Objective Mass transfer and diffusion are core concepts in environmental engineering and pollution control. However, undergraduate students are often exposed to these concepts mainly through mathematical equations or simplified verification experiments, making it difficult for them to relate transport phenomena to complex catalytic reaction systems. In porous catalysts used for advanced oxidation processes, catalytic performance is governed by their active-site chemistry, pore architecture, channel connectivity, reactant accessibility, and diffusion pathways. To address this educational gap, an open experimental teaching module was developed using Fe-, N-, and S-codoped carbon (FeNSC) catalysts with different pore structures as the instructional platform. The module was designed to help students understand how pore architecture affects peroxymonosulfate (PMS) activation and pollutant degradation while developing their ability to interpret catalytic behavior through a structureu2013diffusionu2013performance correlation. Methods Three FeNSC catalysts were selected as experimental materials: FeNSC/SBA-15, FeNSC/KIT-6, and FeNSC/SiO2-NPs, representing a two-dimensional unidirectional channel structure, a three-dimensional ordered interconnected pore network, and a three-dimensional disordered multidirectional porous structure, respectively. The experiment integrated catalyst characterization, PMS activation, pollutant degradation, and comparative data analysis. The FeNSC catalysts were pre-synthesized by the instructor using different SiO2 templates and supplied to students for characterization and performance evaluation. Transmission electron microscopy and nitrogen adsorptionu2013desorption analysis were used to characterize pore morphology, channel architecture, and pore-size distribution, while X-ray diffraction and X-ray photoelectron spectroscopy were employed to determine crystal structure, elemental composition, and surface chemical states. These characterization results provided the structural basis for analyzing the internal migration behavior of PMS, p-nitrophenol (p-NP), and reaction intermediates within different pore systems. PMS decomposition tests were first conducted to evaluate the PMS activation efficiency of each FeNSC catalyst. Residual PMS concentrations were determined using the KI/NaHCO3 colorimetric method using ultravioletu2013visible (UVu2013vis) spectrophotometry at 352 nm. Pollutant degradation experiments were then performed using p-NP as the model pollutant. Adsorption tests were conducted before PMS addition to distinguish adsorption from catalytic oxidation. After PMS was introduced, samples were collected at predetermined time intervals, filtered, and analyzed via UVu2013vis spectrophotometry to generate degradation kinetic curves. Students compared PMS consumption, pollutant removal efficiency, initial reaction rates, residual concentrations, and late-stage reaction behavior under different PMS concentrations and pollutant loadings. Results The experiment enabled students to distinguish the three pore architectures and relate their structural characteristics to diffusion behavior. FeNSC/SBA-15 showed ordered unidirectional channels, providing an effective model for demonstrating one-dimensional diffusion and local mass-transfer limitations resulting from weak lateral connectivity. FeNSC/KIT-6 possessed an ordered three-dimensional interconnected pore network, making it suitable for illustrating multipath diffusion, continuous reactant transport, and improved accessibility to internal active sites. By contrast, FeNSC/SiO2-NPs exhibited a more open but disordered porous structure, helping students understand multidirectional diffusion through irregular pore channels. By correlating structural characterization results with PMS activation and p-NP degradation profiles, students recognized that catalytic performance cannot be explained only by the number of active sites or the apparent reaction rate. Under low reactant loadings, differences in catalytic performance among the three catalysts were relatively small. However, at high PMS concentrations or pollutant loadings, pore connectivity and diffusion pathways became increasingly important. The resulting kinetic curves reflected the combined effects of reactant transport, active-site accessibility, reactive-species utilization, and sustained catalytic activity. Furthermore, correlating performance curves with schematic illustrations of pore structures transformed otherwise invisible diffusion processes into observable and interpretable experimental phenomena. Conclusions An open experimental teaching module based on FeNSC catalysts with different pore architectures was established for undergraduate environmental engineering education. By integrating material characterization, PMS activation, pollutant degradation, and mechanism-oriented analysis, the module provides a distinct connection between microscopic pore structures and macroscopic reaction behavior. Concepts such as diffusion pathways, mass-transfer resistance, active-site accessibility, and reaction sustainability are transformed into experimentally observable phenomena supported by structural characterization and quantitative data. This module improves studentsu2019 experimental skills, data analysis, graphical interpretation, and mechanism-based reasoning while providing a practical model for developing comprehensive open laboratory experiments in environmental engineering.
