4 at low strain and 2.8 at higher strain levels. In addition, the material showed a fast response time of 2.17 s and a short recovery time of 0.46 s under cyclic stretching, which confirms its high reliability and reproducibility. The integration of Ti₃C₂T_x and WS₂ promoted the formation of a conductive network in the hydrogel structure, which simultaneously increased its mechanical strength and signal stability under variable loads. Measurements confirm some potential of the PAM-Ag-g/WS₂/Ti₃C₂T_x composite hydrogel as a flexible wearable strain sensor. Based on measured numbers, we discussed the impact of the WS₂/Ti₃C₂T_x interface on the Gauge factor and conductivity of the composite. Theoretical modeling demonstrates significant changes in the electronic structure of the WS₂/Ti₃C₂T_x interface, and especially the WS₂ surface, induced by substrate strain. Possible applications of the peculiar properties of PAM-Ag-g/WS₂/Ti₃C₂T_x composite were proposed. Full article

This study investigates the influence of two processing methods, namely wet and dry, on the structural, physical, mechanical, and acoustic performance of green lignocellulosic fiber-based composite panels. A comprehensive evaluation was carried out to compare the vertical density profile, affinity to water, thermal insulation and sound absorption, microstructural features, and mechanical performance of two types of experimental panels. The dry-processed samples exhibited 24% more prominent vertical density profile and superior dimensional stability, with lower thickness swelling (TS) and water absorption (WA) due to their more compact fiber arrangement compared to those of the specimens made using the wet process. However, the wet-processed panel demonstrated significantly enhanced mechanical properties, including 36% higher modulus of elasticity (MOE), 61% modulus of rupture (MOR), and 67% internal bonding strength (IB). Such findings could be attributed to their increased fibrillation and improved inter-fiber bonding compared with those of the panels made using the dry process. The thermal conductivity values of the wet- and dry-processed panels were found to be 0.053 W/mK and 0.057 W/mK, respectively. Acoustic analysis of the samples revealed that while the dry-processed panel slightly outperformed in terms of low-frequency sound absorption, the wet-processed panel exhibited superior high-frequency absorption, particularly when perforations were introduced. Microscopic examination of the samples confirmed that wet processing produced a more homogenous and fibrillated microstructure, correlating well with the observed enhancements in mechanical and acoustic performance. In conclusion, it can be stated that the processing strategies of such panels could be applied for diverse engineering applications, including thermal insulation, acoustic damping, and sustainable structural materials. Full article

The fabrication of microfluidic components using low-cost Fused Deposition Modeling (FDM) presents an attractive alternative to conventional manufacturing methods, yet achieving microscale dimensional accuracy remains a significant challenge. This study investigates the influence of five key FDM parameters (nozzle temperature, bed temperature, printing speed, flow rate, and infill overlap) on the dimensional accuracy of microchannels printed with PETG and TPU filaments. A Taguchi L27 orthogonal array was employed to systematically evaluate the effects of these parameters on width and depth deviations across sub-millimeter microchannel geometries. Results show that for PETG, optimal dimensional fidelity was achieved at 240 °C nozzle temperature, 70 °C bed temperature, 30 mm/s speed, 100% flow rate, and 15% overlap, enabling reliable channel widths down to 100 µm. TPU exhibited greater variability due to its elasticity, with optimal settings found at 220 °C, 60 °C bed temperature, 30 mm/s, 100% flow rate, and 25% overlap. Signal-to-noise ratio and ANOVA analyses revealed flow rate and printing speed as dominant factors for both materials. The findings provide a reproducible optimization framework for microscale FDM fabrication and highlight material-specific process sensitivities critical to functional microfluidic device performance. Full article

