Wearable wound dressing is a promising approach for treating wound infection and promoting healing process. However, conventional wearable dressing methods have the drawback of poor long-term stability due to water loss. Herein, a novel hydrogel patch is fabricated by incorporating phosphoric acid and glycerol to enhance the water retention capacity. This hydrogel exhibits an excellent water retention rate of 97.7
Ultrathin native oxides formed on two-dimensional (2D) metallic transition metal dichalcogenides (MTMDs), such as NbSe2, have recently emerged as promising active switching layers for memristive devices. However, these oxides are highly susceptible to surface damage during conventional top-electrode deposition processes, which leads to interfacial disorder and degraded switching reliability. Here, we demonstrate a highly reliable and flexible NbOx–NbSe2 memristor utilizing a damage-free van der Waals (vdW) metal transfer technique. By gently laminating a prefabricated gold (Au) electrode onto the NbOx–NbSe2, a pristine and chemically undisturbed metal/oxide interface is achieved. While metallization-induced barrier damage causes a large OFF-state direct tunneling (DT) current in the evaporated-metal memristor (Ev-MEM), preserving the pristine oxide interface in the transferred-metal memristor (T-MEM) effectively suppresses this OFF-state DT current. Consequently, the T-MEM exhibits an ON/OFF ratio of 105—a 1,000 times improvement over the Ev-MEM (102)—along with a stable retention time of > 104 s and an endurance exceeding 103 cycles. Furthermore, the T-MEM exhibits exceptional synaptic linearity (β = 0.6) and a full dynamic range (0–1), in contrast to the Ev-MEM, which suffers from poor linearity (β = 3.1) and a limited dynamic range (0.2–1). As a result, a hardware-aware convolutional neural network (CNN) simulation shows a near-ideal MNIST image recognition accuracy of 98.1
Abstract New Approach Methodologies (NAMs) are increasingly promoted for animal-free nanosafety assessment, yet their regulatory use remains constrained by fragmented regulatory criteria and nanomaterial-specific testing complexities. This review comprehensively analyzes the convergence of advanced cell biology, nanotechnology, and information technology in reshaping safety evaluations, with a focus on regulatory translation across global frameworks. We first summarize enabling technologies, including advanced in vitro and ex vivo systems, organoids, microphysiological systems, high-dimensional single-cell multi-omics and label-free hyperspectral imaging, AutoML, generative AI, physiologically based kinetic modeling, and in vitro-to-in vivo extrapolation. We then analyze the regulatory landscape, emphasizing OECD harmonization efforts, the Mutual Acceptance of Data system, and regional developments across Europe, Africa, the Americas, and Asia–Pacific. A central theme is that regulatory acceptance of NAMs for nanomaterials requires not only biological relevance, reproducibility, and context-of-use definition, but also robust physicochemical characterization, exposure control, dosimetry, and data interoperability. Industrial implementation in pharmaceuticals, cosmetics, agrochemicals, antimicrobials, and environmental protection is discussed as a measure of regulatory readiness and scalability. Finally, we outline future directions involving Smart NAMs, digital twins, and Safe and Sustainable by Design (SSbD) frameworks. By integrating technological, regulatory, and implementation perspectives, this review identifies pathways toward harmonized, mechanistic, and human- or target species-relevant next-generation risk assessment (NGRA) for nanotechnology. Graphical abstract
Micro-nano plastics (M/NPs) are pervasive environmental pollutants whose small size, persistence, and evolving surface states complicate reliable detection and remediation. As interface-dominated contaminants, their environmental behavior is largely governed by interactions at plastic–bio–nano interfaces. In this article, we review recent advances in three interconnected aspects of M/NPs research: biomolecular recognition, nano-enabled enrichment, and catalytic degradation, with particular emphasis on the central role of interfaces. Biomolecular recognition elements, including antibodies, peptides, aptamers, and molecularly imprinted materials, enable selective identification of plastics through interfacial pattern recognition. Nanomaterials such as magnetic nanoparticles, plasmonic nanostructures, metal–organic frameworks, and carbon-based materials further facilitate selective capture and signal amplification in complex matrices. Emerging degradation strategies, including engineered enzymes, enzyme–nanomaterial hybrids, nanozymes, single-atom nanozymes, and advanced oxidation processes, rely on interface-mediated adsorption, catalytic activation, and polymer transformation. Future research should therefore focus on elucidating plastic–bio–nano interfacial mechanisms and leveraging these insights to integrate molecular recognition, nano-enabled enrichment, and catalytic transformation within multifunctional platforms.
