Yu CAI, Qiang LI, Feihong DU, et al. Polymeric nanocomposites for electrocaloric refrigeration. p450–462
Electrocaloric refrigeration represents an alternative solid-state cooling technology that has the potential to reach the ultimate goal of achieving zero-global-warming potential, highly efficient refrigeration, and heat pumps. To date, both polymeric and inorganic oxides have demonstrated giant electrocaloric effect as well as respective cooling devices. To date, su [Detail] ...
The widespread need to pump heat necessitates improvements that will increase energy efficiency and, more generally, reduce environmental impact. As discussed at the recent Calorics 2022 Conference, heat-pump devices based on caloric materials offer an intriguing alternative to gas combustion and vapor compression.
Electrocaloric refrigeration represents an alternative solid-state cooling technology that has the potential to reach the ultimate goal of achieving zero-global-warming potential, highly efficient refrigeration, and heat pumps. To date, both polymeric and inorganic oxides have demonstrated giant electrocaloric effect as well as respective cooling devices. Although both polymeric and inorganic oxides have been identified as promising cooling methods that are distinguishable from the traditional ones, they still pose many challenges to more practical applications. From an electrocaloric material point of view, electrocaloric nanocomposites may provide a solution to combine the beneficial effects of both organic and inorganic electrocaloric materials. This article reviews the recent advancements in polymer-based electrocaloric composites and the state-of-the-art cooling devices operating these nanocomposites. From a device point of view, it discusses the existing challenges and potential opportunities of electrocaloric nanocomposites.
Solid state refrigeration based on caloric effect is regarded as a potential candidate for replacing vapor-compression refrigeration. Numerous methods have been proposed to optimize the refrigeration properties of caloric materials, of which single field tuning as a relatively simple way has been systemically studied. However, single field tuning with few tunable parameters usually obtains an excellent performance in one specific aspect at the cost of worsening the performance in other aspects, like attaining a large caloric effect with narrowing the transition temperature range and introducing hysteresis. Because of the shortcomings of the caloric effect driven by a single field, multifield tuning on multicaloric materials that have a coupling between different ferro-orders came into view. This review mainly focuses on recent studies that apply this method to improve the cooling performance of materials, consisting of enlarging caloric effects, reducing hysteresis losses, adjusting transition temperatures, and widening transition temperature spans, which indicate that further progress can be made in the application of this method. Furthermore, research on the sign of lattice and spin contributions to the magnetocaloric effect found new phonon evolution mechanisms, calling for more attention on multicaloric effects. Other progress including improving cyclability of FeRh alloys by introducing second phases and realizing a large reversible barocaloric effect by hybridizing carbon chains and inorganic groups is described in brief.
The performance parameters for characterizing the electrocaloric effect are isothermal entropy change and the adiabatic temperature change, respectively. This paper reviews the electrocaloric effect of ferroelectric materials based on different theoretical models. First, it provides four different calculation scales (the first-principle-based effective Hamiltonian, the Landau-Devonshire thermodynamic theory, phase-field simulation, and finite element analysis) to explain the basic theory of calculating the electrocaloric effect. Then, it comprehensively reviews the recent progress of these methods in regulating the electrocaloric effect and the generation mechanism of the electrocaloric effect. Finally, it summarizes and anticipates the exploration of more novel electrocaloric materials based on the framework constructed by the different computational methods.
Thermal energy storage has been a pivotal technology to fill the gap between energy demands and energy supplies. As a solid-solid phase change material, shape-memory alloys (SMAs) have the inherent advantages of leakage free, no encapsulation, negligible volume variation, as well as superior energy storage properties such as high thermal conductivity (compared with ice and paraffin) and volumetric energy density, making them excellent thermal energy storage materials. Considering these characteristics, the design of the shape-memory alloy based the cold thermal energy storage system for precooling car seat application is introduced in this paper based on the proposed shape-memory alloy-based cold thermal energy storage cycle. The simulation results show that the minimum temperature of the metal boss under the seat reaches 26.2 °C at 9.85 s, which is reduced by 9.8 °C, and the energy storage efficiency of the device is 66%. The influence of initial temperature, elastocaloric materials, and the shape-memory alloy geometry scheme on the performance of car seat cold thermal energy storage devices is also discussed. Since SMAs are both solid-state refrigerants and thermal energy storage materials, hopefully the proposed concept can promote the development of more promising shape-memory alloy-based cold and hot thermal energy storage devices.
