Development of active and durable electrocatalyst for oxygen reduction reaction (ORR) remains one challenge for the polymer electrolyte membrane fuel cell (PEMFC) technology. Pt-based nanomaterials show the greatest promise as electrocatalyst for this reaction among all current catalytic structures. This review focuses on Pt-based ORR catalyst material development and covers the past achievements, current research status and perspectives in this research field. In particular, several important categories of Pt-based catalytic structures and the research advances are summarized. Key factors affecting the catalyst activity and durability are discussed. An outlook of future research direction of ORR catalyst research is provided.
Unit commitment (UC) is an optimization problem used to determine the operation schedule of the generating units at every hour interval with varying loads under different constraints and environments. Many algorithms have been invented in the past five decades for optimization of the UC problem, but still researchers are working in this field to find new hybrid algorithms to make the problem more realistic. The importance of UC is increasing with the constantly varying demands. Therefore, there is an urgent need in the power sector to keep track of the latest methodologies to further optimize the working criterions of the generating units. This paper focuses on providing a clear review of the latest techniques employed in optimizing UC problems for both stochastic and deterministic loads, which has been acquired from many peer reviewed published papers. It has been divided into many sections which include various constraints based on profit, security, emission and time. It emphasizes not only on deregulated and regulated environments but also on renewable energy and distributed generating systems. In terms of contributions, the detailed analysis of all the UC algorithms has been discussed for the benefit of new researchers interested in working in this field.
Surface tension plays a core role in dominating various surface and interface phenomena. For liquid metals with high melting temperature, a profound understanding of the behaviors of surface tension is crucial in industrial processes such as casting, welding, and solidification, etc. Recently, the room temperature liquid metal (RTLM) mainly composed of gallium-based alloys has caused widespread concerns due to its increasingly realized unique virtues. The surface properties of such materials are rather vital in nearly all applications involved from chip cooling, thermal energy harvesting, hydrogen generation, shape changeable soft machines, printed electronics to 3D fabrication, etc. owing to its pretty large surface tension of approximately 700 mN/m. In order to promote the research of surface tension of RTLM, this paper is dedicated to present an overview on the roles and mechanisms of surface tension of liquid metal and summarize the latest progresses on the understanding of the basic knowledge, theories, influencing factors and experimental measurement methods clarified so far. As a practical technique to regulate the surface tension of RTLM, the fundamental principles and applications of electrowetting are also interpreted. Moreover, the unique phenomena of RTLM surface tension issues such as surface tension driven self-actuation, modified wettability on various substrates and the functions of oxides are discussed to give an insight into the acting mechanism of surface tension. Furthermore, future directions worthy of pursuing are pointed out.
Recently, the development and fabrication of electrode component of the solid oxide fuel cell (SOFC) have gained a significant importance, especially after the advent of electrode supported SOFCs. The function of the electrode involves the facilitation of fuel gas diffusion, oxidation of the fuel, transport of electrons, and transport of the byproduct of the electrochemical reaction. Impressive progress has been made in the development of alternative electrode materials with mixed conducting properties and a few of the other composite cermets. During the operation of a SOFC, it is necessary to avoid carburization and sulfidation problems. The present review focuses on the various aspects pertaining to a potential electrode material, the double perovskite, as an anode and cathode in the SOFC. More than 150 SOFCs electrode compositions which had been investigated in the literature have been analyzed. An evaluation has been performed in terms of phase, structure, diffraction pattern, electrical conductivity, and power density. Various methods adopted to determine the quality of electrode component have been provided in detail. This review comprises the literature values to suggest possible direction for future research.
