Publications by Sauradeep Majumdar

Nonuniform Chiralization of Metal-Organic Frameworks Using Imine Chemistry

Berend Smit, Emad Oveisi, Natalia Gasilova, Sauradeep Majumdar, Elias Moubarak, Balázs Álmos Novotny, Kevin Maik Jablonka, Andres Adolfo Ortega Guerrero

Homochiral metal-organic frameworks (MOFs) are exceptional media for heterogeneous enantiodifferentiation processes. Modifying available achiral structure-bearing MOF scaffolds is a preferred method to extend this class of materials. Reported postsynthetic ...

AMER CHEMICAL SOC2025

Inverse design of metal-organic frameworks for direct air capture of CO2via deep reinforcement learning

Berend Smit, Xiaoqi Zhang, Sauradeep Majumdar, Hyunsoo Park

The combination of several interesting characteristics makes metal-organic frameworks (MOFs) a highly sought-after class of nanomaterials for a broad range of applications like gas storage and separation, catalysis, drug delivery, and so on. However, the e ...

Royal Soc Chemistry2024

A diversity-driven discovery of potential nanoporous materials for energy-related applications

Sauradeep Majumdar

The design and discovery of potential novel materials is critical for the advancement of climate change mitigation technologies. In this respect, metal-organic frameworks (MOFs) have received considerable attention over the last two decades. The combinatio ...

EPFL2024

Assessment of fine-tuned large language models for real-world chemistry and material science applications

Berend Smit, Rubén Laplaza Solanas, Anne-Clémence Corminboeuf, Sauradeep Majumdar, Beatriz Bueno Mouriño, Kevin Maik Jablonka

The current generation of large language models (LLMs) has limited chemical knowledge. Recently, it has been shown that these LLMs can learn and predict chemical properties through fine-tuning. Using natural language to train machine learning models opens ...

ROYAL SOC CHEMISTRY2024

14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon

Berend Smit, Philippe Schwaller, Xiaoqi Zhang, Sauradeep Majumdar, Andres Camilo Marulanda Bran, Kevin Maik Jablonka

Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronic ...

Royal Soc Chemistry2023

Diversifying Databases of Metal Organic Frameworks for High-Throughput Computational Screening

Berend Smit, Sauradeep Majumdar, Seyedmohamad Moosavi, Daniele Ongari, Kevin Maik Jablonka

By combining metal nodes and organic linkers, an infinite number of metal organic frameworks (MOFs) can be designed in silico. Therefore, when making new databases of such hypothetical MOFs, we need to ensure that they not only contribute toward the growth ...

AMER CHEMICAL SOC2021