Graphene oxide (GO) has established itself as a premier material for electrochemical biosensing due to its exceptional chemical tunability, aqueous processability, and unique sp²-sp³ hybridized structure. This review provides a comprehensive analysis of diverse engineering strategies to functionalize GO, enabling highly sensitive and selective detection of a broad spectrum of biological analytes. We systematically categorize these advancements into five key methodologies: (1) controlled reduction to precisely tune electrical conductivity and surface defects, (2) covalent functionalization for robust bioreceptor immobilization, (3) non-covalent modification to preserve biomolecular conformation, (4) metal nanoparticle hybridization for enhanced electrocatalysis, and (5) integration with polymeric/framework materials to build advanced three-dimensional sensing architectures. By examining applications ranging from small molecule metabolites and proteins to nucleic acids and whole pathogens, we demonstrate how tailored GO interfaces overcome conventional sensing trade-offs. Finally, we highlight the pivotal role of these engineered GO platforms in addressing the challenges of real-time monitoring at complex biological interfaces, including living cells and organoids, and outline the pathway toward clinically deployable diagnostic technologies.
Hard carbon is being actively explored as a candidate anode material for next-generation batteries, offering ion storage mechanisms distinct from and potentially advantageous to those of graphite. However, conventional synthesis of hard carbon usually relies on high-temperature pyrolysis and chemical activation, which involve high energy consumption and environmental challenges. Spent coffee grounds (SCGs), generated in large amounts worldwide, represent an abundant biomass resource with high carbon content that is often discarded with limited recycling. In this study, SCGs were directly converted into hard carbon and partially graphitized structures using femtosecond laser direct writing (FsLDW) under solvent-free and non-vacuum conditions. Localized photothermal reactions induced by the ultrashort pulses promoted particle consolidation and structural rearrangement, and by varying the laser parameters, the carbonization pathway could be directed to favor either hard carbon or graphene domains. A copper substrate was deliberately employed to spontaneously generate copper compound nanoparticles, which were subsequently etched to create micro-porous carbon with tunable pore characteristics. This laser-based approach provides a controllable and one-step pathway for transforming SCGs into functional carbon anodes, highlighting the potential to selectively prepare materials suitable for both lithium-ion and sodium-ion batteries by adjusting only the laser conditions. While this study focused on lithium-ion battery applications, the tunable control of carbon structure and porosity offers the possibility of extending this strategy to sodium-ion batteries.
Enhancement of specific absorption rate (SAR) of iron oxide (Fe3O4) is crucial for ensuring selectivity of hyperthermia tumor therapy, yet both magnetothermal and photothermal approaches endure shortcomings i.e., high dosage and laser power densities, that compromise therapeutic efficacy. This work reports the Scandium (Sc) doped Fe3O4 nanoflakes synthesized by sol-gel route with superior heat generation properties enabling bimodal tumor therapy. The novel Sc_0.05[ Fe^2 + Fe^3 + _1.95]O_4 nanoflakes superstructure exhibits pronounced optical extinction and a high saturation magnetization of 90.33 emu/g, arising from lattice expansion and enhanced magnetic exchange coupling. Photothermal conversion efficiency reached 66.84
Osteosarcoma has poor prognosis owing to its aggressive metastasis and high recurrence rates due to residual cancer cells which are common even after surgical resection. In addition, for irregular defects, site-specific design is essential to ensure anatomical conformity. Consequently, a critical demand exists for a theragenerative approach that simultaneously provides structural reconstruction and functional eradication of residual cancer cells. Herein, we present a patient-specific 3D-printed theragenerative polyetheretherketone (PEEK) scaffold integrated with biofunctional 2D molybdenum disulfide (MoS2) to impart enhanced bioactivity and dual-phototherapy. 2D monolayer MoS2 synthesized via nanoseed-initiated atmospheric pressure chemical vapor deposition (APCVD) was subsequently integrated onto the 3D-printed PEEK through a polymer-assisted transfer process. The fabricated 2D MoS2-conformal 3D-printed PEEK scaffold (MoS2@PEEK) enabled simultaneous photothermal and photodynamic therapy via the intrinsic photoresponsive properties MoS2. Under dual-wavelength irradiation, this combined phototherapy effectively induced pronounced cancer cell apoptosis and exhibited antibacterial activity through the synergistic effects of localized hyperthermia and reactive oxygen species generation. In contrast, under the same photothermal stimulation, pre-osteoblasts and vascular endothelial cells exhibited enhanced attachment, proliferation, and differentiation. Therefore, this theragenerative system represents a promising patient-specific platform for simultaneous tumor suppression, infection control, and bone regeneration after osteosarcoma resection.
