In all types of past, current and future batteries, electrolyte plays a central role in terms of design and control of the electrode processes, material interactions, overall performance, long-term stability, cost and safety of a battery.  In most cases, electrolyte formulations and their ad hoc interfacial/interphasial chemistries govern the fate of each battery chemistry, safety and performance. [2-3] For this reason, there is an urgent need to explore the electrolyte frontier and push our current understanding of electrolyte (electro)-chemistry to advance future battery development.
In this work, we introduce High-Throughput-Screening (HTS) approach with time-efficient strategies for overcoming the numerous optimization problems typically encountered during design and development of novel electrolytes. HTS experiments provide an autonomous tool to generate vast datasets, from which useful knowledge, underlying scientific phenomena and target entries can be obtained using data driven tools and algorithms. Here we develop a data driven model to predict ionic conductivities for suitable electrolyte compositions and temperatures (LiPF6 in EC/EMC mixtures with VC as additives). All data were extracted from HTS experiments with conducting salt, solvent/co-solvent, additive compositions (X (x1,x2,x3)) and temperature (T) as features and ionic conductivity as target quantity. 
The dependence of the conductivity on features changes can be explained based on the dependency on the same variables of following three factors: the number of dissociated ions in the electrolyte, the dielectric constant of the solvent and the viscosity of the electrolyte.
1 M. Winter, B. Barnett, K. Xu, Chem. Rev. 2018, 118, 11433–11456.
2 M. Gauthier, T. J. Carney, A. Grimaud, L. Giordano, N. Pour, H.-H. Chang, D. P. Fenning, S. F. Lux, O. Paschos,
C. Bauer, F. Maglia, S. Lupart, P. Lamp, Y. Shao-Horn, J. Phys. Chem. Lett. 2015, 6, 4653–4672.
3 N. Aspern, G. ‐V. Röschenthaler, M. Winter, I. Cekic‐Laskovic, Angew. Chem. Int. Ed. 2019, 58, 15978–16000.
4 A. Benayad, D. Diddens, A. Heuer, A. N. Krishnamoorthy, M. Maiti, F. L. Cras, M. Legallais, F. Rahmanian, Y.
Shin, H. Stein, M. Winter, C. Wölke, P. Yan, I. Cekic-Laskovic, Adv. Energy Mater. (accepted)