Output Power Research Articles

Optimization and analysis of methanol production from CO2 and solar-driven hydrogen production: A Danish case study

This paper presents a comprehensive techno-economic analysis of the world's first large-scale commercial Power-to-X (PtX) plant in Kassø, Denmark. This innovative facility combines solar photovoltaic (PV), an electrical grid, green hydrogen production, methanol synthesis, and district heating in an integrated system. We conduct an in-depth analysis to explore optimal operating conditions, the potential for sector coupling within the power and heat sectors, and the economic feasibility of the integrated system. In particular, we study different scenarios considering changes in solar PV power generation, electricity market price, CO2 price, and methanol price to explore their impacts on the system performance. Our results show that the electrolyzer's operation, a pivotal component of the system, heavily depends on the electricity spot price as well as the methanol price. Based on the green production of methanol, a premium price of 4800 DKK/t (0.64 €/t) is considered in this study (selling price of 8400 DKK/t). The results show that in case of high electricity prices (2022 spot market) or no premium price for methanol, the optimum annual production of methanol decreases by 58% and 67%, respectively. Furthermore, we observe that the variability of solar power output significantly impacts the plant's performance and economic viability, as it supplies about 30% of the plant's power consumption. Although the results are unique to the Kassø plant, the study's techniques and insights can be applied to other comparable systems around the world. The study also highlights how crucial it is to take market, climate, and technical factors into account when developing and running integrated energy systems.

Hydrogel-based flexible degradable triboelectric nanogenerators for human activity recognition

The development of Internet of Things (IoT) and Artificial Intelligence (AI) technologies has led to an increased demand for wearable electronic devices that can be used in a variety of contexts. Hydrogel sensors have been regarded as an ideal material for the fabrication of multifunctional flexible wearable devices. However, it is difficult to create hydrogel sensors with ideal electrical and mechanical properties. In this study, a conductive hydrogel prepared by a simple method has been introduced. The hydrogel was immersed in a binary solvent of glycerol, water and sodium citrate to form a transparent, long-term stable and highly conductive gelatin-NaCl organohydrogel (GNOH). A stretchable and durable gelatin Ecoflex triboelectric nanogenerator (GE-TENG) was created by combining an organic hydrogel with Ecoflex elastomer. It has high electrical and mechanical performance, with an open-circuit voltage of 142 V, current of 3.8 μA, power output of 19.36 μW and response time of 85 ms. Moreover, the single-electrode mode of the GE-TENG provides high electrical output for powering portable electronic devices and can capture biomechanical energy in temperatures as low as −20 °C. As a result of these capabilities, GE-TENG can effectively identify human movements with precision and transmit signals wirelessly, thereby broadening its potential applications. The GE-TENG-based self-powered intelligent sensing system (GSIS) for human-computer interaction demonstrates a wearable intelligent system for controlling the movement of a tank model and a manipulator by integrating the signal acquisition, signal processing and signal output components. The system achieves 100% signal recognition accuracy when combined with covariance matrix feature analysis and Convolutional Neural Network classification algorithms. This research demonstrates the potential of wearable hydrogel-based electronic devices for monitoring human motion, harvesting biomechanical energy and human-computer interaction.

Predicting the Output Performance of Triboelectric Nanogenerators Using Highly Representative Data‐Based Neural Networks

Triboelectric nanogenerators (TENGs) are promising potential sustainable power sources for wireless sensing networks within the Internet of Things (IoT) realm. Developing an efficient TENG evaluation model, characterized by high speed, accuracy, and representativeness, facilitates its integration into practical applications, which is urgent and lack of investigation currently. Herein, an artificial intelligence (AI) based evaluation model is developed to predict the performance of freestanding rotational TENGs (FR‐TENGs) for demonstration. An accurate and representative train dataset is essential for development of AI‐based evaluation model, which has been generated using finite element analysis and equivalent circuit simulation alongside the non‐dominated sorting genetic algorithm II. Through comprehensive experiments and simulations, the accuracy of the model has been verified in predicting the power output performance of FR‐TENGs, which has 99.6% (three design parameters) and 99.2% (seven design parameters) maximum train set accuracy. More importantly, the predicted results from the AI‐based evaluation model have notably expanded the coverage of data and significantly expedited the generation time from days to seconds. Herein, the use of AI in assessing the performance of TENGs is enhanced. The TENG design process can be significantly simplified, while maintaining a high evaluation model accuracy, thus promising advancements of IoT applications in future.