Ionomer impregnation represents a milestone in the evolution of polymer electrolyte fuel cell (PEFC) catalyst layers. Ionomer acts as the binder, facilitates proton transport, and thereby drastically improves catalyst utilization and effectiveness. However, advanced morphological and functional characterizations have revealed that up to 60% of Pt nanoparticles can be trapped in the micropores of carbon support particles. Ionomer clusters and oxygen molecules can hardly enter into micropores, leading to low Pt utilization and effectiveness. Moreover, the ionomer thin-films covering Pt nanoparticles can cause significant mass transport loss especially at high current densities. Ionomer-free ultra-thin catalyst layers (UTCLs) emerge as a promising alternative to reduce Pt loading by improving catalyst utilization and effectiveness, while theoretical issues such as the proton conduction mechanism remain puzzling and practical issues such as the rather narrow operation window remain unsettled. At present, the development of PEFC catalyst layer has come to a crossroads: staying ionomer-impregnated or going ionomer-free. It is always beneficial to look back into the past when coming to a crossroads. This paper addresses the characterization and modeling of both the conventional ionomer-impregnated catalyst layer and the emerging ionomer-free UTCLs, featuring advances in characterizing microscale distributions of Pt particles, ionomer, support particles and unraveling their interactions; advances in fundamental understandings of proton conduction and flooding behaviors in ionomer-free UTCLs; advances in modeling of conventional catalyst layers and especially UTCLs; and discussions on high-impact research topics in characterizing and modeling of catalyst layers.
Electronics, such as printed circuit board (PCB), transistor, radio frequency identification (RFID), organic light emitting diode (OLED), solar cells, electronic display, lab on a chip (LOC), sensor, actuator, and transducer etc. are playing increasingly important roles in people’s daily life. Conventional fabrication strategy towards integrated circuit (IC), requesting at least six working steps, generally consumes too much energy, material and water, and is not environmentally friendly. During the etching process, a large amount of raw materials have to be abandoned. Besides, lithography and microfabrication are typically carried out in “Cleanroom” which restricts the location of IC fabrication and leads to high production costs. As an alternative, the newly emerging ink-jet printing electronics are gradually shaping modern electronic industry and its related areas, owing to the invention of a series of conductive inks composed of polymer matrix, conductive fillers, solvents and additives. Nevertheless, the currently available methods also encounter some technical troubles due to the low electroconductivity, complex sythesis and sintering process of the inks. As an alternative, a fundamentally different strategy was recently proposed by the authors’ lab towards truly direct writing of electronics through introduction of a new class of conductive inks made of low melting point liquid metal or its alloy. The method has been named as direct writing of electronics based on alloy and metal (DREAM) ink. A series of functional circuits, sensors, electronic elements and devices can thus be easily written on various either soft or rigid substrates in a moment. With more and more technical progresses and fundamental discoveries being kept made along this category, it was found that a new area enabled by the DREAM ink electronics is emerging, which would have tremendous impacts on future energy and environmental sciences. In order to promote the research and development along this direction, the present paper is dedicated to draft a comprehensive picture on the DREAM ink technology by summarizing its most basic features and principles. Some important low melting point metal ink candidates, especially the room temperature liquid metals such as gallium and its alloy, were collected, listed and analyzed. The merits and demerits between conventional printed electronics and the new direct writing methods were comparatively evaluated. Important scientific issues and technical strategies to modify the DREAM ink were suggested and potential application areas were proposed. Further, digestions on the impacts of the new technology among energy, health, and environmental sciences were presented. Meanwhile, some practical challenges, such as security, environment-friendly feature, steady usability, package, etc. were summarized. It is expected that the DREAM ink technology will initiate a series of unconventional applications in modern society, and even enter into peoples’ daily life in the near future.
Hydrogen energy has been regarded as the most promising energy resource in the near future due to that it is a clean and sustainable energy. And the heterogeneous photocatalytic hydrogen production is increasingly becoming a research hotspot around the world today. As visible light response photocatalysts for hydrogen production, cadmium sulfide (CdS) is the most representative material, the research of which is of continuing popularity. In the past several years, there has been significant progress in water splitting on CdS-based photocatalysts using solar light, especially in the development of co-catalysts. In this paper, recent researches into photocatalytic water splitting on CdS-based photocatalysts are reviewed, including controllable synthesis of CdS, modifications with different kinds of cocatalysts, solid solution, intercalated with layered nanocomposites and metal oxides, and hybrids with graphenes etc. Finally, the problems and future challenges in photocatalytic water splitting on CdS-based photocatalysts are described.
