Uncertainty quantification of DFT-predicted finite temperature thermodynamic properties within the Debye model

doi:10.1063/1.5132332

This content will become publicly available on December 23, 2020

Title: Uncertainty quantification of DFT-predicted finite temperature thermodynamic properties within the Debye model

Authors:

^[1];

^[2];

^[3]

Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
Wilton E. Scott Institute for Energy Innovation, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA, Department of Physics, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA, Wilton E. Scott Institute for Energy Innovation, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA, Department of Physics, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA

Publication Date:: 2019-12-28

Sponsoring Org.:: USDOE

OSTI Identifier:: 1580166

Grant/Contract Number:: EE0007810

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: Journal of Chemical Physics

Additional Journal Information:: Journal Name: Journal of Chemical Physics Journal Volume: 151 Journal Issue: 24; Journal ID: ISSN 0021-9606

Publisher:: American Institute of Physics

Country of Publication:: United States

Language:: English

Citation Formats


                    Guan, Pin-Wen, Houchins, Gregory, and Viswanathan, Venkatasubramanian. Uncertainty quantification of DFT-predicted finite temperature thermodynamic properties within the Debye model.  United States: N. p., 2019. 
        Web.  doi:10.1063/1.5132332.

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                    Guan, Pin-Wen, Houchins, Gregory, & Viswanathan, Venkatasubramanian. Uncertainty quantification of DFT-predicted finite temperature thermodynamic properties within the Debye model.  United States.  doi:10.1063/1.5132332.

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                    Guan, Pin-Wen, Houchins, Gregory, and Viswanathan, Venkatasubramanian. Sat .  
        "Uncertainty quantification of DFT-predicted finite temperature thermodynamic properties within the Debye model".  United States.  doi:10.1063/1.5132332.

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@article{osti_1580166,

  title        = {Uncertainty quantification of DFT-predicted finite temperature thermodynamic properties within the Debye model},

  author       = {Guan, Pin-Wen and Houchins, Gregory and Viswanathan, Venkatasubramanian},

  abstractNote = {},

  doi          = {10.1063/1.5132332},

  journal      = {Journal of Chemical Physics},

  number       = 24,

  volume       = 151,

  place        = {United States},

  year         = {2019},

  month        = {12}

}

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This content will become publicly available on December 23, 2020

Title: Uncertainty quantification of DFT-predicted finite temperature thermodynamic properties within the Debye model

Citation Formats

Surface Restructuring of Nickel Sulfide Generates Optimally Coordinated Active Sites for Oxygen Reduction Catalysis journal, November 2017

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Thermal expansion, diffusion and melting of Li 2 O using a compact forcefield derived from ab initio molecular dynamics journal, September 2014

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Elastic Properties of Al2O3 and Si3N4 Matrix Composites with SiC Whisker Reinforcement journal, April 1992

Bayesian strategies for uncertainty quantification of the thermodynamic properties of materials journal, September 2019

Thermal expansion of lithium oxide journal, June 1982

The atomic simulation environment—a Python library for working with atoms journal, June 2017

First-principles calculations and thermodynamic modeling of the S-Se system and implications for chalcogenide alloys journal, February 2017

Asymptotic Theory of Certain "Goodness of Fit" Criteria Based on Stochastic Processes journal, June 1952

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Uncertainty Quantification in First-Principles Predictions of Harmonic Vibrational Frequencies of Molecules and Molecular Complexes journal, January 2019

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Pressure and Temperature Induced Phase Transition of ZnS from First-Principles Calculations journal, February 2008

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journal, July 2016

High-Dimensional Materials and Process Optimization Using Data-Driven Experimental Design with Well-Calibrated Uncertainty Estimates
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Thermal expansion, diffusion and melting of Li ₂ O using a compact forcefield derived from ab initio molecular dynamics
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Calculations of thermophysical properties of cubic carbides and nitrides using the Debye–Grüneisen model
journal, February 2007

Elastic Properties of Al2O3 and Si3N4 Matrix Composites with SiC Whisker Reinforcement
journal, April 1992

Bayesian strategies for uncertainty quantification of the thermodynamic properties of materials
journal, September 2019

Thermal expansion of lithium oxide
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The atomic simulation environment—a Python library for working with atoms
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First-principles calculations and thermodynamic modeling of the S-Se system and implications for chalcogenide alloys
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Asymptotic Theory of Certain "Goodness of Fit" Criteria Based on Stochastic Processes
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