Computational

Graphane as an Efficient and Water-Free Hydrogen Fuel Cell Membrane

  • By Aude Marjolin •
  • 8 May 2017

Hydrogen powered fuel cell cars, developed by almost every major car manufacturer, are ideal zero-emissions vehicles because they produce only water as exhaust. However, their reliability is limited because the fuel cell relies upon a membrane that only functions in when enough water is present, limiting the vehicle’s operating conditions. 

Karl Johnson and his group have found that the unusual properties of graphane – a two-dimensional polymer of carbon and hydrogen – could form a type of anhydrous “bucket brigade” that transports protons without the need for water, potentially leading to the development of more efficient hydrogen fuel cells for vehicles and other energy systems. Graduate research assistant Abhishek Bagusetty is the lead author on their paper “Facile Anhydrous Proton Transport on Hydroxyl Functionalized Graphane”, recently published in Physical Review Letters. Computational modeling techniques coupled with the high performance computational infrastructure at the University’s Center for Research Computing enabled them to design this potentially groundbreaking material. 

Featured
hydrogen fuel cells
Computational

Venkat Viswanathan's Research Featured in MIT News

  • By Aude Marjolin •
  • 22 March 2017

Venkat Viswanathan was featured in MIT News for his research in battery technologies. In collaboration with researchers from MIT, Viswanathan is studying a new kind of electrolyte for "self-healing" lithium battery cells, which could lead to longer driving range, lower cost electric vehicle batteries. 

In the news
Computational
Lithium-ion batteries

Structure-Activity Relations in Heterogeneous Catalysis – A View from Computational Chemistry

Spring 2017
Seminar
Computational
Catalysis
Speaker(s): 
Phillipe Sautet
Dates: 
Friday, March 17, 2017 - 9:30am to 10:30am

The understanding of the catalytic properties of nanoparticle catalysts and the design of optimal composition and structures demands fast methods for the calculation of adsorption energies. By exploring the adsorption of O and OR (R=OH, OOH, OCH3) adsorbates on a large range of surface sites with 9 transition metals, we propose new structure sensitive scaling relations between the adsorption energy of two adsorbates that are valid for all metals and for all surface sites.1 This opens the way for a new class of activity volcano plots where the descriptor is not an energy...

2016 Behrend Computational Materials Meeting, November 19, 2016

  • By Aude Marjolin •
  • 1 November 2016

The Behrend Computational Materials Meeting 2016 will be held Saturday, November 19 from 10 am to 4 pm at Penn State Behrend (Erie, PA). The focus of the meeting will be on Atomic Level Methods and Applications

There is no participation fee, and lunch will be provided. To officially register, please fill out the form below. Registration deadline is Wednesday Nov. 9, 2016. (Early registrations preferred).

Questions or concerns?  Please e-mail Blair Tuttle at brt10@psu.edu

Events
Computational
Materials design

Venkat Viswanathan Awarded Funding to Stop Dendrite Formation in Li-ion Batteries

  • By Aude Marjolin •
  • 19 September 2016

Energy expert Venkat Viswanathan have received funding from the U.S. Department of Energy’s Advanced Research Projects Agency – Energy (ARPA-E) to study the use of dendrite-blocking polymers in lithium-ion batteries. 

When charged repeatedly, lithium-ion batteries run the risk of overheating, and even catching fire. This is due to the formation of dendrites, or microscopic fibers of lithium that can form during the charging cycle. Over time, these dendrites can grow long enough that they connect the battery’s electrodes to one another, causing the battery to short-circuit and become a potential hazard. In order to fully implement future lithium-ion battery technologies, which could greatly increase the battery power of our smartphones, electric vehicles, and more, engineers need to find a way to stop these dendrites from forming.

