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Five High-Impact Research Areas in Machine Learning for Materials Science
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Gas Permeation Properties, Physical Aging, and Its Mitigation in High Free Volume Glassy Polymers
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May 2018 |
Neural networks for the prediction of polymer permeability to gases
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November 2017 |
Deep learning
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Computer Simulations of Ion Transport in Polymer Electrolyte Membranes
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June 2016 |
Prediction of Organic Reaction Outcomes Using Machine Learning
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April 2017 |
Morphology of multi-component polymer systems: single chain in mean field simulation studies
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January 2006 |
Mechanical and Structural Characterization of Semicrystalline Polyethylene under Tensile Deformation by Molecular Dynamics Simulations
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June 2015 |
Mechanical properties of individual electrospun PA 6(3)T fibers and their variation with fiber diameter
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May 2011 |
Advanced polymeric dielectrics for high energy density applications
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October 2016 |
Optimization of Antibacterial Peptides by Genetic Algorithms and Cheminformatics: Optimizing Antibacterial Peptides
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October 2010 |
A slip-link model for rheology of entangled polymer melts with crystallization
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January 2020 |
Designing exceptional gas-separation polymer membranes using machine learning
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May 2020 |
Fast, accurate, and transferable many-body interatomic potentials by symbolic regression
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November 2019 |
Sequence dependent interaction of single stranded DNA with graphitic flakes: atomistic molecular dynamics simulations
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February 2016 |
Genetic programming for experimental big data mining: A case study on concrete creep formulation
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October 2016 |
Boosting Quantum Machine Learning Models with a Multilevel Combination Technique: Pople Diagrams Revisited
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December 2018 |
Polymer Informatics: Opportunities and Challenges
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September 2017 |
Materials discovery and design using machine learning
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September 2017 |
Uncovering electron scattering mechanisms in NiFeCoCrMn derived concentrated solid solution and high entropy alloys
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January 2019 |
Electronic Structure of Polymer Dielectrics: The Role of Chemical and Morphological Complexity
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October 2018 |
Refractive indices of diverse data set of polymers: A computational QSPR based study
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September 2017 |
Ion Conductivity and Correlations in Model Salt-Doped Polymers: Effects of Interaction Strength and Concentration
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May 2020 |
Predicting the thermal conductivity of inorganic and polymeric glasses: The role of anharmonicity
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February 2009 |
Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning
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October 2017 |
Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
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January 2018 |
Highly stable doping of a polar polythiophene through co-processing with sulfonic acids and bistriflimide
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January 2018 |
Is Multitask Deep Learning Practical for Pharma?
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August 2017 |
Rational Co-Design of Polymer Dielectrics for Energy Storage
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May 2016 |
Advanced Dielectrics for Capacitors
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January 2006 |
Molecular graph convolutions: moving beyond fingerprints
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August 2016 |
Predicting Crystallization Tendency of Polymers Using Multifidelity Information Fusion and Machine Learning
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June 2020 |
Active-learning and materials design: the example of high glass transition temperature polymers
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June 2019 |
ChemDataExtractor: A Toolkit for Automated Extraction of Chemical Information from the Scientific Literature
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October 2016 |
Making AI More Human
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May 2017 |
Reproducible and Scalable Synthesis of End-Cap-Functionalized Depolymerizable Poly(phthalaldehydes)
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April 2013 |
Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach
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April 2015 |
Designing High-Refractive Index Polymers Using Materials Informatics
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January 2018 |
A polymer dataset for accelerated property prediction and design
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March 2016 |
Multifidelity Information Fusion with Machine Learning: A Case Study of Dopant Formation Energies in Hafnia
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April 2019 |
Electronic Structure of Polyethylene: Role of Chemical, Morphological and Interfacial Complexity
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July 2017 |
Quantitative Structure–Property Relationship Modeling of Diverse Materials Properties
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January 2012 |
BigSMILES: A Structurally-Based Line Notation for Describing Macromolecules
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September 2019 |
