Investigating the solid-state properties of the Earth’s core and mantle presents a formidable challenge due to the extreme conditions that prevail in these areas. Although we can achieve high pressures using a variety of static and dynamic compression techniques, it is still unfeasible to comprehensively sample the entire pressure-temperature (𝑃-𝑇) domain for materials. Therefore, computational methodologies have evolved as a crucial instrument for examining material properties under increased pressures and temperatures. These techniques have demonstrated their efficacy in navigating the phase space, thereby contributing significantly to the understanding of the intrinsic behavior of materials within the Earth’s interior. In this work, we present 𝚎𝚡𝚙𝚛𝚎𝚜𝚜, a comprehensive suite of simulation tools designed for conducting 𝘢𝘣 𝘪𝘯𝘪𝘵𝘪𝘰 calculations within the realm of the physical sciences. These tools are specifically engineered to streamline the associated data processing tasks, and they leverage the capabilities of the Julia programming language. At the core of this toolset lies a versatile, high-throughput, and user-friendly workflow framework. This framework is capable of automating a wide range of 𝘢𝘣 𝘪𝘯𝘪𝘵𝘪𝘰 calculations. By addressing the limitations encountered with existing libraries, 𝚎𝚡𝚙𝚛𝚎𝚜𝚜 simplifies intricate workflows, offers a software-agnostic interface, and ensures modularity—all of which are pivotal features within this domain. In addition to the workflow, we have developed a diverse set of software packages tailored to tackle the challenges inherent in data manipulation for 𝘢𝘣 𝘪𝘯𝘪𝘵𝘪𝘰 calculations. These packages encompass a wide spectrum of functionalities, including crystal symmetry search, conversion of units and reference frames, data visualization, parsing and generation of files, estimation of computing resources, and database storage, among other capabilities. We proceed to showcase the effectiveness of express across a diverse spectrum of mineral materials. For each substance, we conducted calculations of their thermodynamic properties using the quasi-harmonic approximation (QHA). This method was executed with the assistance of a Python package called 𝚚𝚑𝚊, which we developed specifically for multi-configuration quasi-harmonic approximation computations. In pursuit of our objective, we employ three distinct sets of exchange-correlation functionals: the local-density approximation (LDA), the Perdew–Burke–Ernzerhof generalized gradient approximation (PBE-GGA), and the PBE functional revised for solids (PBEsol). Subsequently, we compared these results with other calculations and experimental data, thereby elucidating the varying suitability of these functionals. Notably, the LDA functional, when integrated with thermal effects, exhibited exceptional overall performance. This observation implies that numerous studies that favored GGA functionals but solely relied on static DFT outcomes may have inadvertently incorporated erroneous material characteristics into their research.