Construction of high accuracy machine learning interatomic potential for surface/interface of nanomaterials—A review

K Wan, J He, X Shi - Advanced Materials, 2024 - Wiley Online Library
The inherent discontinuity and unique dimensional attributes of nanomaterial surfaces and
interfaces bestow them with various exceptional properties. These properties, however, also …

Frontiers of molecular crystal structure prediction for pharmaceuticals and functional organic materials

GJO Beran - Chemical Science, 2023 - pubs.rsc.org
The reliability of organic molecular crystal structure prediction has improved tremendously in
recent years. Crystal structure predictions for small, mostly rigid molecules are quickly …

The first-principles phase diagram of monolayer nanoconfined water

V Kapil, C Schran, A Zen, J Chen, CJ Pickard… - Nature, 2022 - nature.com
Water in nanoscale cavities is ubiquitous and of central importance to everyday phenomena
in geology and biology. However, the properties of nanoscale water can be substantially …

Molecular simulation approaches to study crystal nucleation from solutions: Theoretical considerations and computational challenges

AR Finney, M Salvalaglio - Wiley Interdisciplinary Reviews …, 2024 - Wiley Online Library
Nucleation is the initial step in the formation of crystalline materials from solutions. Various
factors, such as environmental conditions, composition, and external fields, can influence its …

A hybrid machine learning approach for structure stability prediction in molecular co-crystal screenings

S Wengert, G Csányi, K Reuter… - Journal of Chemical …, 2022 - ACS Publications
Co-crystals are a highly interesting material class as varying their components and
stoichiometry in principle allows tuning supramolecular assemblies toward desired physical …

Data-efficient fine-tuning of foundational models for first-principles quality sublimation enthalpies

H Kaur, F Della Pia, I Batatia, XR Advincula… - Faraday …, 2025 - pubs.rsc.org
Calculating sublimation enthalpies of molecular crystal polymorphs is relevant to a wide
range of technological applications. However, predicting these quantities at first-principles …

Free energy predictions for crystal stability and synthesisability

K Tolborg, J Klarbring, AM Ganose, A Walsh - Digital Discovery, 2022 - pubs.rsc.org
What is the likelihood that a hypothetical material—the combination of a composition and
crystal structure—can be formed? Underpinning the reliability of predictions for local or …

How accurate are simulations and experiments for the lattice energies of molecular crystals?

F Della Pia, A Zen, D Alfè, A Michaelides - Physical Review Letters, 2024 - APS
Molecular crystals play a central role in a wide range of scientific fields, including
pharmaceuticals and organic semiconductor devices. However, they are challenging …

Hybrid classical/machine-learning force fields for the accurate description of molecular condensed-phase systems

M Thürlemann, S Riniker - Chemical Science, 2023 - pubs.rsc.org
Electronic structure methods offer in principle accurate predictions of molecular properties,
however, their applicability is limited by computational costs. Empirical methods are …

Improving sample and feature selection with principal covariates regression

RK Cersonsky, BA Helfrecht, EA Engel… - Machine Learning …, 2021 - iopscience.iop.org
Selecting the most relevant features and samples out of a large set of candidates is a task
that occurs very often in the context of automated data analysis, where it improves the …