Multi-fidelity machine learning models for accurate bandgap predictions of solids
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March 2017 |
Computational strategies for polymer dielectrics design
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February 2014 |
Deep materials informatics: Applications of deep learning in materials science
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June 2019 |
Molecular Simulation of Thermoplastic Polyurethanes under Large Compressive Deformation
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November 2018 |
Recent advances and applications of machine learning in solid-state materials science
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August 2019 |
Artificial neural network prediction of glass transition temperature of polymers
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May 2009 |
Electrochemical Stability Window of Polymeric Electrolytes
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September 2019 |
Machine Learning Strategy for Accelerated Design of Polymer Dielectrics
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February 2016 |
Polymer Structure Prediction from First Principles
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July 2020 |
Flexible high-temperature dielectric materials from polymer nanocomposites
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July 2015 |
Solid polymer electrolytes: materials designing and all-solid-state battery applications: an overview
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October 2008 |
A Dielectric Polymer with High Electric Energy Density and Fast Discharge Speed
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July 2006 |
Predicting Materials Properties with Little Data Using Shotgun Transfer Learning
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September 2019 |
Prediction of polymer properties using infinite chain descriptors (ICD) and machine learning: Toward optimized dielectric polymeric materials
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August 2016 |
The upper bound revisited
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July 2008 |
Dynamic and Static Mechanical Properties of Crosslinked Polymer Matrices: Multiscale Simulations and Experiments
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July 2018 |
Machine-learning-driven discovery of polymers molecular structures with high thermal conductivity
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December 2020 |
Polymer Capacitor Dielectrics for High Temperature Applications
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July 2018 |
A polymer dataset for accelerated property prediction and design
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Engineering Polymer Informatics: Towards the Computer-Aided Design of Polymers
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Toward Designing Highly Conductive Polymer Electrolytes by Machine Learning Assisted Coarse-Grained Molecular Dynamics
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April 2020 |
On the Art of Compiling and Using 'Drug-Like' Chemical Fragment Spaces
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October 2008 |
A Kriging-Based Approach to Autonomous Experimentation with Applications to X-Ray Scattering
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August 2019 |
Simulations on the Thermal Decomposition of a Poly(dimethylsiloxane) Polymer Using the ReaxFF Reactive Force Field
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May 2005 |
Extended-Connectivity Fingerprints
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April 2010 |
Targeted gas separations through polymer membrane functionalization
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January 2015 |
A Deep Learning Solvent-Selection Paradigm Powered by a Massive Solvent/Nonsolvent Database for Polymers
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June 2020 |
Accelerated materials property predictions and design using motif-based fingerprints
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July 2015 |
High-performance solid polymer electrolytes for lithium batteries operational at ambient temperature
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December 2015 |
Text-mined dataset of inorganic materials synthesis recipes
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January 2019 |
ChemicalTagger: A tool for semantic text-mining in chemistry
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May 2011 |
Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
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February 2015 |
Critical Assessment of the Hildebrand and Hansen Solubility Parameters for Polymers
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September 2019 |
A robotic platform for flow synthesis of organic compounds informed by AI planning
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August 2019 |
Unsupervised word embeddings capture latent knowledge from materials science literature
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July 2019 |
Effect of chemical structure on thermo-mechanical properties of epoxy polymers: Comparison of accelerated ReaxFF simulations and experiments
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December 2018 |
Active learning in materials science with emphasis on adaptive sampling using uncertainties for targeted design
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February 2019 |
Molecular Dynamics Calculations of the Thermal Conductivity of Molecular Liquids, Polymers, and Carbon Nanotubes
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January 2012 |
Text-mined dataset of inorganic materials synthesis recipes
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October 2019 |
Gas separation using polymer membranes: an overview
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November 1994 |
Development of an Accurate Coarse-Grained Model of Poly(acrylic acid) in Explicit Solvents
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June 2019 |
Machine learning in materials informatics: recent applications and prospects
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December 2017 |
The effect of point mutations on structure and mechanical properties of collagen-like fibril: A molecular dynamics study
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December 2012 |