Objective Current undergraduate environmental engineering education faces pedagogical bottlenecks as laboratory courses on nonpoint source pollution monitoring and prevention lag behind practical needs. This gap is attributable to the failure of traditional steady-state and constant-flow experiments to reproduce the nonstationary, nonlinear, and multifactor-coupled environmental processes associated with real nonpoint source pollution. Meanwhile, natural rainfall monitoring is severely constrained by temporal randomness and the difficulty of deploying field instruments, nearly preventing experimental teaching under real-world conditions. These limitations hinder the cultivation of studentsu2019 ability to solve u201Ccomplex engineering problemsu201D as required by accreditation standards. To address these issues, this study designs a comprehensive experiment to investigate the characteristics of carbon, nitrogen, and phosphorus losses from slopes using an artificial rainfall simulation system. The aim is to integrate the whole chain of u201Crainfallu2013soil erosionu2013pollutant release and transportu2013pollutant prediction and controlu201D into experimental teaching, thereby providing a solid foundation for cultivating multi-skilled talents with engineering practice and innovative skills. Methods The experiment employs a high-precision multinozzle downward-spray rainfall simulator and a variable-slope runoff trough, using typical sandy yellow loam soil from the upper reaches of the Yangtze River as the test subject. An orthogonal array of u201Crainfall intensity u00D7 slope gradientu201D is constructed to systematically investigate the characteristics of runoff generation, sediment yield, and the associated carbon, nitrogen, and phosphorus losses from the slope. The synergistic relationships among runoff, sediment, and nutrient transport are revealed, and predictive estimations of carbon, nitrogen, and phosphorus losses in runoff are further performed. Results Experimental results for the yellow loam slope showed that the runoff rate exhibited a distinct three-stage temporal evolution under all treatment combinations: rapid increase, slow rise, and eventual stabilization. Cumulative runoff per unit area increased significantly with rainfall intensity but decreased with increasing slope gradient, following the order 6u00B0u0026gt;12u00B0u0026gt;18u00B0. The sediment yield rate peaked in the early stage and then declined rapidly to a stable level; total sediment yield increased with rainfall intensity, while its response to slope followed an inverted U-shaped nonlinear trend, with the critical slope angle identified at approximately 12u00B0. Carbon loss was dominated by sediment-associated total carbon (STC), with the highest total carbon load (5286.23 mg/m2) occurring under the combination of high rainfall intensity (90 mm/h) and moderate slope (12u00B0). Sediment-associated total nitrogen (STN) accounted for more than 70% of the total nitrogen loss, and the peak total nitrogen load appeared under the moderate intensity and moderate slope combination. Sediment-associated total phosphorus (STP) constituted 70%u201396% of the total phosphorus loss, and the peak total phosphorus loss occurred under moderate intensity or under the 12u00B0 slope. Correlation analysis revealed that sediment yield was significantly positively correlated with STN, STP, total nitrogen, and total phosphorus. The correlation coefficients exceeded 0.90 in all cases, confirming that sediment serves as the primary carrier for carbon, nitrogen, and phosphorus export. Furthermore, the prediction models for STC, STN, and STP trained using artificial neural networks achieved coefficient-of-determination values exceeding 0.7, demonstrating their capability to effectively support field-scale load estimation. Conclusions Practical implementation demonstrates that the experiment achieves a deep integration of macroscopic hydrodynamic erosion with microscopic pollutant migration. This integration significantly enhances studentsu2019 understanding of complex environmental engineering problems, deepens their mastery of core courses such as environmental monitoring and pollution control engineering, and strengthens their engineering practice ability and innovative thinking. Moreover, the experimental module can be readily extended to incorporate emerging research frontiers such as microplastic transport and pesticide wash-off. It can also be combined with virtual simulation to establish a u201Cvirtualu2013physicalu2013applicationu201D integrated teaching model. This approach provides a scalable and comprehensive experimental platform for cultivating innovative talents in resource and environmental sciences.
