Hydrify

The geologic hydrogen industry is on the verge of a breakthrough as a game changer for the energy transition. However, there are no established methods for finding the “sweet spots” where these hydrogen deposits are located, nor for identifying the best rocks to stimulate for production. Our internal techno-economic analysis highlights a key challenge for scaling geologic hydrogen: high costs associated with locating technically feasible and commercially viable deposits, which represent 40-50% of capital investments. Hydrify tackles this challenge by using proprietary AI/ML algorithms to efficiently identify hydrogen-rich rock formations, reducing both the time and costs of exploration. Furthermore, our analysis indicates that transportation costs for hydrogen could equal or surpass extraction costs. Therefore, our method focuses on finding deposits near existing demand centers or where demand can be created.

Team Members

Yashee Mathur (PhD, Energy Science and Engineering); Henry Moise (PhD, Chemical Engineering); Yalcin Aydin (GSB and MS in Sustainability); PI: Prof. Tapan Mukerji (Energy Science and Engineering)