As all-solid-state battery (ASSB) technologies continue to advance, interest has resurfaced in mid-nickel (mid-Ni) LiNixCoyMnzO2 (NCM; x = 0.5) cathodes due to their enhanced structural stability, reduced oxygen evolution, and higher capacities at elevated cutoff voltages compared to high-nickel compositions. However, interfacial degradation including parasitic reactions with solid-state electrolytes (SSEs) remains a major challenge. To address this issue, we conducted a high-throughput computational screening of oxide-based coating materials, evaluating their electrochemical stability, interfacial robustness, and Li-ion conductivity using Li–Li network descriptors. From this screening, 8 candidates were selected based on strict criteria. Among them, Li3Sc2(PO4)3 emerged as a particularly promising coating material, exhibiting strong electrochemical stability under high-voltage conditions (> 4 V) and substantial ionic conductivity (0.2 mS/cm), exceeding that of most oxide-type SSEs, as confirmed by ab initio molecular dynamics simulations. Furthermore, large-scale molecular dynamics simulations using a universal machine-learning interatomic potential demonstrate its ability to suppress surface degradation of mid-Ni NCM and prevent [PS4]3− decomposition in Li6PS5Cl, confirming its potential as a protective coating. These findings highlight the effectiveness of our computational screening strategy for coating-material discovery and underscore the potential of Li3Sc2(PO4)3 as a robust interfacial layer for stabilizing mid-Ni ASSBs.
Antimony chalcogenides are highly promising thin-film photovoltaic materials. However, their quasi-one-dimensional structure inherently causes severe transport anisotropy. The thermodynamically stable [hk0] horizontal orientation induces van der Waals barriers that hinder carrier transport, whereas the kinetically favorable [hk1] vertical orientation constructs efficient charge pathways and dangling-bond-free “benign grain boundaries”. Focusing on the thermodynamic and kinetic competition mechanisms during film growth, this review systematically summarizes recent optimization strategies for inducing the [hk1] preferred orientation. Four core approaches are highlighted: solvent and precursor engineering, deposition parameter optimization, interface and substrate engineering, and post-treatment reconstruction. Finally, we delineate the “structure-process-performance” relationship and provide perspectives on deep-level defect passivation, heterojunction band engineering, and flexible, large-area applications, aiming to guide the fabrication of high-efficiency antimony-based solar cells approaching their theoretical limit.
