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Liu et al. J Mater Inf 2023;3:17  https://dx.doi.org/10.20517/jmi.2023.19         Page 3 of 17

               phase structure, thermal conductivity, and microstructure of multi-element (ZrNbU)C fuel are
                         [59]
               investigated . Additionally, (U Zr )C  systems exhibit promise as design concepts/strategies for advanced
                                             1-x
                                                y
                                          x
               nuclear power systems due to their unique nuclear properties and thermal stability .
                                                                                    [60]
               In the present work, tantalum (Ta) or yttrium (Y) is added as the third metal atom to the (ZrU)C system to
               explore their effects on the properties of MECs. Proper doping of trace elements has been shown to
                                                                                              [61]
               promote the densification and grain growth of ceramic materials and extend their service life . It has been
               reported that the utilized temperature of (TaZrU)C fuel could be improved by the addition of Ta and Zr
               into the classical UC one , which is selected as the investigated candidacy fuel in the present work. This
                                     [62]
               work investigates the physical property changes and thermodynamic properties of (TMZrU)C (TM = Ta, Y)
               MECs in detail using high-throughput first-principles calculations, providing valuable data and technical
               support for the design of new high entropy fuel from both an electronic and atomic perspective. Specifically,
               we focus on examining the equilibrium volume (V ), Gibbs free energy, constant volume heat capacity (Cv),
                                                          0
               constant pressure heat capacity (Cp), bulk modulus (B ), and thermal conductivity of the (TMZrU)C
                                                                0
               structures. This research holds promise for the advancement of carbide materials, specifically MEC ceramic
               fuels, with implications for NTP systems.


               MATERIALS AND METHODS
               Multicomponent supercell construction via similar atomic environment
               Consideration of the possible quasirandom structure with lattice distortion is important in the modeling of
               disordered structures. In the present work, the similar atomic environment (SAE) toolkit combined in the
               Professional Materials at Extreme (ProME) platform is utilized to construct the supercells of the
               multicomponent system [63,64] , which has the capability to systematically screen the optimal structure of the
               fuel doping system. It is noted that the SAE approach is a novel structural modeling method that employs a
               similarity function to quantitatively describe the deviation between the current configuration and the
               desired disordered solid solution structure. This approach enables the construction of quasirandom
               structures to be transformed into a minimization problem of configuration space. The superlattices of
               (TaZrU)C and (YZrU)C with 64 atoms were constructed using the SAE method, as shown in Figure 1,
               based on the cell structures of ZrC (the space group number No. 225 and the lattice parameter
               a = b = c = 4.48 Å) and YC (the space group number No. 225 and the lattice parameter a = b = c = 5.09 Å).
               The supercells were generated by enlarging the unit cell of 2  × 2  × 2, which were also selected as
               representative models to simulate the solid solution alloys under various occupancy conditions. In order to
               improve the efficiency of structural optimization/selection, two parallel independent calculations were
               performed. In each optimization loop, the number of random structures conforming to the elemental ratios
               was first generated to be 1,000, and then the one with the smallest objective function was selected as the seed
               structure for subsequent optimization. Subsequently, starting with the seed structure, the Metropolis Monte
               Carlo (MMC) algorithm was used to minimize the objective function and exchange atomic positions to
               evolve the structure . Finally, by repeating the above cycle 12 times, the objective function will reach a local
                                [63]
                                                                                   [63]
               minimum, and the criterion to complete the optimization process is expressed as :








                         ) represents the number of classes of configurationally equivalent clusters in A .
               where N(A m                                                                 m
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