ALERT: We are looking for motivated PostDocs candidates to join our group on electrochemical catalysis (CO2RR, OER: experiments and/or Theory)!

About

Welcome to the Materials Research Lab at IITB.

Objective: With rapid industrialization and continuous use of fossil fuels, the atmospheric CO2 level has increased to an ever high value of 400 ppm. Being a greenhouse gas, CO2 contributes to climate change and increase in CO2 emission is a global concern. To keep the mean global temperature rise within 2 °C, the anthropogenic CO2 emission has to be reduced significantly. This requires (a) better utilization of available fossil fuels and (b) search of alternative CO2-free renewable fuels. In our group, we are engineering materials to address these energy challenges. In particular, we are working on the following problems: (click on each link to know more about these problems)

- Materials discovery from machine learning and high-throughput calculations for energy applications. - Thermoelectricity (to convert waste heat into electricity). - Thermochemical reduction of N2 gas to NH3 gas.

Approach: To tackle these problems, we use a variety of approaches varying from paper and pen theory to computer simulations and experiments. Our entire group has access to IITB supercomputing facility SpaceTime (internal link) where we routinely use 100s of CPUs to carry-out our simulations. We are currently in the process of securing resources for setting up a flow reactor for thermochemical reactions at elevated temperatures and pressures.

Tools: Some of the tools that we routinely use are:

Machine Learning Methods: Linear, logistic, and polynomial regressions, Feedforward and convolution neural networks, Gaussian process regression, k-means clustering, k-NN, decision trees/ random forest. Machine Learning Packages: Tensorflow, Scikit-learn. Molecular Simulation Tools: Density Functional Theory, Lattice Dynamics, Molecular Dynamics, Computational Fluid Dynamics, Tight-Binding, Monte Carlo. Molecular Simulation Packages:: Quantum ESPRESSO, VASP, CP2K, ALD (in-house code for thermal properties from lattice dynamics), WANNIER90, EPW, LAMMPS, QNANO (in-house code for tight-binding), Enumerator (in-house code for bulk-enumeration). Computer Languages/ Packages: C/C++, Python, FORTRAN, MATLAB, GNU Octave, PHP, Shell. Miscellaneous: LAPACK(e), BLAS, OpenMP(I), PBS Torque, ASE, Inkscape, VMD, VESTA, FEAST, LATEX.

Research

Novel Materials Discovery from Machine Learning and High-throughput Calculations

Machine learning methods such as neural networks and Gaussian processes are proving increasingly successful in novel materials discovery by either predicting the materials with desired properties or by accelerating the search procedure. Application of these methods to materials research is currently facing two major challenges: (a) Material Fingerprinting, i.e., how to describe material to the computer (which understands only bits) and (b) Availability of systematic/ consistent datasets.

In this project, we are working on both of these challenges. We are designing fingerprints which are suitable for materials discovery and we are developing surrogate machine learning methods and high-throughput calculation frameworks for accelerated discovery of novel materials for energy applications.

Thermoelectric Energy Conversion

The materials ability to convert heat into electricity is characterized by a non-dimensional thermoelectric figure of merit defined as, ZT = σS2T/K, where σ, S, K, and T are electrical conductivity, Seebeck coefficient, thermal conductivity, and temperature. Opposed to many materials, where charge and heat transport are coupled through the same carrier, the charge and heat transport in semiconductors are due to electrons and phonons (i.e., atomic vibrations). Semiconductors, therefore, offer a possibility of reducing the thermal conductivity without affecting the electrical transport.

Si- and Ge-based inorganic clathrates are emerging as an interesting class of materials for thermoelectric applications. Due to a many-atoms-complex unitcell, the phonon thermal conductivity in clathrates is small. This low phonon thermal conductivity can be further reduced with an introduction of heavy atoms in the cage; by scattering heat carrying acoustic phonons.

In this project, we are employing lattice dynamic calculations to study the effect of guest and cage atoms on the phonon thermal conductivity of type-I clathrates.

Thermochemical Reduction of N2 gas to NH3 gas

The world population has tripled in the past century. We are able to feed this ever-increasing population only because of the revolution in fertilizers from ammonia synthesis. The importance of artificial ammonia synthesis has been recognized so far with three Nobel prizes (1918, 1931, and 2007).