Quantum dots (QDs) are fluorescent nanoparticles widely used for single-molecule imaging because of their exceptional brightness and photostability. However, the impact of QD surface chemistry on biomolecular interactions has not been systematically investigated. Here, we report that commercial QDs unexpectedly destabilize protein-DNA complexes by inducing protein dissociation from DNA. Using the human nucleotide excision repair protein, xeroderma pigmentosum complementation group A (XPA) as a model system, we demonstrate that antibody-conjugated QDs promote dissociation of XPA from DNA substrates, independently of sizes and surface modification of QDs, antibody types, epitope tags, buffer conditions, or DNA structures. We find that polyethylene glycol (PEG), a common polymer coating on QD surfaces, is the primary factor responsible for this effect. To tackle this problem, we engineered QDs with precisely controlled surface polymer compositions. By systematically changing the ratio of anchoring, hydrophilic, and PEG-based functional groups, we find that reducing PEG density below a critical threshold effectively suppresses protein dissociation while maintaining excellent colloidal stability and brightness. Furthermore, antibodies conjugated via click chemistry between azide groups and DBCO enabled specific labeling of XPA without perturbing the DNA binding activity. Using these optimized QDs, we conducted single-molecule DNA curtain assays to visualize XPA-DNA interactions. QD-labeled XPA exhibits one-dimensional diffusion with frequent pausing on undamaged DNA. DNA curtain assays revealed that XPA preferentially binds DNA bubbles and searches for bubble structures through both one-dimensional diffusion and three-dimensional collision. Quantitative analysis showed that three-dimensional collision is the dominant pathway for bubble recognition. Taken together, our results uncover a previously unrecognized limitation of PEG-coated QDs in single-molecule studies and provide an improved surface-engineering strategy to preserve native protein-DNA interactions. Newly engineered QDs establish robust platforms for accurate single-molecule visualization of biomolecular processes.
The female reproductive system, including the endometrium, placenta, ovary, cervix, and fallopian tube, plays a critical role in conception, implantation, and fetal development. Recent advances in bioengineered models such as organoids, organ-on-a-chip platforms, and 3D bioprinting have expanded experimental capabilities, however, the rapid growth of this field has resulted in a large and fragmented body of literature, limiting systematic integration and analysis. Here, we present an artificial intelligence (AI)-driven text mining framework to systematically map research trends in the female reproductive system. A total of 347 peer-reviewed articles were collected and analyzed. Abstracts were embedded using BioBERT to capture contextual biomedical semantics. Subsequently, unsupervised topic modeling was performed using BERTopic with UMAP-based dimensionality reduction and HDBSCAN clustering. This analysis identified 15 fine-grained subtopics, which were further consolidated into six major thematic categories. The results show that current research is mainly focused on endometrial receptivity and implantation, placental barrier function and maternal–fetal interface, and tissue regeneration and biofabrication. In contrast, integrated multi-organ modeling and translational validation remain relatively underexplored. Overall, this AI-driven framework provides a quantitative and scalable approach to organizing complex biomedical literature. The findings offer a structured overview of the field and highlight emerging directions for multiscale modeling and personalized reproductive medicine.
Designing and developing innovative, cost-effective nanomaterials with outstanding activity and durability remains a significant challenge for next-generation electrochemical sensors. Herein, we developed an energy-efficient approach to synthesize N/Se-functionalized Co-ZIF-9(III) (CZ@N/Se) nanohybrids with a unique nanorod/nanosheet morphology, which serve as a high-performance platform for ultrasensitive nitrofurantoin (NFT) sensing. The unique nanorod/nanosheet morphology of N/Se-doped CZ provides an excellent platform for NFT sensing by enhancing electron-transfer kinetics and generating a high density of active sites through the synergistic interaction between the Co-framework and N/Se dopants. These features facilitate efficient NFT adsorption and catalytic reduction, thereby markedly improving the electrochemical sensitivity and selectivity. With optimized mass loading, the CZ@N/Se nanohybrid exhibits exceptional repeatability and reproducibility in NFT detection, achieving a low detection limit of 1.03 nM and a high sensitivity of 3.783 µA µM−1 cm−2 as confirmed by multiple electrochemical measurements. Selectivity tests against potential interferents confirmed the sensor's excellent specificity, with negligible interference observed. Besides, the analysis of spiked environmental and biological samples demonstrated accurate detection, validating the sensor reliability and practical applicability for NFT determination in real-world settings.
