Mining Materials Design Rules from Data: The Example of Polymer Dielectrics

Mannodi-Kanakkithodi, Arun; Huan, Tran Doan; Ramprasad, Rampi

doi:10.1021/acs.chemmater.7b02027

Title: Mining Materials Design Rules from Data: The Example of Polymer Dielectrics

Abstract

Mining of currently available and evolving materials databases to discover structure–chemistry–property relationships is critical to developing an accelerated materials design framework. The design of new and advanced polymeric dielectrics for capacitive energy storage has been hampered by the lack of sufficient data encompassing wide enough chemical spaces. Here, data mining and analysis techniques are applied on a recently presented computational data set of around 1100 organic polymers, organometallic polymers, and related molecular crystals, in order to obtain qualitative understanding of the origins of dielectric and electronic properties. By probing the relationships between crucial chemical and structural features of materials and their dielectric constant and band gap, design rules are devised for optimizing either property. Learning from this data set provides guidance to experiments and to future computations, as well as a way of expanding the pool of promising polymer candidates for dielectric applications.

Authors:

^[1]; Huan, Tran Doan ^[1]; Ramprasad, Rampi ^[1]

Univ. of Connecticut, Storrs, CT (United States)

Publication Date:: Tue Oct 03 00:00:00 EDT 2017

Research Org.:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1479688

Resource Type:: Accepted Manuscript

Journal Name:: Chemistry of Materials

Additional Journal Information:: Journal Volume: 29; Journal Issue: 21; Journal ID: ISSN 0897-4756

Publisher:: American Chemical Society (ACS)

Country of Publication:: United States

Language:: English

Subject:: 36 MATERIALS SCIENCE; Insulators; Metals; Organic polymers; Electrical properties; Polymers

Citation Formats


                    Mannodi-Kanakkithodi, Arun, Huan, Tran Doan, and Ramprasad, Rampi. Mining Materials Design Rules from Data: The Example of Polymer Dielectrics.  United States: N. p., 2017. 
Web.  doi:10.1021/acs.chemmater.7b02027.

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                    Mannodi-Kanakkithodi, Arun, Huan, Tran Doan, & Ramprasad, Rampi. Mining Materials Design Rules from Data: The Example of Polymer Dielectrics.  United States.  https://doi.org/10.1021/acs.chemmater.7b02027

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                    Mannodi-Kanakkithodi, Arun, Huan, Tran Doan, and Ramprasad, Rampi. Tue .  
"Mining Materials Design Rules from Data: The Example of Polymer Dielectrics".  United States.  https://doi.org/10.1021/acs.chemmater.7b02027.  https://www.osti.gov/servlets/purl/1479688.

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@article{osti_1479688,

  title        = {Mining Materials Design Rules from Data: The Example of Polymer Dielectrics},

  author       = {Mannodi-Kanakkithodi, Arun and Huan, Tran Doan and Ramprasad, Rampi},

  abstractNote = {Mining of currently available and evolving materials databases to discover structure–chemistry–property relationships is critical to developing an accelerated materials design framework. The design of new and advanced polymeric dielectrics for capacitive energy storage has been hampered by the lack of sufficient data encompassing wide enough chemical spaces. Here, data mining and analysis techniques are applied on a recently presented computational data set of around 1100 organic polymers, organometallic polymers, and related molecular crystals, in order to obtain qualitative understanding of the origins of dielectric and electronic properties. By probing the relationships between crucial chemical and structural features of materials and their dielectric constant and band gap, design rules are devised for optimizing either property. Learning from this data set provides guidance to experiments and to future computations, as well as a way of expanding the pool of promising polymer candidates for dielectric applications.},

  doi          = {10.1021/acs.chemmater.7b02027},

  journal      = {Chemistry of Materials},

  number       = 21,

  volume       = 29,

  place        = {United States},

  year         = {Tue Oct 03 00:00:00 EDT 2017},

  month        = {Tue Oct 03 00:00:00 EDT 2017}

}

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https://doi.org/10.1063/1.4903735

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Title: Mining Materials Design Rules from Data: The Example of Polymer Dielectrics

Abstract

Citation Formats

The Deformation and Ageing of Mild Steel: III Discussion of Results journal, September 1951

