348 citations · 1k across the 41 of their papers we have counts for
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Graph Convolutional Neural Networks for Polymers Property Prediction
Minggang Zeng, Jatin Nitin Kumar, Zeng Zeng +3
A fast and accurate predictive tool for polymer properties is demanding and will pave the way to iterative inverse design. In this work, we apply graph convolutional neural network…
Predicting thermoelectric properties from crystal graphs and material descriptors - first application for functional materials
Leo Laugier, Daniil Bash, Jose Recatala +5
We introduce the use of Crystal Graph Convolutional Neural Networks (CGCNN), Fully Connected Neural Networks (FCNN) and XGBoost to predict thermoelectric properties. The dataset fo…
Polymer morphology and interfacial charge transfer dominate over energy-dependent scattering in organic-inorganic thermoelectrics
Pawan Kumar, Edmond W. Zaia, Erol Yildirim +4
Hybrid (organic-inorganic) materials have emerged as a promising class of thermoelectric materials, achieving power factors exceeding those of either constituent. The mechanism of…
Probing physical origin of anisotropic thermal transport in black phosphorus nanoribbons
Yunshan Zhao, Gang Zhang, Mui Hoon Nai +9
Black phosphorus (BP) has emerged as a promising candidate for next generation electronics and optoelectronics among the 2D family materials due to its extraordinary electrical/opt…
Accelerating Materials Development via Automation, Machine Learning, and High-Performance Computing
Juan Pablo Correa-Baena, Kedar Hippalgaonkar, Jeroen van Duren +6
Successful materials innovations can transform society. However, materials research often involves long timelines and low success probabilities, dissuading investors who have expec…