Laboratory of Molecular Simulation (LSMO)

3
Berend Smit Min

Prof. Berend Smit

Laboratory of Molecular Simulation (LSMO)

CO2 capture


Our mission

We advance materials discovery by uniting molecular simulation, data science, and AI. Through rigorous modeling, high-quality data, and holistic digital platforms, we accelerate breakthroughs in reticular chemistry and carbon capture, creating tools with real-world impact.

Research topics

1

We use advanced computer simulations to understand how new materials work at the atomic level. This helps us predict important properties—such as how they hold heat, absorb gases, or move water—before we make them in the lab.

2

We combine large datasets with modern AI methods to identify which materials are most promising for a given job. Instead of testing thousands of materials experimentally, we let AI narrow the search to the most useful ones.

3

We synthesize and characterize new materials—such as bright, tunable luminescent compounds—to explore their properties experimentally and connect them to our simulations and AI models.

Our key projects


2

A unified platform linking material properties, process design, TEA and LCA to identify optimal CO₂-capture sorbents for real source–sink pairs.Used across >60 global case studies for system-level decisions.


Heriot-Watt University, ETHZ, UC Berkeley, ENS Paris

3

Using data-driven MOF screening, we identified robust CO₂-binding “adsorbaphores” resistant to humidity. Led to synthesis of Al-PMOF and Al-PyrMOF, which outperform commercial sorbents under wet conditions.


Heriot-Watt University, UC Berkeley

1

Fine-tuning large language models enables accurate prediction of materials properties and even inverse design with minimal data. Demonstrated across molecules, alloys and MOFs; surprisingly outperforms specialized ML in low-data regimes.

Our results and highlights

1

2 articles in Nature

2

Highly Cited Researcher in the field of Cross-Field – 2025

3

SNFS Advanced grant

4

DePOLY is a spin off from LSMO

Team & talents

Lab team size

16-18 people

Skills developed by the scientific team

AI, molecular simulation, MOF synthesis

Regional and social impacts

1

Fundamental research

Perspectives and challenges

Main opportunities

Develop AI-drivent materials design

Future Partnerships

Heriot-Watt Univeristy

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