Neuroprostheses have become a pivotal technology for restoring sensory, motor, and cognitive functions, offering transformative therapeutic strategies for neurological disorders by bridging or bypassing damaged neural pathways through electronic systems. However, achieving long-term stability and high-fidelity interaction between biological and electronic systems remains a significant challenge due to the mismatch at the neural interface. This review examines the critical role of nanotechnology in building high performance neuroprostheses across six key classes: motor, visual, tactile, language, memory and olfactory. A system architecture of the neuroprostheses is proposed that highlights two critical interfaces, namely, “neural-electronic” and “environment-electronic” interfaces. We survey recent advances in materials and devices that shape better neural electrodes and novel sensors, and discuss the potential utilization of neuromorphic computing for efficient edge processing in neuroprostheses. This review aims to outline future trajectories toward high-throughput bidirectional interaction, biomimetic encoding, and adaptive closed-loop systems, aspiring to achieve seamless integration between electronic systems and biological neural circuitry.
Synthetic graphites have been widely used in industrial applications, including as anodes in lithium-ion batteries. Because they are produced at temperatures above 3000 °C, which generate highly ordered graphitic domains, there is typically no discernible evidence of their precursor materials. In this study, three types of graphite, coal tar based anisotropic graphite, petroleum fluid oil based anisotropic graphite, and coal tar based isotropic graphite, were prepared. Conventional characterization techniques such as X-ray diffraction, Raman spectroscopy, transmission electron microscopy, and even electrochemical performance were unable to distinguish their precursors. Therefore, we introduced laser desorption/ionization time-of-flight mass spectrometry (LDI-MS) combined with multivariate statistical analysis to characterize three graphites prepared from different synthetic precursors as well as two commercial graphites. The resulting LDI-MS spectra were analyzed using principal component, hierarchical cluster, and heatmap analyses, which are widely used in clinical mass spectrometric diagnostics. Notably, LDI-MS coupled with multivariate statistics successfully classified the graphites depending on their precursor materials and processing parameters, such as heat-treatment temperature, whereas conventional analytical tools failed to reveal these differences. These results clearly demonstrate the strong potential of LDI-MS and statistical analysis for the precise characterization of carbon materials and for distinguishing their origins and processing routes.
Metal-gate interlayer (G.IL)-ferroelectric (FE)-channel interlayer (Ch.IL)-Si (MIFIS) ferroelectric field-effect transistors (FeFETs) are attractive for large memory window (MW) and low-voltage FE NAND operation. Nevertheless, its fundamental operating principle also makes the device vulnerable to threshold voltage (V th ) shift under repeated disturb bias, which remains a major obstacle to array-level reliability. In this study, we employ a TiO 2 nanolayer (NL) at the upper interface of the HZO FE layer to address this issue while preserving the low-voltage advantage of the MIFIS structure. The inserted TiO 2 modifies the interfacial electrostatics and the ferroelectric switching characteristics at the same time. First, owing to its high dielectric constant and band alignment, it facilitates additional gate-side charge storage near the G.IL/FE interface. Second, it alters the switching nature of the underlying HZO toward a more abrupt response associated with enlarged effective domain size and improved remanent polarization. The proposed device with TiO 2 NL operates below 15 V, while maintaining a large MW of 7.57 V, which is 18.9% higher than the reference device. Notably, the proposed device remains disturbance-free even after 10 5 cycles of 9 V/10 µs disturbance stress, whereas the counterpart experiences severe disturbance under the same conditions. Thus, we clarify that partial P switching acts as the primary driver of disturbances, as it precedes charge trapping and accelerates gate charge injection. Finally, while our top-interface engineering successfully optimizes gate-side dynamics, we propose that replacing the Si channel and bottom interlayer with emerging van der Waals (vdW) semiconductors and 2D insulators (e.g., h-BN) can fundamentally suppress channel-side charge injection (Q it ). Combining this vdW-based bottom-interface with our TiO 2 top-interface strategy presents a comprehensive blueprint to expand the MW and realize ultimate disturbance-free operation in next-generation computing architectures.
