Band Gap

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

6 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

29 shown of 29 papers with code (60 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Using Scalable Computer Vision to Automate High-throughput Semiconductor Characterization
  16 Mar 2023 2 repositories listed
  High-throughput materials synthesis methods have risen in popularity due to their potential to accelerate the design and discovery of novel functional materials, such as solution-processed semiconductors.
• Periodic Graph Transformers for Crystal Material Property Prediction
  23 Sep 2022 2 repositories listed Syntology ran 4 of 9 samples · 5 unverified
  Our Matformer is designed to be invariant to periodicity and can capture repeating patterns explicitly.
• Active learning based generative design for the discovery of wide bandgap materials
  28 Feb 2021 2 repositories listed
  Our experiments show that while active learning itself may sample chemically infeasible candidates, these samples help to train effective screening models for filtering out materials with desired properties from the…
• MatMMFuse: Multi-Modal Fusion model for Material Property Prediction
  30 Apr 2025 1 repository listed Syntology ran 1 of 2 samples · 1 unverified
  In this work, we propose Material Multi-Modal Fusion(MatMMFuse), a fusion based model which uses a multi-head attention mechanism for the combination of structure aware embedding from the Crystal Graph Convolution…
• CrystalFormer-RL: Reinforcement Fine-Tuning for Materials Design
  3 Apr 2025 1 repository listed Syntology ran 2 of 3 samples · 1 unverified · 2 pointer-only (licence)
  Reinforcement fine-tuning has instrumental enhanced the instruction-following and reasoning abilities of large language models.
• A Cartesian Encoding Graph Neural Network for Crystal Structures Property Prediction: Application to Thermal Ellipsoid Estimation
  30 Jan 2025 1 repository listed
  In diffraction-based crystal structure analysis, thermal ellipsoids, quantified via Anisotropic Displacement Parameters (ADPs), are critical yet challenging to determine.
• Text to Band Gap: Pre-trained Language Models as Encoders for Semiconductor Band Gap Prediction
  7 Jan 2025 1 repository listed
  In this study, we explore the use of a transformer-based language model as an encoder to predict the band gaps of semiconductor materials directly from their text descriptions.
• Establishing baselines for generative discovery of inorganic crystals
  4 Jan 2025 1 repository listed Syntology ran 0 of 4 samples · 4 unverified
  Generative artificial intelligence offers a promising avenue for materials discovery, yet its advantages over traditional methods remain unclear.
• Rethinking Gradient-Based Methods: Multi-Property Materials Design Beyond Differentiable Targets
  11 Oct 2024 1 repository listed
  Gradient-based methods offer a simple, efficient strategy for materials design by directly optimizing candidates using gradients from pretrained property predictors.
• SciQu: Accelerating Materials Properties Prediction with Automated Literature Mining for Self-Driving Laboratories
  11 Jul 2024 1 repository listed
  As a proof of concept, we predicted the refractive index of materials using data extracted from numerous research articles with SciQu, considering input descriptors such as space group, volume, and bandgap with Root…
• Establishing Deep InfoMax as an effective self-supervised learning methodology in materials informatics
  30 Jun 2024 1 repository listed
  This allows the pretraining of supervised models on large materials datasets without the need for property labels and without requiring the model to reconstruct the crystal from a representation vector.
• Dielectric Tensor Prediction for Inorganic Materials Using Latent Information from Preferred Potential
  15 May 2024 1 repository listed
  Dielectrics are crucial for technologies like flash memory, CPUs, photovoltaics, and capacitors, but public data on these materials are scarce, restricting research and development.
• Pushing the Pareto front of band gap and permittivity: ML-guided search for dielectric materials
  11 Jan 2024 1 repository listed
  Meanwhile, we report the first high-purity synthesis and dielectric characterization of Bi2Zr2O7 with a band gap of 2.
• LLM-Prop: Predicting Physical And Electronic Properties Of Crystalline Solids From Their Text Descriptions
  21 Oct 2023 1 repository listed Syntology ran 0 of 2 samples · 2 unverified
  The prediction of crystal properties plays a crucial role in the crystal design process.
