AI-Guided Computational Design of a Room-Temperature, Ambient- Pressure Superconductor Candidate: Grokene
DEARDAO DeSci Collaborative Team, Yanhuai Ding

TL;DR
This paper presents Grokene, a novel AI-discovered 2D superlattice predicted to be a high-temperature superconductor at ambient pressure, with potential for practical applications after experimental validation.
Contribution
It introduces Grokene, a new 2D superlattice predicted to be a room-temperature superconductor using AI-guided discovery and advanced computational methods.
Findings
Predicted critical temperature around 310-325 K.
High electron-phonon coupling and phonon frequency support superconductivity.
Phase fluctuations limit observable transition to ~120 K in monolayers.
Abstract
We introduce Grokene, a novel two-dimensional superlattice derived from graphene, which was identified through an AI-guided materials discovery workflow utilizing a large language model. Grokene is predicted to exhibit ambient-pressure, room-temperature superconductivity, with computational simulations revealing a high electron-phonon coupling constant and a substantial logarithmic-averaged phonon frequency (~1650 K), leading to a mean-field critical temperature of approximately 325 K. Full isotropic Eliashberg solutions further support a critical temperature around 310 K, underscoring its strong potential for room-temperature superconductivity. However, the strict two-dimensional nature of Grokene introduces phase fluctuations, limiting the observable superconducting transition to a Berezinskii-Kosterlitz-Thouless (BKT) temperature of about 120 K in monolayers. To elevate TBKT toward…
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Taxonomy
TopicsMachine Learning in Materials Science · 2D Materials and Applications · Electronic and Structural Properties of Oxides
