智能化电子信息技术发展及应用分析

文章首先对智能化电子信息技术进行了深入的研究,而后分析了该技术在应用过程中出现的问题,最后结合该技术的相关特点给出了相应的问题解决措施,希望能够对智能化电子信息技术的发展提供帮助。     

Porous CoNiOOH nanosheets derived from the well-mixed MOFs as stable and highly efficient electrocatalysts for water oxidation

The development of efficient and stable electrocatalysts is of great significance for improving water splitting. Among them, transition metal oxyhydroxides show excellent performance in oxygen evolution reactions (OER), but there are certain difficulties in direct preparation. Recently, Metal–organic frameworks (MOFs) as precatalysts or precursors have shown promising catalytic performance in OER and can be decomposed under alkaline conditions. Therefore, using a mild and controllable way to convert MOFs into oxyhydroxides and retaining the original structural advantages is crucial for improving the catalytic activity. Herein, a rapid electrochemical strategy is used to activate well-mixed MOFs to prepare Co/Ni oxyhydroxide nanosheets for efficient OER catalysts, and the structural transformation in this process was investigated in detail by using scanning electron microscope, X-ray diffraction, Raman, X-ray photoelectron spectroscopy and electrochemical methods. It is discovered that electrochemical activation can promote ligand substitution of well-mixed MOFs to form porous oxyhydroxide nanosheets and tune the electronic structure of the metal (Co and Ni), which can lead to more active site exposure and accelerate charge transfer. In addition, the change of structure also improves hydrophilicity, as well as benefiting from the strong synergistic effect between multiple species, the optimal a-MCoNi–MOF/NF has excellent OER performance and long-term stability. More obviously, the porous CoNiOOH nanosheets are formed in situ during electrochemical activation process through structural transformation and acts as the active centers. This work provides new insights for mild synthesis of MOFs derivatives and also provides ideas for the preparation of highly efficient catalysts.     

Machine learning algorithm selection for windage alteration fault diagnosis of mine ventilation system

Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation.     

Flexible,Mechanically Stable,Porous Self-Standing Microfiber Network Membranes of Covalent Organic Frameworks: Preparation Method and Characterization

Covalent organic frameworks (COFs) show advantageous characteristics, such as an ordered pore structure and a large surface area for gas storage and separation, energy storage, catalysis, and molecular separation. However, COFs usually exist as difficult-to-process powders, and preparing continuous, robust, flexible, foldable, and rollable COF membranes is still a challenge. Herein, such COF membranes with fiber morphology for the first time prepared via a newly introduced template-assisted framework process are reported. This method uses electrospun porous polymer membranes as a sacrificial large dimension template for making self-standing COF membranes. The porous COF fiber membranes, besides having high crystallinity, also show a large surface area (1153 m² g⁻¹), good mechanical stability, excellent thermal stability, and flexibility. This study opens up the possibility of preparation of large dimension COF membranes and their derivatives in a simple way and hence shows promise in technical applications in separation, catalysis, and energy in the future.     

Organic Semiconducting Luminophores for Near-Infrared Afterglow,Chemiluminescence, and Bioluminescence Imaging

Optical imaging has played a pivotal role in deciphering in vivo bioinformatics but is limited by shallow penetration depth and poor imaging performance owing to interfering tissue autofluorescence induced by concurrent photoexcitation. The emergence of near-infrared (NIR) self-luminescence imaging independent of real-time irradiation has timely addressed these problems. There are two main kinds of self-luminescent agents, namely inorganic and organic luminophores. Inorganic luminophores usually suffer from long-term biotoxicity concerns resulting from potential heavy-metal ions leakage and nonbiodegradability, which hinders their further translational application. In contrast, organic luminophores, especially organic semiconducting luminophores (OSLs) with good biodegradable potential, tunable design, and outstanding optical properties, are preferred in biological applications. This review summarizes the recent progress of OSLs used in NIR afterglow, chemiluminescence, and bioluminescence imaging. Molecular manipulation and nanoengineering approaches of OSLs are discussed, with emphasis on strategies that can extend the emission wavelength from visible to NIR range and amplify luminescence signals. This review concludes with a discussion of current challenges and possible solutions of OSLs in the self-luminescence field.     

