Publications by Seyedmohamad Moosavi

Crossing the Valley of Death: A Holistic Approach to Assess the Potential of Sorbent-Based Carbon Capture Technologies

Seyedmohamad Moosavi, Berend Smit, Elias Moubarak, Kevin Maik Jablonka

Elsevier BV2025

A holistic platform for accelerating sorbent-based carbon capture

Seyedmohamad Moosavi, Berend Smit, Elias Moubarak, Kevin Maik Jablonka

Reducing carbon dioxide (CO2) emissions urgently requires the large-scale deployment of carbon-capture technologies. These technologies must separate CO2 from various sources and deliver it to different sinks1,2. The quest for optimal solutions for specifi ...

2024

Reticular chemistry for the rational design of mechanically robust mesoporous merged-net metal-organic frameworks

Seyedmohamad Moosavi, Berend Smit

Access to metal-organic frameworks (MOFs) with enhanced me-chanical stability is key to their successful deployment in practical applications. However, the high porosity of the material often af-fects mechanical stability. In this article, to achieve highl ...

CELL PRESS2023

A Robust Framework for Generating Adsorption Isotherms to Screen Materials for Carbon Capture

Seyedmohamad Moosavi, Berend Smit, Elias Moubarak, Susana Garcia Lopez

To rank the performanceof materials for a given carbon captureprocess, we rely on pure component isotherms from which we predictthe mixture isotherms. For screening a large number of materials,we also increasingly rely on isotherms predicted from molecular ...

AMER CHEMICAL SOC2023

Using genetic algorithms to systematically improve the synthesis conditions of Al-PMOF

Fatmah Ebrahim, Seyedmohamad Moosavi, Berend Smit, Christopher Patrick Ireland, Christoph Leopold Talirz, Kevin Maik Jablonka

The synthesis of metal-organic frameworks (MOFs) is often complex and the desired structure is not always obtained. In this work, we report a methodology that uses a joint machine learning and experimental approach to optimize the synthesis conditions of A ...

NATURE PORTFOLIO2022

A data-science approach to predict the heat capacity of nanoporous materials

Seyedmohamad Moosavi, Berend Smit, Mehrdad Asgari, Daniele Ongari, Elias Moubarak, Andres Adolfo Ortega Guerrero, Özge Kadioglu, Balázs Álmos Novotny, Susana Garcia Lopez

The heat capacity of a material is a fundamental property of great practical importance. For example, in a carbon capture process, the heat required to regenerate a solid sorbent is directly related to the heat capacity of the material. However, for most m ...

NATURE PORTFOLIO2022

A data-driven perspective on the colours of metal-organic frameworks

Luc Patiny, Seyedmohamad Moosavi, Berend Smit, Mehrdad Asgari, Christopher Patrick Ireland, Kevin Maik Jablonka

Colour is at the core of chemistry and has been fascinating humans since ancient times. It is also a key descriptor of optoelectronic properties of materials and is often used to assess the success of a synthesis. However, predicting the colour of a materi ...

2021

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

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

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

Using collective knowledge to assign oxidation states of metal cations in metal-organic frameworks

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

Knowledge of the oxidation state of metal centres in compounds and materials helps in the understanding of their chemical bonding and properties. Chemists have developed theories to predict oxidation states based on electron-counting rules, but these can f ...

NATURE RESEARCH2021

Toward smart carbon capture with machine learning

Mohammad Rahimi, Seyedmohamad Moosavi, Berend Smit

Machine learning (ML) is emerging as a powerful approach that has recently shown potential to affect various frontiers of carbon capture, a key interim technology to assist in the mitigation of climate change. In this perspective, we reveal how ML implemen ...

ELSEVIER2021

Big-Data Science in Porous Materials: Materials Genomics and Machine Learning

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

By combining metal nodes with organic linkers we can potentially synthesize millions of possible metal–organic frameworks (MOFs). The fact that we have so many materials opens many exciting avenues but also create new challenges. We simply have too many ma ...

2020

Thermoelasticity of Flexible Organic Crystals from Quasi-harmonic Lattice Dynamics: The Case of Copper(II) Acetylacetonate

Seyedmohamad Moosavi, Berend Smit, Daniele Ongari

A computationally affordable approach, based on quasi-harmonic lattice dynamics, is presented for the quantum-mechanical calculation of thermoelastic moduli of flexible, stimuli-responsive, organic crystals. The methodology relies on the simultaneous descr ...

2020

Understanding the diversity of the metal-organic framework ecosystem

Seyedmohamad Moosavi, Berend Smit, Yongjin Lee, Daniele Ongari, Peter George Boyd, Kevin Maik Jablonka

Millions of distinct metal-organic frameworks (MOFs) can be made by combining metal nodes and organic linkers. At present, over 90,000 MOFs have been synthesized and over 500,000 predicted. This raises the question whether a new experimental or predicted s ...

Nature Research2020

The Role of Machine Learning in the Understanding and Design of Materials

Seyedmohamad Moosavi, Berend Smit, Kevin Maik Jablonka

Developing algorithmic approaches for the rational design and discovery of materials can enable us to systematically find novel materials, which can have huge technological and social impact. However, such rational design requires a holistic perspective ov ...

2020

Advancing computational and data-driven methods for the design and discovery of nanoporous materials

Seyedmohamad Moosavi

Metal-organic framework (MOFs) and related nanoporous materials have emerged as promising candidates for a variety of applications, such as gas separation and storage, catalysis, sensing, etc. Their building block structure allows us to generate a huge num ...

EPFL2020

Geometric landscapes for material discovery within energy–structure–function maps

Seyedmohamad Moosavi, Berend Smit, Henglu Xu

Porous molecular crystals are an emerging class of porous materials formed by crystallisation of molecules with weak intermolecular interactions, which distinguishes them from extended nanoporous materials like metal–organic frameworks (MOFs). To aid disco ...

2020

Preserving Porosity of Mesoporous Metal-Organic Frameworks through the Introduction of Polymer Guests

Mohammad Khaja Nazeeruddin, Emad Oveisi, Seyedmohamad Moosavi, Berend Smit, Mehrdad Asgari, Wendy Lee Queen, Aron Joel Huckaba, Li Peng, Sudabeh Jawahery, Shuliang Yang

High internal surface areas, an asset that is highly sought after in material design, has brought metal-organic frameworks (MOFs) to the forefront of materials research. In fact, a major focus in the field is on creating innovative ways to maximize MOF sur ...

2019

Capturing chemical intuition in synthesis of metal-organic frameworks

Seyedmohamad Moosavi, Berend Smit, Kyriakos Stylianou, Arunraj Chidambaram, Christoph Leopold Talirz

Nature Research2019

Guest-dependent negative thermal expansion in a lanthanide-based metal-organic framework

Seyedmohamad Moosavi, Berend Smit, Kyriakos Stylianou, Andrzej Gladysiak

A lanthanide-based metal-organic framework (MOF) named SION-2 displays strong and tuneable uniaxial negative thermal expansion (NTE). The coefficient of thermal expansion alpha(1) reaches -153(6) MK-1 between 100 and 340 K, which is the highest value repor ...

2019

Ab Initio Flexible Force Field for Metal-Organic Frameworks Using Dummy Model Coordination Bonds

Seyedmohamad Moosavi, Berend Smit, Sudabeh Jawahery, Matthew David Witman, Nakul Rampal

We present force fields developed from periodic density functional theory (DFT) calculations that can be used in classical molecular simulations to model M MOF-74 (M = Co, Fe, Mg, Mn, Ni, Zn) and its extended linker analogs. Our force fields are based on c ...

2019