International Journal on Artificial Intelligence Tools

ABSTRACTOrganic electrochemical transistors (OECTs) hold potential for in‐sensor computing and wearable healthcare systems. Nevertheless, their inherent limitations in stretchability and conformability hinder their scalability and practical deployment. In a recent study, Liu et al. introduce a wearable in‐sensor computing platform that leverages stretchable OECTs, exhibiting over 50% elongation capability while preserving stable operational performance. This innovation enables the development of wearable systems that can accurately acquire biosignals.

ABSTRACTElectrocatalytic CO reduction (COR) offers a promising alternative approach for synthesizing valuable chemicals, potentially at a lower carbon intensity as compared to conventional chemical production. Cu‐based catalysts have shown encouraging selectivity and activity toward multi‐carbon (C2+) products, albeit typically in the form of a mixture. Steering COR selectivity toward specific types of C2+ products, such as liquid products with high energy density, remains a challenge. In this study, we developed a Cu/Zn bimetallic catalyst composite and demonstrated enhanced selectivity toward liquid products as compared to reference CuO and Cu‐based catalysts, approaching 60% at a high current density of 300 mA/cm2. Our investigation highlights that the introduction of Zn promoted the emergence of a Cu/Zn heterojunction interface during COR. Density functional theory simulations were used to rationalize the observed differences in selectivity, revealing that interface plays a crucial role in diminishing the oxygen adsorption at the Cu‐sites and modifying the adsorption energy of COR reaction intermediates, consequently leading to enhanced selectivity toward liquid products.

ABSTRACTWith the demand for sustainable preparation of nanocellulose, the extraction of holocellulose nanofibers with surface‐coated hemicellulose from various biomass is drawing more and more attention. However, detailed preparation processes and some fundamental properties of holocellulose nanofibers, such as rheological behavior and redispersibility, still need systematic investigation. An in‐depth understanding of these processes and properties plays a crucial role in guiding the preparation and subsequent material design of holocellulose nanofibers. Herein, a concise method is reported to prepare bamboo‐derived holocellulose nanofibers (BHCNFs) from bamboo residue and has been characterized in detail. To facilitate subsequent application, comprehensive exploration and understanding of the rheological behavior of BHCNF were conducted, along with an investigation into the redispersibility after freeze‐drying. The presence of hemicellulose significantly affects the rheological behavior and gives BHCNF a certain redispersibility. To achieve better redispersibility, aerogel powder was prepared via spray freeze‐drying, offering new insights into the drying and practical application of BHCNF.

ABSTRACTTwo‐dimensional (2D) materials, such as MoS2, show exceptional potential for next‐generation electronics. However, the poor stability of these materials, particularly under long‐term operations and high temperature, impedes their practical applications. Here, we develop a terminal passivation interface decoupling (TPID) strategy to significantly improve the stability of MoS2, by mitigating the interaction between the substrate and the 2D material within the in‐situ growth process. Specifically, the strong electron‐withdrawing terminal group hydroxyl, prevalent on the oxide substrate, is passivated by carbon groups. Due to this, the structure of MoS2 materials remains stable during long‐term storage, and its electronic devices, field‐effect transistors (FETs), show remarkable operational and high‐temperature (400°C) stability over 60 days, with much‐improved performance. For example, mobility increases from 9.69 to 85 cm2/(V·s), the highest value for bottom‐up transfer‐free single crystal MoS2 FETs. This work provides a new avenue to solve reliability issues of 2D materials and devices, laying a foundation for their applications in the electronic industry.

ABSTRACTLight‐emitting transistors (LETs) as novel integrated optoelectronic devices demonstrate great potential applications in smart displays and visual intelligent perception. The construction of high‐performance area‐emission LETs with low power consumption and good reliability is urgently needed for advancing their applications, however, this integration has not been realized within a single device. Herein, we demonstrate a kind of planar‐driven hybrid LET (PDHLET) that makes use of the unique advantages of high mobility and stability of inorganic and organic semiconductors in the same device. By incorporating an indium‐zinc‐gallium‐oxide (InZnGeO) conducting layer and organic emissive layer, a high‐performance stable blue‐emissive PDHLET is constructed, giving a high Ion/Ioff ratio approaching 6.1 × 108 and a low Von of 5.5 V along with maximum brightness of 1264 cd/m2 as well as small VTH shift of 0.5 V after 1000 s positive stress bias. Finally, a systematic simulation, including charge concentration and Langevin recombination rate, is carried out on PDHLET for the first time, demonstrating good consistency with experimental results. This confirms the uniformity of high redistributed charge concentration in the InZnGeO conducting layer which thus enables good area emission. This study provides a new avenue for constructing high‐performance stable LETs to advance various field applications.

