KIM REVIEW
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Commentaries on key articles in the domain of classical molecular simulations. Target articles represent critical new or foundational contributions to the field. www.kimreview.org
Ice in a tube: new phases of water at the nanoscale and a solid–liquid critical point A commentary by Erik E. Santiso on Koga, Gao, Tanaka & Zeng (Nature, 412:802–805 (2001)), presenting the contributions of a landmark paper in molecular simulations kimreview.org/commentaries...
Event-Chain Monte Carlo: The global-balance breakthrough A commentary by E.A.J.F. (Frank) Peters on Bernard, Krauth and Wilson (Phys. Rev. E, 80:056704 (2009)): How a surprising specific result (ECMC) developed into a powerful general class of sampling algorithms. kimreview.org/commentaries...
Path Sampling for Rare Events Boosted by Machine Learning Porhouy Minh & Sapna Sarupria on Jung et al. (Nat. Comput. Sci. (2023)) Minh & Sarupria discuss and analyze the AIMMD (AI for Molecular Mechanism Discovery) framework—its extensions, impact and limitations. kimreview.org/commentaries...
The Transformative Capability of Quantum-Accurate Machine Learning Interatomic Potentials Alfredo Correa and Sebastien Hamel on Nguyen et al. (J Phys Chem Lett 2024), and contributions to research on atomic interactions under extreme pressure and temperature conditions kimreview.org/commentaries...
From GAP to ACE to MACE Noam Bernstein on extensions to the Gaussian approximation potential (GAP) formalism, as well as atomic cluster expansion and multilayer NN extension-based frameworks that maintain the good features and mitigate the limitations of the GAP approach. doi.org/10.25950/67c...
Present and future of atomistic simulations of dislocation plasticity F Maresca, E van der Giessen On Zepeda-Ruiz et al. (Nat. Mater. 2021): what ultra-large-scale atomistic simulations can teach us about plastic deformation of metallic single crystals... kimreview.org/commentaries...
Boltzmann Generators and the New Frontier of Computational Sampling in Many-Body Systems A Coretti, S Falkner, J Weinreich, C Dellago, O A von Lilienfeld On Noé et al. (Science, 2021) and the necessity for a new generation of sampling methods beyond molecular dynamics kimreview.org/commentaries...
Ultra-sensitive binding response by Stefano Angioletti-Uberti, Tine Curk On the physical origins of superselectivity and how combinatorial entropy provides a fruitful point of view to understand ultra-sensitive responses involving multivalent agents kimreview.org/commentaries...
ParSplice: strong exa-scaling of molecular dynamics ParSplice is a molecular dynamics method for parallel-in-time trajectory generation, allowing this workhorse of in silico science to strong scale on massively parallel computers... kimreview.org/commentaries...
On the Atomic Cluster Expansion: interatomic potentials and beyond ACE is being used extensively in newly emerging interatomic potentials based on machine learning. This commentary discusses the ACE framework and its potential impact. kimreview.org/commentaries...