Miniaturized design of multi-octave PA using spoof surface plasmon polaritons

Surface Plasmon Polariton (SSPP), which exhibits subwavelength-scaled field confinement, can be realized at microwave frequencies by ultrathin corrugated metallic strips, providing significant potential for circuit and system miniaturization. A number of SSPP units were employed in this study to design input and output matching networks of a multi-octave RF power amplifier (PA) for the purpose of reducing the overall circuit size. The designed SSPP-based PAs were fabricated and demonstrated to have an output power between 39.1 dBm and 41.8 dBm, and a power added efficiency (PAE) ranging between 60.2 % and 69.8 % in the frequency range of 0.8 GHz to 3.1 GHz, with a size of 35.5 mm * 46.7 mm, which achieves a 47 % size reduction compared to the traditional transmission-line based PA. A highly efficient global optimization method, the Bayesian Optimization (BO), was utilized to further enhance performance. SSPP PA's average output power and PAE have been improved by approximately 0.3 dBm and 2.6 %, respectively. Its overall size remains at the same level. With the use of a 20 MHz 5GNR signal, digital pre-distortion (DPD) has been implemented, and the linearity of the PA has been improved.

Calculation of the parameters of an axial flux motor as an actuator of automotive systems

Problem. Axial flux electric motors offer several significant advantages compared to electric motors of traditional design. Currently, scientific periodicals contain numerous publications regarding the development and use of axial flux electric motors with printed windings across various fields. These include applications such as HDD-drives in computer technology, fans and pumps of various capacities, propulsion systems for bicycles and motorcycles, including in-wheel motors, manipulator drives for machine tools and industrial robots, and even within space technologies. Research confirms the high efficiency and size-to-weight ratios of axial flux motors when modern technologies are employed. However, there is little information available regarding the application of such motors in automotive electromechanical equipment. A distinctive feature of automotive electrical systems is their predominantly 12 V onboard power supply, along with high demands on size-to-weight ratios and reliability in conditions of elevated vibrations and wide temperature ranges. In this context, the development of an axial flux motor for automotive applications becomes relevant, particularly as an actuating mechanism for auxiliary systems such as window lifters, windshield wipers, air conditioning, and cooling fans, etc. Goal. The goal of the article is to determine the feasibility of using an axial flux electric motor as an actuator for automotive auxiliary systems by comparing its calculated parameters with the parameters of motors of traditional design using modern technologies and materials. Methodology. The methods and algorithms used for the calculation of electric machines take into account the characteristics and physical processes specific to axial flux machines with printed windings and permanent magnet arrays. Results. A comparison of the obtained characteristics of the designed motor with the characteristics of a modern prototype of traditional design was conducted. Based on the comparison, it was determined that the designed motor has better size-to-weight ratios while maintaining energy performance. Consequently, a conclusion was drawn about the feasibility of using electric motors with axial flux as actuators for automotive auxiliary systems. Originality. The prototype of the designed motor is considered to be a 250 W DC motor with a supply voltage of 12 V. The imposed constraint on the external diameter of the designed motor is set to 100 mm. Practical value. At the same output power and nearly identical torque, the calculated motor exhibits higher size-to-weight ratios. The weight of the calculated motor is 46% of the weight of the prototype. With an external diameter 54% larger than the prototype, the axial length of the calculated motor is 73% smaller. The mass of the calculated motor is 2.34 times smaller than the mass of the prototype.

INSCYD physiological performance software is valid to determine the maximal lactate steady state in male and female cyclists.

