Physics-informed machine learning for inorganic scintillator discovery

Pilania, Ghanshyam; McClellan, Kenneth James; Stanek, Christopher Richard; Uberuaga, Blas P.

doi:10.1063/1.5025819

Title: Physics-informed machine learning for inorganic scintillator discovery

Abstract

Applications of inorganic scintillators—activated with lanthanide dopants, such as Ce and Eu—are found in diverse fields. As a strict requirement to exhibit scintillation, the 4f ground state (with the electronic configuration of [Xe]4fn 5d0) and 5d1 lowest excited state (with the electronic configuration of [Xe]4fn−1 5d1) levels induced by the activator must lie within the host bandgap. Here we introduce a new machine learning (ML) based search strategy for high-throughput chemical space explorations to discover and design novel inorganic scintillators. Building upon well-known physics-based chemical trends for the host dependent electron binding energies within the 4f and 5d1 energy levels of lanthanide ions and available experimental data, the developed ML model—coupled with knowledge of the vacuum referred valence and conduction band edges computed from first principles—can rapidly and reliably estimate the relative positions of the activator’s energy levels relative to the valence and conduction band edges of any given host chemistry. Using perovskite oxides and elpasolite halides as examples, the presented approach has been demonstrated to be able to (i) capture systematic chemical trends across host chemistries and (ii) effectively screen promising compounds in a high-throughput manner. While a number of other application-specific performance requirements need to be considered formore »« less

Authors:

^[1];

^[1]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Publication Date:: Wed Apr 25 00:00:00 EDT 2018

Research Org.:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Org.:: USDOE Laboratory Directed Research and Development (LDRD) Program

OSTI Identifier:: 1467213

Alternate Identifier(s):: OSTI ID: 1434562

Report Number(s):: LA-UR-18-21016
Journal ID: ISSN 0021-9606

Grant/Contract Number:: AC52-06NA25396; 20180009DR

Resource Type:: Accepted Manuscript

Journal Name:: Journal of Chemical Physics

Additional Journal Information:: Journal Volume: 148; Journal Issue: 24; Journal ID: ISSN 0021-9606

Publisher:: American Institute of Physics (AIP)

Country of Publication:: United States

Language:: English

Subject:: 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats


                    Pilania, Ghanshyam, McClellan, Kenneth James, Stanek, Christopher Richard, and Uberuaga, Blas P. Physics-informed machine learning for inorganic scintillator discovery.  United States: N. p., 2018. 
Web.  doi:10.1063/1.5025819.

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                    Pilania, Ghanshyam, McClellan, Kenneth James, Stanek, Christopher Richard, & Uberuaga, Blas P. Physics-informed machine learning for inorganic scintillator discovery.  United States.  https://doi.org/10.1063/1.5025819

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                    Pilania, Ghanshyam, McClellan, Kenneth James, Stanek, Christopher Richard, and Uberuaga, Blas P. Wed .  
"Physics-informed machine learning for inorganic scintillator discovery".  United States.  https://doi.org/10.1063/1.5025819.  https://www.osti.gov/servlets/purl/1467213.

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@article{osti_1467213,

  title        = {Physics-informed machine learning for inorganic scintillator discovery},

  author       = {Pilania, Ghanshyam and McClellan, Kenneth James and Stanek, Christopher Richard and Uberuaga, Blas P.},

  abstractNote = {Applications of inorganic scintillators—activated with lanthanide dopants, such as Ce and Eu—are found in diverse fields. As a strict requirement to exhibit scintillation, the 4f ground state (with the electronic configuration of [Xe]4fn 5d0) and 5d1 lowest excited state (with the electronic configuration of [Xe]4fn−1 5d1) levels induced by the activator must lie within the host bandgap. Here we introduce a new machine learning (ML) based search strategy for high-throughput chemical space explorations to discover and design novel inorganic scintillators. Building upon well-known physics-based chemical trends for the host dependent electron binding energies within the 4f and 5d1 energy levels of lanthanide ions and available experimental data, the developed ML model—coupled with knowledge of the vacuum referred valence and conduction band edges computed from first principles—can rapidly and reliably estimate the relative positions of the activator’s energy levels relative to the valence and conduction band edges of any given host chemistry. Using perovskite oxides and elpasolite halides as examples, the presented approach has been demonstrated to be able to (i) capture systematic chemical trends across host chemistries and (ii) effectively screen promising compounds in a high-throughput manner. While a number of other application-specific performance requirements need to be considered for a viable scintillator, the scheme developed here can be a practically useful tool to systematically down-select the most promising candidate materials in a first line of screening for a subsequent in-depth investigation.},

