Mueller, Tim

Assistant Professor
Materials Science And Engineering

Maryland Hall 101E
(410) 516-8145
tmueller@jhu.edu

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About

Education
  • Ph.D. 2007, MASS INSTITUTE TECHNOLOGY
Experience
  • 2012 - Present:  Assistant Professor, Materials Science and Engineering, Johns Hopkins University, Baltimore, MD
  • 2010 - 2011:  Postdoctoral Associate, Massachusetts Institute of Technology, Cambridge, MA
  • 2009 - 2010:  Co-founder, Pellion Technologies, Inc., Cambridge, MA
  • 2008 - 2010:  Consultant, Computational Modeling Consultants, LLC, Cambridge, MA
  • 2007 - 2010:  Postdoctoral Associate / Visiting Scientist, Massachusetts Institute of Technology, Cambridge, MA
  • 2007 - 2009:  Teaching Assistant, Massachusetts Institute of Technology, Cambridge, MA
  • 2002 - 2007:  Research Assistant, Massachusetts Institute of Technology, Cambridge, MA
  • 1999 - 2001:  Pre-sales Consultant, Trilogy Software, Paris, France
  • 1998 - 1999:  Systems Integration Consultant, Trilogy Software, Austin, TX
  • 1996 - 1998:  Teaching Fellow, Harvard University, Cambridge, MA
  • 1995 - 1998:  Research Assistant, Harvard University, Cambridge, MA
Research Areas
  • Energy storage and convesion
  • Materials informatics
  • Nanoscale materials
Awards
  • 2014:  NSF CAREER Award
  • 2002:  John F. Elliott Graduate Fellowship (Massachusetts Institute of Technology)
  • 1998:  Certificate for Distinction in Teaching (Harvard University)
  • 1998:  Thomas T. Hoopes Prize (Harvard University)
  • 1997:  Certificate for Distinction in Teaching (Harvard University)
Presentations
  • "The use of machine learning to develop models of nanoscale materials from first principles", NSF Nanoscale Science and Engineering Grantees Conference.  December 12, 2017
  • "The effective use of data in materials research", Materials Science & Technology 2017.  October 11, 2017
  • "Practical applications of Bayesian cluster expansions", NOMAD summer.  September 27, 2017
  • "The effective use of data in materials research".  September 12, 2017
  • "Predicting the structure and properties of nanoscale materials through ab-initio calculations and machine learning".  July 13, 2017
  • "Accelerating materials research through the effective use of data", American Chemical Society spring meeting.  April 2, 2017
  • "The effective use of data in materials research", 57th Sanibel Symposium.  February 21, 2017
  • "The effective use of data in materials research", 2017 Workshop on Simulation and Modeling of Emerging Electronics.  January 12, 2017
  • "The effective use of data in materials research”", Materials Science & Technology 2017.  January 1, 2017
  • "Design of Nanoscale Cu-Based Catalysts from First Principles", NSF Nanoscale Science and Engineering Grantees Conference.  January 1, 2017
  • "Accelerated Calculations through the Use of Efficient k-Point Grids", Spring meeting of the Materials Research Society.  January 1, 2016
  • "Applications of Supervised Machine Learning to Materials Research", Workshop on Machine Learning for Materials Research.  The University of Maryland College Park.  January 1, 2016
  • "Accelerating materials research through the effective use of data", American Chemical Society fall meeting.  January 1, 2016
  • "The effective use of data in materials research".  McGill University, Department of Materials Engineering.  January 1, 2016
  • "A tool for accelerating material calculations through the generation of highly efficient k-point grids", March meeting of the American Physical Society.  January 1, 2016
  • "Towards the Rational Design of Alloy Catalysts for the Oxygen Reduction Reaction", Fall meeting of the Materials Research Society.  January 1, 2016
  • "Identification of descriptors using genetic programming", CECAM workshop on Big Data of Materials Science -- Critical Next Steps.  January 1, 2015
