Tim Rein | Searcharxiv

arXiv2026

Six Open Questions in Machine-Learned Interatomic Potential Foundation Models

Machine-learned interatomic potentials (MLIPs) have had a profound impact on molecular modelling in recent years, promising to resolve the long-standing tension between the scale and accuracy of simulations. There has been a proliferation of new models and designs, and recently the paradigm of ``foundational'' MLIPs has become prevalent. Broadly speaking, foundation models are trained on large diverse datasets and promise to work well for new systems with minimal updates required. However, in such a new and fast moving field, there are many unanswered questions. In this article, we set out to articulate and explore what we see as the most important among these questions. We start by developing a working definition for foundational MLIPs and use this definition to frame the subsequent open questions. Despite the rapid progress in the field of MLIP models, we believe that these are fundamental questions which will continue to define cutting edge research in MLIPs in the years to come.

cond-mat.mtrl-sci↗

arXiv2026

Correcting hybrid density functionals to model Y6 and other non-fullerene acceptors

Recently developed fused-ring electron-acceptors such as Y6 (BTP-4F) have strong oscillator strength, good charge-carrier transport and a small bandgap. They therefore have enormous current technical application to organic optoelectronics, such as solar cells. To design new materials, it would be useful to predict the electronic structure accurately. Due to the large number of atoms involved in representative aggregates of these materials, we need an efficient electronic structure method. Standard density functional theory poorly describes charge-transfer states, and were typically parameterised for vacuum calculations of individual molecules. In this work we tune a range-separated hybrid functional for Y6, and characterise representative dimers extracted from the solid-state. We demonstrate that the extensive solvatochromic effects of Y6 are due, in part, to oscillator strength borrowing between the charge-transfer and Frenkel excitons. We provide an explanation for the short optimally-tuned range-separation parameter, based on the Penn model for the frequency dependent dielectric of a semiconductor. We caution that non-tuned range-separated hybrids are less accurate than global hybrids for these, and similar, materials. We show how reducing the range-separation length improves the accuracy of standard range-separation functionals, without an involved tuning process.

cond-mat.mtrl-sci↗