The maximal lactate steady state (MLSS) is defined as the highest workload that can be maintained without blood lactate accumulation over time. The power output at MLSS (PMLSS) is regularly implemented to define training zones, quantify training progress, or predict race performance. The gold standard methodology for MLSS determination requires two to five trials of constant-load exercise, which limits the practical application in training. The INSCYD software can calculate the PMLSS (PMLSSINSCYD) based on physiological data that can be obtained during a ∼1 h laboratory visit. However, to the best of our knowledge, the validity of the most recent software version has not yet been investigated. This study aimed to assess the validity of the software's calculations on PMLSS in cycling. The data for this study were retrieved from two published scientific sources. Thirty-one cyclists (19 males, 12 females) performed a 15 s sprint to estimate the VLamax, a ramp test for the assessment, and two to five constant-load tests to determine the PMLSS. The INSCYD software was used to calculate the PMLSS based on the , VLamax, sex, body mass, and body composition. The PMLSSINSCYD was higher than the PMLSS in the entire sample (mean difference: 4.6 W, p < 0.05, 95% CI 0.8-8.3 W) and in men (mean difference: 6.6 W, p < 0.05, 95% CI 1.3-11.8 W), but not in women (mean difference: 0.8 W, n.s., 95% CI -3.7 to 5.3 W), which was within the typical error of the PMLSS estimations (∼3%). In 12 subjects (nine males, three females), the PMLSSINSCYD differed by 3.1-7.3% compared to the MLSS. The Pearson correlations between the measured PMLSS and the calculated PMLSS (PMLSSINSCYD) were very strong in men (r = 0.974, p < 0.001, 95% CI 0.933-0.99), women (r = 0.984, p < 0.001, 95% CI 0.931-0.996), and for the entire sample (r = 0.992, p < 0.001, 95% CI 0.982-0.996). In conclusion, the PMLSS can be accurately calculated using the INSCYD software, but it still requires advanced testing equipment to collect valid and VLamax data.

Recent advances in solid–liquid triboelectric nanogenerator technologies, affecting factors, and applications

Converting dispersed mechanical energy into electrical energy can effectively improve the global energy shortage problem. The dispersed mechanical energy generated by liquid flow has a good application prospect as one of the most widely used renewable energy sources. Solid–liquid triboelectric nanogenerator (S–L TENG) is an inspiring device that can convert dispersed mechanical energy of liquids into electrical energy. In order to promote the design and applications of S–L TENG, it is of vital importance to understand the underlying mechanisms of energy conversion and electrical energy output affecters. The current research mainly focuses on the selection of materials, structural characteristics, the liquid droplet type, and the working environment parameters, so as to obtain different power output and meet the power supply needs of diversified scenarios. There are also studies to construct a theoretical model of S–L TENG potential distribution mechanism through COMSOL software, as well as to obtain the adsorption status of different kinds of ions with functional groups on the surface of friction power generation layer through molecular dynamics simulation. In this review, we summarize the main factors affecting the power output from four perspectives: working environment, friction power generation layer, conductive part, and substrate shape. Also summarized are the latest applications of S–L TENG in energy capture, wearable devices, and medical applications. Ultimately, this review suggests the research directions that S–L TENG should focus on in the future to enhance electrical energy output, as well as to expand the diversity of application scenarios.

Performance improvement of PV systems during dynamic partial shading conditions using optimization algorithms