Accelerating materials property predictions using machine learning journal, September 2013

Machine learning bandgaps of double perovskites journal, January 2016

Combinatorial screening for new materials in unconstrained composition space with machine learning journal, March 2014

Machine Learning Energies of 2 Million Elpasolite ( A B C 2 D 6 ) Crystals journal, September 2016

Finding Nature’s Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory journal, June 2010

Finding New Perovskite Halides via Machine Learning journal, April 2016

Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach journal, April 2015

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning journal, January 2012

AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations journal, June 2012

Machine Learning in Materials Science book, January 2016

Adaptive machine learning framework to accelerate ab initio molecular dynamics journal, December 2014

Machine Learning Force Fields: Construction, Validation, and Outlook journal, December 2016

A study of adatom ripening on an Al (1 1 1) surface with machine learning force fields journal, March 2017

Understanding machine-learned density functionals: Understanding Machine-Learned Density Functionals journal, November 2015

Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies journal, July 2013

Computational predictions of energy materials using density functional theory journal, January 2016

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation journal, July 2013

Predicting crystal structure by merging data mining with quantum mechanics journal, July 2006

Predicting Crystal Structures with Data Mining of Quantum Calculations journal, September 2003

From Organized High-Throughput Data to Phenomenological Theory using Machine Learning: The Example of Dielectric Breakdown journal, February 2016

Rational design of all organic polymer dielectrics journal, September 2014

Theoretical Prediction and Experimental Realization of New Stable Inorganic Materials Using the Inverse Design Approach journal, June 2013

Accelerated search for materials with targeted properties by adaptive design journal, April 2016

Material synthesis and design from first principle calculations and machine learning journal, February 2016

Critical assessment of regression-based machine learning methods for polymer dielectrics journal, December 2016

Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD) journal, September 2013

The Computational Materials Repository journal, November 2012

A polymer dataset for accelerated property prediction and design journal, March 2016

Rationally Designed Polyimides for High-Energy Density Capacitor Applications journal, June 2014

Poly(dimethyltin glutarate) as a Prospective Material for High Dielectric Applications journal, November 2014

Rational Design of Organotin Polyesters journal, April 2015

Rational design and synthesis of polythioureas as capacitor dielectrics journal, January 2015

The rational design of polyurea & polyurethane dielectric materials journal, June 2013

Optimization of Organotin Polymers for Dielectric Applications journal, August 2016

Rational Co-Design of Polymer Dielectrics for Energy Storage journal, May 2016

π-Conjugated Polymers for Organic Electronics and Photovoltaic Cell Applications † journal, February 2011

Synthesis, Characterization, and Photovoltaic Properties of Novel Semiconducting Polymers with Thiophene−Phenylene−Thiophene (TPT) as Coplanar Units journal, August 2008

Polymer electronic memories: Materials, devices and mechanisms journal, October 2008

A high-mobility electron-transporting polymer for printed transistors journal, January 2009

Multi-objective optimization techniques to design the Pareto front of organic dielectric polymers journal, December 2016

Inhomogeneous Electron Gas journal, November 1964

Ab initiomolecular dynamics for liquid metals journal, January 1993

Projector augmented-wave method journal, December 1994

Phonons and related crystal properties from density-functional perturbation theory journal, July 2001

Polarization-Based Calculation of the Dielectric Tensor of Polar Crystals journal, November 1997

Hybrid functionals based on a screened Coulomb potential journal, May 2003

Energy band gaps and lattice parameters evaluated with the Heyd-Scuseria-Ernzerhof screened hybrid functional journal, November 2005

Machine Learning Strategy for Accelerated Design of Polymer Dielectrics journal, February 2016

Accelerated materials property predictions and design using motif-based fingerprints journal, July 2015

Quantitative Structure–Property Relationship Modeling of Diverse Materials Properties journal, January 2012

Crystal structure representations for machine learning models of formation energies journal, April 2015

Image driven machine learning methods for microstructure recognition journal, October 2016

Machine learning scheme for fast extraction of chemically interpretable interatomic potentials journal, August 2016

Prediction model of band gap for inorganic compounds by combination of density functional theory calculations and machine learning techniques journal, March 2016