  • "Accelerating materials research through machine learning", Pacifichem 2015.  January 1, 2015
  • "Materials Research in the Age of Big Data", Interagency Coordinating Committee on Ceramic Research and Development.  January 1, 2015
  • "Machine Learning in Materials Science and Engineering".  January 1, 2014
  • "Structural Descriptors for Hole Traps in Hydrogenated Amorphous Silicon Revealed through Machine Learning", Fall Meeting.  January 1, 2014
  • "Quantum Monte Carlo for Materials Design", Spring Meeting.  January 1, 2014
  • "The Origins of Hole Traps in Hydrogenated Nanocrystalline and Amorphous Silicon Revealed through Machine Learning", Conference on Electronic Materials and Applications.  January 1, 2014
  • "Structural Descriptors for Hole Traps in Hydrogenated Amorphous Silicon Revealed through Machine Learning", Annual Meeting.  January 1, 2014
  • "Designing Materials for a Sustainable Fuel Cycle", E2SHI Seminar.  January 1, 2014
  • "Ensemble Effects in Cu-alloy Catalysts for CO2 Reduction", ACS Fall Meeting.  January 1, 2014
  • "Quantum Monte Carlo for Materials Design", Quantum Monte Carlo in the Apuan Alps VIII.  January 1, 2013
  • "Materials Informatics for Energy Storage", Massive Energy Storage for the Broader Use of Renewable Energy Sources.  January 1, 2013
  • "Computational Materials Discovery and Design".  January 1, 2013
  • "Towards the Rational Design of Nanoparticles for Energy Applications", ACS Fall Meeting.  January 1, 2013
  • "Accelerating Materials Design and Development through Machine Learning".  January 1, 2013
  • "Computational Materials Discovery and Design".  January 1, 2012
  • "Design of Materials for Energy Storage".  January 1, 2012
  • "Computational Design of Energy-Related Materials", Webinar on Energy Storage.  January 1, 2012
  • "Computational Materials Discovery and Design".  January 1, 2012
  • "Quantum Monte Carlo for Materials Design", Workshop on Perspectives and Challenges of Many-Particle Methods.  Bremen, Germany.  January 1, 2011
  • "A Computational Study of Tavorite-Structured Cathode Materials", Spring Meeting.  January 1, 2011
  • "Hydrogen Release from Sodium Alanate Nanoparticles", Physical Behavior of Materials Contractors Meeting.  January 1, 2011
  • "Quantum Monte Carlo for Materials Design", March Meeting.  January 1, 2011
  • "The Effect of Particle Size on Hydrogen Release from Sodium Alanate", Spring Meeting.  January 1, 2011
  • "A Density Functional Theory Study of Atomic Order in Au-Pd Nanoparticles", Spring Meeting.  January 1, 2011
  • "An Efficient Method to Study Ordering in Low-Symmetry Materials".  Stuttgart.  January 1, 2009
  • "An Efficient Method to Study Substitutional Order in Nanoparticles", March Meeting.  January 1, 2009
  • "A Density Functional Theory Study of Sodium Alanate Nanoparticles", Fall Meeting.  January 1, 2009
  • "An Efficient Method to Study Ordering in Low-Symmetry Materials", Spring Meeting.  January 1, 2009
  • "Computational Methods for Determining the Structure of Hydrogen Storage Materials", March Meeting.  January 1, 2009
  • "Advances in Cluster Expansions: new Computational Tools to Study Surfaces and Nanoparticles", Nanoscience Colloquium.  January 1, 2009
  • "An Efficient Method to Study Ordering in Low-Symmetry Materials", Fall Meeting.  January 1, 2008
  • "Identifying the Structure of Hydrogen Storage Materials", Theory Focus Session on Hydrogen Storage Materials.  San Francisco, CA.  January 1, 2008
  • "A Density Functional Theory Study of the Structure and Thermodynamics of Lithium Imide", International Symposium on Materials issues in Hydrogen Production and Storage.  January 1, 2006
  • "First-principles Analysis of Materials for Hydrogen Storage: MOF-5", Spring Meeting.  January 1, 2005
  • "The Structure and Thermodynamic Properties of Lithium Imide from First Principles", Fall Meeting.  January 1, 2005
  • "A Computational Study of Lithium Imide".  January 1, 2005