Machine-Learning-Based Predictive Modeling of Glass Transition Temperatures: A Case of Polyhydroxyalkanoate Homopolymers and Copolymers
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November 2019 |
SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules
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February 1988 |
Computable Bulk and Interfacial Electronic Structure Features as Proxies for Dielectric Breakdown of Polymers
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July 2020 |
Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases
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March 2015 |
Role of Solvation on Diffusion of Ions in Diblock Copolymers: Understanding the Molecular Weight Effect through Modeling
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October 2019 |
Rational design of all organic polymer dielectrics
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September 2014 |
Neural networks and graph theory as computational tools for predicting polymer properties
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March 1994 |
Autonomous robotic searching and assembly of two-dimensional crystals to build van der Waals superlattices
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April 2018 |
Depolymerizable polymers: preparation, applications, and future outlook
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June 2015 |
Review on composite polymer electrolytes for lithium batteries
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July 2006 |
Effects of chemical defects on anisotropic dielectric response of polyethylene
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April 2019 |
Soft Matter Informatics: Current Progress and Challenges
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November 2018 |
Accelerated ReaxFF Simulations for Describing the Reactive Cross-Linking of Polymers
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July 2018 |
A charge density prediction model for hydrocarbons using deep neural networks
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March 2020 |
Support vector machine-based QSPR for the prediction of glass transition temperatures of polymers
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August 2010 |
Accelerating materials property predictions using machine learning
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September 2013 |
High dielectric constant conjugated materials for organic photovoltaics
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January 2017 |
Thermal Conductivity of Polyisoprene and Polybutadiene from Molecular Dynamics Simulations and Transient Measurements
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May 2020 |
Author Correction: Text-mined dataset of inorganic materials synthesis recipes
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November 2019 |
Machine learning approach for accurate backmapping of coarse-grained models to all-atom models
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January 2020 |
Designed to degrade
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November 2017 |
Machine learning enabled autonomous microstructural characterization in 3D samples
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January 2020 |
Perspective: NanoMine: A material genome approach for polymer nanocomposites analysis and design
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March 2016 |
Scoping the polymer genome: A roadmap for rational polymer dielectrics design and beyond
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September 2018 |
ChemSpot: a hybrid system for chemical named entity recognition
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April 2012 |
A multi-fidelity information-fusion approach to machine learn and predict polymer bandgap
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February 2020 |
Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders
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December 2020 |
A graph-convolutional neural network model for the prediction of chemical reactivity
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January 2019 |
Electrochemical Stability Window of Polymeric Electrolytes
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May 2019 |
Molecular Dynamics Simulation of Homogeneous Crystal Nucleation in Polyethylene
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May 2013 |
Polymer Genome: A Data-Powered Polymer Informatics Platform for Property Predictions
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July 2018 |
Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks
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December 2017 |
Autonomy in materials research: a case study in carbon nanotube growth
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October 2016 |
Machine-learning predictions of polymer properties with Polymer Genome
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November 2020 |
Polymer design using genetic algorithm and machine learning
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January 2021 |
A neural network approach to prediction of glass transition temperature of polymers
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January 2007 |
Machine learning: Trends, perspectives, and prospects
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July 2015 |
Merging Materials and Data Science: Opportunities, Challenges, and Education in Materials Informatics
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February 2020 |
Prediction of Glass Transition Temperatures for Polystyrenes by a Four-Descriptors QSPR Model
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January 2006 |
Predicting the output from a complex computer code when fast approximations are available
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March 2000 |
Planning chemical syntheses with deep neural networks and symbolic AI
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March 2018 |
Prediction model of band gap for inorganic compounds by combination of density functional theory calculations and machine learning techniques
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March 2016 |
Graph embedding on biomedical networks: methods, applications and evaluations
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October 2019 |