To significantly reduce the cost of proton exchange membrane fuel cells, platinum-group metal (PGM)-free cathode catalysts are highly desirable. Current M-N-C (M: Fe, Co or Mn) catalysts are considered the most promising due to their encouraging performance. The challenge thus has been their stability under acidic conditions, which has hindered their use for any practical applications. In this review, based on the author’s research experience in the field for more than 10 years, current challenges and possible solutions to overcome these problems were discussed. The current Edisonian approach (i.e., trial and error) to developing PGM-free catalysts has been ineffective in achieving revolutionary breakthroughs. Novel synthesis techniques based on a more methodological approach will enable atomic control and allow us to achieve optimal electronic and geometric structures for active sites uniformly dispersed within the 3D architectures. Structural and chemical controlled precursors such as metal-organic frameworks are highly desirable for making catalysts with an increased density of active sites and strengthening local bonding structures among N, C and metals. Advanced electrochemical and physical characterization, such as electron microscopy and X-ray absorption spectroscopy should be combined with first principle density functional theory (DFT) calculations to fully elucidate the active site structures.
This paper presents a novel modified interactive honey bee mating optimization (IHBMO) base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting. A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduction in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power of DERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method.
Radiative thermoelectric energy converters, which include thermophotovoltaic cells, thermoradiative cells, electroluminescent refrigerators, and negative electroluminescent refrigerators, are semiconductor p-n devices that either generate electricity or extract heat from a cold body while exchanging thermal radiation with their surroundings. If this exchange occurs at micro or nanoscale distances, power densities can be greatly enhanced and near-field radiation effects may improve performance. This review covers the fundamentals of near-field thermal radiation, photon entropy, and nonequilibrium effects in semiconductor diodes that underpin device operation. The development and state of the art of these near-field converters are discussed in detail, and remaining challenges and opportunities for progress are identified.
In this paper, a passive neuro-wavelet based islanding detection technique for grid-connected inverter-based distributed generation was developed. The weight parameters of the neural network were optimized by intelligent water drop (IWD) to improve the capability of the proposed technique in the proposed problem. The proposed method utilizes and combines wavelet analysis and artificial neural network (ANN) to detect islanding. Connecting distributed generator to the distribution network has many benefits such as increasing the capacity of the grid and enhancing the power quality. However, it gives rise to many problems. This is mainly due to the fact that distribution networks are designed without any generation units at that level. Hence, integrating distributed generators into the existing distribution network is not problem-free. Unintentional islanding is one of the encountered problems. Discrete wavelet transform (DWT) is capable of decomposing the signals into different frequency bands. It can be utilized in extracting discriminative features from the acquired voltage signals. In passive schemes with a large non-detection zone (NDZ), concern has been raised on active method due to its degrading power quality effect. The main emphasis of the proposed scheme is to reduce the NDZ to as close as possible and to keep the output power quality unchanged. The simulation results from Matlab/Simulink shows that the proposed method has a small non-detection zone, and is capable of detecting islanding accurately within the minimum standard time.
The latent heat of condensation is lost to the atmosphere; hence it is not utilized to increase distillate output of single basin solar stills. This difficulty was overcome by attaching an additional basin to the main basin. The performance of the double basin solar still was also increased by attaching vacuum tubes to the lower basin; hence the lower basin possessed a higher temperature throughout the day. The latent heat of condensation of the bottom basin was also utilized to increase distillate. But the distillate output of the top basin was even lower compared with that of the bottom basin. This paper proposed a novel approach to increase the distillate output of the double basin solar still attached with vacuum tubes by introducing different sensible energy storage materials like pebbles, black granite gravel and calcium stones to increase the basin area. Experiments were conducted in climate conditions of Mehsana (23.6000° N, 72.4000° E) Gujarat from April to September 2013 with a constant water depth of 2 cm in the top basin with and without the use of basin materials. The results showed that the distillate output of basin material with calcium stones is greater (74%) compared with that of black granite gravel and pebbles. The integration of vacuum tubes with solar still greatly increases the distillate output of the solar still by providing hot water at the lower basin.
