“模式识别”课程线上线下混合教学模式探索与实践

在模式识别课程教学中,针对传统线下课程短板,开展线上与线下相结合的混合教学模式教学改革探索。阐述了本课程教学改革的教学环节设计、教学实施方法、考核方式等,以思维导图和综合案例串联庞杂知识点,采用多样化手段,加强对学生创新思维和能力的培养。教学实践证明,该课程教学改革调动了学生主动性,培育了其创新能力与科学精神,丰富了线上线下混合教学改革的理论研究。     

农林高校电气类专业教学改革与思政探索

在以德为先的教育背景下,高校意识形态问题是人才培养的关键。如何将课程思政的思想以专业知识为载体巧妙渗透到课堂中,是未来高等教育需要思考的重要问题。本文基于农林高校电气类专业实际情况,深入挖掘具有思政元素且特色鲜明的电气专业教学体系,提出面向“三农需求”的“一主线、四段式、八深入”课程体系改革融入构架,并给出以“林区新能源发电技术”为例的课程思政改革方案实例。     

检测技术类专业课程的思政教育实践探索

高校专业课程课堂教学是实践思政教育的主战场。针对检测技术类课程专业理论知识教学内容,探索了课程思政教育方法。通过设计思政教学切入点、凝练思政元素,形成课程知识与思政内容深度融合、互为促进的课程体系,实现了价值塑造与专业培养的目标融合。     

Doped/Undoped A1-A2 Typed Copolymers as ETLs for Highly Efficient Organic Solar Cells

The electron transport layer (ETL) is a critical component in achieving high device performance and stability in organic solar cells. Conjugated polyelectrolytes (CPEs) have become an attractive alternative due to film-forming properties and ease of preparation. However, p-type CPEs generally exhibit poor charge mobility and conductivity, incorporation of electron-withdrawing units forming alternated D-A conjugated backbone can make up for these deficiencies. Herein, the ratio of electron withdrawing moieties are further increased and two poly(A1-alt-A2) typed PIIDNDI-Br and PDPPNDI-Br based on the combination of naphthalene diimide (NDI) with isoindigo (IID) or diketopyrrolopyrrole (DPP) via direct arylation polycondensation are synthesized. These CPEs possess excellent alcohol solubility, a suitable lowest unocuppied molecular orbital energy level, and work function tunability. Surprisingly, the incorporation of IID and DPP units generate distinct self-doping behaviors, which are confirmed by UV–vis absorption and ESR spectra. However, no matter doped or undoped, both CPEs present better charge-transporting properties and conductivity when utilized as ETLs. The PIIDNDI-Br and PDPPNDI-Br display good universal compatibility with the blend of PM6:Y6 and PM6:L8-BO, and PCEs of 18.32% and 18.36% are obtained, respectively, which also present excellent storage stability. In short, the combination of two different acceptors demonstrates an efficient strategy to design highly efficient ETLs for high performance photovoltaic devices.     

Self-Adhesive Polydimethylsiloxane Foam Materials Decorated with MXene/Cellulose Nanofiber Interconnected Network for Versatile Functionalities

Polydimethylsiloxanes (PDMS) foam as one of next-generation polymer foam materials shows poor surface adhesion and limited functionality, which greatly restricts its potential applications. Fabrication of advanced PDMS foam materials with multiple functionalities remains a critical challenge. In this study, unprecedented self-adhesive PDMS foam materials are reported with worm-like rough structure and reactive groups for fabricating multifunctional PDMS foam nanocomposites decorated with MXene/cellulose nanofiber (MXene/CNF) interconnected network by a facile silicone foaming and dip-coating strategy followed by silane surface modification. Interestingly, such self-adhesive PDMS foam produces strong interfacial adhesion with the hybrid MXene/CNF nano-coatings. Consequently, the optimized PDMS foam nanocomposites have excellent surface super-hydrophobicity (water contact angle of ≈159^o), tunable electrical conductivity (from 10⁻⁸ to 10 S m⁻¹), stable compressive cyclic reliability in both wide-temperature range (from −20 to 200 ^oC) and complex environments (acid, sodium, and alkali conditions), outstanding flame resistance (LOI value of >27% and low smoke production rate), good thermal insulating performance and reliable strain sensing in various stress modes and complex environmental conditions. It provides a new route for the rational design and development of advanced PDMS foam nanocomposites with versatile multifunctionalities for various promising applications such as intelligent healthcare monitoring and fire-safe thermal insulation.     

Improved aquila optimization-based parameter evaluation framework and meta-heuristic algorithm in radio-over-fiber SpatialMux multi-input multi-output long-term evolution system

In heterogeneous access network, Multiple-Input Multiple-Output (MIMO) radio-over-fiber (RoF) system is an efficient approach for multiple signal transmission with low cost and complexity. The performance of RoF fronthaul system in MIMO system will be varied with different nonlinear effects. By adjusting various transmission parameters, such as the input signal power or the laser bias current, the nonlinear impacts produced by the RoF system can be reduced. In this paper, a novel algorithm Improved Aquila Optimization (IAO) is proposed to optimize transmission circumstances of MIMO RoF system. It determines the appropriate bias current for both lasers and Radio Frequency (RF) signal power in a short period. The input signals are wavelength multiplexed with Intensity Modulation and Direct Detection (IM/DD) applied. The carrier as well as transmission frequency is governed by the MIMO-Long-Term Evolution (LTE) standard. The proposed system is implemented in MATLAB, and the performance is evaluated. The experimental results show that fast convergence and trade-off between noise and nonlinearity are obtained with varying bandwidth. In the experimental scenario, the maximum Error Vector Magnitude (EVM) of 1.88, 3.14, and signal-to-noise ratio (SNR) of 3.204, and 2.698 was attained for both quadrature phase shift keying (QPSK) and quadrature amplitude modulation (QAM) modulation. [Correction added on 24 April 2023, after first online publication: the SNR values were corrected in the preceding sentence.] For 100 iterations, the processing time was reduced to 0.137 s. When compared with the conventional state-of-the-art approaches, the accuracy and computational complexity of the proposed approach are improved.     

