Nano Convergence最新文献

Post-infectious pulmonary fibrosis remains difficult to prevent due to limited mechanistic understanding and the lack of human-relevant models. We engineered an immune-integrated lung-on-a-chip incorporating endothelial cells, fibroblasts, and macrophages to dissect early fibrotic signaling. Intravascular exposure to thymocyte selection-associated high mobility group box protein (TOX), a T cell–derived factor elevated after severe infection, impaired endothelial barrier function, upregulated intercellular adhesion molecule-1 (ICAM-1), and, through macrophages, induced fibroblast activation with increased α-smooth muscle actin (α-SMA), fibronectin, and extracellular matrix (ECM) remodeling. Pre-treatment with a receptor for advanced glycation end products (RAGE)-blocking antibody preserved barrier integrity and suppressed macrophage activation, fibroblast expansion, and collagen bundling. Similar protective effects were observed in a mouse model of TOX-induced fibrosis, where RAGE blockade improved survival and reduced collagen deposition. Analysis of profibrotic mediators revealed a conserved TOX–RAGE–macrophage signature across the chip model, mouse lungs, and patient bronchoalveolar lavage fluid (BALF) samples. These results identify TOX–RAGE signaling as a driver of post-infectious fibrotic remodeling and establish RAGE blockade as a potential preventive strategy.

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Flexible solar cells (FSCs) are a revolutionary photovoltaic innovation that possesses superior power conversion efficiencies greater than 26.7%, cost-effective production techniques, and intrinsic integration with large-scale manufacturing processes. Among various FSC technologies, flexible perovskite solar cells (FPSCs) are one of the top candidates for commercialization due to their suitability for roll-to-roll (R2R) printing techniques, making it simple to operate on a mass production scale. This review compiles an extensive summary of the advances made in FPSCs over the past few years, particularly focusing on FPSCs, examining their recent advances and performance metrics of flexible photovoltaic systems, silicon-based, dye-sensitized, organic, quantum dot, and hybrid technologies. Detailed overview of the most important components of FPSCs i.e. flexible substrates, perovskite absorber layers, charge transport materials, processing techniques, and encapsulation strategies are provided. Each material is discussed in terms of impact on device performance, efficiency, and longevity with the aim of overcoming the challenge which prevents their commercialization. Eventually, the discussion covers the future prospects of FPSCs, strategies for boosting their lab-scale performance and their potential impact on the development of flexible energy-harvesting technologies.

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Reservoir computing (RC) has emerged as a promising computational paradigm for processing temporally correlated and nonlinear data with low training cost. Among various physical implementations, optoelectronic devices provide a unique opportunity to directly interface light with nonlinear dynamical systems, enriching the reservoir state space through device-intrinsic responses. Light can encode information in wavelength, intensity, and pulse duration, and stimulate multiple nodes in parallel with minimal delay or added power. Recent advances in photodiodes, optically modulated memristors, and phototransistors have revealed device-level pathways to enhance nonlinearity, temporal memory, and node diversity, moving beyond purely electrical control toward hybrid optical–electrical tuning. This review revisits these developments from a device physics perspective, highlighting mechanisms for multi-state generation, bidirectional synaptic weight modulation, and temporal response tailoring. We compare diverse excitation schemes, ranging from wavelength- and intensity-selective photocarrier modulation to con optical-assisted filament control and gate–light co-modulation. We also discuss their impact on reservoir performance in pattern recognition, time-series prediction, and dynamic signal processing. We connect material design, device architecture, and reservoir dynamics to outline emerging strategies for scaling optoelectronic RC. This review provides timely insights for researchers working at the intersection of device engineering and neuromorphic computing.

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Ferroelectric memories have undergone a transformative evolution from conventional perovskite-based materials to modern fluorite-structured ferroelectrics, driven by the pursuit of scalable, low-power, and CMOS-compatible non-volatile memory solutions. The observation of ferroelectricity in nanoscale HfO₂-based films has enabled integration with CMOS-compatible processes, providing advantages such as potential scalability, low power consumption, and non-volatility, while facilitating continued scaling and high-density integration. Leveraging established materials infrastructure in the semiconductor industry, hafnia–based ferroelectrics have been incorporated in various memory architectures, including ferroelectric random-access memory (FeRAM), ferroelectric tunnel junctions (FTJs), ferroelectric field-effect transistors (FeFETs), and ferroelectric memcapacitors (FeCAPs). Beyond conventional non-volatile storage, these devices have also emerged as promising building blocks for in-memory computing applications, including neuromorphic systems, hardware security primitives, and associative memory. In this review, we explore the historical development of ferroelectric memories from a materials–device co-design perspective, examine recent advances in device architectures and in-memory computing applications, and discuss the remaining challenges in endurance, retention, variability, and scaling. Finally, we propose future research directions that integrating material innovation, interface engineering, and circuit-level optimization to realize the full potential of ferroelectric memories in next-generation computing platforms.