Organic light-emitting diodes (OLEDs) have been developed to enhance device lifetime, efficiency, and operational stability. However, the widely used hole injection layer (HIL) material poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) exhibits limitations such as high work function and acidity, which degrade device performance. This study introduces a [2-(9H-carbazol-9-yl)ethyl]phosphonic acid (2PACz) self-assembled monolayer (SAM) as an alternative to PEDOT:PSS. 2PACz-based OLEDs achieved lower turn-on voltages and higher external quantum efficiencies (EQEs) compared with PEDOT:PSS-based devices. The maximum EQE of green and red fiber organic light emitting diodes (FOLEDs) were 10.71% and 8.97%, respectively, representing 16.9% and 12.9% improvements compared with those of reference devices using PEDOT:PSS as the HIL. Furthermore, compared with TiO2 fiber-shaped dye-sensitized solar cells (FS-DSSCs), the incorporation of TiO2/2PACz increased the power conversion efficiency (PCE) from 5.67% to 6.53%, corresponding to an improvement of approximately 17%. Notably, the TiO2/2PACz-based fiber-shaped gas sensors (FS-GSs) also exhibited enhanced gas sensing characteristics, including increased response and sensitivity, highlighting the multifunctionality and broad applicability of this interfacial engineering strategy across diverse optoelectronic platforms.
Soft electronic devices require durability to endure their inherent exposure to diverse mechanical deformations, including scratches, punctures, and repeated bending. Without intrinsic damage recovery mechanisms, such deformations inevitably compromise mechanical integrity and limit device lifetime. To address this issue, the strategic incorporation of reversible dynamic bonds enables autonomous self-healing while simultaneously achieving high mechanical toughness through energy dissipation during bond rupture. To this end, optimizing the glass transition temperature and bond exchange kinetics is essential to ensure sufficient chain mobility for rapid interfacial diffusion and autonomous mechanical recovery. Building on the reversible bond nature, this review presents emerging self-healable and tough soft electronics applications in three major areas: (1) Multimodal electronic skins capable of comprehensive physiological signal sensing; (2) modularly reconfigurable systems with adhesive-free interlayer bonding that enable user-on-demand device assembly; (3) optoelectronic devices that seamlessly integrate light-emitting and pressure-sensing capabilities. These applications demonstrate that dynamic bond engineering enables elastomeric devices to simultaneously achieve mechanical robustness, functional adaptability, and autonomous self-healing. Such advancements position them as durable platforms with extended operational lifetimes, paving the way for next-generation wearable and implantable bioelectronics in real-world applications.
Two-dimensional (2D) semiconductors enable atomically thin channels and attractive electrostatics, but practical scaling increasingly hinges on gate-dielectric integration rather than channel performance. A key challenge is forming high-quality dielectrics on chemically inert, dangling-bond-free 2D surfaces while pushing equivalent oxide thickness to the sub-nanometer regime without excessive leakage, traps, or electrical breakdown. This review addresses the materials and process physics that govern dielectric formation in 2D devices, with an emphasis on atomic layer deposition nucleation, surface pretreatment and functionalization, and the use of seed and buffer layers for conformal high-κ oxides. The roles of layered insulators, such as hexagonal boron nitride, are discussed in terms of interface quality, electrostatic scaling limits, and transport limitations. The impact of dielectrics and processing on leakage mechanisms, defect generation, device-to-device variability, and reliability metrics, including time-dependent dielectric breakdown, bias-temperature instability, hysteresis, and threshold-voltage drift, is examined. Finally, we highlight van der Waals dry integration and dielectric transfer approaches that reduce process-induced damage and support wafer-scale uniformity, as well as opportunities for mixed-dimensional and 3D stacked architectures across logic, memory, and emerging functional systems.
Compute-in-memory (CIM) has emerged as a promising solution to mitigate the data movement bottleneck in von Neumann architectures. While vertical NAND (V-NAND) flash memory has been explored for CIM, its structural constraints, including pass-bias overhead and interconnect parasitic capacitances, limit energy efficiency. In this work, we present a comprehensive comparison between V-NAND and vertical AND (V-AND) flash memory for CIM applications. Analytical modeling and experimental validation demonstrate that V-AND achieves superior energy efficiency, particularly with low-inference-count regimes and increased stack height, by eliminating the bias pass requirement. These results demonstrate that V-AND offers compelling advantages over V-NAND, establishing it as a promising candidate for energy-efficient, scalable, and fast CIM accelerators.