PV power plants encounter varying levels of irradiance, temperature fluctuations, and partial shading because of the differences in sunlight conditions. Partial shading can cause an increase in the power loss, leading to a reduction in efficiency. Maximum Power Point Tracking (MPPT) is of utmost importance in the functioning of photovoltaic (PV) systems for electricity generation because it is indispensable for maximizing power extraction from PV modules, thereby increasing the overall power output. In situations where partial shading is present, the utilization of MPPT algorithms to achieve maximum power output becomes complex because of the existence of multiple distinct peak power points, each having a unique local optimum. To overcome this issue, a method is proposed that uses Darts Game Optimization (DGO), a game-based optimization process, to efficiently determine and extract the maximum power from various local optimal peaks. A population-based optimization method known as the Darts Game Optimization algorithm exists. In this approach, the optimization process begins by creating a population of random players. Then, the algorithm iteratively updates and improves the population to search for the best player or solution. In this study, the DGO algorithm was applied to the MPPT process for voltage optimization in the PV procedure. The DC-DC converter is utilized to capture the maximum available power, and the findings demonstrate that the DGO algorithm efficiently identifies the global maximum, resulting in accelerated convergence, reduced settling time, and minimized power oscillation. Through simulations, the feasibility and effectiveness of the DGO centered MPPT approach was confirmed and compared with MPPT algorithms relying on perturb and observe (P&amp;O) and Particle Swarm Optimization (PSO). The simulation results offer compelling evidence that the DGO algorithm, as proposed in this study, proficiently traces the global maximum, thereby substantiating its practicality and efficiency.

Diode-pumped continuous-wave Pr:YLF cyan laser

We demonstrate continuous-wave quasi-three-energy level laser operation in the cyan region with an LD-pumped Pr:YLF laser. Based on the 3P0→3H4 transition, a continuously tunable Pr:YLF cyan laser was realized with a wavelength tunable range of 490.41 nm–491.72 nm, corresponding to a maximum power of 72 mW–244 mW. Under the same pumping scheme, a maximum output power of 255 mW was achieved at 491 nm using Pr:YLF, corresponding to a slope efficiency of 7.2 %. To our knowledge, this is the highest power produced at room temperature by a cyan laser demonstrated with a Pr:YLF crystal. This work provides a simple and effective scheme to generate high-power cyan lasers at room temperature for various applications, such as underwater communications and fluorescence detection.

A Hybrid Wild Horses Optimization (WHO) and Dwarf Mongoose Optimization (DMO) method for optimum energy management in SG system

AbstractA hybrid technique is proposed for the energy management (EM) of smart grid (SG) systems. The proposed method integrates the Wild Horse Optimization (WHO) and dwarf mongoose optimization (DMO) methods; hence, it is named the WHO–DMO approach. The Micro‐grid (MG)‐tied system is a combination of battery, micro turbine (MT), photovoltaic (PV), and Wind Turbine (WT). The key aim of the proposed approach is to manage the resources and power of the SG model and reduce the cost of electricity. The objective of the system is to improve load demand. The WHO method is enhanced by the DMO method, which minimizes the objective of the system. Access to power demand, state of charge (SOC), and renewable energy sources (RESs) for storing elements are considered constraints of the system. The unit of renewable power systems relies on batteries as energy sources to stabilize and sustain stable and consistent output power throughout the operation. The proposed technique is done in MATLAB platform and its implementation is calculated using the existing methods. From the simulation, the proposed method has less cost and higher power than the existing methods.

Design and optimization of three segmented thermoelectric generator for nuclear reactor application

With the scientific exploration in deep space and deep sea, traditional fossil energy and solar energy cannot supply energy for deep space aircrafts and deep sea vehicles continuously, new energy power systems with the features of long endurance, high reliability and high energy density are imperative. Small nuclear reactor has become one of the best solutions for deep space energy demand in the future due to its strong environmental adaptability and long-life time. To improve the reliability of the static heat pipe reactor, the thermoelectric generators (TEGs) are utilized to convert fission heat into electrical energy. Focusing on the demands of improving the conversion efficiency, a new three segmented TEG is proposed based on the Bi2Te3, CoSb3 and Half-Heusler thermoelectric materials in this paper. Combined with the application requirements of heat pipe reactor, the geometric configuration such as different heights and the cross-sectional area of the three different materials in the PN legs is designed and optimized under different heat flux boundary conditions. The influences of contact electrical resistance and contact thermal resistance on the conversion efficiency have been investigated. When the contact electrical resistivity increases from 0.01 μΩ cm2 to 1000 μΩ cm2, the conversion efficiency loss increases from 2.6% to 80.1%. As the surface roughness rises from 0.1 μm to 100 μm, the conversion efficiency loss increases from 0.9% to 42.7%. Based on the heat flux boundary conditions provided by the heat pipes, the thermoelectric conversion performances of three segmented TEG under different external loads are investigated. Through the geometric optimization of the three segmented TEG with total height 20 mm, the thermoelectric conversion efficiency improves from 6.9% to 15.34%. For the simulation heat flux density conditions of 70 kW m−2, 75 kW m−2, 80 kW m−2, 85 kW m−2 and 90 kW m−2, the maximum output power of a thermoelectric generator can reach 8.56W, 9.71W, 10.85W, 12.00W, and 13.11W, respectively. The output characteristics of the three segmented TEGs meet the design demands of the static conversion system.