The aims of this paper is to investigate the effects of various materials inside the solar still on the increase of the productivity of potable water. Here, blue metal stones and cow dung cakes were used as materials. To investigate their effect, three identical solar stills with an effective area of 1 m square made from locally available materials were tested in climate conditions of Mehsana (23°50′ N 72° 23′). The first and second solar stills were filled with blue metal, stones and cow dung cakes, while the third one was taken as a reference which consisted of only blue paint at the basin. The experiments show that blue metal stones have the highest distillate output at daytime, followed by cow dung cakes solar still and reference solar still. On the other hand, the overall distillate output of blue metal stones and cow dung cakes at daytime as well as at night were 35% and 20% compared with that of reference solar still.
This paper proposes the generation scheduling approach for a microgrid comprised of conventional generators, wind energy generators, solar photovoltaic (PV) systems, battery storage, and electric vehicles. The electrical vehicles (EVs) play two different roles: as load demands during charging, and as storage units to supply energy to remaining load demands in the MG when they are plugged into the microgrid (MG). Wind and solar PV powers are intermittent in nature; hence by including the battery storage and EVs, the MG becomes more stable. Here, the total cost objective is minimized considering the cost of conventional generators, wind generators, solar PV systems and EVs. The proposed optimal scheduling problem is solved using the hybrid differential evolution and harmony search (hybrid DE-HS) algorithm including the wind energy generators and solar PV system along with the battery storage and EVs. Moreover, it requires the least investment.
This study investigates the dynamic causal relationship between energy consumption and economic growth in the U.S. at different time scales. The main novelty of the study is that this paper complements the existing studies on the nexus between energy consumption and economic growth by employing the wavelet transformation to obtain different time scales in order to investigate causality between energy consumption and economic growth. This method is first developed by Ramsey and Lampart. Their approach consists of first decomposing the series into time scales by wavelet filters and testing causality of each time scale with the pertinent time scale of the other series separately. The data span from 1973q1 to 2012q1 on a quarterly basis. The main empirical insight is that the causal relationship is stronger at finer time scales, whereas the relationship is less and less apparent at longer time horizons. The results indicate that energy consumption causes economic growth, while the reverse is not true at the original frequency of the data. At the very finest scale the same result arises. However, at coarser scales feedback is observed. In particular, at intermediate time scales the evidence indicates that energy consumption causes economic growth, while the reverse is also true. These empirical findings are expected to be of high importance in terms of the effective design and implementation of energy and environmental policies, especially when a number of countries in the pursuit of high economic growth targets do not pay any serious attention on environmental issues.
The key technologies of liquefied hydrogen have been developing rapidly due to its prospective energy exchange effectiveness, zero emissions, and long distance and economic transportation. However, hydrogen liquefaction is one of the most energy-intensive industrial processes. A small reduction in energy consumption and an improvement in efficiency may decrease the operating cost of the entire process. In this paper, the detailed progress of design and optimization for hydrogen liquefaction in recent years are summarized. Then, based on the refrigeration cycles, the hydrogen liquefaction processes are divided into two parts, namely precooled liquefaction process and cascade liquefaction process. Among the existing technologies, the SEC of most hydrogen liquefaction processes is limited in the range of 5–8 kWh/
This paper presents various approaches used by researchers for handling the uncertainties involved in renewable energy sources, load demands, etc. It gives an idea about stochastic programming (SP) and discusses the formulations given by different researchers for objective functions such as cost, loss, generation expansion, and voltage/V control with various conventional and advanced methods. Besides, it gives a brief idea about SP and its applications and discusses different variants of SP such as recourse model, chance constrained programming, sample average approximation, and risk aversion. Moreover, it includes the application of these variants in various power systems. Furthermore, it also includes the general mathematical form of expression for these variants and discusses the mathematical description of the problem and modeling of the system. This review of different optimization techniques will be helpful for smart grid development including renewable energy resources (RERs).
