I am a Ph.D. candidate in Mechanical Engineering at Carnegie Mellon University (CMU) advised by Venkat Viswanathan. My research interests include computational material design and electrocatalysis in the context of next-generation energy storage and conversion devices. Prior to CMU, I graduated from IIT-Madras in 2015 with a B.Tech. degree in Mechanical Engineering and an M. Tech. degree in Automotive Engineering. A more detailed account can be found in my CV. Follow my group's research activities here and our publications here.
|| 3404 Wean Hall
| Mailing address:
|| Dilip Krishnamurthy|
Department of Mechanical Engineering
Carnegie Mellon University
5000 Forbes Ave.
Pittsburgh, PA 15213
| Email address:
|| dkrishn1 at andrew dot cmu dot edu
- Machine learning for accelerating energy materials discovery
- Material Design for Enabling Next Generation Battery Chemistries
- Computational Design of Electrocatalysts
- Geometric Descriptors for Activity and Stability of Catalyst Materials
- Uncertainty Quantification in Density Functional Theory Calculated Properties
Papers and Patents
Note: The material on this website is intended for the private use of individual scholars. It is not for commercial use or for financial gain. Some of the material is protected by copyright. Requests for permission to make public use of any of the papers, or the material therein, should be sought from the copyright holder/original publisher, or from the authors, as appropriate.
Quantifying Robustness of DFT Predicted Pathways and Activity Determining Elementary Steps for Electrochemical Reactions.
J. Chem. Phys. 150, 041717 (2019).
D. Krishnamurthy, V. Sumaria, and V. Viswanathan
Accelerating Energy Materials Discovery and Optimization through Machine Learning based Approaches.
ACS Energy Lett. 4, 187 (2018).
D. Krishnamurthy, H. Weiland, A.B. Farimani, E. Anton, J. Green and V. Viswanathan
Quantifying Confidence in Density Functional Theory Predicted Surface Pourbaix Diagrams at Solid-Liquid Interfaces and its Implications for Electrochemical Processes.
Langmuir 34, 12259 (2018).
O. Vinogradova, D. Krishnamurthy, V. Pande, and V. Viswanathan
Quantifying Confidence in DFT Predicted Surface Pourbaix Diagrams and Associated Reaction Pathways for Chlorine Evolution.
ACS Catal. 8, 9024 (2018).
V. Sumaria, D. Krishnamurthy, and V. Viswanathan.
Exploring MXenes as Cathodes for Non Aqueous Lithium Oxygen Batteries: Design Rules for Selectively Nucleating Li2O2.
ChemSusChem 11, 1911 (2018).
A. Lee†, D. Krishnamurthy†, and V. Viswanathan.(†equal contribution)
Maximal predictability approach for identifying the right descriptors for electrocatalytic reactions.
J. Phys. Chem. Lett. 9, 588 (2018).
D. Krishnamurthy†, V. Sumaria†, and V. Viswanathan. (†equal contribution)
[journal link] [arXiv link]
Towards Synergistic Electrode-Electrolyte Design Principles for Nonaqueous Li-O2 batteries.
Top. Curr. Chem. (Z) 376, 11 (2018).
A. Khetan, D. Krishnamurthy, and V. Viswanathan.
Surface Restructuring of Nickel Sulfide Generates Optimally Coordinated Active Sites for Oxygen Reduction Catalysis.
Joule 1, 600 (2017).
B. Yan†, D. Krishnamurthy†, C. H. Hendon, S. Deshpande, Y. Surendranath, and V. Viswanathan. (†equal contribution)
[journal link] [arXiv link] [article highlight]
Universality in Nonaqueous Alkali Oxygen reduction on Metal Surfaces: Implications for Li-O2 and Na-O2 Batteries.
ACS Energy Lett. 94, 162 (2016).
D. Krishnamurthy, H. A. Hansen, and V. Viswanathan.
LITHIUM METAL ELECTRODES AND BATTERIES THEREOF.
U.S. Patent Application 15/480, 235 (2017).
Y-M Chiang, V. Viswanathan, L. Li, V. Pande, D. Krishnamurthy, Z. Ahmad, and W. H. Woodford.
- 2018 Batteries Conference Gordon Research Conference
- 2017 MRS Fall Meeting & Exhibit - Materials Research Society
- 2017 ISE 68th Annual Meeting - International Society of Electrochemistry
- 2017 NAM25 North American Catalysis Society Meeting
- Teaching Assistant, 24-311: Numerical Methods, Spring 2018.
- Teaching Assistant, 24-311: Numerical Methods, Spring 2017.
Pittsburgh Quantum Institute