Intense NIR-II luminescence through stabilization of tetrahedral (Mn5+O4) lumophore in apatites with high external quantum efficiency

The discovery of highly efficient near-infrared (NIR) emitting phosphors is essential for multiple spectroscopic applications. Pentavalent-manganese (Mn5+) is a rarely-reported NIR-II activator due to the its instability in inorganic solids. In this study, Mn5+-activated apatite phosphors A5(B1-xMnxO4)3X (A = Sr, Ba; B = P, V; X = OH, F, Cl, Br) were reported. Benefiting from the discrete P/VO4 tetrahedron and stabilization effect of alkaline-earth cation, Mn5+ existed as MnO43− anion can be effectively incorporated into the A5(P/VO4)3X. A selection of 16 different apatites is conducted to test the structural and compositional effect on Mn5+ stabilization and luminescence. The structure-property relationship was discussed with a detailed analysis on Mn5+ Tanabe-Sugano diagram and Dq/B calculation. Particularly, the optimized Ba5(VO4)3Cl: 0.01Mn5+ (λex = 650 nm, λem = 1181 nm) reveals an exceptional external quantum efficiency of 61.1 % with vivid turquoise body color. The multiparametric thermometry by luminescence intensity ratio (LIR) and 1E lifetime were demonstrated with excellent linear regressions (R2 > 99.9 %) and high relative sensitivities of > 1.0% K−1 in the range of physiological temperatures. A NIR-II phosphor-converted light-emitting diode (pc-LED) is fabricated with a NIR output power of 30.18 mW at 60 mA driven current and photoelectric conversion efficiency of 6.63 %.

Joint energy management with integration of renewable energy sources considering energy and reserve minimization

In light of electric vehicles (EVs) and demand-side management, a combined optimization paradigm for microgrid (MG) resource scheduling is proposed in this study. Renewable energy sources, including wind and solar power, fulfill a fraction of the consumption demand, while the MG maintains a connection to the electrical network to facilitate power transactions. By utilizing EVs, we can mitigate the inherent volatility of renewable energy production with manageable loads and level out the system's demand profile. The proposed system employs a bi-level programming strategy, wherein the initial level is dedicated to the minimization of aggregate costs, encompassing those related to energy and reserves. Additionally, costs associated with resource redistribution due to the uncertainty of solar and wind power output are minimized at the second level. Subsequently, the objective function is addressed using the enhanced adapted approach of modified marine predators algorithm (MMPA), chosen for its robustness and effectiveness as an optimization technique. The outcomes obtained for a microgrid underscore the superior performance of the results achieved through the application of the MMPA algorithm when contrasted with alternative established methodologies. The outcomes have demonstrated that integrating EVs and adaptable loads contributes to a decrease in operational expenses and emissions. Furthermore, the uncertainties associated with WT and PV are effectively counterbalanced. Additionally, the results garnered from the simulations indicate that the recommended MMPA technique has the capacity to yield superior solutions compared to several other widely recognized optimization algorithms. Scheduling with both DR and EVs with three cost components are considered, generation cost, reserve cost, and initial unit cost, amounting to $740.11, $9.61, and $6.07, correspondingly and it can lead to decreased emission levels and increased incentives for proprietors of EVs, responsive load participants, and RES.

