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The prediction of reaction pathways for solid-solid transformations remains akey challenge. Here, we develop a pathway sampling method via swarmintelligence and graph theory, and demonstrate that our PALLAS method is aneffective tool to help understand phase transformations in solid-state systems.The method is capable of finding low-energy transition pathways between twominima without having to specify any details of transition mechanism a priori.We benchmarked our PALLAS method against known phase transitions in cadmiumselenide (CdSe) and silicon (Si). PALLAS readily identifiespreviously-reported, low-energy phase transition pathways for the wurtzite torock-salt transition in CdSe and reveals a novel lower-energy pathway that hasnot yet been observed. In addition, PALLAS provides detailed information thatexplains the complex phase transition sequence observed during thedecompression of Si from high pressure. Given the efficiency to identifylow-barrier-energy reaction pathways, the PALLAS methodology represents apromising tool for materials by design with valuable insights for novelsynthesis.

Phase Transition Pathway Sampling via Swarm Intelligence and Graph Theory