Abstract Pancreatic cancer (PC) remains an extremely lethal malignancy due to its dense desmoplastic stroma and aberrant tumor microenvironment (TME), which severely impedes the efficacy of conventional therapies. Herein, a biomimetic dual-driven Janus nanorobot (rCeGLI@PM) is strategically constructed via the asymmetric decoration of l-arginine (l-Arg)-functionalized and indocyanine green (ICG)-loaded poly(amidoamine) dendrimers onto CeOx nanozymes, followed by homologous Panc02 cell membrane camouflage. The formed nanorobots exhibit precise tumor accumulation via homologous targeting and deep penetration through NIR-induced thermophoresis and gas generation propulsion. Within the TME, nanorobots initiate cascade catalysis that generates toxic hydroxyl radicals and depletes glutathione to exaggerate oxidative stress while replenishing oxygen to alleviate tumor hypoxia and amplify photodynamic therapy (PDT). Meanwhile, NIR-triggered photothermal therapy (PTT) accelerates the nanozymatic activity for enhanced catalytic therapy, and PDT-triggered NO forms peroxynitrite (ONOO–) to degrade the extracellular matrix. This establishes a self-amplifying feedback loop for enhanced intratumoral infiltration and overall therapeutic efficacy. Comprehensive evaluations in subcutaneous and orthotopic PC models confirmed that rCeGLI@PM achieved superior therapeutic outcomes through synergistic PTT/PDT/gas/catalytic therapy. In summary, the strategic asymmetrical decoration of multifunctional dendrimers on nanozymes establishes a facile and versatile paradigm for engineering self-propelled nanorobots capable of multimodal synergistic therapies.
Abstract Home-based immunoassay platforms constitute critical tools for the rapid screening of infectious respiratory viruses. Notably, viral loads can remain low at certain stages yet vary over several orders of magnitude during infection, and such variations are closely associated with the disease progression and transmission potential. This self-testing demand necessitates diagnostic kits that combine high sensitivity with accurate human-vision discriminability and portable terminal quantification across the entire detectable range. In response, an ultrabright label was fabricated via template-confined, quasi-compact stacking of quantum dots (QDs). This architecture retained high photoluminescence quantum yield with an elevated QD accumulation number, substantially amplifying the immunosignal output and thereby lowering the limit of detection (LOD). Inspired by the highly discernible visualization principle of multi-index universal pH strips, a color-fixed lateral flow immunoassay (c-LFIA) was established by antigen-driven production of composite colors through narrow-emissive dual QD constituent emitters. This strategy enabled sensitive and discriminable chromatic gradients that were assigned unique identification codes to successive antigen-concentration intervals. Accordingly, the c-LFIA could visually categorize SARS-CoV-2 antigen concentration into 9 discrete intervals spanning 0.1–2000 ng mL−1 with an average interpretation accuracy of 90.19%, while portable terminal analysis achieved a quantitative LOD of 47 pg mL−1. Clinical validation further demonstrated an accurate 6-tier viral abundance-associated category stratification by user visual inspection, complemented by companion one-click smartphone reporting of diagnostic information, thus facilitating decentralized detection and scientific response to respiratory pathogen infections.
Abstract Electrically conductive and highly elastic fibers serve as essential building blocks for smart fabrics and wearable electronics. Nevertheless, conventional conductive fibers tend to exhibit pronounced strain sensitivity, which results in substantial degradation of their electromagnetic interference (EMI) shielding performance under deformation. Here, a coaxial wet-spinning technique was employed to fabricate an ST@MPLM fiber. The fiber featured a silica (SiO2)/thermoplastic polyurethane (TPU) sheath (ST) and an MXene-permeating-liquid metal (MPLM) core, containing a rigid–flexible bridging dynamic conductive network. The resulting fiber exhibited large-strain tolerance, achieving a maximum strain of 632.8%. The corresponding fabric retained 102.4% of its EMI shielding effectiveness (SE) at 200% strain, demonstrating strain-enhanced EMI shielding behavior. The hydrogen bonds between TPU and LM, together with the Ti–O → Ga3+ coordination bonds at the MXene–LM droplet interfaces, facilitate the dynamic reconstruction and bridging of the conductive network during stretching. Furthermore, the fabric integrated Joule heating, infrared stealth, and dynamic visual camouflage capabilities, highlighting its potential in smart wearables and multispectral protection.
Abstract In Li-ion battery anodes, sodium carboxymethyl cellulose (CMC) serves as an indispensable binder despite its minimal electrochemical contribution. Even at low concentrations, CMC imparts colloidal stability, ensures adequate flow during coating, and promotes uniform distribution of active materials. Within the slurry, CMC simultaneously exists in adsorbed and nonadsorbed (free) states, each interacting with active components through distinct mechanisms. This coexistence gives rise to a complexity that belies the apparent simplicity of binder chemistry, raising fundamental questions about how binders govern slurry microstructure and rheological behavior. In this study, we systematically vary CMC molecular weight and concentration to control the degree of intermolecular interactions between CMC and active components, and explicitly decouple the roles of adsorbed and free polymer fractions in governing dispersion quality and processability. Through comprehensive characterization of graphite anode slurry microstructures─combining small-angle scattering, rheology, and dispersion stability analysis─we demonstrate that short CMC chains primarily stabilize graphite aggregates through electrostatic and steric repulsion, while long CMC chains bridge neighboring aggregates through continuous polymer–polymer association, yielding a well-defined network structure. Removing free CMC reveals that long-adsorbed chains alone can sustain the bridged aggregate structure, whereas short adsorbed chains fail to maintain dispersion stability without the support of free polymer in the continuous phase. Furthermore, in situ rheo-SAXS experiments show that the interplay between adsorbed and free CMC drives distinct flow-induced structural evolutions, ultimately governing macroscopic processability and electrochemical performance of the resulting electrodes.
Abstract Two-dimensional (2D) semiconductors exhibit significant potential for next-generation optoelectronic and neuromorphic applications. In particular, intrinsic defect states in 2D materials not only modulate the doping level but also play key roles in the photoresponse time of optoelectronic devices. Depending on the role of the defect states, either high-speed photodetection or low-speed defect-mediated synaptic functions can be realized within individual device. However, the integration of these two functions into a single device remains a challenge. Here, we report a dual-mode optoelectronic device based on an n-ReS2/p-PdSe2 heterojunction, enabling bias-switchable operation between self-driven photodetection and synaptic functions. At zero bias, the strong built-in electric field enables self-driven broadband detection with fast response times of 22.3 μs/22.8 μs. Under an applied bias, intrinsic defects and interfacial traps at the 2D material/substrate interface act as charge-trapping centers to emulate synaptic behaviors. Furthermore, the device emulates the “perception-memory-processing” capabilities of an artificial visual system and exhibits polarization-sensitive neuromorphic responses for spatial-domain image processing. Combined with artificial neural networks, it achieves efficient image denoising and contrast enhancement, reducing training epochs for high-precision handwritten digit recognition by 70%. This work presents a universal strategy for integrating high-speed detection and synaptic functions in multifunctional optoelectronics, showing promise for next-generation artificial vision and neuromorphic computing.