Numerical investigation of smart material-based structures for vibration energy-harvesting applications

Abstract The present work deals with energy-harvesting devices, which are useful in scavenging power using piezoelectric materials. Utilizing classical beam theory and classical plate theory, finite element modelling has been carried out to optimize the performance of output power of a cantilever beam and a flexible rectangular plate. Harmonic oscillations and base excitation will be the two different forcing functions used to drive the system. Based on this, numerical investigations of the performance of output power for the piezoelectric cantilever beam and flexible rectangular plate with different cases are considered. The present work is also useful for designing the piezoelectric cantilever beams and plates to extract maximum output power within the frequency ranges from 0 to 200 Hz. Numerical investigations on the piezoelectric cantilever beam and flexible rectangular plate with different cases reveal that the performance of output power is influenced by factors like load resistance, applications of with and without host structures, and different design parameters like unimorph, bimorph, embedded, line- and cross-type piezoelectric patch arrangements.

Modelling and Output Power Estimation of a Combined Gas Plant and a Combined Cycle Plant Using an Artificial Neural Network Approach

Artificial neural networks (ANNs) have gained prominence among contemporary computing techniques due to their capacity to handle complicated stochastic datasets and nonlinear modelling in combined gas and combined cycle power (COGAS) plants. Researchers, academicians, and stakeholders have been unable to predict, ensure effective operation, and prevent power outages in COGAS due to the nonlinearity. The first implementation of the simultaneous adoption of three types of ANNs using Levenberg–Marquardt (LM), Bayesian regularisation (BR), and scaled conjugate gradient (SCG) configurations for training and assessing a combined cycle power plant output is presented. The dataset used in this research is a 9568-unit full combined cycle power plant basis load dataset, accessible through the public UCI Machine Learning Repository. It incorporates ambient temperature, exhaust vacuum, ambient pressure, and relative humidity as input parameters to predict the electric output power. The most accurate and dependable electric power predictions could be identified for 70% of the total data, of which 6698 were trained, 15% were tested, and 15% were validated (2870). By using the three training techniques, namely, LM, BR, and SCG, the parameterized networks are studied, increasing the number of hidden layers from 20 to 500. The lowest root-mean-square error value for a multilayer perceptron (MLP) architecture is 3.631%, which is lower than the values of 4.17%, 4.35%, and 4.63% for comparable MLP structures (20 to 500), documented in the literature. The LM and BR algorithms outperform SCG. These adopted algorithms could be a cutting-edge application in the power plant industry and other real-world applications for reliable solutions, to satisfy emerging societal needs with environmental benefits.

5.4 W, 2.35 µm cascaded Raman fiber laser pumped by dissipative soliton resonance-like pulses

We present a nonlinear amplifying loop mirror-based mode-locked fiber laser. By adjusting the pump power, the proposed laser exhibits a dissipative soliton resonance (DSR)-like pulse operation with a maximum pulse width of 150 ns. Subsequently, a three-stage Tm3+-doped fiber amplifier is implemented using a single-mode double-cladding Tm3+-doped fiber to increase the DSR-like pulse output power to 52.5 W, achieving a pump slope efficiency of 47.1% in the main amplifier. A 25 m first-order Raman-gain fiber (UHNA7) is pumped by a DSR-like pulse, and 16.3 W of pure 2.135 µm first-order Raman light with a spectral purity of 73.4% is obtained. Finally, 5.4 W of 2.35 µm second-order Raman light with a spectral purity of 66% is obtained using a 10 m 98% germania-core fiber as a second-order Raman-gain fiber cascaded after UHNA7 fiber. To the best of our knowledge, this is the highest output power ever obtained from a 2.3 µm laser.

Lasing from a Large-Area 2D Material Enabled by a Dual-Resonance Metasurface.

