AI 中文总结
本研究结合机器学习数据库挖掘与实验，发现38种未被识别的ml-MXene，用快速自蔓延高温合成法重新发现5种MXenes，还制备11种稀土基M₂CT₂ MXenes，扩展了MXene家族并提供数据驱动的可持续材料发现策略。
AI 中文摘要
MXenes（二维过渡金属碳化物和氮化物）通常从MAX相获得，但历史报道表明存在更广阔且大部分未被探索的化学空间。本研究将机器学习辅助的数据库挖掘与实验相结合，以发现被忽视的多层（ml）MXenes。对数据库的筛选揭示了一个包含38种先前已合成但未被识别的ml-MXene候选物的“宝库”。基于这些发现，研究人员使用无需持续外部加热、在数分钟内即可完成的快速可扩展自蔓延高温合成法，重新发现了5种MXenes。受已识别化学物质的启发，研究人员进一步制备了11种先前未被探索的基于稀土的M₂CT₂ MXenes（M为Pr、Nd、Sm、Gd、Tb、Ho和Tm）。实验与理论研究表明，该家族具有半导体行为和多样的磁态。这些结果共同扩展了MXene家族，并展示了一种通过可持续方法加速材料发现的数据驱动策略。
英文摘要
MXenes, two-dimensional transition-metal carbides and nitrides, are typically obtained from MAX phases, yet historical reports suggest a broader, largely unexplored chemical space. Here we combine machine-learning-assisted database mining with experiments to uncover overlooked multilayer (ml) MXenes. Screening of repositories reveals a "Treasure Chest" of 38 previously synthesized but unrecognized ml-MXene candidates. Guided by these findings, we rediscover five MXenes using a rapid, scalable self-propagating high-temperature synthesis that requires no sustained external heating and completes within minutes. Inspired by the identified chemistries, we further realize 11 previously unexplored rare-earth-based M2CT2 MXenes (M= Pr, Nd, Sm, Gd, Tb, Ho, and Tm). Experiments and theory reveal semiconducting behavior and diverse magnetic states across this family. Together, these results expand the MXene family and demonstrate a data-driven strategy for accelerating materials discovery through sustainable methods.