The ammonia synthesis is, unfortunately, a very energy intensive process. The nitrogen gas, needed for ammonia synthesis, is one of the most inert gases and it is often employed to provide an inert environment for other chemical processes. Because of this non-reactivity of nitrogen gas, extremely high temperatures and pressures are required for the synthesis of the ammonia gas which results in centralized synthesis facilitites requiring excess of 100 million dollars for setup. The transportation of gas from these decentralized plants to farming lands further adds to the ammonia cost. The ammonia synthesis accounts for around 1% of the world total energy usage and the cost that farmers pay for ammonia is often 4-5 times higher than the production cost because of transportation cost.

In this project, we are carrying out a computations-guided search of new heterogeneous catalysts which are capable of stabilizing the N2 triple-bond-dissociation reaction intermediates and hence reduce the temperature and pressure requirements for artificial ammonia synthesis.

Method (Code) Development

Due to the computational nature of our work, we are actively involved in the development of high-performance computer codes for scientific/engineering applications. These codes are highly optimized for memory/speed using OpenMPI/OpenMP, BLAS, LAPACK, etc libraries. Many of our developed computer codes are employed by research groups from across the globe. Some of the codes developed in our research group include:

Boltzmann Transport Equation Solver

Publications: [1] [2] [3] [4] [5] [6] [7] [8] [11] [18] [23]

Crystal Enumerator

Publications: [22], Wyckoff Bulk Generator and Prototype Search applications hosted by SUNCAT center at Stanford University

Non-radiative Auger Loss Solver

Publications: [12] [14] [15] [17]

Team

Dr.  Ankit Jain (PI)

Education:

Ph.D.: Mechanical Engineering, Carnegie Mellon University, USA (2011-2015)

B.Tech.: Mechanical Engineering, IIT Kanpur, India (2007-2011)

Professional Experience:

2019- : Assistant Professor, Mechanical Engineering, IIT Bombay, India

2018-2019: Postdoctoal Fellow, Technical University of Denmark, Denmark with Prof. Jens Norskov

2017-2018: Postdoctoal Fellow, Stanford University, USA with Dr. Thomas Bliggard and Prof. Jens Norskov

2015-2017: IBM SOSCIP Postdoctoral Fellow, University of Toronto, Canada with Prof. Edward (Ted) Sargent

PostDocs

Dr. Hardik L. Kagdada
(2023-)

Education:


B.Sc.: Saurashtra University, Rajkot, India (2011-2014)

M.Sc.: The Maharaja Sayajirao University of Baroda, Vadodara, India (2014-2016)

PhD: Institute of Infrastructure Technology Research and Management (IITRAM), Ahmedabad, India (2019-2023)

Research Interests: Electrocatalysis

Publication(s): [46] [50]

Dr. Jyotishraj Thoudam
(2024-)

Education:


B.Tech.: National Institute of Technology, Manipur, India (2013-2017)

PhD: IIT Gandhinagar, Gujarat, India (2017-2024)

Research Interests: Electrocatalysis

Link Jyotishraj Thoudam

Ph.D. Candidates

Yagyank Srivastava
(2019-)

Education:

B.Tech.: Shri Mata Vaishno Devi University, India (2012-2016)

Research Interests:

- Thermal and electrical properties of materials from ab-initio calculations

Publication(s): [33] [43] [45] [49]

Amey Gajanan Gokhale
(2019-)

Education:

M.Tech.: IIT Bhubaneshwar, India (2017-2019)

B.Tech.: University of Mumbai, India (2012-2016)

Research Interests:

- Methods development for thermoelectric properties of materials from ab-initio calculations

Publication(s): [30] [40] [42]

Neha Rajput
(2022-)

Education:

M.Tech.: IIT Roorkee (2017-2019)

B.Tech.: G.B.Pant University of Agriculture and Technology (2011-2015)

Research Interests:

- Computational heterogeneous catalysis

Nidheesh Virakante
PMRF Fellow
(2022-)

Education:

M.Tech.: IIT Hyderabad (2015-2017)

B.Tech.: Mahatma Gandhi University, Kerala (2010-2014)

Research Interests:

- Thermal Transport in Nuclear Fuels

Shantanu Devendra Pradhan
(2023-)