ABSTRACTElectrocatalytic CO2 reduction (ECR) is a promising approach to converting CO2 into chemicals and fuels. Among the ECR products, C2 products such as ethylene, ethanol, and acetate have been extensively studied due to their high industrial demands. However, the mechanistic understanding of C2 product formation remains unclear due to the lack of in situ or operando measurements that can observe the complex and instantaneous atomic evolutions of adsorbates at the electrode/electrolyte interface. Moreover, the sensitivity of ECR reactions to variations at the interface further widens the gap between mechanistic understanding and performance enhancement. To bridge this gap, first‐principle studies provide insights into how the interface influences ECR. In this study, we present a review of mechanistic studies investigating the effects of various factors at the interface, with an emphasis on the C2 product formation. We begin by introducing ECR and the essential metrics. Next, we discuss the factors classified by their components at the interface, namely, electrocatalyst, electrolyte, and adsorbates, respectively, and their effects on the C2 product formation. Due to the interplay among these factors, we aim to deconvolute the influence of each factor and clearly demonstrate their impacts. Finally, we outline the promising directions for mechanistic studies of C2 products.

ABSTRACTOrganic single crystals with long‐range molecular periodic ordering ensure superior charge‐transport properties and low defect density, which have been considered promising candidates for charge‐transporting materials in organic light‐emitting devices (OLEDs). The functional interfaces of OLEDs play a critical role in charge‐transporting and light‐emitting behaviors, while the interfacial properties of organic single crystals in OLEDs and their impact on device performance have been rarely investigated. Herein, two typical organic single crystals, 1,4‐bis(4‐Methylstyryl)benzene (BSB‐Me) and 2,6‐diphenylanthracene (DPA) with different molecular formulas and packing structures, are introduced as the single‐crystal hole‐transporting layers (HTLs) for a systematic investigation of the interfacial properties between single‐crystal HTLs and active emissive layers. BSB‐Me single‐crystal HTLs offer satisfied surface wettability and enhanced interfacial interaction, which dominate the charge‐transporting and light‐emitting behaviors of the OLEDs. Such improved interfacial properties are responsible for the superior light out‐coupling efficiency of BSB‐Me single‐crystal OLEDs with efficient exciton recombination and minimal Joule heat loss. In consequence, BSB‐Me single‐crystal OLEDs exhibit a maximum luminance of 50,170 cd/m2 and a peak EQE of 8.78%, which are better than DPA‐based devices. Furthermore, BSB‐Me single‐crystal HTLs with favorable interfacial properties enable large‐area OLEDs with uniform EL emission over the whole light‐emitting area of 1 mm × 1 mm.

ABSTRACTThe biodegradable polymer poly(lactic acid) (PLA) is brittle. PLA‐based composites reinforced by indium selenide (InSe) particles or flakes are prepared; each is found to have outstanding plasticity. InSe nanosheets are prepared by sonication of solid InSe in N‐methyl pyrrolidone, followed by washing/dispersion in ethanol, and subsequent drying. These InSe nanosheets, or in separate studies InSe particles, are mixed with PLA to make composite materials. The PLA composite materials are 3D‐printed into “dogbone” samples that are tensile‐loaded. The optimum dogbone specimen is 1.5 times stronger and 5.5 times tougher than neat PLA specimens prepared in the same way. To the best of our knowledge, this concurrent improvement in tensile strength and toughness has not been achieved before in PLA with any filler type. Finite element analysis, together with experimental analysis of (i) fracture surfaces, (ii) the PLA crystal structure, and (iii) the internal structure by micro‐CT scanning, suggests that the exceptional mechanical performance is due to the intrinsic properties of InSe and, particularly, the emergence of crack shielding and crack deflection at the interfaces of PLA and InSe flakes. These findings indicate that PLA–InSe composites may offer opportunities to broaden the applications of PLA composites, including as load‐bearing materials.

ABSTRACTHydrogels loaded with microRNA (miRNA) have shown promise in bone‐defect repair. Here, we present the first report of miRNA‐loaded hydrogels containing bioactivities to treat steroid‐induced osteonecrosis of the femoral head (SONFH), based on the mechanism of competing endogenous RNAs. Transcriptome sequencing of human bone marrow mesenchymal stem cells (HBMSCs) extracted from the proximal femoral bone marrow and subsequent functional assays revealed that the circSRPK1/miR‐320a axis promotes HBMSCs osteogenic differentiation. By incorporating antagomir‐320a (a miR‐320a inhibitor) encapsulated in liposomes into injectable hyaluronic acid (HA) hydrogels, we constructed an injectable hydrogel, HA@antagomir‐320a. This hydrogel demonstrated exceptional osteogenic properties, targeting multiple osteogenic pathways via CDH2 and Osterix and exhibited excellent in vitro biocompatibility. In vivo, it substantially enhanced bone formation in the osteonecrotic area of the femoral head. This injectable HA@antagomir‐320a hydrogel, which exhibited exceptional biocompatibility and osteogenic properties in vivo and in vitro, offers a promising and minimally invasive solution for the treatment of SONFH.

