Datasets & Benchmarks

ScientificML

A public dataset for partial differential equation modeling, providing data resources for physics-field simulation and machine learning model training.

Electromagnetics

LithoBench-PDE is a benchmark dataset for PDE learning in computational lithography, providing high-fidelity 3D reference simulations and intermediate 2D/3D field data for photomasks.

Materials

HetCat26 provides benchmark tests for assessing the transferability of pre-trained machine learning interatomic potentials across key aspects of heterogeneous catalytic modeling.

ScientificML

PDE-OBS provides complete numerical solutions for seven families of partial differential equations in the PDE-OBS benchmark, including stationary Darcy, Poisson, and Helmholtz equations and heat-related PDEs.

ScientificML

A downloadable model resource centered on partial differential equation modeling for scientific computing applications, with the exact physical domain and methodology left unspecified in the source. The repository name is the only substantive detail provided.

ScientificML

A question-and-answer dataset centered on physics, providing examples for data preparation, learning, and evaluation workflows in Physics AI. The resource is hosted on Hugging Face and identifies Qwen3.5 in its dataset name.

Electromagnetics

FSSDataBase provides 5,000 procedurally generated single- and multilayer frequency-selective surface unit cells with simulated electromagnetic transmission and reflection responses for data-driven design.

ScientificML

A benchmark dataset of complete numerical solutions for seven PDE families including Darcy, Poisson, and Helmholtz, generated by the benchmark's own solvers for scientific ML model evaluation.

Materials

A technical Q&A dataset covering fundamental and advanced topics in materials science, including material properties, synthesis methods, characterization techniques, and engineering applications, designed for training technical response models.

ScientificML

A benchmark dataset for PDE surrogate tasks within the ai4sci-tasks evaluation framework, containing training trajectories and evaluation splits for assessing neural operator and surrogate modeling performance.

Multibody

Proposes specification-conditioned human demonstration collection for embodied AI in construction, bridging the gap between design model configurations and physical environments.

Materials

A materials science dataset hosted on HuggingFace, supporting machine learning and materials science cross-disciplinary research, containing relevant domain training or evaluation samples.

CFD

A 36M-parameter UNet-based model for solving Navier-Stokes equations using a point-wise coupling strategy for high-accuracy flow field prediction.

CFD

A dataset of 2000 steady-state CFD simulations for a liquid-cooled dual-chip pin-fin cold plate, accompanied by a POD-NN surrogate model and code to reproduce all figures in the associated paper.

ScientificML

A HuggingFace dataset repository related to PDE interpolants, supporting research at the intersection of physics modeling and machine learning.

ScientificML

A provenance-bearing benchmark for verifying symbolic candidate solutions to PDEs, containing 20 records with generator outputs, verification cases, and human annotations for assessing symbolic solver reliability.

ScientificML

A PDE evaluation dataset containing 32 physical systems, each with four representations: source code, natural-language description, governing equation, and numerical trajectory, with both correct and corrupted variants.

ScientificML

A code perturbation dataset with 256 PDE solver implementations comprising 64 base programs and 4 lexical perturbation variants each, designed for evaluating LLM understanding of physics simulation code.

ScientificML

Simulation training datasets for PDE control containing 3000 controlled trajectories generated by classical numerical solvers under randomly sampled control sequences, designed for training TI-DeepONet surrogate models.

Physics-Informed Neural Networks

A HuggingFace repository containing a potential flow PINN clustering model, providing physics-informed neural network resources for potential flow modeling.