Education:

B.Tech.: IIT Bombay, India (2007-2012)

Research Interests:

- Electrochemical H2 production, Alkaline Electrolysors

Rajan Kumar
(2024-)

Education:

B.Tech.: Aryabhatta Knowledge University, Patna, India (2018-2022)

M.Tech.: IIT Patna, India (2022-2024)

Research Interests:

- Molecular dynamics and Lattice dynamics for thermal transport in solids

M.Tech. Candidates

Group Alumni

Dr. Sundheep R
(Institute PostDoc,
2020-2022)

Education:

PhD.: Pondicherry University, India (2013-2019)

M.Sc.: Gandhigram Rural Institute, India (2011-2013)

B.Sc.: University of Calicut, India (2008-2011)

Research Interests:

- 2D/3D perovskite interfaces

Publication(s): [31] [34]

Placement/Next Position:

- PostDoc @ Chungnam National University, South Korea (2022-)

Dr. Harish Peruswamula Veeravenkata
(PhD, 2019-2024)

Education:

M.Tech.: University of Hyderabad, India (2017-2019)

B.Tech.: Acharya Nagarjuna University, India (2013-2017)

Research Interests:

- Hybrid organic/inorganic perovskites for optoelectronic applications

Internship(s):

- BASF, Germany (Aug 2022 - Jan 2023)

Publication(s): [29] [38] [39]

Shadab Alam
(MTech, 2021-2023)

Education:

B.Tech.: IIEST Shibpur (2012-2016)

Research Interests:

- Molecular Dynamics for Thermal Transport

Publication(s): [40] [44]

Placement/Next Position:

- Reliance Industries Ltd

Shahid Ahmed
(2022-2024)

Education:      

B.Tech.: NIT Silchar (2015-2019)

Research Interests:

- Thermal Transport in Twisted Bilayer Graphene

Publication(s): [44]

Placement/Next Position:

- PhD, Carnegie Mellon University, USA (2024-)

Praveen Kumar Yadav
(2022-2024)

Education:             

B.Tech.: IIT BHU (2015-2019)

Research Interests:

- Thermal Transport in Ultralow Thermal Conductivity Solids

Publication(s): [48]

Placement/Next Position:

- Bajaj Auto Limited

Dhvaneel Visaria
(Undergrad Researcher,
2019-2021)

Education:

B.Tech.: IIT Bombay, India (2017-2021)

Research Interests:

- Thermal transport in two-dimensional materials

Internship(s):

- Purdue University, USA (May 2020 - Jul 2020)

Publication(s): [27] [30]

Placement/Next Position:

- MS @ Stanford University, USA (2021-)

Shravan Godse
(Undergrad Researcher,
2020-2022)

Education:

B.Tech.: IIT Bombay, India (2018-2022)

Research Interests:

- Machine learning assisted forcefield development for accelerated discovery of materials

Internship(s):

- Technical University of Munich, Germany (May 2021 - Jul 2021)

Publication(s): [33]

Placement/Next Position:

- PhD @ Carnegie Mellon University, USA (2022-)

