TDCM25: A Multi-Modal Multi-Task Benchmark for Temperature-Dependent Crystalline Materials

Materials exhibit phase and temperature dependent properties that are critical for applications ranging from catalysis to energy storage and environmental remediation and accurate modeling of these dependencies requires high-quality, multi-modal datasets. In this work, TDCM25 (Temperature Dependent Crystalline Materials 2025) is introduced as a comprehensive dataset featuring approximately 100,000 entries spanning three crystalline phases of TiO$_2$ (anatase, brookite, and rutile) sampled over 21 temperatures from 0K to 1000K. Each entry comprises 3D atomic coordinates, corresponding RGB molecular images, and detailed textual metadata including Ti:O ratios, temperature, spatial dimensions, and transformation parameters. TDCM25 provides a benchmark for developing and evaluating machine learning methods that integrate multi-modal data to capture temperature dependent material behavior. The dataset is publicly available at https://github.com/KurbanIntelligenceLab/TDCM25.