Machine Learning with Enormous “Synthetic” Data Sets: Predicting Glass Transition Temperature of Polyimides Using Graph Convolutional Neural Networks

Accurate Prediction of Aqueous Free Solvation Energies Using 3D Atomic Feature-Based Graph Neural Network with Transfer Learning

(2022) Dongdong Zhang et al.   Journal of Chemical Information and Modeling

Evaluation of Deep Learning Architectures for Aqueous Solubility Prediction

(2022) Gihan Panapitiya et al.   ACS Omega

Transfer learning with graph neural networks for optoelectronic properties of conjugated oligomers

(2021) Chee-Kong Lee et al.   JOURNAL OF CHEMICAL PHYSICS

Transfer learning for solvation free energies: From quantum chemistry to experiments

(2021) Florence H. Vermeire et al.   CHEMICAL ENGINEERING JOURNAL

Benchmarking Machine Learning Models for Polymer Informatics: An Example of Glass Transition Temperature

(2021) Lei Tao et al.   Journal of Chemical Information and Modeling

Knowledge-Embedded Message-Passing Neural Networks: Improving Molecular Property Prediction with Human Knowledge

(2021) Tatsuya Hasebe   ACS Omega

Machine-Learning-Assisted De Novo Design of Organic Molecules and Polymers: Opportunities and Challenges

(2020) Guang Chen et al.   Polymers

Opportunities and Challenges for Machine Learning in Materials Science

(2020) Dane Morgan et al.   Annual Review of Materials Research

Developing an improved crystal graph convolutional neural network framework for accelerated materials discovery

(2020) Cheol Woo Park et al.   Physical Review Materials

Predicting Crystallization Tendency of Polymers Using Multifidelity Information Fusion and Machine Learning

(2020) Shruti Venkatram et al.   JOURNAL OF PHYSICAL CHEMISTRY B

A Comprehensive Survey on Transfer Learning

(2020) Fuzhen Zhuang et al.   PROCEEDINGS OF THE IEEE

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

(2019) Chi Chen et al.   CHEMISTRY OF MATERIALS

Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining

(2019) Mohammad Atif Faiz Afzal et al.   Journal of Physical Chemistry C

Message-passing neural networks for high-throughput polymer screening

(2019) Peter C. St. John et al.   JOURNAL OF CHEMICAL PHYSICS

Accurate Thermochemistry with Small Data Sets: A Bond Additivity Correction and Transfer Learning Approach

(2019) Colin A. Grambow et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm

(2019) Stephen Wu et al.   npj Computational Materials

Big Data Creates New Opportunities for Materials Research: A Review on Methods and Applications of Machine Learning for Materials Design

(2019) Teng Zhou et al.   Engineering

Machine-Learning-Based Predictive Modeling of Glass Transition Temperatures: A Case of Polyhydroxyalkanoate Homopolymers and Copolymers

(2019) Ghanshyam Pilania et al.   Journal of Chemical Information and Modeling

Rapid and Accurate Prediction of pKa Values of C–H Acids Using Graph Convolutional Neural Networks

(2019) Rafał Roszak et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning

(2019) Dipendra Jha et al.   Nature Communications

A multi-fidelity information-fusion approach to machine learn and predict polymer bandgap

(2019) Abhirup Patra et al.   COMPUTATIONAL MATERIALS SCIENCE

Graph Convolutional Neural Networks as “General-Purpose” Property Predictors: The Universality and Limits of Applicability

(2019) Vadim Korolev et al.   Journal of Chemical Information and Modeling

Polymer Genome: A Data-Powered Polymer Informatics Platform for Property Predictions

(2018) Chiho Kim et al.   Journal of Physical Chemistry C

Building and deploying a cyberinfrastructure for the data-driven design of chemical systems and the exploration of chemical space

(2018) Johannes Hachmann et al.   MOLECULAR SIMULATION

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

(2018) Tian Xie et al.   PHYSICAL REVIEW LETTERS

Impact of dataset uncertainties on machine learning model predictions: the example of polymer glass transition temperatures

(2018) Anurag Jha et al.   MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING

Scale-Dependent Miscibility of Polylactide and Polyhydroxybutyrate: Molecular Dynamics Simulations

(2017) Artyom D. Glova et al.   MACROMOLECULES

Influence of specific intermolecular interactions on the thermal and dielectric properties of bulk polymers: atomistic molecular dynamics simulations of Nylon 6

(2017) N. V. Lukasheva et al.   Soft Matter

Polymer Informatics: Opportunities and Challenges

(2017) Debra J. Audus et al.   ACS Macro Letters

Molecular graph convolutions: moving beyond fingerprints

(2016) Steven Kearnes et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

A new approach for assessment of glass transition temperature of acrylic and methacrylic polymers from structure of their monomers without using any computer codes

(2016) Mohammad Hossein Keshavarz et al.   JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY

ImageNet Large Scale Visual Recognition Challenge

(2015) Olga Russakovsky et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Parameterization of electrostatic interactions for molecular dynamics simulations of heterocyclic polymers

(2015) Victor M. Nazarychev et al.   JOURNAL OF POLYMER SCIENCE PART B-POLYMER PHYSICS

PubChem Substance and Compound databases

(2015) Sunghwan Kim et al.   NUCLEIC ACIDS RESEARCH

The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies

(2015) Scott Kirklin et al.   npj Computational Materials

The database “Gas Separation Properties of Glassy Polymers” (Topchiev Institute): Capabilities and prospects

(2014) A. Alentiev et al.   PETROLEUM CHEMISTRY

Quantum chemistry structures and properties of 134 kilo molecules

(2014) Raghunathan Ramakrishnan et al.   Scientific Data

Thermal properties of bulk polyimides: insights from computer modeling versus experiment

(2013) Sergey V. Lyulin et al.   Soft Matter

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

(2013) Anubhav Jain et al.   APL Materials

Prediction of glass transition temperatures for polystyrenes from cyclic dimer structures using artificial neural networks

(2012) Jie Xu et al.   FIBERS AND POLYMERS

Novel descriptors from main and side chains of high-molecular-weight polymers applied to prediction of glass transition temperatures

(2012) Damián Palomba et al.   JOURNAL OF MOLECULAR GRAPHICS & MODELLING

Prediction of glass transition temperatures of aromatic heterocyclic polyimides using an ANN model

(2010) Wanqiang Liu   POLYMER ENGINEERING AND SCIENCE

Molecular dynamics simulations of glassy polymers

(2010) Jean-Louis Barrat et al.   Soft Matter

Artificial neural network prediction of glass transition temperature of polymers

(2009) Wanqiang Liu et al.   COLLOID AND POLYMER SCIENCE

A Review on Methods and Theories to Describe the Glass Transition Phenomenon: Applications in Food and Pharmaceutical Products

(2009) M. G. Abiad et al.   Food Engineering Reviews