Publications

Please visit Google Scholar for complete up-to-date list of our publications.
  1. Hardik L. Kagdada and Ankit Jain "Anomalous phonon thermal transport in boron chalcogenides: Role of four-phonon scattering", Journal of Applied Physics 137 025106 (2025).
  2. Yagyank Srivastava and Ankit Jain "Accelerating prediction of phonon thermal conductivity by an order of magnitude through machine learning assisted extraction of anharmonic force constants", Physical Review B 110 165202 (2024).
  3. Praveen K Yadav and Ankit Jain "Revisiting thermal transport in CuInTe2: Role of temperature-dependent anharmonicity and higher-order phonon-phonon interactions", Applied Physics Letters 125 042110 (2024).
  4. Ankit Jain "Impact of four-phonon scattering on thermal transport in carbon nanotubes", Physical Review B 109 155413 (2024).
  5. Hardik L. Kagdada and Ankit Jain "Impact of Vacancy Defects on Electrochemical Nitrogen Reduction Reaction Performance of MXenes", ChemPhysChem 25 e202300993 (2024).
  6. Yagyank Srivastava and Ankit Jain "Accelerated thermal conductivity prediction through Machine-Learning: Two Orders of Magnitude Reduction in Phonon-Phonon Scattering Rates Calculation", Materials Today Physics 2542 101345 (2024).
  7. Shahid Ahmed, Shadab Alam, and Ankit Jain "Understanding phonon thermal transport in twisted bilayer graphene", Physical Review B 108 235202 (2023).
  8. Yagyank Srivastava and Ankit Jain "End-to-end material thermal conductivity prediction through machine learning", Journal of Applied Physics 134 225101 (2023). Featured Article
  9. Amey G. Gokhale and Ankit Jain "Cross-plane Thermal Transport in Layered Materials", Applied Physics Letters 123 232202 (2023).
  10. Jin Yang, Ankit Jain, Liwu Fan, Yee Sin Ang, Hanying Li, and Wee-Liat Ong "Anomalous Pressure-Resilient Thermal Conductivity in Hybrid Perovskites with Strong Lattice Anharmonicity and Small Bulk Modulus", Chemistry of Materials 35 5185 (2023).
  11. Shadab Alam, Amey G. Gokhale, and Ankit Jain "Revisiting thermal transport in single-layer graphene: On the applicability of thermal snapshot interatomic force constant extraction methodology for layered materials", Journal of Applied Physics 133 215105 (2023). Editor's Pick
  12. Harish P. Veeravenkata and Ankit Jain "Hydrodynamic thermal transport in BNC2", Diamond & Related Materials 131 109568 (2023).
  13. Naini Bajaj, Dhanashree Chemate, Harish P Veeravenkata, Ashish Khandelwal, M. K. Chattopadhyay, Moinak Dutta, Aditya Roy, Archna Sagdeo, Ankit Jain, Shriganesh Prabhu, Kanishka Biswas, and Dipanshu Bansal "Sublinear temperature dependence of thermal conductivity in the incommensurate phase of TlInTe2", Physical Review B 106 214101 (2022).
  14. Jin Yang, Ankit Jain, and Wee-Liat Ong "Inter-channel Conversion between Population-/Coherence-channel Dictates Thermal Transport in MAPbI3 Crystals", Materials Today Physics 28 100892 (2022).
  15. Ankit Jain "Single-channel or multichannel thermal transport: Effect of higher-order anharmonic corrections on the predicted phonon thermal transport properties of semiconductors", Physical Review B 106 045207 (2022).
  16. Vikram, Bhawna Sahni, Ankit Jain, and Aftab Alam "Quasi-2D carrier transport in KMgBi for promising thermoelectric performance", Applied Energy Materials 5 9141 (2022).
  17. Sundheep R. and Ankit Jain "Design rules for defect-free 3D perovskite-perovskite interfaces", Surfaces and Interfaces 31 102073 (2022).
  18. Shravan Godse, Yagyank Srivastava, and Ankit Jain "Anharmonic lattice dynamics and thermal transport in type-I inorganic clathrates", Journal of Physics: Condensed Matter 34 145701 (2022).
  19. Haofan Lu, Yi Yu, Ankit Jain, Yee Sin Ang, and Wee-Liat Ong "Deep learning techniques elucidate and modify the shape factor to extend the effective medium theory beyond its original formulation", International Journal of Heat and Mass Transfer 184 122305 (2021).
