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Band Gap

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TitleStatusHype
MatMMFuse: Multi-Modal Fusion model for Material Property PredictionCode0
Design Topological Materials by Reinforcement Fine-Tuned Generative Model—0
CrystalFormer-RL: Reinforcement Fine-Tuning for Materials DesignCode2
Accurate predictive model of band gap with selected important features based on explainable machine learning—0
CAST: Cross Attention based multimodal fusion of Structure and Text for materials property prediction—0
Deep Neural Network for Phonon-Assisted Optical Spectra in Semiconductors—0
A Cartesian Encoding Graph Neural Network for Crystal Structures Property Prediction: Application to Thermal Ellipsoid EstimationCode1
Text to Band Gap: Pre-trained Language Models as Encoders for Semiconductor Band Gap PredictionCode0
Predicting band gap from chemical composition: A simple learned model for a material property with atypical statistics—0
Establishing baselines for generative discovery of inorganic crystalsCode1
AI-driven Inverse Design of Band-Tunable Mechanical Metastructures for Tailored Vibration Mitigation—0
Graph Transformer Networks for Accurate Band Structure Prediction: An End-to-End Approach—0
Assessing data-driven predictions of band gap and electrical conductivity for transparent conducting materials—0
Energy-GNoME: A Living Database of Selected Materials for Energy Applications—0
Rethinking Gradient-Based Methods: Multi-Property Materials Design Beyond Differentiable TargetsCode0
Evaluating the Performance and Robustness of LLMs in Materials Science Q&A and Property Predictions—0
Phononic materials with effectively scale-separated hierarchical features using interpretable machine learning—0
Enhancing material property prediction with ensemble deep graph convolutional networks—0
SciQu: Accelerating Materials Properties Prediction with Automated Literature Mining for Self-Driving LaboratoriesCode0
Establishing Deep InfoMax as an effective self-supervised learning methodology in materials informaticsCode0
A Shared-Aperture Dual-Band sub-6 GHz and mmWave Reconfigurable Intelligent Surface With Independent Operation—0
Dielectric Tensor Prediction for Inorganic Materials Using Latent Information from Preferred PotentialCode1
Estimation of Electronic Band Gap Energy From Material Properties Using Machine Learning—0
Pushing the Pareto front of band gap and permittivity: ML-guided search for dielectric materialsCode1
PyNanospacing: TEM image processing tool for strain analysis and visualization—0
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