Strong coupling has emerged as a central topic in nanophotonics, offering a powerful platform for light–matter interaction studies and advancing quantum technologies. Low-dimensional materials, such as quantum dots (QDs) and two-dimensional (2D) semiconductors, possess pronounced excitonic resonances, high stability, and size-dependent tunability, making them ideal candidates for achieving strong coupling with plasmonic structures. In this review, we systematically summarize recent progress in plasmon low-dimensional material strong coupling. We first introduce the fundamental principles and experimental methods of plasmon–exciton strong coupling, then highlight representative studies on plasmon–QDs and plasmon–2D material hybrid systems, and finally discuss recent advances in multimode strong coupling. This review will provide a comprehensive overview and offer valuable guidance for future studies in strong coupling. Full article

This review summarizes recent advances in multifunctional metamaterials (MF-MMs) for electromagnetic (EM) wave absorption. MF-MMs overcome the key limitations of conventional absorbers—such as narrow bandwidth, limited functionality, and poor environmental adaptability—offering enhanced protection against EM security threats in radar, aerospace, and defense applications. This review focuses on an integrated structure-material-function co-design strategy, highlighting advances in three-dimensional (3D) lattice architectures, composite laminates, conformal geometries, bio-inspired topologies, and metasurfaces. When synergized with multicomponent composites, these structural innovations enable the co-regulation of impedance matching and EM loss mechanisms (dielectric, magnetic, and resistive dissipation), thereby achieving broadband absorption and enhanced multifunctionality. Key findings demonstrate that 3D lattice structures enhance mechanical load-bearing capacity by up to 935% while enabling low-frequency broadband absorption. Composite laminates achieve breakthroughs in ultra-broadband coverage (1.26–40 GHz), subwavelength thickness (<5 mm), and high flexural strength (>23 MPa). Bio-inspired topologies provide wide-incident-angle absorption with bandwidths up to 31.64 GHz. Metasurfaces facilitate multiphysics functional integration. Despite the significant potential of MF-MMs in resolving broadband stealth and multifunctional synergy challenges via EM wave absorption, their practical application is constrained by several limitations: limited dynamic tunability, incomplete multiphysics coupling mechanisms, insufficient adaptability to extreme environments, and difficulties in scalable manufacturing and reliability assurance. Future research should prioritize intelligent dynamic response, deeper integration of multiphysics functionalities, and performance optimization under extreme conditions. Full article

In this work, the gas sensing properties and adsorption mechanisms of Ag- and Au-doped SnSe₂ monolayers toward NO, NO₂, SO₂, H₂S, and HCN were systematically investigated via first-principles calculations. The results demonstrate that NO₂ exhibits the strongest interaction and the highest charge transfer in both doped systems, indicating superior sensing selectivity. Biaxial strain (ranging from −8% to 6%) was further applied to modulate adsorption behavior. By evaluating changes in equilibrium height, adsorption energy, charge transfer, and recovery time across ten representative adsorption systems, it was found that both compressive and tensile strains enhance the interaction between gas molecules and doped SnSe₂ monolayers. Specifically, H₂S/Au–SnSe₂ and HCN/Au–SnSe₂ are highly sensitive to tensile strain, while NO/Au–SnSe₂, H₂S/Ag–SnSe₂, NO/Ag–SnSe₂, and NO₂/Ag–SnSe₂ respond more strongly to compressive strain. Systems such as NO₂/Au–SnSe₂, SO₂/Au–SnSe₂, and SO₂/Ag–SnSe₂ respond to both types of strain, whereas HCN/Ag–SnSe₂ shows relatively low sensitivity in charge transfer. Recovery time analysis indicates that NO₂ exhibits the slowest desorption kinetics and is most affected by strain modulation. Nevertheless, increasing the operating temperature or applying appropriate strain can significantly shorten recovery times. While other gas systems show smaller variations, strain engineering remains an effective strategy to tune desorption behavior and enhance overall sensor performance. These findings offer valuable insights into strain-tunable gas sensing behavior and provide theoretical guidance for the design of high-performance gas sensors based on two-dimensional SnSe₂ materials. Full article