Machine learning with systematic density-functional theory calculations: Application to melting temperatures of single- and binary-component solids journal, February 2014

Finding Density Functionals with Machine Learning journal, June 2012

Optimizing transition states via kernel-based machine learning journal, May 2012

Neural network approach to quantum-chemistry data: Accurate prediction of density functional theory energies journal, August 2009

Electronic spectra from TDDFT and machine learning in chemical space journal, August 2015

Understanding kernel ridge regression: Common behaviors from simple functions to density functionals journal, May 2015

Atomistic calculations and materials informatics: A review journal, June 2017

Big Data of Materials Science: Critical Role of the Descriptor journal, March 2015

Constrained evolutionary algorithm for structure prediction of molecular crystals: methodology and applications journal, May 2012

New Group IV Chemical Motifs for Improved Dielectric Permittivity of Polyethylene journal, April 2013

How Critical Are the van der Waals Interactions in Polymer Crystals? journal, September 2012

Predicting polymeric crystal structures by evolutionary algorithms journal, October 2014

Minima hopping: An efficient search method for the global minimum of the potential energy surface of complex molecular systems journal, June 2004

Crystal structure prediction using the minima hopping method journal, December 2010

Polymer Properties book, December 2009

Organometallic reactions. Part VI. The addition of the Sn–O bond to the carbonyl group journal, January 1967

Low-Bandgap Near-IR Conjugated Polymers/Molecules for Organic Electronics journal, August 2015

Electronegativity chart journal, May 1962

Advanced polymeric dielectrics for high energy density applications journal, October 2016

Compounds based on Group 14 elements: building blocks for advanced insulator dielectrics design journal, October 2014

Francis Galton's Account of the Invention of Correlation journal, May 1989

Computational Screening of New Perovskite Materials Using Transfer Learning and Deep Learning journal, December 2019

The Deformation and Ageing of Mild Steel: III Discussion of Results
journal, September 1951

Accelerating materials property predictions using machine learning
journal, September 2013

Machine learning bandgaps of double perovskites
journal, January 2016

Combinatorial screening for new materials in unconstrained composition space with machine learning
journal, March 2014

Machine Learning Energies of 2 Million Elpasolite $(A B C_{2} D_{6})$ Crystals
journal, September 2016

Finding Nature’s Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory
journal, June 2010

Finding New Perovskite Halides via Machine Learning
journal, April 2016

Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach
journal, April 2015

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
journal, January 2012

AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations
journal, June 2012

Machine Learning in Materials Science
book, January 2016

Adaptive machine learning framework to accelerate ab initio molecular dynamics
journal, December 2014

Machine Learning Force Fields: Construction, Validation, and Outlook
journal, December 2016

A study of adatom ripening on an Al (1 1 1) surface with machine learning force fields
journal, March 2017

Understanding machine-learned density functionals: Understanding Machine-Learned Density Functionals
journal, November 2015

Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies
journal, July 2013

Computational predictions of energy materials using density functional theory
journal, January 2016

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
journal, July 2013

Predicting crystal structure by merging data mining with quantum mechanics
journal, July 2006

Predicting Crystal Structures with Data Mining of Quantum Calculations
journal, September 2003

From Organized High-Throughput Data to Phenomenological Theory using Machine Learning: The Example of Dielectric Breakdown
journal, February 2016

Rational design of all organic polymer dielectrics
journal, September 2014

Theoretical Prediction and Experimental Realization of New Stable Inorganic Materials Using the Inverse Design Approach
journal, June 2013

Accelerated search for materials with targeted properties by adaptive design
journal, April 2016

Material synthesis and design from first principle calculations and machine learning
journal, February 2016

Critical assessment of regression-based machine learning methods for polymer dielectrics
journal, December 2016

Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)
journal, September 2013

The Computational Materials Repository
journal, November 2012

A polymer dataset for accelerated property prediction and design
journal, March 2016

Rationally Designed Polyimides for High-Energy Density Capacitor Applications
journal, June 2014

Poly(dimethyltin glutarate) as a Prospective Material for High Dielectric Applications
journal, November 2014

