Materials science optimization benchmark dataset for multi-objective, multi-fidelity optimization of hard-sphere packing simulations.

ABSTRACT: In scientific disciplines, benchmarks play a vital role in driving progress forward. For a benchmark to be effective, it must closely resemble real-world tasks. If the level of difficulty or relevance is inadequate, it can impede progress in the field. Moreover, benchmarks should have low computational overhead to ensure accessibility and repeatability. The objective is to achieve a kind of ``Turing test'' by creating a surrogate model that is practically indistinguishable from the ground truth observation, at least within the dataset's explored boundaries. This objective necessitates a large quantity of data. This data encompasses numerous features that are characteristic of chemistry and materials science optimization tasks that are relevant to industry. These features include high level

SUBMITTER: Baird SG 

PROVIDER: S-EPMC10465850 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature