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Bibliographic Details
Main Authors: DEARDAO DeSci Collaborative Team, Ding, Yanhuai
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.00931
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author DEARDAO DeSci Collaborative Team
Ding, Yanhuai
author_facet DEARDAO DeSci Collaborative Team
Ding, Yanhuai
contents 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 room temperature, strategies such as few-layer stacking, substrate or gate engineering, and optimization of superlattice structure and doping levels are proposed. Our integrated workflow, combining AI-driven materials discovery with advanced many-body theories (DFPT/EPW, Eliashberg, and RPA), provides a systematic and reproducible framework for exploring novel superconductors. We suggest that experimental synthesis and comprehensive characterization of Grokene will be essential to assess these computational predictions and to explore routes toward practical superconductivity under ambient pressure.
format Preprint
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institution arXiv
publishDate 2026
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spellingShingle AI-Guided Computational Design of a Room-Temperature, Ambient- Pressure Superconductor Candidate: Grokene
DEARDAO DeSci Collaborative Team
Ding, Yanhuai
Superconductivity
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 room temperature, strategies such as few-layer stacking, substrate or gate engineering, and optimization of superlattice structure and doping levels are proposed. Our integrated workflow, combining AI-driven materials discovery with advanced many-body theories (DFPT/EPW, Eliashberg, and RPA), provides a systematic and reproducible framework for exploring novel superconductors. We suggest that experimental synthesis and comprehensive characterization of Grokene will be essential to assess these computational predictions and to explore routes toward practical superconductivity under ambient pressure.
title AI-Guided Computational Design of a Room-Temperature, Ambient- Pressure Superconductor Candidate: Grokene
topic Superconductivity
url https://arxiv.org/abs/2601.00931