  doi          = {10.1063/1.5025819},

  journal      = {Journal of Chemical Physics},

  number       = 24,

  volume       = 148,

  place        = {United States},

  year         = {Wed Apr 25 00:00:00 EDT 2018},

  month        = {Wed Apr 25 00:00:00 EDT 2018}

}

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All the Lanthanides Do It and Even Uranium Does Oxidation State +2
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Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan
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Works referencing / citing this record:

Guest Editorial: Special Topic on Data-Enabled Theoretical Chemistry
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Rupp, Matthias; von Lilienfeld, O. Anatole; Burke, Kieron
The Journal of Chemical Physics, Vol. 148, Issue 24
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Emerging role of machine learning in light-matter interaction
journal, September 2019

Zhou, Jiajia; Huang, Bolong; Yan, Zheng
Light: Science & Applications, Vol. 8, Issue 1
DOI: 10.1038/s41377-019-0192-4

Emerging role of machine learning in light-matter interaction
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Zhou, Jiajia; Huang, Bolong; Yan, Zheng
Light: Science & Applications, Vol. 8, Issue 1
DOI: 10.1038/s41377-019-0192-4

Energy Gap-Refractive Index Relations in Perovskites
journal, April 2020

Lamichhane, Aneer; Ravindra, Nuggehalli M.
Materials, Vol. 13, Issue 8
DOI: 10.3390/ma13081917

Data-enabled structure–property mappings for lanthanide-activated inorganic scintillators
journal, February 2019

Pilania, G.; Liu, Xiang-Yang; Wang, Zhehui
Journal of Materials Science, Vol. 54, Issue 11
DOI: 10.1007/s10853-019-03434-7

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Title: Physics-informed machine learning for inorganic scintillator discovery

Abstract

Citation Formats

Crystal structure representations for machine learning models of formation energies text, January 2015

Energy position of 4 f levels in rare-earth metals journal, August 1979

5d-level energies of Ce3+ and the crystalline environment. IV. Aluminates and “simple” oxides journal, October 2002

High-Throughput Combinatorial Database of Electronic Band Structures for Inorganic Scintillator Materials journal, June 2011

Machine Learning for Quantum Mechanical Properties of Atoms in Molecules text, January 2015

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

The growth and scintillation properties of Cs2NaCeCl6 single crystal journal, April 2009

Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space journal, June 2015

Luminescence and Scintillation Characteristics of ${\rm Rb}_{2}{\rm LiCeBr}_{6}$ Single Crystal journal, December 2010

5 d − level energies of Ce 3 + and the crystalline environment. II. Chloride, bromide, and iodide compounds journal, December 2000

Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach text, January 2015

Band offsets and optical bowings of chalcopyrites and Zn‐based II‐VI alloys journal, September 1995

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

Machine learning for quantum mechanics in a nutshell journal, July 2015

Optical and scintillation properties of Cs/sub 2/LiYCl/sub 6/:Ce/sup 3+/ and Cs/sub 2/LiYCl/sub 6/:Pr/sup 3+/ crystals conference, January 2004

The absolute energy positions of conduction and valence bands of selected semiconducting minerals journal, March 2000

Surface core-level shifts of clean and oxygen-covered Ru(0001) journal, May 2001

Rational design of binary halide scintillators via data mining journal, July 2012

Learning physical descriptors for materials science by compressed sensing journal, February 2017

5 d -level energies of Ce 3 + and the crystalline environment. I. Fluoride compounds journal, December 2000

Energy gap–refractive index relations in semiconductors – An overview journal, March 2007

Fractional charge perspective on the band-gap in density-functional theory text, January 2007

Broadband near‐infrared luminescence of Cr + 3 in the elpasolite lattices Cs 2 NaInCl 6 , Cs 2 NaYCl 6 , and Cs 2 NaYBr 6 journal, October 1986