Rational Design of Organotin Polyesters
journal, April 2015

Rational design and synthesis of polythioureas as capacitor dielectrics
journal, January 2015

The rational design of polyurea & polyurethane dielectric materials
journal, June 2013

Optimization of Organotin Polymers for Dielectric Applications
journal, August 2016

Rational Co-Design of Polymer Dielectrics for Energy Storage
journal, May 2016

π-Conjugated Polymers for Organic Electronics and Photovoltaic Cell Applications ^†
journal, February 2011

Synthesis, Characterization, and Photovoltaic Properties of Novel Semiconducting Polymers with Thiophene−Phenylene−Thiophene (TPT) as Coplanar Units
journal, August 2008

Polymer electronic memories: Materials, devices and mechanisms
journal, October 2008

A high-mobility electron-transporting polymer for printed transistors
journal, January 2009

Multi-objective optimization techniques to design the Pareto front of organic dielectric polymers
journal, December 2016

Inhomogeneous Electron Gas
journal, November 1964

Ab initiomolecular dynamics for liquid metals
journal, January 1993

Projector augmented-wave method
journal, December 1994

Phonons and related crystal properties from density-functional perturbation theory
journal, July 2001

Polarization-Based Calculation of the Dielectric Tensor of Polar Crystals
journal, November 1997

Hybrid functionals based on a screened Coulomb potential
journal, May 2003

Energy band gaps and lattice parameters evaluated with the Heyd-Scuseria-Ernzerhof screened hybrid functional
journal, November 2005

Machine Learning Strategy for Accelerated Design of Polymer Dielectrics
journal, February 2016

Accelerated materials property predictions and design using motif-based fingerprints
journal, July 2015

Quantitative Structure–Property Relationship Modeling of Diverse Materials Properties
journal, January 2012

Crystal structure representations for machine learning models of formation energies
journal, April 2015

Image driven machine learning methods for microstructure recognition
journal, October 2016

Machine learning scheme for fast extraction of chemically interpretable interatomic potentials
journal, August 2016

Prediction model of band gap for inorganic compounds by combination of density functional theory calculations and machine learning techniques
journal, March 2016

Machine learning with systematic density-functional theory calculations: Application to melting temperatures of single- and binary-component solids
journal, February 2014

Finding Density Functionals with Machine Learning
journal, June 2012

Optimizing transition states via kernel-based machine learning
journal, May 2012

Neural network approach to quantum-chemistry data: Accurate prediction of density functional theory energies
journal, August 2009

Electronic spectra from TDDFT and machine learning in chemical space
journal, August 2015

Understanding kernel ridge regression: Common behaviors from simple functions to density functionals
journal, May 2015

Atomistic calculations and materials informatics: A review
journal, June 2017

Big Data of Materials Science: Critical Role of the Descriptor
journal, March 2015

Constrained evolutionary algorithm for structure prediction of molecular crystals: methodology and applications
journal, May 2012

New Group IV Chemical Motifs for Improved Dielectric Permittivity of Polyethylene
journal, April 2013

How Critical Are the van der Waals Interactions in Polymer Crystals?
journal, September 2012

Predicting polymeric crystal structures by evolutionary algorithms
journal, October 2014

Minima hopping: An efficient search method for the global minimum of the potential energy surface of complex molecular systems
journal, June 2004

Crystal structure prediction using the minima hopping method
journal, December 2010

Polymer Properties
book, December 2009

Organometallic reactions. Part VI. The addition of the Sn–O bond to the carbonyl group
journal, January 1967

Low-Bandgap Near-IR Conjugated Polymers/Molecules for Organic Electronics
journal, August 2015

Electronegativity chart
journal, May 1962

Advanced polymeric dielectrics for high energy density applications
journal, October 2016

Compounds based on Group 14 elements: building blocks for advanced insulator dielectrics design
journal, October 2014

Francis Galton's Account of the Invention of Correlation
journal, May 1989

Computational Screening of New Perovskite Materials Using Transfer Learning and Deep Learning
journal, December 2019

Empirical modeling of dopability in diamond-like semiconductors
journal, December 2018

Active-learning and materials design: the example of high glass transition temperature polymers
journal, June 2019

Soft Matter Informatics: Current Progress and Challenges
journal, November 2018