  20. Sundheep R. and Ankit Jain "Contact passivatio for defect mitigation in multi-dimensional perovskite interfaces", Applied Physics Letters 119 141602 (2021).
  21. Amey G. Gokhale, Dhvaneel Visaria, and Ankit Jain "Cross-plane thermal transport in MoS2", Physical Review B 104 115403 (2021).
  22. Harish P. Veeravenkata and Ankit Jain "Density functional theory driven phononic thermal conductivity prediction of biphenylene: A comparison with graphene", Carbon 183 893 (2021).
  23. Ankit Jain "Multichannel thermal transport in crystalline Tl3VSe4", Physical Review B 102 201201 (2020).
  24. Dhvaneel Visaria and Ankit Jain "Machine-learning-assisted space-transformation accelerates discovery of high thermal conductivity alloys", Applied Physics Letters 117 202107 (2020).
  25. Raul Flores, Christopher Paolucci, Kirsten Winther, Ankit Jain, Jose Torres, Muratahan Aykol, Joseph Montaya, Jens K Norskov, Michal Bajdich, and Thomas Bligaard "Active Learning Accelearted Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction", Chemistry of Materials 32 5854 (2020).
  26. Oleksandr Voznyy, Larissa Levina, James Fan, Mikhail Askerka, Ankit Jain, Min-Jae Choi, Olivier Ouellete, Petar Todorovic, Laxmi Sagar, and Edward H Sargent, "Machine Learning Accelerates Discovery of Optimal Colloidal Quantum Dot Synthesis", ACS Nano 13 11122 (2019).
  27. Ankit Jain, Zhenbin Wang, and Jens K Norskov, "Stable Two-dimensional Materials for Oxygen Reduction and Oxygen Evolution Reactions", ACS Energy Letters 4 1410 (2019).
  28. Alan JH McGaughey, Ankit Jain, Hyun-Young Kim, and Bo Fu, "Phonon properties and thermal conductivity from first principles, lattice dynamics, and the Boltzmann transport equation", Journal of Applied Physics 125 011101 (2019).
  29. Ankit Jain and Thomas Bligaard, "Atomic-position independent descriptor for machine learning of material properties", Physical Review B 98 214112 (2018).
  30. Cao-Thang Dinh*, Ankit Jain*, F Pelayo García de Arquer*, Phil De Luna, Jun Li, Ning Wang, Xueli Zheng, Jun Cai, Benjamin Z Gregory, Oleksandr Voznyy, Bo Zhang, Min Liu, David Sinton, Ethan J Crumlin, and Edward H Sargent, "Multi-site electrocatalysts for hydrogen evolution in neutral media by destabilization of water molecules", Nature Energy 4 107 (2018).
  31. Makhsud I Saidaminov, Junghwan Kim, Ankit Jain, Rafael Quintero-Bermudez, Hairen Tan, Guankui Long, Furui Tan, Andrew Johnston, Yicheng Zhao, Oleksandr Voznyy, and Edward H Sargent, "Suppression of atomic vacancies via incorporation of isovalent small ions to increase the stability of halide perovskite solar cells in ambient air", Nature Energy 3 648 (2018).
  32. Xiwen Gong, Oleksandr Voznyy, Ankit Jain, Wenjia Liu, Randy Sabatini, Zachary Piontkowski, Grant Walters, Golam Bappi, Sergiy Nokhrin, Oleksandr Bushuyev, Mingjian Yuan, Riccardo Comin, David McCamant, Shana O Kelley, and Edward H Sargent, "Electron–phonon interaction in efficient perovskite blue emitters", Nature Materials 17 550 (2018).
  33. Kevin D Parrish, Justin R Abel, Ankit Jain, Jonathan A Malen, Alan JH McGaughey, "Phonon-boundary scattering in nanoporous silicon films: Comparison of Monte Carlo techniques", Journal of Applied Physics 122 125101 (2018).
  34. Ankit Jain, Oleksandr Voznyy, Marek Korkusinski, Pawel Hawrylak, and Edward H Sargent, "Ultrafast Carrier Trapping in Thick-Shell Colloidal Quantum Dots", The Journal of Physical Chemistry Letters 8 3179 (2017).
  35. Li Na Quan, Rafael Quintero‐Bermudez, Oleksandr Voznyy, Grant Walters, Ankit Jain, James Zhangming Fan, Xueli Zheng, Zhenyu Yang, and Edward H Sargent, "Highly emissive green perovskite nanocrystals in a solid state crystalline matrix", Advanced Materials 29 1605945 (2017).