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

Electronic structure of AlFeN films exhibiting crystallographic orientation change from c- to a-axis with Fe concentrations and annealing effect journal, February 2020

Heterojunction band offset engineering journal, January 1996

Luminescence of the elpasolite series MI2MIIMCl6 (MI=Cs, Rb; MII=Li, Na; M=Lu, Y, Sc, In) doped with europium using synchrotron radiation excitation journal, April 2012

Relating the energy of the [ Xe ] 5 d 1 configuration of Ce 3 + in inorganic compounds with anion polarizability and cation electronegativity journal, June 2002

Multi-fidelity machine learning models for accurate bandgap predictions of solids journal, March 2017

The 5d level positions of the trivalent lanthanides in inorganic compounds journal, November 2000

First-Principles Studies of Luminescence in Ce doped Inorganic Scintillators text, January 2010

Optical and scintillation properties of Cs/sub 2/LiYCl/sub 6/:Ce/sup 3+/ and Cs/sub 2/LiYCl/sub 6/:Pr/sup 3+/ crystals journal, October 2005

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

Reducing Dzyaloshinskii-Moriya interaction and field-free spin-orbit torque switching in synthetic antiferromagnets journal, May 2021

Structure and scintillation properties of Ce3+-activated Cs2NaLaCl6, Cs3LaCl6, Cs2NaLaBr6, Cs3LaBr6, Cs2NaLaI6 and Cs3LaI6 journal, May 2014

Ce3+ 5d-centroid shift and vacuum referred 4f-electron binding energies of all lanthanide impurities in 150 different compounds journal, March 2013

Luminescence and scintillation characterizations of cerium doped Cs2LiGdBr6 single crystal journal, February 2014

Accelerated materials property predictions and design using motif-based fingerprints text, January 2015

A learning scheme to predict atomic forces and accelerate materials simulations text, January 2015

Eu2+-doped Ba2CsI5, a new high-performance scintillator journal, December 2009

Using Machine Learning To Identify Factors That Govern Amorphization of Irradiated Pyrochlores journal, November 2016

Structure maps for. Pseudobinary and ternary phases journal, August 1988

Inorganic scintillators: today and tomorrow journal, December 2002

Cs2LiGdCl6 (Ce): New scintillation material journal, July 2010

Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis journal, February 2013

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

Lanthanide 4f-electron binding energies and the nephelauxetic effect in wide band gap compounds journal, April 2013

5 d -level energies of Ce 3 + and the crystalline environment. III. Oxides containing ionic complexes journal, September 2001

High-energy-resolution scintillator: Ce3+ activated LaBr3 journal, September 2001

Systematic behaviour in trivalent lanthanide charge transfer energies journal, November 2003

Phase equilibria, crystal structures, and dielectric anomaly in the BaZrO3–CaZrO3 system journal, November 2003

By-passing the Kohn-Sham equations with machine learning text, January 2016

The 4f ↔4f − 15d transitions of the trivalent lanthanides in halogenides and chalcogenides journal, September 2000

Prediction of Flatband Potentials at Semiconductor-Electrolyte Interfaces from Atomic Electronegativities journal, January 1978

Design Rules for Ce-Activated Scintillating Radiation Detection Materials: Compromises Between Luminosity and Stopping Power journal, June 2008

Crystal structure of double oxides of the perovskite type journal, May 1946

Prospects for High Energy Resolution Gamma Ray Spectroscopy with Europium-Doped Strontium Iodide journal, January 2009

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning text, January 2011

Investigation of scintillation and luminescence properties of cerium doped Rb2LiGdCl6 single crystals journal, August 2013

A Review on How Lanthanide Impurity Levels Change with Chemistry and Structure of Inorganic Compounds journal, November 2012

Scintillation and spectroscopy of the pure and Ce 3 -doped elpasolites: Cs 2 LiYX 6 (X Cl, Br) journal, August 2002

Ce3+ doped inorganic scintillators journal, September 1994

Growth and scintillation characterization of Ce3+-doped Rb2LiGdBr6 single crystals journal, October 2016

Machine learning in materials informatics: recent applications and prospects journal, December 2017

Scintillation characteristics of Cs2LiCeBr6 crystal journal, October 2011

BaHfO3:Ce sintered ceramic scintillators journal, March 2010

Machine learning properties of binary wurtzite superlattices journal, January 2018