• Band-gap regression with architecture-optimized message-passing neural networks
  12 Sep 2023 1 repository listed
  The domain of applicability of the ensemble model is analyzed with respect to the crystal systems, the inclusion of a Hubbard parameter in the density functional calculations, and the atomic species building up the…
• Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction
  12 Jun 2023 1 repository listed
  This is enabled by our approximations of infinite potential summations, where we extend the Ewald summation for several potential series approximations with provable error bounds.
• Materials Property Prediction with Uncertainty Quantification: A Benchmark Study
  4 Nov 2022 1 repository listed
  Uncertainty quantification (UQ) has increasing importance in building robust high-performance and generalizable materials property prediction models.
• OQM9HK: A Large-Scale Graph Dataset for Machine Learning in Materials Science
  30 Sep 2022 1 repository listed
  We introduce a large-scale dataset of quantum-mechanically calculated properties of crystalline materials for graph representation learning that contains approximately 900k entries (OQM9HK).
• Random projections and Kernelised Leave One Cluster Out Cross-Validation: Universal baselines and evaluation tools for supervised machine learning for materials properties
  17 Jun 2022 1 repository listed
  We also find that the radial basis function improves the linear separability of chemical datasets in all 10 datasets tested and provide a framework for the application of this function in the LOCO-CV process to improve…
• Element selection for functional materials discovery by integrated machine learning of elemental contributions to properties
  2 Feb 2022 1 repository listed
  Before specific differences emerge according to the precise ratios of elements in a given crystal structure, a material can be represented by the set of its constituent chemical elements.
• How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning
  10 Nov 2021 1 repository listed
  Machine learning models can assist with metamaterials design by approximating computationally expensive simulators or solving inverse design problems.
• Scalable deeper graph neural networks for high-performance materials property prediction
  25 Sep 2021 1 repository listed
  Machine learning (ML) based materials discovery has emerged as one of the most promising approaches for breakthroughs in materials science.
• Distributed Representations of Atoms and Materials for Machine Learning
  30 Jul 2021 1 repository listed
  To build effective models of the chemistry of materials, useful machine-based representations of atoms and their compounds are required.
• Inverse design of two-dimensional materials with invertible neural networks
  6 Jun 2021 1 repository listed
  The ability to readily design novel materials with chosen functional properties on-demand represents a next frontier in materials discovery.
• Learning Extremal Representations with Deep Archetypal Analysis
  3 Feb 2020 1 repository listed
  The real-world applicability of the proposed method is demonstrated by exploring archetypes of female facial expressions while using multi-rater based emotion scores of these expressions as side information.
• Deep-Learning Estimation of Band Gap with the Reading-Periodic-Table Method and Periodic Convolution Layer
  16 Nov 2019 1 repository listed
  Deep Learning Model for Finding New Superconductors, which utilizes deep learning to read the periodic table and the laws of the elements, is applicable not only for superconductors, for which the method was originally…
• Crystal Graph Neural Networks for Data Mining in Materials Science
  27 May 2019 1 repository listed
  This paper proposes crystal graph neural networks (CGNNs) that use no bond distances, and introduces a scale-invariant graph coordinator that makes up crystal graphs for the CGNN models to be trained on the dataset…
• MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction
  14 Nov 2018 1 repository listed
  Some of the major challenges involved in developing such models are, (i) limited availability of materials data as compared to other fields, (ii) lack of universal descriptor of materials to predict its various…
• Band gap prediction for large organic crystal structures with machine learning
  30 Oct 2018 1 repository listed
  Machine-learning models are capable of capturing the structure-property relationship from a dataset of computationally demanding ab initio calculations.

Syntology lines on 5 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.