Objective With the rapid development of the Internet of Things and wireless sensor networks, the trade-off between enhancing information transmission and moderating device power requirements is becoming increasingly prominent. To help students understand the fieldu2011circuit cou2011design mechanism in microwave technology, this paper describes a comprehensive experimental project based on simultaneous wireless information and power transfer (SWIPT) technology. This project focuses on the joint design of a rectifying metasurface antenna, translating a cuttingu2011edge research topic into a feasible undergraduate teaching case. Methods The experiment follows two main approaches: decomposing a complex problem and simulationu2011driven design. The SWIPT receiving end is divided into three modules: a circularly polarized antenna, an energyu2011harvesting metasurface, and a rectifying diode. A singleu2011stage parallel rectifier circuit using an HSMS2860 Schottky diode was simulated in Keysight Advanced Design System (ADS), in which a harmonic balance simulation with parameter sweeps determined the optimal input impedance and load. An arrowu2011shaped metasurface unit operating at 5.8 GHz was designed in CST Microwave Studio with periodic boundary conditions. A time-domain solver with open boundary conditions is used to simulate an infinite array. A lumped RC element with R = 87.81 u03A9 and C = 0.65 pF modeled the diode. The unit's energy-harvesting efficiency was calculated by dividing the power dissipated in the lumped element by the total incident power. The communication antenna is a circularly polarized microstrip antenna operating at 2.45 GHz, designed using the singleu2011feed corneru2011truncation method. The antenna's reflection coefficient, axial ratio, and faru2011field gain were simulated. Finally, a sharedu2011aperture system was built in CST using a stacked structure comprising a bottom ground, a 1.575 mm-thick middle patch antenna, and a 2 mm-thick top metasurface array. After analyzing the surface current distributions, the load resistors in the strongest coupling region were repositioned to reduce mutual interference. Results The rectifier circuit achieved a peak efficiency of 65.62% at 5.8 GHz with an input power of 14.77 dBm and a load of 150 u03A9. Under these conditions, the diode impedance is 87.81u2212j42.22 u03A9. The individual metasurface unit showd S11 = u221219.23 dB at 5.8 GHz and an energy-harvesting efficiency of 99.2% at normal incidence. The efficiency was above 80% for incident angles up to 50u00B0 and above 98% for polarization angles of 0u00B0u221280u00B0, demonstrating good polarization insensitivity and wideu2011angle stability. In the initial shared-aperture system, the 5.8 GHz energy-harvesting efficiency was 84.53%. The 2.45 GHz antenna had S11 = u221213.45 dB, an axial ratio of 0.396 (well below 3 dB), and a maximum gain of 5.65 dBi. However, surface current analysis showed that approximately 35% of the antenna's radiated power is absorbed by the metasurface owing to strong coupling. After relocating the load resistors, the antenna performance improved significantly. S11 increased to u221218.61 dB, the axial ratio remains at 1.20 (still below 3 dB), and the gain increased to 7.46 dBi. This represented a gain improvement of 1.81 dB compared to the initial design. The energy harvesting efficiency at 5.8 GHz decreased moderately to 76.10% but remains above 70% over the 5.62~5.89 u202FGHz band. This tradeu2011off clearly illustrated the cou2011design principle of SWIPT systems. Conclusions This experiment integrates metasurface electromagnetic manipulation, nonlinear rectifier analysis, and cou2011aperture design for energy and information. The cou2011simulation workflow using CST for fullu2011wave simulation and ADS for circuit simulation reflects real engineering practice. Tradeu2011off optimization helps students grasp the fieldu2011circuitu2013energyu2011information cou2011design concept. This project provides a practical, inquiryu2011based experimental case for electronic information engineering education.
Objective The high penetration of distributed photovoltaic generation and energy storage has intensified the dynamic interactions between grid-connected converters and low-voltage distribution networks. In three-phase four-wire systems, the integration of single-phase inverters, unbalanced operating conditions, neutral-line impedance, and zero-sequence components further complicates small-signal stability analysis. Existing state-space and impedance-based methods have been primarily developed for three-phase three-wire systems and are insufficient for describing the coupled oscillation characteristics arising from positive-, negative-, and zero-sequence interactions. To address this issue, this study proposes a quantitative stability analysis and improvement method for multinode three-phase four-wire systems with distributed renewable energy integration. Methods Admittance models of key components, including single-phase photovoltaic inverters, three-phase four-leg energy storage inverters, grid impedance, line impedance, and impedance loads, were established in the sequence domain. Dual-frequency and sequence-component coupling were considered during the modeling process. Based on the component admittance models and the system topology, an s-domain nodal admittance matrix was constructed for the multinode three-phase four-wire system. Oscillation modes were obtained by solving for the zeros of the determinant of the nodal admittance matrix. To identify the dominant oscillation sources and weak nodes, a nodal participation factor was derived from the modal information of the nodal admittance matrix. In addition, a parameter sensitivity calculation method was developed to quantify the influence of control parameters on the damping and frequency of each oscillation mode. A stability improvement strategy was then designed by jointly considering nodal participation factors and parameter sensitivities. During the optimization process, parameters with a strong influence on unstable modes but a limited influence on other stable modes were selected and adjusted within their allowable ranges. Results A Belgian seven-node low-voltage radial distribution feeder equipped with distributed photovoltaic units and a three-phase four-leg energy storage inverter was used for verification. The results show that the oscillation modes of the three-phase four-wire system form coupled mode groups because of interactions among different sequence components and frequencies. Nodal participation factor analysis indicates that photovoltaic units connected to terminal nodes make dominant contributions to the critical oscillation modes. Before optimization, one oscillation mode exhibited insufficient damping, indicating potential instability. After applying the proposed parameter optimization strategy, the phase-locked-loop and current-controller parameters were adjusted in a coordinated manner, and the critical oscillation mode moved into the stable region. Compared with a strategy that adjusts only a single control parameter, the proposed method avoids deteriorating other stable modes and improves the overall stability margin. Time-domain simulation results further show that oscillatory components in the grid-connected current, voltage, and power are rapidly attenuated after parameter optimization. Fast Fourier Transform(FFT) results demonstrate that the total harmonic distortion of the grid-connected current decreases. Conclusions The proposed method can accurately characterize the coupled oscillation behavior of three-phase four-wire systems by incorporating dual-frequency and sequence-component coupling into the nodal admittance matrix. The nodal participation factor provides an effective tool for locating oscillation sources and weak nodes, whereas parameter sensitivity analysis offers a quantitative basis for control-parameter optimization. The case study verifies that the proposed stability improvement strategy can suppress coupled oscillations, enhance system damping, and improve the systemu2019s operational stability in three-phase four-wire grid-connected systems with a high penetration of distributed renewable energy.