The Chemistry of DPPH· Free Radical and Congeners

Since the discovery in 1922 of 2,2-diphenyl-1-(2,4,6-trinitrophenyl) hydrazyl stable free radical (DPPH^·), the chemistry of such open-shell compounds has developed continuously, allowing for both theoretical and practical advances in the free radical chemistry area. This review presents the important, general and modern aspects of the chemistry of hydrazyl free radicals and the science behind it.     

Thiol-Functionalized Covalent Organic Frameworks as Thermal History Indictor for Temperature and Time History Monitoring

Various products, including foods and pharmaceuticals, are sensitive to temperature fluctuations. Thus, temperature monitoring during production, transportation, and storage is critical. Facile indicators are required to monitor temperature conditions via color changes in real time. This study aimed to prepare and apply thiol-functionalized covalent organic frameworks (COFs) as a novel indicator for monitoring thermal history and temperature abuse. The COFs underwent obvious color changes from bright yellow to purple after exposure to different temperatures for varying durations. The reaction kinetics are analyzed under isothermal conditions, which reveal that the order of reaction rates is k_−20°C < k_4°C < k_20°C < k_35°C < k_55°C. The activation energy (E_a) of the COFs is calculated using the Arrhenius equation as 50.71 kJ moL⁻¹. The COFs are capable of sensitive color changes and offer a broad temperature tracking range, thereby demonstrating their application potential for the monitoring of temperature and time exposure history during production, transportation, and storage. This excellent performance thermal history indicator also shows promise for expanding the application field of COFs.     

High-Performance Solution-Processed Nondoped Circularly Polarized OLEDs with Chiral Triptycene Scaffold-Based TADF Emitters Realizing Over 20% External Quantum Efficiency

Recently, circularly polarized organic light-emitting diodes (CP-OLEDs) fabricated with thermally activated delayed fluorescence (TADF) emitters are developed rapidly. However, most devices are fabricated by vacuum deposition technology, and developing efficient solution-processed CP-OLEDs, especially nondoped devices, is still a challenge. Herein, a pair of triptycene-based enantiomers, (S,S)-/(R,R)-TpAc-TRZ, are synthesized. The novel chiral triptycene scaffold of enantiomers avoids their intermolecular π–π stacking, which is conducive to their aggregation-induced emission characteristics and high photoluminescence quantum yield of 85% in the solid state. Moreover, the triptycene-based enantiomers exhibit efficient TADF activities with a small singlet-triplet energy gap (ΔE_ST) of 0.03 eV and delayed fluorescence lifetime of 1.1 µs, as well as intense circularly polarized luminescence with dissymmetry factors (|g_PL|) of about 1.9 × 10⁻³. The solution-processed nondoped CP-OLEDs based on (S,S)-/(R,R)-TpAc-TRZ not only display obvious circularly polarized electroluminescence signals with g_EL values of +1.5 × 10⁻³ and −2.0 × 10⁻³, respectively, but also achieve high efficiencies with external quantum, current, and power efficiency up to 25.5%, 88.6 cd A⁻¹, and 95.9 lm W⁻¹, respectively.     

Boosting the hydrogenation activity of dibenzyltoluene catalyzed by Mg-based metal hydrides

Hydrogenation of dibenzyltoluene (DBT) is of great significance for the application in liquid organic hydrogen carriers (LOHCs). We successfully develop Mg-based metal hydrides (Mg₂NiH₄, MgH₂, and LaH₃) reactive ball-milling for the hydrogenation of DBT. Mg-based metal hydrides milled with 500 min exhibit the best catalytic activity, the hydrogen uptake of DBT can reach 4.63 wt% at the first 4 h and finally achieve 5.70 wt% through 20 h, which is the first time to use hydrogen storage material as a catalyst for the hydrogenation of DBT. The excellent catalytic hydrogenation performance of Mg-based metal hydrides mostly originates from numerous catalytic activity centers formed at the surfaces of Mg₂NiH₄ nanoparticles in the MgH₂ matrix. Inspired by this mechanism, more general metal hydrides can be explored for catalyzing the hydrogenation of LOHCs. The new application of Mg-based metal hydrides is beneficial to developing efficient LOHC based hydrogen storage systems and offers novel insights to hydride-based catalysts.