Publications (6)
Distilling and exploiting quantitative insights from Large Language Models for enhanced Bayesian optimization of chemical reactions
Roshan Patel, Saeed Moayedpour, Louis De Lescure +4
Machine learning and Bayesian optimization (BO) algorithms can significantly accelerate the optimization of chemical reactions. Transfer learning can bolster the effectiveness of B…
Many-Shot In-Context Learning for Molecular Inverse Design
Saeed Moayedpour, Alejandro Corrochano-Navarro, Faryad Sahneh +14
Large Language Models (LLMs) have demonstrated great performance in few-shot In-Context Learning (ICL) for a variety of generative and discriminative chemical design tasks. The new…
Structure Prediction of Epitaxial Organic Interfaces with Ogre, Demonstrated for TCNQ on TTF
Saeed Moayedpour, Imaneul Bier, Wen Wen +3
Highly ordered epitaxial interfaces between organic semiconductors are considered as a promising avenue for enhancing the performance of organic electronic devices including solar…
First Principles Study of the Electronic Structure of the NiMnIn/InAs and TiMnIn/InSb interfaces
Brett Heischmidt, Maituo Yu, Derek Dardzinski +5
We present a first-principles study of the electronic and magnetic properties of epitaxial interfaces between the Heusler compounds TiMnIn and NiMnIn and the III-V semicond…
Dependence of the electronic structure of the EuS/InAs interface on the bonding configuration
Maituo Yu, Saeed Moayedpour, Shuyang Yang +4
Recently, the EuS/InAs interface has attracted attention for the possibility of inducing magnetic exchange correlations in a strong spin-orbit semiconductor, which could be useful…
Structure Prediction of Epitaxial Inorganic Interfaces by Lattice and Surface Matching with Ogre
Saeed Moayedpour, Derek Dardzinski, Shuyang Yang +2
We present a new version of the Ogre open source Python package with the capability to perform structure prediction of epitaxial inorganic interfaces by lattice and surface matchin…