Dependency on oil-derived fuels in various sectors, most notably in mobility, has left the global economy vulnerable to several macroeconomic economic side effects. Numerous studies have addressed the effect of price volatility on specific economic parameters. However, the current literature lacks a comprehensive review of the interactions between global macroeconomic performance and oil price volatility (OPV). Price volatility is intrinsic in commodity markets, but has been advancing at a faster rate in the crude oil market in comparison to other commodities over the past decade, reflecting the status of oil as the most globalised commodity. In this paper, the analytical literature review and analysis of the behavioral responses of macroeconomic agents to OPV shows that such volatility has several damaging and destabilizing macroeconomic impacts that will present a fundamental barrier to future sustainable economic growth if left unchecked. To ensure macroeconomic isolation from OPV, a combination of supply and demand-side policies have been recommended that can help to mitigate and build resilience to the economic uncertainty advanced by OPV.
Aeroelasticity has become a critical issue for Multi-Megawatt wind turbine due to the longer and more flexible blade. In this paper, the development of aeroelasticity and aeroelastic codes for wind turbine is reviewed and the aeroelastic models for wind turbine blade are described, based on which, the current research focuses for large scale wind turbine are discussed, including instability problems for onshore and offshore wind turbines, effects of complex inflow, nonlinear effects of large blade deflection, smart structure technologies, and aerohydroelasticity. Finally, the future development of aeroelastic code for large scale wind turbine: aeroservoelasticity and smart rotor control; nonlinear aeroelasticity due to large blade deflection; full-scale 3D computational fluid dynamics (CFD) solution for dynamics; and aerohydroelasticity are presented.
Solar photo voltaic array (SPVA) generates a smaller amount of power than the standard rating of the panel due to the partial shading effect. Since the modules of the arrays receive different solar irradiations, the P-V characteristics of photovoltaic (PV) arrays contain multiple peaks or local peaks. This paper presents an innovative method (magic square) in order to increase the generated power by configuring the modules of a shaded photovoltaic array. In this approach, the physical location of the modules in the total cross tied (TCT) connected in the solar PV array is rearranged based on the magic square arrangement pattern. This connection is done without altering any electrical configurations of the modules in the PV array. This method can distribute the shading effect over the entire PV array, without concentrating on any row of modules and can achieve global peaks. For different types of shading patterns, the output power of the solar PV array with the proposed magic square configuration is compared with the traditional configurations and the performance is calculated. This paper presents a new reconfiguration technique for solar PV arrays, which increases the PV power under different shading conditions. The proposed technique facilitates the distribution of the effect of shading over the entire array, thereby, reducing the mismatch losses caused by partial shading. The theoretical calculations are tested through simulations in Matlab/Simulink to validate the results. A comparison of power loss for different types of topologies under different types of shading patterns for a 4 × 4 array is also explained.
Cogeneration units, which produce both heat and electric power, are found in many process industries. These industries also consume heat directly in addition to electricity. The cogeneration units operate only within a feasible zone. Each point within the feasible zone consists of a specific value of heat and electric power. These units are used along with other units, which produce either heat or power exclusively. Hence, the economic dispatch problem for these plants to optimize the fuel cost is quite complex and several classical and meta-heuristic algorithms have been proposed earlier. This paper applies the firefly algorithm, which is inspired by the behavior of fireflies which attract each other based on their luminosity. The results obtained have been compared with those obtained by other methods earlier and showed a marked improvement over the earlier methods.
Photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is intermittent because of depending on weather conditions. Therefore, the wind power can be considered to assist for a stable and reliable output from the PV generation system for loads and improve the dynamic performance of the whole generation system in the grid connected mode. In this paper, a novel topology of an intelligent hybrid generation system with PV and wind turbine is presented. In order to capture the maximum power, a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. The average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison with the conventional methods. The pitch angle of the wind turbine is controlled by radial basis function network-sliding mode (RBFNSM). Different conditions are represented in simulation results that compare the real power values with those of the presented methods. The obtained results verify the effectiveness and superiority of the proposed method which has the advantages of robustness, fast response and good performance. Detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink.