  36. Fengjia Fan, Oleksandr Voznyy, Randy P Sabatini, Kristopher T Bicanic, Michael M Adachi, James R McBride, Kemar R Reid, Young-Shin Park, Xiyan Li, Ankit Jain, Rafael Quintero-Bermudez, Mayuran Saravanapavanantham, Min Liu, Marek Korkusinski, Pawel Hawrylak, Victor I Klimov, Sandra J Rosenthal, Sjoerd Hoogland, and Edward H Sargent, "Continuous-wave lasing in colloidal quantum dot solids enabled by facet-selective epitaxy", Nature 544 75 (2017).
  37. Ankit Jain, Oleksandr Voznyy, and Edward H Sargent, "High-throughput screening of lead-free perovskite-like materials for optoelectronic applications", The Journal of Physical Chemistry C 121 7183 (2017).
  38. Hairen Tan, Ankit Jain, Oleksandr Voznyy, Xinzheng Lan, F Pelayo García de Arquer, James Z Fan, Rafael Quintero-Bermudez, Mingjian Yuan, Bo Zhang, Yicheng Zhao, Fengjia Fan, Peicheng Li, Li Na Quan, Yongbiao Zhao, Zheng-Hong Lu, Zhenyu Yang, Sjoerd Hoogland, and Edward H Sargent, "Efficient and stable solution-processed planar perovskite solar cells via contact passivation", Science 355 722 (2017).
  39. Ankit Jain, Oleksandr Voznyy, Sjoerd Hoogland, Marek Korkusinski, Pawel Hawrylak, and Edward H Sargent, "Atomistic Design of CdSe/CdS Core–Shell Quantum Dots with Suppressed Auger Recombination", Nano Letters 16 6491 (2016).
  40. Riccardo Comin, Michael K Crawford, Ayman H Said, Norman Herron, William E Guise, Xiaoping Wang, Pamela S Whitfield, Ankit Jain, Xiwen Gong, Alan JH McGaughey, and Edward H Sargent, "Lattice dynamics and the nature of structural transitions in organolead halide perovskites", Physical Review B 94 094301 (2016).
  41. Younghoon Kim, Zhenyu Yang, Ankit Jain, Oleksandr Voznyy, Gi‐Hwan Kim, Min Liu, Li Na Quan, F Pelayo García de Arquer, Riccardo Comin, James Z Fan, and Edward H Sargent, "Pure Cubic‐Phase Hybrid Iodobismuthates AgBi2I7 for Thin‐Film Photovoltaics", Angewandte Chemie International Edition 55 9586 (2016).
  42. Oleksandr Voznyy, Junais Habeeb Mokkath, Ankit Jain, Edward H Sargent, and Udo Schwingenschlögl, "Computational Study of Magic-Size CdSe Clusters with Complementary Passivation by Carboxylic and Amine Ligands", The Journal of Physical Chemistry C 120 10015 (2016).
  43. Ankit Jain and Alan JH McGaughey, "Thermal transport by phonons and electrons in aluminum, silver, and gold from first principles", Physical Review B Rapid 93 081206 (2016).
  44. Ankit Jain and Alan JH McGaughey, "Effect of exchange–correlation on first-principles-driven lattice thermal conductivity predictions of crystalline silicon", Computational Materials Science 110 115 (2015).
  45. Zhi Liang, Ankit Jain, Alan JH McGaughey, and Pawel Keblinski, "Molecular simulations and lattice dynamics determination of Stillinger-Weber GaN thermal conductivity", Journal of Applied Physics 118 125104 (2015).
  46. Ankit Jain and Alan JH McGaughey, "Strongly anisotropic in-plane thermal transport in single-layer black phosphorene", Scientific Reports 5 8501 (2015).
  47. Kevin D Parrish, Ankit Jain, Jason M Larkin, Wissam A Saidi, and Alan JH McGaughey, "Origins of thermal conductivity changes in strained crystals", Physical Review B 90 235201 (2014).
  48. Ankit Jain and Alan JH McGaughey, "Thermal conductivity of compound semiconductors: Interplay of mass density and acoustic-optical phonon frequency gap", Journal of Applied Physics 116 073503 (2014).
  49. Ankit Jain, Ying-Ju Yu, and Alan JH McGaughey, "Phonon transport in periodic silicon nanoporous films with feature sizes greater than 100 nm", Physical Review B 87 195301 (2013).
  50. Alan JH McGaughey and Ankit Jain, "Nanostructure thermal conductivity prediction by Monte Carlo sampling of phonon free paths", Applied Physics Letters 100 061911 (2012).

Openings

We are expanding!

We are looking for motivated candidates with interest(s) in thermal transport, machine learning, high-throughput calculations, atomistic simulations, catalysis, and/or coding to join our team. We do not expect candidates to have prior knowledge on these topics but we ONLY hire candidates who are passionate about learning.

Copyright © Ankit Jain 2019