Grants
Computational
Lithium-ion batteries
Email: 
venkvis@cmu.edu
Phone: 
412-268-4675
Office: 
5109 Scott Hall
Websites: 
Personal | Department
Department of Mechanical Engineering, Carnegie Mellon University
Ph.D., Mechanical Engineering, Stanford University, 2013
Summary:

Venkat Viswanathan's research focus is on identifying the scientific principles governing material design, inorganic, organic and biomaterials, for novel energy conversion and storage routes. The material design is carried out through a suite of computational methods being developed in the group validated by experiments.  Some key research thrusts include identifying principles of electrolytes design (organic material) that can tune electrode catalysis, identification of new anode, cathode (inorganic materials) and electrolyte materials for next generation batteries, new electrocatalysts (inorganic) and biomaterials for energy storage and separation applications. In addition to material design, our group is involved in several cross-cutting areas such as battery controls, electric vehicle security and GPU accelerated computing.

Research interests:

  • Computational material design
  • Density functional theory simulations
  • Phase-field modeling
  • Next generation batteries, fuel cells
  • Electrocatalysis for energy conversion and storage
  • Data-driven material discovery
  • Bio-inspired and bio-mimetic materials
  • Controls for energy systems
  • GPU accelerated computing
Most Cited Publications: 
  1. "Twin Problems of Interfacial Carbonate Formation in Nonaqueous Li–O2 Batteries," B. D. McCloskey, A. Speidel, R. Scheffler, D. C. Miller, V. Viswanathan, J. S. Hummelshøj, J. K. Nørskov, and A. C. Luntz, J. Phys. Chem. Lett. 3, 997 (2012)
  2. "Electrical conductivity in Li2O2 and its role in determining capacity limitations in non-aqueous Li-O2 batteries," V. Viswanathan, K. S. Thygesen, J. S. Hummelshøj, J. K. Nørskov, G. Girishkumar, B. D. McCloskey and A. C. Luntz, J. Chem. Phys. 135, 214704 (2011)
  3. "Solvating additives drive solution-mediated electrochemistry and enhance toroid growth in non-aqueous Li–O2 batteries" Nagaphani B. Aetukuri, Bryan D. McCloskey, Jeannette M. García, Leslie E. Krupp, Venkatasubramanian Viswanathan & Alan C. Luntz, Nature Chemistry 7, 50 (2015)
  4. "Universality in Oxygen Reduction Electrocatalysis on Metal Surfaces," Venkatasubramanian Viswanathan, Heine Anton Hansen, Jan Rossmeisl, and Jens K. Nørskov, ACS Catal. 2, 1654 (2012)
  5. "Direct observation of the oxygenated species during oxygen reduction on a platinum fuel cell cathode," Hernan Sanchez Casalongue, Sarp Kaya, Venkatasubramanian Viswanathan, Daniel J. Miller, Daniel Friebel, Heine A. Hansen, Jens K. Nørskov, Anders Nilsson & Hirohito Ogasawara, Nature Communications 4, 2817 (2013)
Recent Publications: 
  1. "Anisotropy in stability of electrodeposition at solid-solid interfaces and implications for metal anodes," Zeeshan Ahmad, Venkatasubramanian Viswanathan, arXiv:1707.00064
  2. "Performance Metrics Required of Next-Generation Batteries to Make a Practical Electric Semi Truck," Shashank Sripad and Venkatasubramanian Viswanathan, ACS Energy Lett. 2, 1669 (2017)
  3. "Surface Restructuring of Nickel Sulfide Generates Optimally-Coordinated Active Sites for ORR Catalysis," Bing Yan, Dilip Krishnamurthy, Christopher H. Hendon, Siddharth Deshpande, Yogesh Surendranath, Venkatasubramanian Viswanathan, arXiv:1706.04090
  4. "Quantifying Confidence in Density Functional Theory Predicted Magnetic Ground States," Gregory Houchins, Venkatasubramanian Viswanathan, arXiv:1706.00416
  5. "Effect of Dynamic Surface Polarization on the Oxidative Stability of Solvents in Nonaqueous Li-O2 Batteries," Abhishek Khetan, Heinz Pitsch, Venkatasubramanian Viswanathan, arXiv:1705.03862
Email: 
jiz38@pitt.edu
Phone: 
412-624-9577
Office: 
G-01 Allen Hall
Websites: 
Personal | Department
Department of Physics and Astronomy, University of Pittsburgh
Ph.D. Physics, University of Science & Technology of China, 2003
Summary:

1. The wet electron structure of the H/H2O/TiO2(110) surfaces system using Density Functional Theory.

2. The excited state structure of H/H2O/TiO2(110) using delta-scf method and TDDFT.

3. The resonance of alkali atoms adsorbed on Ag and Cu surface using first-principle and model potential calculation methods.

Selected Publications: 
  • "Time-resolved photoemission study of the electronic structure and dynamics of chemisorbed alkali atoms on Ru(0001)," Shengmin Zhang, Cong Wang, Xuefeng Cui, Yanan Wang, Adam Argondizzo, Jin Zhao and Hrvoje Petek, Phys. Rev. B 93, 045401 (2016)
  • "Temperature- and Coverage-Dependent Kinetics of Photocatalytic Reaction of Methanol on TiO2(110)-(1x1) Surface," Hao Feng, Shijing Tan, Haoqi Tang, Qijing Zheng, Yongliang Shi, Xuefeng Cui, Xiang Shao, Aidi Zhao, Jin Zhao, and Bing Wang, J. Phys. Chem. C, 120, 5503 (2016)
  • "Nano-scale Polar-Nonpolar Oxide Heterostructures for Photocatalysis," Hongli Guo, Wissam A. Saidi, Jinlong Yang and Jin Zhao, Nanoscale 8, 6057 (2016)
Email: 
nmarom@andrew.cmu.edu
Phone: 
412-268-1393
Office: 
143 Roberts Engineering Hall
Websites: 
Personal | Department
Department of Materials Science and Engineering, Carnegie Mellon University
Ph.D., Chemistry, Weizmann Institute of Science, 2010
Summary:

Computational Materials Science

The goal of our research is to computationally design materials with desired properties for target applications.

Through the portal of computer simulations we gain access to the vast configuration space of materials structure and composition. We can explore the uncharted territories of materials that have not been synthesized yet and predict their properties from first principles, based solely on the knowledge of their elemental composition and the laws of quantum mechanics.

To navigate the configuration space we use genetic algorithms, steered to the most promising regions by the evolutionary principle of survival of the fittest. We develop a massively parallel genetic algorithm code, GAtor, and run it on some of the world’s most powerful supercomputers. We apply our methods to study functional nano-structured interfaces in organic and hybrid solar cells, molecular crystals, layered materials, and cluster-based nanocatalysts.