Semiconducting transition metal dichalcogenides (TMDs) have gained significant attention as a gain medium for nanolasers, owing to their unique ability to be easily placed and stacked on virtually any substrate. However, the atomically thin nature of the active material in existing TMD lasers and the limited size due to mechanical exfoliation presents a challenge, as their limited output power makes it difficult to distinguish between true laser operation and other "laser-like" phenomena. Here, we present room temperature lasing from a large-area tungsten disulfide (WS2) monolayer, grown by a wafer-scale chemical vapor deposition (CVD) technique. The monolayer is placed on a dual-resonance dielectric metasurface with a rectangular lattice designed to enhance both absorption and emission, resulting in an ultralow threshold operation (threshold well below 1 W/cm2). We provide a thorough study of the laser performance, paying special attention to directionality, output power, and spatial coherence. Notably, our lasers demonstrated a coherence length of over 30 μm, which is several times greater than what has been reported for 2D material lasers so far. Our realization of a single-mode laser from a CVD-grown monolayer presents exciting opportunities for integration and the development of real-world applications.

High efficiency continuous-wave Ho: LSO laser wing-pumped by the laser diode at 1.91 μm

We present a high-efficiency continuous-wave Ho: LSO laser wing-pumped by a 1.91 μm laser diode. The impact of different output transmittances on the laser output power is compared and analyzed. The optimal result was achieved with a −500-mm radius curvature and a 6% transmission output coupler. The maximum output power of the Ho: LSO laser is 7.81 W, with a slope efficiency of 44.7%, a center wavelength of 2,106.6 nm, and beam quality factors of 1.4 in the x-direction and 1.3 in the y-direction.

Solar photothermal self-deicing composite films based on fluorinated polyimide and phosphorene nanoflakes for passive anti-icing of photovoltaic panels

Snow and ice coverage greatly deteriorates the power output of photovoltaic (PV) solar cells due to sunlight obstruction and thus makes a great impact on their electricity generation. To address this problem, we design a type of passive self-deicing composite films based on colorless fluorinated polyimide as a polymeric matrix and phosphorene (PR) nanoflakes as a light absorber for the photothermal deicing of PV panels driven by solar energy. The composite films were successfully fabricated through in situ polycondensation, followed by temperature-programmed thermal imidization. The resultant composite films exhibit a colorless transparent feature along with high transmittance and high absorptivity. The presence of PR nanoflakes enhances the absorption of solar light and conversion of photothermal energy by the composite films, resulting in good photothermal self-deicing effectiveness for solar PV panels. There is an accelerated melting process occurring in the ice covering on the surface of the composite films under solar illumination. The composite film containing 2.0 wt % PR nanoflakes exhibits an optimal photothermal self-deicing performance under a high photothermal conversion efficiency of 92.9 %. The use of this composite film can promote a rapid recovery of the output voltage to an ideal value for the snow- or ice-covered PV panels through fast photothermal self-deicing. This study provides a novel approach for the development of passive self-deicing materials to enhance the power output and electricity generation efficiency of solar PV panels in the snowy and icy weather.

Hydrogen and electricity cogeneration driven by the salinity gradient from actual brine and river water using reverse electrodialysis

Reverse electrodialysis (RED) is a promising method for harvesting the salinity gradient energy (SGE) between the brine and river water. Many investigations are carried out by using the artificially brine and fresh water, bringing difficulties in reflecting the practical RED performance under the complex influences of feed solutions. This work explores the performance of the RED system for hydrogen and electricity co-generation that is driven by salinity gradient between the actual concentrated brine and natural river water, and compared with the simulative brines and river waters under six testing schemes. The results show both the working current and solutions influence the system performances, including the output voltage, power density, hydrogen production, and energy conversion efficiency. Besides, the effects of salinity gradient of feed solutions are greater than that of the presence of trace multivalent ions and anionic radical in brine. The effective monovalent ion ionic strength is vital. The experimental maximum hydrogen production and power density are 82.12 mL·h−1 and 0.124 W·m−2 respectively at the current is 0.2 A, and the total power reached 0.32 W with the energy conversion efficiency of 25%. The research offers recommendations for harnessing SGE from actual brines and freshwater to produce hydrogen.