Electronic Structure book, January 2004

Machine Learning Assisted Predictions of Intrinsic Dielectric Breakdown Strength of ABX 3 Perovskites journal, June 2016

Machine Learning in Materials Science book, January 2016

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

Machine Learning for Quantum Mechanical Properties of Atoms in Molecules journal, July 2015

Ionization energies of doubly and triply ionized rare earths journal, August 1973

Accelerating materials property predictions using machine learning journal, September 2013

Surface Core Level Shifts of Clean and Oxygen Covered Ru(0001) text, January 2001

Machine learning bandgaps of double perovskites journal, January 2016

Vacuum Referred Binding Energies of the Lanthanides in Transition Metal Oxide Compounds journal, January 2014

Crystal structure representations for machine learning models of formation energies
text, January 2015

Energy position of $4 f$ levels in rare-earth metals
journal, August 1979

5d-level energies of Ce3+ and the crystalline environment. IV. Aluminates and “simple” oxides
journal, October 2002

High-Throughput Combinatorial Database of Electronic Band Structures for Inorganic Scintillator Materials
journal, June 2011

Machine Learning for Quantum Mechanical Properties of Atoms in Molecules
text, January 2015

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

The growth and scintillation properties of Cs2NaCeCl6 single crystal
journal, April 2009

Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space
journal, June 2015

Luminescence and Scintillation Characteristics of ${\rm Rb}_{2}{\rm LiCeBr}_{6}$ Single Crystal
journal, December 2010

$5 d - level$ energies of ${Ce}^{3 +}$ and the crystalline environment. II. Chloride, bromide, and iodide compounds
journal, December 2000

Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach
text, January 2015

Band offsets and optical bowings of chalcopyrites and Zn‐based II‐VI alloys
journal, September 1995

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

Machine learning for quantum mechanics in a nutshell
journal, July 2015

Optical and scintillation properties of Cs/sub 2/LiYCl/sub 6/:Ce/sup 3+/ and Cs/sub 2/LiYCl/sub 6/:Pr/sup 3+/ crystals
conference, January 2004

The absolute energy positions of conduction and valence bands of selected semiconducting minerals
journal, March 2000

Surface core-level shifts of clean and oxygen-covered Ru(0001)
journal, May 2001

Rational design of binary halide scintillators via data mining
journal, July 2012

Learning physical descriptors for materials science by compressed sensing
journal, February 2017

$5 d$ -level energies of ${Ce}^{3 +}$ and the crystalline environment. I. Fluoride compounds
journal, December 2000

Energy gap–refractive index relations in semiconductors – An overview
journal, March 2007

Fractional charge perspective on the band-gap in density-functional theory
text, January 2007

Broadband near‐infrared luminescence of Cr ⁺ ³ in the elpasolite lattices Cs ₂ NaInCl ₆ , Cs ₂ NaYCl ₆ , and Cs ₂ NaYBr ₆
journal, October 1986

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

Electronic structure of AlFeN films exhibiting crystallographic orientation change from c- to a-axis with Fe concentrations and annealing effect
journal, February 2020

Heterojunction band offset engineering
journal, January 1996

Luminescence of the elpasolite series MI2MIIMCl6 (MI=Cs, Rb; MII=Li, Na; M=Lu, Y, Sc, In) doped with europium using synchrotron radiation excitation
journal, April 2012

Relating the energy of the $[Xe] {5 d}^{1}$ configuration of ${Ce}^{3 +}$ in inorganic compounds with anion polarizability and cation electronegativity
journal, June 2002

Multi-fidelity machine learning models for accurate bandgap predictions of solids
journal, March 2017

The 5d level positions of the trivalent lanthanides in inorganic compounds
journal, November 2000

First-Principles Studies of Luminescence in Ce doped Inorganic Scintillators
text, January 2010

Optical and scintillation properties of Cs/sub 2/LiYCl/sub 6/:Ce/sup 3+/ and Cs/sub 2/LiYCl/sub 6/:Pr/sup 3+/ crystals
journal, October 2005

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

Reducing Dzyaloshinskii-Moriya interaction and field-free spin-orbit torque switching in synthetic antiferromagnets
journal, May 2021