An Artificial Autonomic Nervous System That Implements Heart and Pupil as Controlled by Artificial Sympathetic and Parasympathetic Nerves

The autonomic nervous system maintains homeostasis in organisms through complex neural pathways and responds adaptively to changes in the external and internal environment. The fabrication of an artificial autonomic nervous system is reported that replicates combined effects of sympathetic and parasympathetic nerves on cardiac activity and pupillary control, to mimic the regulation of autonomic nervous system to external changes. The artificial autonomic nerve-controlled pupil contraction and relaxation, modulating the rate of heartbeats for normal cardiac rhythm and arrhythmia as reflected by blink rates of a signal indicator. These functions are switched by using a parallel-channeled synaptic transistor with a special n-i-p heterostructure that has a 2D h-BN insulator in the middle to provide barrier against ion injection into the 2D MoS₂ bottom n-channel and enable short-term plasticity as induced by acetylcholine, and the electrochemical doping reaction occurred at the P3HT nanowire p-channels on top to enable relatively long-term plasticity as induced by noradrenaline. Low-energy consumption down to femtojoule and an ultrahigh paired-pulse facilitation index up to ≈455% are demonstrated. An artificial neural network based on device characteristics achieves a high recognition accuracy for electrocardiogram patterns. This study extends insights into artificial nerves-inspired biological signal processing and recognition.     

Kinetically Accelerating Elementary Steps via Bridged Ru-H State for the Hydrogen-Evolution in Anion-Exchange Membrane Electrolyzer

Designing hydrogen evolution reaction (HER) electrocatalysts for facilitating its sluggish adsorption kinetics is crucial in generating green hydrogen via sustainable water electrolysis. Herein, a high-performance ultra-low Ruthenium (Ru) catalyst is developed consisting of atomically-layered Ru nanoclusters with adjacent single Ru sites, which executs a bridging-Ru-H activation strategy to kinetically accelerate the HER elementary steps. Owing to its optimal electronic structure and unique adsorption configuration, the hybrid Ru catalyst simultaneously displayed a drastically reduced overpotential of 16 mV at 10 mA cm⁻² as well as a low Tafel slope of 35.2 mV dec⁻¹ in alkaline electrolyte. When further coupled with a commercial IrO₂ anode catalyst, the ensembled anion-exchange membrane water electrolyzer achievs a current density of 1.0 A cm⁻² at a voltage of only 1.70 V_cell. In situ spectroscopic analysis verified that Ru single atom and atomically-layered Ru nanoclusters in the hybrid materials play a critical role in facilitating water dissociation and weakening *H adsorption, respectively. Theoretical calculations further elucidate the underlaying mechanism, suggesting that the dissociated proton at the single atom Ru site orients itself adjacently with Ru nanoclusters in a bridged structure through targeted charge transfer, thus promoting Volmer-Heyrovsky dynamics and boosting the HER activity.     

Electret Molecular Configuration Induced Programmable Photonic Memory for Advanced Logic Operation and Data Encryption

Nonvolatile organic photonic transistor (OPT) memories have attracted widespread attention due to their nondestructive readout, remote controllability, and robust tunability. Developing electrets with similar molecular structures but different memory behaviors and light-responsive features is crucial for light-wavelength-modulated data encryption. However, reported OPT memories have yet to meet this challenge. Here a new electret molecule (“H-PDI”) is developed via reconfiguring the linear perylene diimide molecule (“L-PDI”) to a helical shape. Respectively incorporating H-PDI and L-PDI into the floating gate layer results to H-PDI OPT and L-PDI OPT. Attributing to their remarkably different electronic structures and energy bandgaps, H-PDI OPT and L-PDI OPT preferably respond to 405 and 532 nm light irradiation, respectively. Upon electrical programming, data can be written and stored in both memories with good retention features and a high “1”/“0” state current ratio over 10⁵, though the data can only be erased by light with correct wavelengths, rather than the electrical field. Moreover, data stored in a memory array consisting of both H-PDI OPT and L-PDI OPT can only be read out by correct inputs, and wrong inputs will lead to highly deceptive outputs. This study provides a general design strategy of OPT for advanced data encryption and protection.     

On-chip Diamond MEMS Magnetic Sensing through Multifunctionalized Magnetostrictive Thin Film

Electrically integrable, high-sensitivity, and high-reliability magnetic sensors are not yet realized at high temperatures (500 °C). In this study, an integrated on-chip single-crystal diamond (SCD) micro-electromechanical system (MEMS) magnetic transducer is demonstrated by coupling SCD with a large magnetostrictive FeGa film. The FeGa film is multifunctionalized to actuate the resonator, self-sense the external magnetic field, and electrically readout the resonance signal. The on-chip SCD MEMS transducer shows a high sensitivity of 3.2 Hz mT⁻¹ from room temperature to 500 °C and a low noise level of 9.45 nT Hz^−1/2 up to 300 °C. The minimum fluctuation of the resonance frequency is 1.9 × 10⁻⁶ at room temperature and 2.3 × 10⁻⁶ at 300 °C. An SCD MEMS resonator array with parallel electric readout is subsequently achieved, thus providing a basis for the development of magnetic image sensors. The present study facilitates the development of highly integrated on-chip MEMS resonator transducers with high performance and high thermal stability.