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Per- and polyfluoroalkyl substances (PFASs) are a category of extremely persistent environmental pollutants. Metal–organic frameworks (MOFs) have appeared as promising adsorbents for PFAS removal due to their large surface area, tunable porosity, and versatile surface chemistry, which are among the numerous treatment technologies available. This review critically evaluates current developments in the design, fabrication, and application of MOF-based (nano)materials for the adsorption of PFAS in aqueous environments. The adsorption efficacies of MOFs (e.g., pore size, surface charge, and functional groups) and PFASs (e.g., chain length, head group functionality, and polarity) are significantly influenced by their physicochemical properties. The selective and efficient removal of PFASs is governed by the interaction mechanisms such as electrostatic attraction, hydrophobic interactions, H-bonding, and Lewis acid–base coordination. In addition, the adsorption efficacy is significantly influenced by water quality conditions, including pH, ionic strength, background ions, and natural organic matter. Functionalized MOFs (e.g., those with amine, fluorinated, or hydrophobic groups) exhibit resilience to interference, although these factors can sometimes hinder their removal. Both experimental and computational studies have provided valuable mechanistic insights into the rational design of MOFs with improved selectivity and capacity. In addition, this review identifies critical challenges and future perspectives, such as the necessity of standard performance testing under realistic water matrices; the development of scalable, stable, and regenerable MOFs; and their integration into life-cycle assessment and toxicity evaluation.

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Complementary logic and memory circuits based on n-type indium gallium zinc oxide (IGZO) and p-type tin monoxide (SnO) thin-film transistors (TFTs) were demonstrated with low-voltage, hysteresis-free operation. Optimization of IGZO channel thickness precisely tuned the inverter switching point to near V_DD/2, achieving a high voltage gain of 146.6 V/V at V_DD = 3 V and ultra-low static power consumption in the nanowatt range. SU-8 passivation effectively suppressed bias-stress-induced degradation in both IGZO and SnO TFTs, enhancing long-term stability and reducing device variation. Using these optimized devices, a 3-stage ring oscillator exhibited stable oscillations, and 6T-SRAM cells achieved tunable static noise margins by adjusting transistor strength ratios. This work represents one of the first implementations of IGZO/SnO-based  6T-SRAM and demonstrates the potential of oxide semiconductor complementary circuits for low-power and reliable system integration, with promising future applicability to non-volatile memory and on-device artificial intelligence hardware.

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Spatiotemporal mapping of thrombus remodeling remains a major unmet challenge due to the lack of diagnostic tools capable of dynamically converting local biochemical activity into quantitative imaging signals. Current clinical methods lack sensitivity and specificity for accurate thrombus staging. Here, we present a programmable MRI nanoplatform enabling enzyme-gated dual-mode contrast switching for dynamic thrombus profiling and guided thrombolysis. The nanoprobe achieves broad-spectrum thrombus targeting by recognizing two complementary biomarkers uniquely expressed at distinct thrombus maturation stages, and integrates gelatin-guided structural reconfiguration with magnetic nanoparticle clustering to modulate MRI contrast. Gelatin modulates the nanoprobe structure, restricting water proton accessibility and promoting internal densification, thereby synchronously suppressing T1-weighted signals and amplifying T2-weighted contrast. Upon activation by thrombus-associated MMP-2/9, the nanoprobe disassembles, reversing its nano-architecture and signal behavior. This smart signal transformation quantitatively correlates with MMP activity, thrombus age, and collagen content, generating stage-dependent T1/T2 ratios. The nanoprobe also enables enzyme-triggered fibrinolytic release, achieving site-specific thrombolysis with minimal hemorrhagic risk. This materials-based strategy translates dynamic microenvironmental remodeling into high-resolution MRI outputs, establishing a programmable framework for precision imaging and therapy. These programmable imaging outputs support data-driven diagnostics, enable clinical treatment stratification, and offer a standardized reference for modeling enzyme-rich pathological environments.

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Colloidal quantum dot-based short-wave infrared (SWIR) photodetectors are often limited by surface traps and high noise levels at room temperature. In this work, we present a low-temperature chemical bath deposition (CBD) strategy to grow a heterojunction passivation layer on HgTe quantum dot (QD) photoactive layers, enabling high-performance SWIR photodetection at room temperature. The CBD process achieves interfacial modification through a dual mechanism: sulfur ions penetrate the HgTe QD surface to form an Hg-S bonded interfacial region while simultaneously reacting with Cd²⁺ in the bath to create a CdS electron-accepting layer, resulting in a compositionally graded CdS/Hg-S/HgTe structure. The resulting interfacial improvement, coupled with energy level modification, facilitates carrier separation and passivates surface defects, thus simultaneously enhancing the responsivity and reducing noise current of photodetectors. As a result, the phototransistor based on the CdS/HgTe photoactive layer demonstrates a high room-temperature specific detectivity of 4.43 × 10¹¹ Jones at 1550 nm and maintains detectivity around 10¹⁰ Jones at extended wavelengths up to 2500 nm. These results underscore the importance of interfacial engineering in colloidal QDs-based photodetectors and demonstrate CBD as a scalable, silicon-compatible passivation approach for achieving cryogen-free SWIR optoelectronic devices.

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In conventional catalytic reactions, the specific surface area of the catalyst plays a pivotal role in determining the reaction rate. Similarly, in piezocatalysis, the modulation of pore structure is equally critical. In this study, BaTiO₃ nanowires were synthesized via a two-step solvothermal process, wherein the pore architecture of the catalyst was engineered by adjusting the reaction solvent and other parameters. This structural optimization not only facilitated the transport of reactants and enhanced the bulk resistivity, but also induced an internal electric field within the catalyst. Consequently, the screening charges generated by the piezoelectric effect were more effectively localized on the sample surface to engage in redox reactions, thereby yielding a highly active piezocatalyst. The optimized catalyst achieved a degradation efficiency of 98% for Rhodamine B (RhB) solution within 10 min, accompanied by a reaction rate constant as high as 0.38 min⁻¹. By integrating experimental observations with finite element simulations, the contribution of the porous structure to the enhanced piezocatalytic activity was elucidated, offering new insights for the future development and application of piezocatalytic materials.