A two-stage gas-coupled Stirling/pulse tube refrigerator (SPR), whose first and second stages respectively involve Stirling and pulse tube refrigeration cycles, is a very promising spaceborne refrigerator. The SPR has many advantages, such as a compact structure, high reliability, and high performance, and is expected to become an essential refrigerator for space applications. In research regarding gas-coupled regenerative refrigerator, the energy flow distribution between the two stages, and optimal phase difference between the pressure wave and volume flow, are two critical parameters that could widely influence refrigerator performance. The effects of displacer displacement on the pressure wave, phase difference, acoustic power distribution, and inter-stage cooling capacity shift of the SPR have been investigated experimentally. Notably, to obtain the maximum first-stage cooling capacity, an inflection point in displacement exists. When the displacer displacement is larger than the inflection point, the cooling capacity could be distributed between the first and second stages. In the present study, an SPR was designed and manufactured to work between the liquid hydrogen and liquid oxygen temperatures, which can be used to cool small-scale zero boil-off systems and space detectors. Under appropriate displacer displacement, the SPR can reach a no-load cooling temperature of 15.4 K and obtain 2.6 W cooling capacity at 70 K plus 0.1 W cooling capacity at 20 K with 160 W compressor input electric power.
Intelligent power systems can improve operational efficiency by installing a large number of sensors. Data-based methods of supervised learning have gained popularity because of available Big Data and computing resources. However, the common paradigm of the loss function in supervised learning requires large amounts of labeled data and cannot process unlabeled data. The scarcity of fault data and a large amount of normal data in practical use pose great challenges to fault detection algorithms. Moreover, sensor data faults in power systems are dynamically changing and pose another challenge. Therefore, a fault detection method based on self-supervised feature learning was proposed to address the above two challenges. First, self-supervised learning was employed to extract features under various working conditions only using large amounts of normal data. The self-supervised representation learning uses a sequence-based Triplet Loss. The extracted features of large amounts of normal data are then fed into a unary classifier. The proposed method is validated on exhaust gas temperatures (EGTs) of a real-world 9F gas turbine with sudden, progressive, and hybrid faults. A comprehensive comparison study was also conducted with various feature extractors and unary classifiers. The results show that the proposed method can achieve a relatively high recall for all kinds of typical faults. The model can detect progressive faults very quickly and achieve improved results for comparison without feature extractors in terms of F1 score.
The effect of oxygen vacancies on the adsorption and activation of CO2 on the surface of different phases of ZrO2 is investigated by density functional theory (DFT) calculations. The calculations show that the oxygen vacancies contribute greatly to both the adsorption and activation of CO2. The adsorption energy of CO2 on the c-ZrO2, t-ZrO2 and, m-ZrO2 surfaces is enhanced to 5, 4, and 3 folds with the help of oxygen vacancies, respectively. Moreover, the energy barrier of CO2 dissociation on the defective surfaces of c-ZrO2, t-ZrO2, and m-ZrO2 is reduced to 1/2, 1/4, and 1/5 of the perfect surface with the assistance of oxygen vacancies. Furthermore, the activation of CO2 on the ZrO2 surface where oxygen vacancies are present, and changes from an endothermic reaction to an exothermic reaction. This finding demonstrates that the presence of oxygen vacancies promotes the activation of CO2 both kinetically and thermodynamically. These results could provide guidance for the high-efficient utilization of CO2 at an atomic scale.
Exploring cathode materials that combine excellent cycling stability and high energy density poses a challenge to aqueous Zn-ion hybrid supercapacitors (ZHSCs). Herein, polyaniline (PANI) coated boron-carbon-nitrogen (BCN) nanoarray on carbon cloth surface is prepared as advanced cathode materials via simple high-temperature calcination and electrochemical deposition methods. Because of the excellent specific capacity and conductivity of PANI, the CC@BCN@PANI core-shell nanoarrays cathode shows an excellent ion storage capability. Moreover, the 3D nanoarray structure can provide enough space for the volume expansion and contraction of PANI in the charging/discharging cycles, which effectively avoids the collapse of the microstructure and greatly improves the electrochemical stability of PANI. Therefore, the CC@BCN@PANI-based ZHSCs exhibit superior electrochemical performances showing a specific capacity of 145.8 mAh/g, a high energy density of 116.78 Wh/kg, an excellent power density of 12 kW/kg, and a capacity retention rate of 86.2% after 8000 charge/discharge cycles at a current density of 2 A/g. In addition, the flexible ZHSCs (FZHSCs) also show a capacity retention rate of 87.7% at the current density of 2 A/g after 450 cycles.