Big-Data Science in Porous Materials: Materials Genomics and Machine Learning. - Kevin Maik Jablonka; Daniele Ongari; Seyed Mohamad Moosavi; Berend Smit (CoRR, 2020)

SELFIES and the future of molecular string representations. - Mario Krenn; Qianxiang Ai; Senja Barthel; Nessa Carson; Angelo Frei; Nathan C. Frey; Pascal Friederich; Théophile Gaudin; Alberto Alexander Gayle; Kevin Maik Jablonka; Rafael F. Lameiro; Dominik Lemm; et al. (Patterns, 2022)

Agent-based Learning of Materials Datasets from Scientific Literature. - Mehrad Ansari; Seyed Mohamad Moosavi (CoRR, 2023)

Design of New Inorganic Crystals with the Desired Composition Using Deep Learning. - Seunghee Han; Jaewan Lee; Sehui Han; Seyed Mohamad Moosavi; Jihan Kim; Changyoung Park (J. Chem. Inf. Model., 2023)

Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry. - Yoel Zimmermann; Adib Bazgir; Zartashia Afzal; Fariha Agbere; Qianxiang Ai; Nawaf Alampara; Alexander Al-Feghali; Mehrad Ansari; Dmytro Antypov; Amro Aswad; Jiaru Bai; Viktoriia Baibakova; et al. (CoRR, 2024)

34 Examples of LLM Applications in Materials Science and Chemistry: Towards Automation, Assistants, Agents, and Accelerated Scientific Discovery. - Yoel Zimmermann; Adib Bazgir; Alexander Al-Feghali; Mehrad Ansari; Joshua D. Bocarsly; L. Catherine Brinson; Yuan Chiang; Defne Circi; Min-Hsueh Chiu; Nathan Daelman; Matthew L. Evans; Abhijeet Sadashiv Gangan; et al. (CoRR, 2025)

CheMixHub: Datasets and Benchmarks for Chemical Mixture Property Prediction. - Ella M. Rajaonson; Mahyar Rajabi Kochi; Luis Martin Mejia Mendoza; Seyed Mohamad Moosavi; Benjamín Sánchez-Lengeling (CoRR, 2025)

MOFSimBench: Evaluating Universal Machine Learning Interatomic Potentials In Metal-Organic Framework Molecular Modeling. - Hendrik Kraß; Ju Huang; Seyed Mohamad Moosavi (CoRR, 2025)