Publications

Journal Articles
  • Li C, Raciti D, Pu T, Cao L, He C, Wang C, Mueller T (2018).  Improved Prediction of Nanoalloy Structures by the Explicit Inclusion of Adsorbates in Cluster Expansions.  Journal of Physical Chemistry C.  122(31).
  • Jia Q, Zhao Z, Cao L, Li J, Ghoshal S, Davies V, Stavitski E, Attenkofer K, Liu Z, Li M, Duan X, Mukerjee S, Mueller T, Huang Y (2018).  Roles of Mo Surface Dopants in Enhancing the ORR Performance of Octahedral PtNi Nanoparticles.  Nano Letters.  18(2).
  • Jia Q, Zhao Z, Cao L, Li J, Ghoshal S, Davies V, Stavitski E, Attenkofer K, Liu Z, Li M, Duan X, Mukerjee S, Mueller T, Huang Y (2018).  Roles of Mo Surface Dopants in Enhancing the ORR Performance of Octahedral PtNi Nanoparticles.  Nano Letters.  18.  798-804.
  • Cao L, Li C, Mueller T (2018).  The Use of Cluster Expansions to Predict the Structures and Properties of Surfaces and Nanostructured Materials.  Journal of Chemical Information and Modeling.
  • Cao L, Raciti D, Li C, Livi KJT, Rottmann PF, Hemker KJ, Mueller T, Wang C (2017).  Mechanistic Insights for Low-Overpotential Electroreduction of CO2to CO on Copper Nanowires.  ACS Catalysis.  7(12).
  • Yuan F, Mueller T (2017).  Identifying models of dielectric breakdown strength from high-throughput data via genetic programming.  Scientific Reports.  7(1).
  • Raciti D, Cao L, Livi KJT, Rottmann PF, Tang X, Li C, Hicks Z, Bowen KH, Hemker KJ, Mueller T, Wang C (2017).  Low-Overpotential Electroreduction of Carbon Monoxide Using Copper Nanowires.  ACS Catalysis.  7(7).
  • Mueller T (2017).  Comment on "cluster expansion and the configurational theory of alloys".  Physical Review B.  95(21).
  • Saritas K, Mueller T, Wagner L, Grossman JC (2017).  Investigation of a Quantum Monte Carlo Protocol To Achieve High Accuracy and High-Throughput Materials Formation Energies.  Journal of Chemical Theory and Computation.  13(5).
  • Cao L, Mueller T (2016).  Theoretical Insights into the Effects of Oxidation and Mo-Doping on the Structure and Stability of Pt-Ni Nanoparticles.  Nano Letters.  16(12).
  • Wisesa P, McGill KA, Mueller T (2016).  Efficient generation of generalized Monkhorst-Pack grids through the use of informatics.  Physical Review B.  93(15).
  • Wisesa P, McGill K, Mueller T (2016).  Efficient K-point grid generation through the use of informatics.  Computation Molecular Science and Engineering Forum 2016 - Core Programming Area at the 2016 AIChE Annual Meeting.
  • Cao L, Mueller T (2015).  Rational Design of Pt<inf>3</inf>Ni Surface Structures for the Oxygen Reduction Reaction.  Journal of Physical Chemistry C.  119(31).
  • Huang X, Zhao Z, Cao L, Chen Y, Zhu E, Lin Z, Li M, Yan A, Zettl A, Wang YM, Duan X, Mueller T, Huang Y (2015).  High-performance transition metal-doped Pt3Ni octahedra for oxygen reduction reaction.  Science.  348(6240).
  • Mueller T, Johlin E, Grossman JC (2014).  Origins of hole traps in hydrogenated nanocrystalline and amorphous silicon revealed through machine learning.  Physical Review B - Condensed Matter and Materials Physics.  89(11).
  • Hautier G, Jain A, Mueller T, Moore C, Ong SP, Ceder G (2013).  Designing multielectron lithium-ion phosphate cathodes by mixing transition Metals.  Chemistry of Materials.  25(10).
  • Mueller T (2012).  Ab initio determination of structure-property relationships in alloy nanoparticles.  Physical Review B - Condensed Matter and Materials Physics.  86(14).
  • Mueller T, Hautier G, Jain A, Ceder G (2011).  Evaluation of tavorite-structured cathode materials for lithium-ion batteries using high-throughput computing.  Chemistry of Materials.  23(17).
  • Jain A, Hautier G, Moore CJ, Ping Ong S, Fischer CC, Mueller T, Persson KA, Ceder G (2011).  A high-throughput infrastructure for density functional theory calculations.  Computational Materials Science.  50(8).
  • Mueller T, Ceder G (2010).  Ab initio study of the low-temperature phases of lithium imide.  Physical Review B - Condensed Matter and Materials Physics.  82(17).
  • Mueller T, Ceder G (2010).  Exact expressions for structure selection in cluster expansions.  Physical Review B - Condensed Matter and Materials Physics.  82(18).
  • Mueller T, Ceder G (2010).  Effect of particle size on hydrogen release from sodium alanate nanoparticles.  ACS Nano.  4(10).
  • Hautier G, Fischer CC, Jain A, Mueller T, Ceder G (2010).  Finding natures missing ternary oxide compounds using machine learning and density functional theory.  Chemistry of Materials.  22(12).
  • Chan MKY, Reed J, Donadio D, Mueller T, Meng YS, Galli G, Ceder G (2010).  Cluster expansion and optimization of thermal conductivity in SiGe nanowires.  Physical Review B - Condensed Matter and Materials Physics.  81(17).
  • Mueller T, Ceder G (2009).  Bayesian approach to cluster expansions.  Physical Review B - Condensed Matter and Materials Physics.  80(2).
  • Predith A, Ceder G, Wolverton C, Persson K, Mueller T (2008).  Ab initio prediction of ordered ground-state structures in ZrO2 -Y2 O3.  Physical Review B - Condensed Matter and Materials Physics.  77(14).
  • Mueller T, Ceder G (2006).  Effective interactions between the N-H bond orientations in lithium imide and a proposed ground-state structure.  Physical Review B - Condensed Matter and Materials Physics.  74(13).
  • Mueller T, Ceder G (2005).  A density functional theory study of hydrogen adsorption in MOF-5.  Journal of Physical Chemistry B.  109(38).
  • Chen M, Clark PG, Mueller T, Friend CM (1999).  Resolving discrepancies between leed and stm through ab initio calculations: surface and bonding of sulfur on mo(110).  Physical Review B - Condensed Matter and Materials Physics.  60(16).
  • Mueller T, Kusne AG, Ramprasad R (2015).  Machine Learning in Materials Science: Recent Progress and Emerging Applications.  Rev. Comput. Chem..
Book Chapters
  • Mueller T, Kusne AG, Ramprasad R (2016).  Machine Learning in Materials Science: Recent Progress and Emerging Applications.  Reviews in Computational Chemistry.  29.
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