Most Cited Publications: 
  1. "Dispersion Interactions with Density-Functional Theory: Benchmarking Semiempirical and Interatomic Pairwise Corrected Density Functionals," Noa Marom, Alexandre Tkatchenko, Mariana Rossi, Vivekanand V. Gobre, Oded Hod, Matthias Scheffler, and Leeor Kronik, J. Chem. Theory Comput. 7, 3944 (2011)
  2. "Stacking and Registry Effects in Layered Materials: The Case of Hexagonal Boron Nitride," Noa Marom, Jonathan Bernstein, Jonathan Garel, Alexandre Tkatchenko, Ernesto Joselevich, Leeor Kronik, and Oded Hod, Phys. Rev. Lett. 105, 046801 (2010)
  3. "Electronic structure of copper phthalocyanine: A comparative density functional theory study," Noa Marom, Oded Hod, Gustavo E. Scuseria, and Leeor Kronik, J. Chem. Phys. 128, 164107 (2008)
  4. "Describing Both Dispersion Interactions and Electronic Structure Using Density Functional Theory: The Case of Metal−Phthalocyanine Dimers," Noa Marom, Alexandre Tkatchenko, Matthias Scheffler and Leeor Kronik, J. Chem. Theory Comput. 6, 81 (2010)
  5. "Density functional theory of transition metal phthalocyanines, I: electronic structure of NiPc and CoPc—self-interaction effect," Noa Marom, Leeor Kronik, Appl. Phys. A 95, 159 (2009)
Recent Publications: 
  1. "Effect of packing motifs on the energy ranking and electronic properties of putative crystal structures of tricyano-1,4-dithiino[c]-isothiazole," F. Curtis, X. Wang and N. Marom, Acta Cryst. B72, 562 (2016)
  2. "Accurate Ionization Potentials and Electron Affinities of Acceptor Molecules IV: Electron-Propagator Methods," O. Dolgounitcheva, Manuel Díaz-Tinoco, V. G. Zakrzewski, Ryan M. Richard, Noa Marom, C. David Sherrill, and J. V. Ortiz J. Chem. Theory Comput. 12, 627 (2016)
  3. "Accurate Ionization Potentials and Electron Affinities of Acceptor Molecules III: A Benchmark of GW Methods," Joseph W. Knight, Xiaopeng Wang, Lukas Gallandi, Olga Dolgounitcheva, Xinguo Ren, J. Vincent Ortiz, Patrick Rinke, Thomas Körzdörfer, and Noa Marom, J. Chem. Theory Comput. 12, 615 (2016)
  4. "Accurate Ionization Potentials and Electron Affinities of Acceptor Molecules II: Non-Empirically Tuned Long-Range Corrected Hybrid Functionals," Lukas Gallandi, Noa Marom, Patrick Rinke, and Thomas Körzdörfer, J. Chem. Theory Comput. 12, 605 (2016)
  5. "Accurate Ionization Potentials and Electron Affinities of Acceptor Molecules I. Reference Data at the CCSD(T) Complete Basis Set Limit," Ryan M. Richard, Michael S. Marshall, O. Dolgounitcheva, J. V. Ortiz, Jean-Luc Brédas, Noa Marom, and C. David Sherrill, J. Chem. Theory Comput. 12, 595 (2016)

PQI Seminar Noa Marom (Tulane University): Toward Computational Design of Functional Nanostructures

Computational materials design offers tremendous potential for discovery and innovation. This powerful concept relies on computational exploration of the vast configuration space of materials structure and composition to identify promising candidates with desired properties for target applications. In fact, many applications do not rely on a single material but on the combination of several materials in a functional nano-structure. Examples for functional nano-structures include the dye-oxide interface, at which charge separation is achieved in dye-sensitized solar cells, and nanocatalysts based on clusters dispersed on a large surface area support. Therefore, we would like to design not just a material, but a functional nano-structure. This requires the combination of accurate electronic structure methods with efficient optimization algorithms.
The electronic properties and the resulting functionality of a nano-structure cannot be deduced directly from those of its isolated constituents. Rather, they emerge from a complex interplay of quantum mechanical interactions that depend on the local environment at the nano-scale. Describing these effects requires a fully quantum mechanical first principles approach. In the first part of the talk, many-body perturbation theory within the GW approximation, where G is the one-particle Green’s function and W is the screened Coulomb interaction, is used to elucidate the size effects in the energy level alignment at the interface between dye molecules and TiO2 clusters of increasing size.
In the second part of the talk, a new approach is presented for computational design of clusters using property-based genetic algorithms (GAs). These algorithms perform optimization by simulating an evolutionary process, whereby child structures are created by combining fragments (“mating”) of the fittest parent structures with respect to the target property. Property-based GAs tailored to search for low energy, high vertical electron affinity (VEA), and low vertical ionization potential (VIP) are applied to TiO2 clusters with up to 20 stoichiometric units. Analysis of the resulting structures reveals the structural features associated with a high VEA and a low VIP and explains the absence of the expected size trends.

Noa Marom
Spring 2016
Lecture
Computational
Materials design

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