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Despite the power and flexibility of configuration interaction (CI) based methods in computational chemistry, their broader application is limited by an exponential increase in both computational and storage requirements, particularly due to the substantial memory needed for excitation lists that are crucial for scalable parallel computing. The objective of this work is to develop a new CI framework, namely, the small tensor product distributed active space (STP-DAS) framework, aimed at drastically reducing memory demands for extensive CI calculations on individual workstations or laptops, while simultaneously enhancing scalability for extensive parallel computing. Moreover, the STP-DAS framework can support various CI-based techniques, such as complete active space (CAS), restricted active space, generalized active space, multireference CI, and multireference perturbation theory, applicable to both relativistic (two- and four-component) and non-relativistic theories, thus extending the utility of CI methods in computational research. We conducted benchmark studies on a supercomputer to evaluate the storage needs, parallel scalability, and communication downtime using a realistic exact-two-component CASCI (X2C-CASCI) approach, covering a range of determinants from 109 to 1012. Additionally, we performed large X2C-CASCI calculations on a single laptop and examined how the STP-DAS partitioning affects performance. 

Thermally regenerative electrochemical cycles and thermogalvanic cells harness redox entropy changes (ΔSrc) to interconvert heat and electricity with applications in heat harvesting and energy storage. Their efficiencies depend on ΔSrc because it relates directly to the Seebeck coefficient, yet few approaches exist for controlling the reaction entropy. Here, we demonstrate the design principle of using highly charged molecular species as electrolytes in thermogalvanic devices. As a proof-of-concept, the highly charged Wells-Dawson ion [P2W18O62]6– exhibits a large ΔSrc (−195 J mol–1 K–1) and a Seebeck coefficient comparable to state-of-the-art electrolytes (−1.7 mV K–1), demonstrating the potential of linking the rich chemistry of polyoxometalates to thermogalvanic technologies.