ABSTRACTWith the advances of nanochemistry in the past several decades, a diverse set of nanomaterials has been developed as electrocatalysts with enhanced activity, selectivity, and durability for electrocatalytic reactions. However, it has remained as a long challenge to systematically understand the mechanism of electrocatalytic reactions, which involves multiple protons‐coupled electron transfer processes and varied products at the atomic level, intrinsically because of the complexity and polydispersity of the traditional nanomaterials. By sharp contrast, ligand‐protected metal nanoclusters (NCs) possess atomically precise structures and abundant active sites, facilitating their applications as effective model electrocatalysts for revealing the mechanism of electrocatalytic reactions. This review summarizes recent progress in atom‐level engineering of metal NCs as model catalysts for electrocatalytic reactions. Specifically, we first discuss the effects of metal composition engineering, including doping and size effects, on the electrocatalytic performance of metal NCs. Then similar electrocatalytic discussion extends to ligand effects of metal NCs, where ligand type and coverage engineering are deciphered. Moreover, we discuss how the overall charge and morphology of NCs modify their electrocatalytic performance. The fundamental and methodological insights summarized in this review should serve as useful references guiding the future development of effective metal electrocatalysts in diverse sectors of industry.

ABSTRACTMachine learning (ML), material genome, and big data approaches are highly overlapped in their strategies, algorithms, and models. They can target various definitions, distributions, and correlations of concerned physical parameters in given polymer systems, and have expanding applications as a new paradigm indispensable to conventional ones. Their inherent advantages in building quantitative multivariate correlations have largely enhanced the capability of scientific understanding and discoveries, thus facilitating mechanism exploration, target prediction, high‐throughput screening, optimization, and rational and inverse designs. This article summarizes representative progress in the recent two decades focusing on the design, preparation, application, and sustainable development of polymer materials based on the exploration of key physical parameters in the composition–process–structure–property–performance relationship. The integration of both data‐driven and physical insights through ML approaches to deepen fundamental understanding and discover novel polymer materials is categorically presented. Despite the construction and application of robust ML models, strategies and algorithms to deal with variant tasks in polymer science are still in rapid growth. The challenges and prospects are then presented. We believe that the innovation in polymer materials will thrive along the development of ML approaches, from efficient design to sustainable applications.

ABSTRACTInterface engineering based on polymer dielectrics shows great promise in organic field‐effect transistors (OFETs)‐based neuromorphic vision sensors (NeuVS). However, the highly disordered chain arrangement of polymer dielectrics often has a negative impact on the dynamic behavior of charge carriers, thereby affecting the sensing, memory, and computing performance of devices. To this end, we report an effective strategy to improve the orientation of polymer dielectrics by using a coordination combination of metal–organic frameworks (MOFs) and polymer. As a result, the coordination of MOFs with polymers improves the polarization of hydroxyl (−OH) and the resulting interfacial dipole could achieve an increase of photogenerated carriers in NeuVS with both higher mobility (above 20 cm2/(V ∙ s)) and better optical figures of merit than devices without the coordination of MOFs. Furthermore, the new MOFs‐polymer dielectric gives NeuVS devices temporal dynamics that enable better color extraction in static images. More importantly, in‐sensor perception of moving objects was simulated, allowing postprocessing to produce over 95% action recognition accuracy. This attempt provides a new idea for the development of dielectric materials for highly sensitive light detection and visuomorphic computing.

ABSTRACTIn human interactions, social touch communication is widely used to convey emotions, emphasizing its critical role in advancing human–robot interactions by enabling robots to understand and respond to human emotions, thereby significantly enhancing their service capabilities. However, the challenge is to dynamically capture social touch with sufficient spatiotemporal and mechanical resolution for deep haptic data analysis. This study presents a robotic system with flexible electronic skin and a high‐frequency signal circuit, utilizing deep neural networks to recognize social touch emotions. The electronic skin, made from double cross‐linked ionogels and microstructured arrays, has a low force detection threshold (8 Pa) and a wide perception range (0–150 kPa), enhancing the mechanical resolution of touch signals. By incorporating a high‐speed readout circuit capable of capturing spatiotemporal features of social touch gesture information at 30 Hz, the system facilitates precise analysis of touch interactions. A 3D convolutional neural network with a Squeeze‐and‐Excitation Attention module achieves 87.12% accuracy in recognizing social touch gestures, improving the understanding of emotions conveyed through touch. The effectiveness of the system is validated through interactive demonstrations with robotic dogs and humanoid robots, demonstrating its potential to enhance the emotional intelligence of robots.