Thermionic energy conversion (TEC) using nano materials is an emerging field of research. Graphene can stand high temperature as high as 4600 K in vacuum. Its work function can be engineered from its high value (for monolayer/bilayer) 4.6 eV to 3. 7 eV, 3.8 eV, 3.5 eV and 3.4 eV, through the use of K2CO3, Li2CO3, Rb2CO3, Cs2CO3 as shown by Kwon et al43 and to as low as 0.7 eV as shown by Yuan et al. Such remarkable property along with good electrical conductivity, high dielectric constant makes engineered graphene an ideal candidate to be used as both emitter and collector in a thermionic energy converter. Since large size parabolic trough solar concentrator is now available, there is a great possibility of harnessing solar energy efficiently and cost effectively, if complex functional relation of efficiency of solar energy conversion with solar insolation, area of solar concentrator, work functions (We, Wc) & temperatures, emissivity of emitter and collector, space charge control etc. can be understood clearly. Using modified Richardson-Dushman equation this work focuses on theoretical studies of these aspects, excluding the space charge control. What is necessary for high efficiency is good combination of (We, Wc), with a difference > 0.5 eV, proper collector temperature and high solar energy input. Such solar energy conversion would reduce the dependence on silicon solar panel and has great potential for future applications.

Theoretical studies of thermionic conversion of solar energy with graphene as emitter & collector

Abstract Chemical engine is an abstract model of some devices, such as solid state, photochemical, and electrochemical devices, photovoltaic cell, and mass exchangers. Finite chemical-potential source is one of its features. Finite time thermodynamics provides effective theoretical tool for determining performance limits for given thermal systems, and determining optimal process paths of thermal systems for given performance objectives. Endoreversible model is its basic model. A model of endoreversible non-isothermal chemical engines operating between a finite chemical-potential source and an infinite chemical-potential sink with mass resistance and heat resistance is established. Mass transfer processes between chemical potential reservoir and working fluid of the model are assumed to obey Onsager equations in linear irreversible thermodynamics. With a fixed cycle period, optimal cycle configuration for the maximum work output of the model is derived by applying optimal control theory. The results obtained include optimal performance and optimal path results in many previous literatures, and can provide some theoretical guidelines for optimal designs of practical chemical plants.

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Maximum work configuration of finite potential source endoreversible non-isothermal chemical engines

Experimental and theoretical study on hybrid thermionic-photovoltaic energy converters with graphene/semiconductor Schottky junction

According to the established model of a single resonance energy selective electron refrigerator with heat leakage in the previous literature, this paper performs multi-objective optimization with finite-time thermodynamic theory and NSGA-II algorithm. Cooling load (R¯), coefficient of performance (ε), ecological function (ECO¯), and figure of merit (χ¯) of the ESER are taken as objective functions. Energy boundary (E′/kB) and resonance width (ΔE/kB) are regarded as optimization variables and their optimal intervals are obtained. The optimal solutions of quadru-, tri-, bi-, and single-objective optimizations are obtained by selecting the minimum deviation indices with three approaches of TOPSIS, LINMAP, and Shannon Entropy; the smaller the value of deviation index, the better the result. The results show that values of E′/kB and ΔE/kB are closely related to the values of the four optimization objectives; selecting the appropriate values of the system can design the system for optimal performance. The deviation indices are 0.0812 with LINMAP and TOPSIS approaches for four-objective optimization (ECO¯−R¯−ε−χ¯), while the deviation indices are 0.1085, 0.8455, 0.1865, and 0.1780 for four single-objective optimizations of maximum ECO¯, R¯, ε, and χ¯, respectively. Compared with single-objective optimization, four-objective optimization can better take different optimization objectives into account by choosing appropriate decision-making approaches. The optimal values of E′/kB and ΔE/kB range mainly from 12 to 13, and 1.5 to 2.5, respectively, for the four-objective optimization.

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Four-Objective Optimizations of a Single Resonance Energy Selective Electron Refrigerator

Based on the existing model of an irreversible magnetohydrodynamic cycle, this paper uses finite time thermodynamic theory and multi-objective genetic algorithm (NSGA-II), introduces heat exchanger thermal conductance distribution and isentropic temperature ratio of working fluid as optimization variables, and takes power output, efficiency, ecological function, and power density as objective functions to carry out multi-objective optimization with different objective function combinations, and contrast optimization results with three decision-making approaches of LINMAP, TOPSIS, and Shannon Entropy. The results indicate that in the condition of constant gas velocity, deviation indexes are 0.1764 acquired by LINMAP and TOPSIS approaches when four-objective optimization is performed, which is less than that (0.1940) of the Shannon Entropy approach and those (0.3560, 0.7693, 0.2599, 0.1940) for four single-objective optimizations of maximum power output, efficiency, ecological function, and power density, respectively. In the condition of constant Mach number, deviation indexes are 0.1767 acquired by LINMAP and TOPSIS when four-objective optimization is performed, which is less than that (0.1950) of the Shannon Entropy approach and those (0.3600, 0.7630, 0.2637, 0.1949) for four single-objective optimizations, respectively. This indicates that the multi-objective optimization result is preferable to any single-objective optimization result.

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Four-Objective Optimization of an Irreversible Magnetohydrodynamic Cycle

The maximum efficiency enhancement of a solar-driven graphene-anode thermionic converter realizing total photon reflection

A nanostructured thermoelectric device is designed by connecting a double-barrier resonant tunneling heterostructure to two electron reservoirs. Based on Landauers equation and Fermi-Dirac statistics, the exact solution of the heat flow is calculated. The maximum power output and efficiency are calculated through the optimizations of several key parameters. The optimum characteristic curve of the performance is obtained. The reasonably working region of the device is determined, the selection criteria of main parameters are provided, and the optimum configuration of the device is drawn. Results show that the heterojunction becomes a perfect energy filter by appropriately regulating the chemical potentials of electron reservoirs and optimally choosing the widths of barrier and quantum well and the nanostructured thermoelectric device with resonance tunneling may obtain simultaneously a large power output and a high efficiency. 

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Dinesh Khattar

Papers

The maximum efficiency enhancement of a solar-driven graphene-anode thermionic converter realizing total photon reflection

The maximum efficiency enhancement of a solar-driven graphene-anode thermionic converter realizing total photon reflection

The optimum configuration design of a nanostructured thermoelectric device with resonance tunneling