arXiv:2606. 28578v1 Announce Type: cross Abstract: Closed-loop materials discovery iterates between proposing candidate structures and evaluating their properties, and property evaluation dominates the cost.
By Sk Md Ahnaf Akif Alvi, Jan Janssen, Danny Perez, Douglas Allaire, Raymundo Arroyave
arXiv:2607. 29225v1 Announce Type: new Abstract: Bayesian Optimization (BO) is widely adopted for data-efficient optimization in scientific and engineering applications, yet its computational cost is rarely evaluated alongside optimization performance.
By Panagiotis Krokidas, Christoforos Rekatsinas, Vassilis Sioros, Grigorios M. Chatziathanasiou, Efi-Maria Papia, George Giannakopoulos
arXiv:2510. 07474v2 Announce Type: replace Abstract: When designing new materials, it is often necessary to design a material with specific desired properties.
By Shaan Pakala, Aldair E. Gongora, Brian Giera, Evangelos E. Papalexakis
PhysicsBench is a unified benchmark and leaderboard that evaluates both generative and predictive AI models for engineering design and simulation under a single standardized procedure. It covers seven generation and prediction tasks across 1D, 2D, and 3D domains, ranking 66 models on nine industrial‑scale CAD/CFD/FEA datasets and public references, expanded into 28 configurations. The evaluation uses realistic, limited data scales and a common metric suite that captures geometric fidelity, physical‑field accuracy, and engineering‑specific validity, with rankings derived via a PageRank‑based dominance graph and a separate efficiency view.
By Sang Won Lee, Hyogu Jeong, Namwoo Kang
The paper introduces PRISMS, a framework that uses expert pairwise rankings of varying fidelity to curate scientific designs without relying on data-intensive regression models. By escalating queries from lower- to higher-fidelity rankers based on Fisher-information, PRISMS improves discovery recall and reduces the number of screening rounds compared to regression-only and non‑escalated ranking methods. In optimization tasks, PRISMS outperforms Bayesian optimization by achieving higher hypervolume.
By Kevin Tirta Wijaya, Alston Lo, Michael Sun, Wojciech Matusik, Vahid Babaei
arXiv:2607. 13688v1 Announce Type: new Abstract: Emerging sustainable materials increasingly rely on engineered hierarchy and microstructure to achieve control of their properties and mechanical behavior.
By J. Storm, I. B. C. M. Rocha, S. Schyck, K. Masania, F. P. van der Meer