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In recent decades, data-driven methodologies have emerged as irreplaceable tools in materials science, particularly for elucidating structure-property relationships and facilitating the discovery of novel materials. However, despite the rapid development witnessed in other domains, amorphous materials have received relatively less attention in this context. The disordered atomic structure of amorphous materials resulting from irreversible reactions between building blocks has posed a difficulty in structural modeling, leading to a lack of databases that accurately reflect the amorphous nature of these materials. In this work, a database composed of 10,237 porous polymer networks (PPNs) was constructed from self-assembly simulations, resulting in the largest database of PPNs considering their amorphous characteristics. Through the distinct differences observed in comparison with existing databases, we emphasize that carefully considering the structural disorder of PPNs is essential for accurately characterizing their chemical behaviors. Machine learning models trained on the constructed database have confirmed that the macroscopic properties of amorphous PPNs can be predicted solely from the atomic structures of their monomers, implying that the characteristics of previously unseen PPNs can be assessed without the need for additional self-assembly simulations.

In this study, we examined the nanostructured molecular packing and orientations of poly[[ N , N '-bis(2-octyldodecyl)-naphthalene-1,4,5,8-bis(dicarboximide)-2,6-diyl]- alt -5,5'-(2,2'-bithiophene)] (P(NDI2OD-T2)) films formed on water for the application of nanotechnology-based organic electronic devices. First, the nanoscale molecule-substrate interaction between the polymer and water was modulated by controlling the alkyl side chain length in NDI-based copolymers. Increasing alkyl side chain lengths induced a nanomorphological transition from face-on to edge-on orientation, confirmed by molecular dynamics simulations revealing nanostructural behavior. Second, the nanoscale intermolecular interactions of P(NDI2OD-T2) were controlled by varying the volume ratio of the high-boiling-point additive solvent in the binary solvent blends. As the additive solvent ratio increased, the nanostructured molecular orientation of the P(NDI2OD-T2) films on water changed remarkably from edge-on to bimodal with more face-on crystallites, thereby affecting charge transport. Our finding provides essential insights for precise nanoscale morphological control on water substrates, enabling the formation of high-performance polymer films for organic electronic devices.

Most photocatalytic and photovoltaic devices operate under broadband, constant illumination. Electron and hole dynamics in these devices, however, are usually measured by using ultrafast pulsed lasers in a narrow wavelength range. In this work, we use excited-state X-ray theory originally developed for transient X-ray experiments to study steady-state photomodulated X-ray spectra. We use this method to attempt to extract electron and hole distributions from spectra collected at a nontime-resolved synchrotron beamline. A set of plasmonic metal core-shell nanoparticles is designed as the control experiment because they can systematically isolate photothermal, hot electron, and thermalized electron-hole pairs in a TiO 2 shell. Steady-state changes in the Ti L 2,3 edge are measured with and without continuous-wave illumination of the nanoparticle's localized surface plasmon resonance. The results suggest that within error the quasi-equilibrium carrier distribution can be determined even from relatively noisy data with mixed excited-state phenomena. Just as importantly, the theoretical analysis of noisy data is used to provide guidelines for the beamline development of photomodulated steady-state spectroscopy.

Graphene-based e-textile gas sensors have received significant attention as wearable electronic devices for human healthcare and environmental monitoring. Theoretically, more the attached graphene on the devices, better is the gas-sensing performance. However, it has been hampered by poor adhesion between graphene and textile platforms. Meanwhile, amyloid nanofibrils are reputed for their ability to improve adhesion between materials, including between graphene and microorganisms. Despite that fact, there has been no attempt to apply amyloid nanofibrils to fabricate graphene-based e-textiles. By biomimicking the adhesion ability of amyloid nanofibrils, herein, we developed a graphene-amyloid nanofibril hybrid e-textile yarn (RGO/amyloid nanofibril/CY) for the detection of NO 2 . Compared to traditional e-textile yarn, the RGO/amyloid nanofibril/CY showed better performance in response time, sensing efficiency, sensitivity, and selectivity for NO 2 . Last, we suggested a practical use of RGO/amyloid nanofibril/CY combined with a light-emitting diode as a wearable e-textile gas sensor.

Spiders synthesize their web using a liquid bridge-to-solidification mechanism at the end of their glands. Inspired by this process, in this work, we fabricated micro-glue threads (μGTs, polymer microwires) by a simple "pinch and spread" process using just two fingertips. The μGTs exhibited excellent tensile strength (∼50 GPa), comparable to those of spider silk and biological fibers. The chemical, physical, and mechanical properties of the μGTs were investigated, and it was confirmed that the thickness of the μGTs could be controlled by ethanol treatment in varying concentrations. Moreover, electrically conductive μGTs were easily fabricated by simply mixing them with various nanomaterials such as gold nanoparticles, zinc oxide nanowires, and reduced graphene oxide (rGO). Interestingly, the conductive μGTs, fabricated using rGO, exhibited remarkable electrical conductivity (0.45 μS) compared to those fabricated using other materials. The conductive μGTs are applicable not only to NO 2 gas sensing but also as electrical fuselike materials that melt when the humidity increases. Collectively, the results present μGTs as cost-effective, simple, and versatile materials, which enables their application in a variety of sensors.

We present that the tailored nanopatterning with tunable shape, depth, and dimension for diverse application-specific designs can be realized by utilizing controlled dynamic nanoinscribing (DNI), which can generate bur-free plastic deformation on various flexible substrates via continuous mechanical inscription of a small sliced edge of a nanopatterned mold in a compact and vacuum-free system. Systematic controlling of prime DNI processing parameters including inscribing force, temperature, and substrate feed rate can determine the nanopattern depths and their specific profiles from rounded to angular shapes as a summation of the force-driven plastic deformation and heat-driven thermal deformation. More complex nanopatterns with gradient depths and/or multidimensional profiles can also be readily created by modulating the horizontal mold edge alignment and/or combining sequential DNI strokes, which otherwise demand laborious and costly procedures. Many practical user-specific applications may benefit from this study by tailor-making the desired nanopattern structures within desired areas, including precision machine and optics components, transparent electronics and photonics, flexible sensors, and reattachable and wearable devices. We demonstrate one vivid example in which the light diffusion direction of a light-emitting diode can be tuned by application of specifically designed DNI nanopatterns.

The detection of circulating protein (CP) is very important for the diagnosis and therapeutics of cancer. Conventional techniques based on a specific antibody-antigen interaction are still lacking because of a shortage of cost effectiveness, complicated sandwich structure and tagging process, and inconsistent detection of CP due to the inherent instability of antibodies. Herein, we demonstrate a hybrid device consisting of two-dimensional (2D) nanoscale molybdenum disulfide (MoS 2 ) field-effect transistor (FET) with an amyloid-β 1-42 (Aβ 1-42 ) functionalized surface, which amplifies electric signals of the FET in order to detect matrix metalloproteinase-9 (MMP-9), which is a certain type of CP that degrades Aβ 1-42 . With the hybrid device, we detected the concentrations of MMP-9 in the range from 1 pM to 10 nM. Moreover, using tapping-mode atomic force microscopy and Kelvin probe force microscopy, we verified that the signal amplification corresponding to the MMP-9 concentrations was caused by the reduced length and the decreased surface potential of degraded Aβ 1-42 due to MMP-9. The hybrid device studied in this paper can be very useful for monitoring MMP-9 activity, as well as serving as a sensing platform for the electrical signal amplification of 2D MoS 2 FET-biosensors.

Recent technological advances have expanded fluorescence (FL) imaging into the second near-infrared region (NIR-II; wavelength = 1000-1700 nm), providing high spatial resolution through deep tissues. However, bright and compact fluorophores are rare in this region, and sophisticated control over NIR-II probes has not been fully achieved yet. Herein, we report an enzyme-activatable NIR-II probe that exhibits FL upon matrix metalloprotease activity in tumor microenvironment. Bright and stable PbS/CdS/ZnS core/shell/shell quantum dots (QDs) were synthesized as a model NIR-II fluorophore, and activatable modulators were attached to exploit photoexcited electron transfer (PET) quenching. The quasi type-II QD band alignment allowed rapid and effective FL modulations with the compact surface ligand modulator that contains methylene blue PET quencher. The modulator was optimized to afford full enzyme accessibility and high activation signal surge upon the enzyme activity. Using a colon cancer mouse model, the probe demonstrated selective FL activation at tumor sites with 3-fold signal enhancement in 10 min. Optical phantom experiments confirmed the advantages of the NIR-II probe over conventional dyes in the first near-infrared region.