We are at a pivotal time in climate action. To fight climate change, we need to accelerate scale-up of clean energy technologies, like fuel cells, electrolyzers, and batteries, which underpin our energy transition. A major bottleneck in accelerating rational design of next-generation devices is the non-optimal, heterogenous, and often stochastic nature of porous materials within these devices. A vital design parameter of porous materials is pore-scale wettability, which can fundamentally alter transport of species, and thereby dictate device performance. However, we do not yet know the ideal wettability configuration to design our devices around due to fundamental gaps in our understanding of mixed wettability. In this project, I plan to synergistically combine three fields – physics, energy engineering, and automation – to provide a fundamental blueprint to design two-phase flow in next-generation energy materials. First, I will create a microfluidic platform to conduct high-throughput experiments and statistically analyse the effect of a wide range of wettability combinations on flow patterns. State-of-the-art wettability models will be advanced and validated using experiments and create a “mixed-wet phase diagram”. I will then computationally explore the established phase diagram to create designer porous materials with directed transport properties for energy application. Then, superior computational designs will be tested experimentally to cross-validate model capabilities and propose porous media for energy applications (with a focus on water transport in fuel cells). The multi-disciplinary physics-informed design strategy employed in the study is expected to benefit diverse clean energy technologies, with potential applications in microfluidic disease diagnosis and other engineered flow systems.