arXiv subjects

Alin Elena

Publications and source records attributed to Alin Elena.

4 recordsLinked to original sources

arXiv2026

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

Machine-learned interatomic potentials (MLIPs) promise to provide near density-functional theory accuracy at a fraction of the computational cost, offering a transformative route toward genuinely predictive chemistry. Yet their predictive validity beyond the training regime remains largely untested experimentally. Here we use pressure-dependent broadband inelastic neutron spectroscopy (INS) as a direct experimental probe of MLIP transferability. Employing a newly developed high-pressure superalloy clamp cell, we measure INS spectra of crystalline 2,5-diiodothiophene at 10~K under ambient conditions and at 1.5~GPa. A MACE-based MLIP, fine-tuned on targeted DFT data, reproduces the experimental spectra across 0--1200~cm$^{-1}$ at both pressures and remains thermodynamically stable under rigorous molecular dynamics validation at 300~K. The model captures systematic pressure-induced blue shifts arising from steric stiffening and reproduces an anomalous red shift at 453~cm$^{-1}$ driven by pressure-modified intermolecular interactions, providing direct validation of its many-body character. This constitutes the first experimental demonstration of MLIP transferability across distinct thermodynamic states using neutron spectroscopy, and establishes high-pressure INS as a stringent benchmark for predictive machine-learned potentials.

cond-mat.mtrl-sci↗

arXiv2025

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

Performing density functional theory (DFT) calculations requires a careful choice of computational parameters to ensure convergence and obtain meaningful results. This represents a particularly important problem for high-throughput and agentic workflows, where due to computational cost, any additional convergence studies are preferably to be avoided. So, there is a need for tools and models which are able to predict DFT parameters from basic input information, such as a structure. In this work, we develop a machine learning approach to predict the appropriate k-point sampling in DFT calculations and generate the input files for Quantum Espresso self-consistent field calculations. To achieve this, we first generated a training dataset comprising over 20,000 materials, each with an energy convergence threshold of 1 meV/atom. Several ML models were evaluated for their ability to predict k-points distance, and uncertainty estimation was incorporated to guarantee that, for at least 85-95% of compounds, the predicted k-distance lies within the convergence region. The best-performing models are made publicly available through an open-access web application.

cond-mat.mtrl-sci↗

arXiv2021

Radiation damage effects on helium diffusion in zircon

We report the effects of radiation damage on helium diffusion in zircon using data from molecular dynamics simulations. We observe an increase in activation energy for helium diffusion as a result of radiation damage and increasing structural disorder. The activation energy in a heavily damaged region is smaller than in a completely amorphous system which is correlated with remaining order in the cation sublattices of the damaged structure not present in the fully amorphized system. The reduction of activation energy is related to the disappearance of fast diffusion pathways that present in the crystal. Consistent with the change in activation energy, we observe the accumulation of helium atoms in the damaged structure and discuss the implications of this effect for the formation of helium bubbles and zircon's performance as an encapsulation material for nuclear waste.

cond-mat.mtrl-sci↗

arXiv2020

Radiation damage effects in amorphous zirconolite

We report the results of a large-scale modelling study of radiation damage effects in the nuclear waste form zirconolite. We particularly focus on the effects of radiation damage in amorphous zirconolite and have developed a new way to analyse the damaged structure in terms of local coordination statistics. On the basis of this analysis, we find that the amorphous structure responds to radiation damage differently from the crystal. Amorphous zirconolite is found to be "softer" than crystalline zirconolite with a much larger number of atoms becoming displaced and changing coordination during a 70 keV cascade. The local coordination and connectivity analysis shows that the amorphous structure continues to evolve as a result of repeated radiation damage, changes which cannot be identified from globally averaged properties such as pair distribution functions. We also find large density inhomogeneities at the local level which we suggest may play an important role for future developments in nuclear waste storage. Finally, we find a correlation between the changes in enthalpy and local coordination, suggesting that measurements of enthalpy change can be linked quantitatively to structural radiation damage. Our results raise an interesting possibility of whether an evolution of the amorphous structure due to radiation damage can converge to a new equilibrium amorphous regime, posing the fundamental question of what that structure may be.

cond-mat.mtrl-sci↗