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20242026
most citedMACE-POLAR-1: A Polarisable Electrostatic Foundation Model for Molecular Chemistry

6 citations · 6 across the 6 of their papers we have counts for

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cond-mat.mtrl-sci2026

Data-driven Design of Metal-Organic Frameworks with Tunable Negative Thermal Expansion

Prathami Divakar Kamath, Francesco Tavani, Alin Marin Elena +6

Materials with negative thermal expansion (NTE) are essential for applications requiring precise control of thermal expansion. Owing to their exceptional chemical tunability, flexi…

cond-mat.mtrl-sci2026

Bond, orbital and spin order in d4/d6/d7 perovskite oxides: successes and limitations of foundation interatomic potentials

Swagata Acharya, Dimitar Pashov, Mark van Schilfgaarde +1

Foundation machine-learning interatomic potentials (MLIPs) are rapidly replacing density-functional theory (DFT) for modeling structure and nuclear dynamics, making their fidelity…

cond-mat.mtrl-sci2026

High-Pressure Inelastic Neutron Spectroscopy: A true test of Machine-Learned Interatomic Potential energy landscapes

Jeff Armstrong, Adam Jackson, Alin Elena

Machine-learned interatomic potentials (MLIPs) promise to provide near density-functional theory accuracy at a fraction of the computational cost, offering a transformative route t…

cond-mat.mtrl-sci2025

Automatic generation of input files with optimised k-point meshes for Quantum Espresso self-consistent field single point total energy calculations

Elena Patyukova, Junwen Yin, Susmita Basak +3

Performing density functional theory (DFT) calculations requires a careful choice of computational parameters to ensure convergence and obtain meaningful results. This represents a…

cond-mat.mtrl-sci2025

Machine Learned Potential for High-Throughput Phonon Calculations of Metal-Organic Frameworks

Alin Marin Elena, Prathami Divakar Kamath, Théo Jaffrelot Inizan +3

Metal-organic frameworks (MOFs) are highly porous and versatile materials studied extensively for applications such as carbon capture and water harvesting. However, computing phono…

cond-mat.mtrl-sci2024

Modelling Silica using MACE-MP-0 Machine Learnt Interatomic Potentials

Jamal Abdul Nasir, Jingcheng Guan, Woongkyu Jee +4

Silica polymorphs and zeolites are fundamental to a wide range of industrial applications owing to their diverse structural characteristics, thermodynamic and mechanical stability…