Structure and scintillation properties of Ce3+-activated Cs2NaLaCl6, Cs3LaCl6, Cs2NaLaBr6, Cs3LaBr6, Cs2NaLaI6 and Cs3LaI6
journal, May 2014

Ce3+ 5d-centroid shift and vacuum referred 4f-electron binding energies of all lanthanide impurities in 150 different compounds
journal, March 2013

Luminescence and scintillation characterizations of cerium doped Cs2LiGdBr6 single crystal
journal, February 2014

Accelerated materials property predictions and design using motif-based fingerprints
text, January 2015

A learning scheme to predict atomic forces and accelerate materials simulations
text, January 2015

Eu²⁺-doped Ba₂CsI₅, a new high-performance scintillator
journal, December 2009

Using Machine Learning To Identify Factors That Govern Amorphization of Irradiated Pyrochlores
journal, November 2016

Structure maps for. Pseudobinary and ternary phases
journal, August 1988

Inorganic scintillators: today and tomorrow
journal, December 2002

Cs2LiGdCl6 (Ce): New scintillation material
journal, July 2010

Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis
journal, February 2013

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

Lanthanide 4f-electron binding energies and the nephelauxetic effect in wide band gap compounds
journal, April 2013

$5 d$ -level energies of ${Ce}^{3 +}$ and the crystalline environment. III. Oxides containing ionic complexes
journal, September 2001

High-energy-resolution scintillator: Ce³⁺ activated LaBr₃
journal, September 2001

Systematic behaviour in trivalent lanthanide charge transfer energies
journal, November 2003

Phase equilibria, crystal structures, and dielectric anomaly in the BaZrO3–CaZrO3 system
journal, November 2003

By-passing the Kohn-Sham equations with machine learning
text, January 2016

The 4f ↔4f − 15d transitions of the trivalent lanthanides in halogenides and chalcogenides
journal, September 2000

Prediction of Flatband Potentials at Semiconductor-Electrolyte Interfaces from Atomic Electronegativities
journal, January 1978

Design Rules for Ce-Activated Scintillating Radiation Detection Materials: Compromises Between Luminosity and Stopping Power
journal, June 2008

Crystal structure of double oxides of the perovskite type
journal, May 1946

Prospects for High Energy Resolution Gamma Ray Spectroscopy with Europium-Doped Strontium Iodide
journal, January 2009

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
text, January 2011

Investigation of scintillation and luminescence properties of cerium doped Rb2LiGdCl6 single crystals
journal, August 2013

A Review on How Lanthanide Impurity Levels Change with Chemistry and Structure of Inorganic Compounds
journal, November 2012

Scintillation and spectroscopy of the pure and Ce ³ -doped elpasolites: Cs ₂ LiYX ₆ (X Cl, Br)
journal, August 2002

Ce3+ doped inorganic scintillators
journal, September 1994

Growth and scintillation characterization of Ce3+-doped Rb2LiGdBr6 single crystals
journal, October 2016

Machine learning in materials informatics: recent applications and prospects
journal, December 2017

Scintillation characteristics of Cs2LiCeBr6 crystal
journal, October 2011

BaHfO3:Ce sintered ceramic scintillators
journal, March 2010

Machine learning properties of binary wurtzite superlattices
journal, January 2018

Electronic Structure
book, January 2004

Machine Learning Assisted Predictions of Intrinsic Dielectric Breakdown Strength of ABX ₃ Perovskites
journal, June 2016

Machine Learning in Materials Science
book, January 2016

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

Machine Learning for Quantum Mechanical Properties of Atoms in Molecules
journal, July 2015

Ionization energies of doubly and triply ionized rare earths
journal, August 1973

Accelerating materials property predictions using machine learning
journal, September 2013

Surface Core Level Shifts of Clean and Oxygen Covered Ru(0001)
text, January 2001

Machine learning bandgaps of double perovskites
journal, January 2016

Vacuum Referred Binding Energies of the Lanthanides in Transition Metal Oxide Compounds
journal, January 2014

The electronic structure of lanthanide doped compounds with 3d, 4d, 5d, or 6d conduction band states
journal, July 2014

Scintillation Characterization of Rb$_{2}$LiCeCl$_{6}$ Single Crystal
journal, October 2012

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