High-entropy alloys (HEAs) have attracted great attention due to their many unique properties and potential applications. The nature of interatomic interactions in this unique class of complex multicomponent alloys is not fully developed or understood. We report a theoretical modeling technique to enable in-depth analysis of their electronic structures and interatomic bonding, and predict HEA properties based on the use of the quantum mechanical metrics, the total bond order density (TBOD) and the partial bond order density (PBOD). Application to 13 biocompatible multicomponent HEAs yields many new and insightful results, including the inadequacy of using the valence electron count, quantification of large lattice distortion, validation of mechanical properties with experiment data, modeling porosity to reduce Young’s modulus. This work outlines a road map for the rational design of HEAs for biomedical applications.

Chalcogenide crystals have a wide range of applications, especially as thermoelectric materials for energy conversion. Thermoelectric materials can be used to generate an electric current from a temperature gradient based on the Seebeck effect and based on the Peltier effect, and they can be used in cooling applications. Using first-principles calculations and semiclassical Boltzmann theory, we have computed the Seebeck coefficient, electrical conductivity, electronic thermal conductivity, power factor, and figure of merit of 30 chalcogenide crystals. A Quantum Espresso package is used to calculate the electronic properties and locate the Fermi level. The transport properties are then calculated using the BoltzTraP code. The 30 crystals are divided into two groups. The first group has four crystals with quaternary composition (A₂BCQ₄) (A = Tl; B = Cd, Hg; C = Si, Ge, Sn; Q = S, Se, Te). The second group contains 26 crystals with the ternary composition (A’B’Q₂) (A’ = Ag, Cu, Au, Na; B’ = B, Al, Ga, In; Q = S, Se, Te). Among these 30 chalcogenide crystals, the results for 11 crystals: Tl₂CdGeSe₄, Tl₂CdSnSe₄, Tl₂HgSiSe₄, Tl₂HgSnS₄, AuBSe₂, AuBTe₂, AuAlTe₂, AuGaTe₂, AuInTe₂, AgAlSe₂, and AgAlTe₂ are revealed for the first time. In addition, temperature-dependent transport properties of pure and doped AgSbSe₂ and AgSbTe₂ crystals with dopant compositions of AgSb_0.94Cd_0.06Te₂ and AgSbTe_1.85Se_0.15 were explored. These results provide an excellent database for bulk chalcogenides crucial for a wide range of potential applications in renewable energy fields.

In this study, solid polymer blend electrolytes (SPBEs) based on chitosan (CS) and methylcellulose (MC) incorporated with different concentrations of ammonium fluoride (NH₄F) salt were synthesized using a solution cast technique. Both Fourier transformation infrared spectroscopy (FTIR) and X-ray diffraction (XRD) results confirmed a strong interaction and dispersion of the amorphous region within the CS:MC system in the presence of NH₄F. To gain better insights into the electrical properties of the samples, the results of electrochemical impedance spectroscopy (EIS) were analyzed by electrical equivalent circuit (EEC) modeling. The highest conductivity of 2.96 × 10⁻³ S cm⁻¹ was recorded for the sample incorporated with 40 wt.% of NH₄F. Through transference number measurement (TNM) analysis, the fraction of ions was specified. The electrochemical stability of the electrolyte sample was found to be up to 2.3 V via the linear sweep voltammetry (LSV) study. The value of specific capacitance was determined to be around 58.3 F/g. The stability test showed that the electrical double layer capacitor (EDLC) system can be recharged and discharged for up to 100 cycles with an average specific capacitance of 64.1 F/g. The synthesized EDLC cell was found to exhibit high efficiency (90%). In the 1st cycle, the values of internal resistance, energy density and power density of the EDLC cell were determined to be 65 Ω, 9.3 Wh/kg and 1282 W/kg, respectively.

Molten lithium tetrafluoroberyllate (Li₂BeF₄) salt, also known as FLiBe, with a 2:1 mixture of LiF and BeF₂ is being proposed as a coolant and solvent in advanced nuclear reactor designs, such as the molten salt reactor or the fluoride salt cooled high-temperature reactor. We present the results on the structure and properties of FLiBe over a wide range of temperatures, 0–2000 K, from high-throughput ab initio molecular dynamics simulation using a supercell model of 504 atoms. The variations in the local structures of solid and liquid FLiBe with temperature are discussed in terms of a pair distribution function, coordination number, and bond angle distribution. The temperature-dependent electronic structure and optical and mechanical properties of FLiBe are calculated. The optical and mechanical property results are reported for the first time. The results above and below the melting temperature (∼732 K) are compared with the experimental data and with data for crystalline FLiBe. The electronic structure and interatomic bonding results are discussed in correlation with the mechanical strength. A novel concept of total bond order density (TBOD), an important quantum mechanical parameter, is used to characterize the internal cohesion and strength in the simulated models. The results show a variation in the rate of change in properties in solid and liquid phases with anomalous behavior across the melting region. The observed trend is the decrease in mechanical strength, band gap, and TBOD in a nonlinear fashion as a function of temperature. The refractive index shows a surprising minimum at 850 K, among the tested temperatures, which lies above the melting point. These findings provide a new platform to understand the interplay between the temperature-dependent structures and properties of FLiBe salt.

Ni-Co-Cr-Al-Fe-based high-entropy alloys (HEAs) have been demonstrated to possess exceptional oxidation resistance, rendering them promising candidates as bond coats to protect critical components in turbine power systems. However, with the conventional time-consuming alloy design approach, only a small fraction of Ni-Co-Cr-Al-Fe-based HEAs, focusing on equiatomic compositions, has been explored to date. In this study, we developed an effective design framework with the aid of machine learning (ML) and high throughput computations, enabling the rapid exploration of high-temperature oxidation-resistant non-equiatomic HEAs. This innovative approach leverages ML techniques to swiftly select candidates with superior oxidation resistance within the expansive high-entropy composition landscape. Complemented by a thermodynamic-informed ranking-based selection process, several novel non-equiatomic Ni-Co-Cr-Al-Fe HEA candidates surpassing the oxidation resistance of the state-of-the-art bond coat material MCrAlY have been identified and further experimentally demonstrated. Our findings offer a pathway for the development of advanced bond coats in the realm of next-generation turbine engine technology.