There is a sprawl of MAPs in various fields but unique challenges abound to non-aqueous battery research have resulted in but a few larger MAP efforts . This complexity arises from the special housing and safety measures necessary to conduct battery research and a large chemical space for optimizing e.g. electrolytes, electrodes, design, and physical properties . Significant efforts have been made in each of these areas, in particular, in electrolyte optimization; for instance, Dave et al. developed an autonomous workflow which was able to combine 251 aqueous electrolyte salts for a mixed-anion sodium electrolyte. This workflow analyzed the ionic conductivity and electrochemical stability in approximately 25 minutes. In subsequent work, they extended their study in a non-aqueous system and optimized the electrolyte formulation for a single salt and ternary solvent design at various ratios for Lithium-ion batteries (LiBs) by utilizing a robotic platform. However, the autonomous investigation on CEI and solid electrolyte interphase (SEI) within MAPs are not extensively explored . This highlights the ongoing need for innovative approaches in battery research, especially in understanding and optimizing the complex interactions at these interfaces . A primary challenge in developing a system capable of providing a multifaceted solution for the next generation of battery materials is the substantial costs involved in integrating a single laboratory with all the necessary devices . However, this integration is essential as conducting comprehensive tests, such as correlating electrochemical and spectroscopic tests, is crucial for achieving multifidelity. Additionally, due to variations arising from different samples, this correlation and integration within a single lab on a single sample become even more important. This approach ensures consistency and reliability of results, as it effectively minimizes discrepancies that might occur from diverse laboratory environments.