Absorption heat pump attracts increasing attention due to its advantages in low grade thermal energy utilization. It can be applied for waste heat reuse to save energy consumption, reduce environment pollution, and bring considerable economic benefit. In this paper, three important aspects for absorption heat pump for waste heat reuse are reviewed. In the first part, different absorption heat pump cycles are classified and introduced. Absorption heat pumps for heat amplification and absorption heat transformer for temperature upgrading are included. Both basic single effect cycles and advanced cycles for better performance are introduced. In the second part, different working pairs, including the water based working pairs, ammonia based working pairs, alcohol based working pairs, and halogenated hydrocarbon based working pairs, for absorption heat pump are classified based on the refrigerant. In the third part, the applications of the absorption heat pump and absorption heat transformer for waste heat reuse in different industries are introduced. Based on the reviews in the three aspects, essential summary and future perspective are presented at last.
Due to several factors, wind energy becomes an essential type of electricity generation. The share of this type of energy in the network is becoming increasingly important. The objective of this work is to present the modeling and control strategy of a grid connected wind power generation scheme using a doubly fed induction generator (DFIG) driven by the rotor. This paper is to present the complete modeling and simulation of a wind turbine driven DFIG in the second mode of operating (the wind turbine pitch control is deactivated). It will introduce the vector control, which makes it possible to control independently the active and reactive power exchanged between the stator of the generator and the grid, based on vector control concept (with stator flux or voltage orientation) with classical PI controllers. Various simulation tests are conducted to observe the system behavior and evaluate the performance of the control for some optimization criteria (energy efficiency and the robustness of the control). It is also interesting to play on the quality of electric power by controlling the reactive power exchanged with the grid, which will facilitate making a local correction of power factor.
In this paper, the effect of rib (circular sectioned) spacing on average Nusselt number and friction factor in an artificially roughened solar air heater (duct aspect ratio, AR= 5:1) is studied by adopting the computational fluid dynamics (CFD) approach. Numerical solutions are obtained using commercial software ANSYS FLUENT v12.1. The computations based on the finite volume method with the semi-implicit method for pressure-linked equations (SIMPLE) algorithm have been conducted. Circular sectioned transverse ribs are applied at the underside of the top of the duct, i.e., on the absorber plate. The rib-height-to-hydraulic diameter ratio (e/D) is 0.042. The rib-pitch-to-rib-height (P/e) ratios studied are 7.14, 10.71, 14.29 and 17.86. For each rib spacing simulations are executed at six different relevant Reynolds numbers from 3800 to 18000. The thermo-hydraulic performance parameter for P/e = 10.71 is found to be the best for the investigated range of parameters at a Reynolds number of 15000.
Greenhouse technology is a practical option for the production and drying of agricultural products in controlled environment. For the successful design of a greenhouse, the selection of a suitable shape and orientation is of great importance. Of various shapes of greenhouses, the even-span roof and the Quonset shape greenhouses are the most commonly used for crop cultivation and drying. The orientation of greenhouses is kept east–west for maximum utilization of solar radiations. Hybrid and modified greenhouse dryers have been proposed for drying of products. The agricultural products dried in greenhouses are found to be better in quality as compared to open sun drying because they are protected from dust, rain, insects, birds and animals. Moreover, various greenhouses shapes along with their applications have been reviewed.
Partial shading is a common phenomenon in PV arrays. They drastically reduce the power output because of mismatch losses, which are reliant on the shape of the shade as well as the locations of shaded panels in the array. The power output can be improved by distributing the shade over various rows to maximize the current entering the node. A Su-Do-Ku configuration can be used to rearrange the physical locations of the PV modules in a total cross tied PV array with the electrical connections left unchanged. However, this arrangement increases the length of the wire required to interconnect the panels thus increasing the line losses. In this paper, an improved Su-Do-Ku arrangement that reduces the length of the wire required for the connection is proposed. The system is designed and simulated in a Matlab/Simulink environment for various shading patterns and the efficacies of various arrangements are compared. The results prove that the power output is higher in the proposed improved Su-Do-Ku reconfiguration technique compared to the earlier proposed Su-Do-Ku technique.
