Faculty

Tim Mueller

Assistant Professor

Research Interests

Computational Materials Science, Nanomaterials, and Materials for Energy

Timothy Mueller is an assistant professor in the Department of Materials Science and Engineering. His research focuses on computational materials science, nanomaterials, materials informatics, and materials for energy storage and conversion. He came to Johns Hopkins in 2012 from the Massachusetts Institute of Technology, where he was a postdoctoral associate. He earned his doctorate there in 2007.

Education
  • Ph.D. 2007, Mass. Institute of Technology (MIT)
Experience
  • 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)
Journal Articles
  • Chowdhury T, Kim J, Li C, Lee S,-W, Xi W, Gracias D.H, Drichko N.V, Brintlinger T.H, Mueller TK, Park H,-G, Kemoa T.J (2019).  Substrate directed synthesis of MoS2 nanocrystals with tunable dimensionality and optical properties.
  • Lile P, Mueller TK (2019).  Identifying structural patterns in atomically precise nanoclusters across the periodic table.
  • 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.  58(12).  2401-2413.
  • 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).  18040-18047.
  • 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).  798-804.
  • Mueller TK, Cao L, Zhao Z, Liu Z, Gao P, Dai S, Gha J, Xue W, Sun H, Duan X, Pan X, Huang Y (2018).  The Effect of Cu on Differential Surface Elemental Distribution and Stability of PtNi ORR Catalysts.
  • Mueller TK, Wu L, Farid A, Armitage NP (2018).  A compact broadband Terahertz range quarter-wave plate.
  • Mueller TK, Nyshadham C, Rupp M, Bekker B, Shapeev AV, Rosenbrock CW, Csányi G, Wingate DW, Hart GLW (2018).  Machine-learned surrogate models for materials prediction: Combining multiple systems in a single model.
  • Mueller TK, Ouyang B, Chakraborty T, Kim N, Perry NH, Aluru NR, Ertekin E (2018).  A Cluster Expansion Framework for the Sr(Ti1-xFex)O3-x/2 (0 < x < 1) Mixed Ionic Electronic Conductor: Properties based on Realistic Configurations.
  • Mueller TK, Sun D, Wang C, Wang Y, Luo R, Li C, An F, Gaskey B, Hall AS (2018).  Accessing Catalytically Active Ordered Intermetallic Pd3Bi by Electrochemical Induced Non-equilibrium Phase Transformation from PdBi2.
  • Cao L, Raciti D, Li C, Livi KJT, Rottmann PF, Hemker KJ, Mueller T, Wang C (2017).  Mechanistic Insights for Low-Overpotential Electroreduction of CO2 to CO on Copper Nanowires.  ACS Catalysis.  7(12).  8578-8587.
  • 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).  4467-4472.
  • 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).  1943-1951.
  • 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).  7748-7754.
  • 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.  214-240.
  • 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).  17735-17747.
  • 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 Pt 3 Ni octahedra for oxygen reduction reaction.  Science.  348(6240).  1230-1234.
  • 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).  2064-2074.
  • 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).  3854-3862.
  • 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).  2295-2310.
  • 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).  5647-5656.
  • 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).  3762-3767.
  • 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).  17974-17983.
  • 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).  11783-11788.
  • 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.  186-273.
  • "“The Use of Cluster Expansions to Predict the Structure and Properties of Catalysts” The Minerals, Metals & Materials Society (TMS) meeting".  January 1, 2018
  • "“The Effective Use of Data in Materials Research” International Materials Research Society Meeting".  January 1, 2018
  • "“The use of machine learning and informatics to design material interfaces” 2nd International Workshop on Phase Interfaces for Highly Efficient Energy Utilization", 2nd International Workshop on Phase Interfaces for Highly Efficient Energy Utilization.  January 1, 2018
  • "“The Effective Use of Data in Materials Research” Johns Hopkins Department of Materials Science and Engineering".  January 1, 2018
  • ""The Effective Use of Data in Materials Research” University of Maryland Baltimore County Department of Physics".  January 1, 2018
  • "“The Effective Use of Data in Materials Research” Machine Learning in Science and Engineering, Carnegie Mellon University".  January 1, 2018
  • "“The Effective Use of Data in Materials Research” University of California Santa Barbara Materials Department".  January 1, 2018
  • "“The Effective Use of Data in Materials Research” BASF Catalysts Division".  January 1, 2018
  • "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
  • "Design of Nanoscale Cu-Based Catalysts from First Principles", NSF Nanoscale Science and Engineering Grantees Conference.  January 1, 2017
  • "The effective use of data in materials research”", Materials Science & Technology 2017.  January 1, 2017
  • "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
  • "The effective use of data in materials research".  McGill University, Department of Materials Engineering.  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
  • "Towards the Rational Design of Alloy Catalysts for the Oxygen Reduction Reaction", Fall meeting of the Materials Research Society.  January 1, 2016
  • "Accelerated Calculations through the Use of Efficient k-Point Grids", Spring meeting of the Materials Research Society.  January 1, 2016
  • "Materials Research in the Age of Big Data", Interagency Coordinating Committee on Ceramic Research and Development.  January 1, 2015
  • "Accelerating materials research through machine learning", Pacifichem 2015.  January 1, 2015
  • "Identification of descriptors using genetic programming", CECAM workshop on Big Data of Materials Science -- Critical Next Steps.  January 1, 2015
  • "The Origins of Hole Traps in Hydrogenated Nanocrystalline and Amorphous Silicon Revealed through Machine Learning", Conference on Electronic Materials and Applications.  January 1, 2014
  • "Machine Learning in Materials Science and Engineering".  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", Spring Meeting.  January 1, 2014
  • "Structural Descriptors for Hole Traps in Hydrogenated Amorphous Silicon Revealed through Machine Learning", Annual Meeting.  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", Quantum Monte Carlo in the Apuan Alps VIII.  January 1, 2013
  • "Accelerating Materials Design and Development through Machine Learning".  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
  • "Computational Materials Discovery and Design".  January 1, 2012
  • "Design of Materials for Energy Storage".  January 1, 2012
  • "Computational Materials Discovery and Design".  January 1, 2012
  • "Computational Design of Energy-Related Materials", Webinar on Energy Storage.  January 1, 2012
  • "A Density Functional Theory Study of Atomic Order in Au-Pd Nanoparticles", Spring Meeting.  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
  • "Quantum Monte Carlo for Materials Design", Workshop on Perspectives and Challenges of Many-Particle Methods.  Bremen, Germany.  January 1, 2011
  • "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".  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
  • "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
  • "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
  • "First-principles Analysis of Materials for Hydrogen Storage: MOF-5", Spring Meeting.  January 1, 2005
/**/
Back to top