The recent development of accurate and efficient semilocal density functionals on the third rung of Jacob’s ladder of density functional theory, such as the revised regularized strongly constrained and appropriately normed (r2SCAN) density functional, could enable rapid and highly reliable prediction of the elasticity and temperature dependence of thermophysical parameters of refractory elements and their intermetallic compounds using the quasi-harmonic approximation (QHA). Here, we present a comparative evaluation of equilibrium cell volumes, cohesive energy, mechanical moduli, and thermophysical properties (Debye temperature and thermal expansion coefficient) for 22 transition metals using semilocal density functionals, including the local density approximation (LDA), Perdew–Burke–Ernzerhof (PBE) and PBEsol generalized gradient approximations (GGAs), and the r2SCAN meta-GGA. PBEsol and r2SCAN deliver the same level of accuracies for structural, mechanical, and thermophysical properties. PBE and r2SCAN perform better than LDA and PBEsol for calculating cohesive energies of transition metals. Among the tested density functionals, r2SCAN provides an overall well-balanced performance for reliably computing cell volumes, cohesive energies, mechanical properties, and thermophysical properties of various 3d, 4d, and 5d transition metals using QHA. Therefore, we recommend that r2SCAN could be employed as a workhorse method to evaluate thermophysical properties of transition metal compounds and alloys in high throughput workflows.

Carbon dioxide emissions are the primary and most direct contributor to global warming, posing a significant hazard to both the environment and human health. In response to this challenge, there has been a growing interest in the development of effective carbon capture technologies. This study involved the synthesis of 13-X molecular sieve porous materials using solid waste coal gangue as a source of silicon and aluminum. The synthesis process involved the controlled utilization of an “alkali fusion-hydrothermal” reaction system. The resulting materials were characterized for their structure, morphology, and crystal composition using X-ray diffraction and field emission scanning electron microscopy. These 13-X molecular sieve materials were employed as adsorbents to capture carbon dioxide gas, and their adsorption performance was investigated. The findings indicated that the 13-X molecular sieve materials possess uniform pores and complete crystalline morphologies, and they exhibited an adsorption capacity of 1.82 mmol/g for carbon dioxide at 0 °C. Consequently, this study not only converted solid waste gangue into high-value products but also demonstrated effective atmospheric carbon dioxide capture, suggesting that gangue-based 13-X molecular sieves may serve as a potential candidate for carbon capture.

In a battery management system, the accurate estimation of the battery’s state of health (SOH) and state of capacity (SOC) are vital functions. The traditional estimation methods have limitations. To accurately estimate the SOC and SOH of power battery and improve the performance of the long-term estimation of a battery’s SOC, a joint estimation method based on a Kalman filter is proposed in this work. First, a second-order RC equivalent circuit model of a ternary lithium battery was built, whose parameters were identified online, and the model’s accuracy was verified. Then, the battery data under actual working conditions were collected. The SOC and SOH were estimated based on the Kalman filter algorithm, and the simulation was implemented using MATLAB. Finally, according to a time scale transformation, the battery state was jointly estimated, the SOC was estimated at a short-time scale, the SOH was estimated at a long-time scale, and the SOH estimation results were updated to the model parameters for SOC estimation. The results show that the accuracy of the method is very good, and it can effectively improve estimation accuracy and ensure batteries’ long-term estimation performance.