Water is perhaps the most widely adopted working fluid in conventional industrial heat transport engineering. However, it may no longer be the best option today due to the increasing scarcity of water resources. Furthermore, the wide variations in water supply throughout the year and across different geographic regions also makes it harder to easily access. To address this issue, finding new alternatives to replace water-based technologies is imperative. In this paper, the concept of a water-free heat exchanger is proposed and comprehensively analyzed for the first time. The liquid metal with a low melting point is identified as an ideal fluid that can flexibly be used within a wide range of working temperatures. Some liquid metals and their alloys, which have previously received little attention in thermal management areas, are evaluated. With superior thermal conductivity, electromagnetic field drivability, and extremely low power consumption, liquid metal coolants promise many opportunities for revolutionizing modern heat transport processes: serving as heat transport fluid in industries, administrating thermal management in power and energy systems, and innovating enhanced cooling in electronic or optical devices. Furthermore, comparative analyses are conducted to understand the technical barriers encountered by advanced water-based heat transfer strategies and clarify this new frontier in heat-transport study. In addition, the unique merits of liquid metals that could lead to innovative heat exchanger technologies are evaluated comprehensively. A few promising industrial situations, such as heat recovery, chip cooling, thermoelectricity generation, and military applications, where liquid metals could play irreplaceable roles, were outlined. The technical challenges and scientific issues thus raised are summarized. With their evident ability to meet various critical requirements in modern advanced energy and power industries, liquid metal-enabled technologies are expected to usher a new and global era of water-free heat exchangers.
Fuel cell vehicles, as the most promising clean vehicle technology for the future, represent the major chances for the developing world to avoid high-carbon lock-in in the transportation sector. In this paper, by taking China as an example, the unique advantages for China to deploy fuel cell vehicles are reviewed. Subsequently, this paper analyzes the greenhouse gas (GHG) emissions from 19 fuel cell vehicle utilization pathways by using the life cycle assessment approach. The results show that with the current grid mix in China, hydrogen from water electrolysis has the highest GHG emissions, at 3.10 kgCO2/km, while by-product hydrogen from the chlor-alkali industry has the lowest level, at 0.08 kgCO2/km. Regarding hydrogen storage and transportation, a combination of gas-hydrogen road transportation and single compression in the refueling station has the lowest GHG emissions. Regarding vehicle operation, GHG emissions from indirect methanol fuel cell are proved to be lower than those from direct hydrogen fuel cells. It is recommended that although fuel cell vehicles are promising for the developing world in reducing GHG emissions, the vehicle technology and hydrogen production issues should be well addressed to ensure the life-cycle low-carbon performance.
Biodiesel is an alternative fuel to replace fossil-based diesel fuel. It has fuel properties similar to diesel which are generally determined experimentally. The experimental determination of various properties of biodiesel is costly, time consuming and a tedious process. To solve these problems, artificial neural network (ANN) has been considered as a vital tool for estimating the fuel properties of biodiesel, especially from its fatty acid (FA) composition. In this study, four ANNs have been designed and trained to predict the cetane number (CN), flash point (FP), kinematic viscosity (KV) and density of biodiesel using ANN with logsig and purelin transfer functions in the hidden layer of all the networks. The five most prevalent FAs from 55 feedstocks found in the literature utilized as the input parameters for the model are palmitic, stearic, oleic, linoleic and linolenic acids except for density network with a sixth parameter (temperature). Other FAs that are present in the biodiesels have been considered based on the number of carbon atom chains and the level of saturation. From this study, the prediction accuracy and the average absolute deviation of the networks are CN (96.69%; 1.637%), KV (95.80%; 1.638%), FP (99.07%; 0.997%) and density (99.40%; 0.101%). These values are reasonably better compared to previous studies on empirical correlations and ANN predictions of these fuel properties found in literature. Hence, the present study demonstrates the ability of ANN model to predict fuel properties of biodiesel with high accuracy.