Objective Coal spontaneous combustion fires are a major hazard threatening coal mine safety. Accurate and efficient prediction technologies are essential for underground mine fire prevention and control, with odor analysis emerging as an important research area for the early warning of coal spontaneous combustion. Owing to its advantages, including rapid response, short detection times, long monitoring periods, low power consumption, high sensitivity, simple operation, and portability, electronic nose technology has been widely applied in food safety supervision, environmental monitoring, clinical diagnosis, and chemical safety evaluation. To facilitate the reform of interdisciplinary experimental teaching and broaden senior undergraduate students' understanding of cutting-edge scientific research, this study introduces electronic-nose sensing technology into the prediction of coal spontaneous combustion and develops a comprehensive experimental course entitled Prediction Method of Coal Spontaneous Combustion Odor Based on Electronic Nose Technology. The experimental design enables students to independently complete literature reviews, experimental scheme design, and result analysis, thereby stimulating their enthusiasm for scientific exploration and cultivating their innovative awareness and comprehensive scientific literacy. Methods A self-developed coupled experimental system integrating programmed temperature rise and electronic nose detection was constructed. The system comprised three functional modules: a programmed coal-sample temperature control unit, a gas supply unit, and an electronic nose signal detection unit. A teaching framework integrating instructor guidance with group-based collaborative experimentation was adopted. Students were divided into multiple groups to conduct programmed heating tests that reproduced the complete evolutionary process of coal spontaneous combustion. Characteristic odor signals released during coal oxidation were captured using the electronic nose system. Following data preprocessing and quantitative analysis, radar charts illustrating the relationship between odor response signals and coal temperature were generated. The coupling relationship between odor characteristics and temperature variations was quantified, and linear discriminant analysis was implemented to distinguish various oxidation stages of coal spontaneous combustion. Finally, an odor-driven prediction model for coal spontaneous combustion was established. Results The self-built integrated platform for programmed heating and odor signal collection enabled real-time monitoring and feature extraction of volatile odor signals released during the thermal oxidation of coal. The system effectively tracked the dynamic evolution of typical gaseous products, including aldehydes, ketones, benzene homologs, and alkanes, throughout the coal oxidation process, providing a stable and reliable experimental platform for analyzing odor signatures induced by coal spontaneous combustion. Significant correlations were observed among electronic nose sensor responses, coal temperature, and oxidation stages; specifically, the Spearman correlation coefficient between acetaldehyde response intensity and coal temperature reached 0.92. Meanwhile, the oxidation stage classification model constructed using an artificial neural network achieved an overall recognition accuracy of 91%, confirming the reliability of the proposed method for identifying different stages of coal spontaneous combustion. Conclusions Two semesters of teaching practice involving seven student groups verified the effectiveness of the proposed experiment. By integrating multidisciplinary theories and techniques related to coal spontaneous combustion monitoring, sensing technology, and artificial intelligence, the experiment demonstrates highly comprehensive, forward-looking, and exploratory characteristics. It effectively improves students' abilities in literature screening and analysis, experimental equipment operation, and data processing. Furthermore, it strengthens their skills in academic writing, research result organization, and oral presentation; stimulates their motivation to address practical engineering problems using emerging technologies; and improves their innovative thinking and teamwork abilities. Satisfactory outcomes have been achieved in undergraduate experimental teaching. Future research could expand the range of coal samples and further optimize the generalizability and engineering applicability of the classification models, thereby continuously updating and enriching the content of experimental teaching.
