Materials Horizons Emerging Investigator Series: Professor Kedar Hippalgaonkar, Nanyang Technological University, Singapore

Asst. Prof. Kedar Hippalgaonkar is a joint appointee between the Materials Science and Engineering Department at Nanyang Technological University (NTU) and a Senior Scientist at the Institute of Materials Research and Engineering (IMRE) at the Agency for Science Technology and Research (A*STAR). He got his PhD from University of California at Berkeley in 2014 and his undergraduate degree in Mechanical Engineering at Purdue University in 2005. He is leading the Accelerated Materials Development for Manufacturing (AMDM) program from 2018–2023, focusing on the development of new materials, processes and optimization using machine learning, AI and high-throughput computations and experiments in electronic and plasmonic materials and polymers. He also led the Pharos Program on hybrid (inorganic–organic) thermoelectrics for ambient applications from 2016–2020.

Kedar's interests are in designing functional materials, especially for sustainability and energy applications. He has a fundamental knowledge of solid state physics as well as 1D (nanowires), 2D (TMDCs) and inorganic–organic (hybrid) materials. His approach to materials design is built on creating and utilizing materials data from high-performance computing and high-throughput experiments to synthesize and characterize materials for optical and electronic properties. In addition, he is developing machine learning and data science methods for materials discovery. He is keen on developing tools such as process optimization, design of experiments and materials and process fingerprinting from materials development to device applications. His background is in the transport properties of materials, specifically in understanding their thermal, optical and thermoelectric properties.

Read Kedar Hippalgaonkar's Emerging Investigator Series article ‘Electronic transport descriptors for the rapid screening of thermoelectric materials’ (10.1039/D1MH00751C) and read more about him in the interview below:

MH: Your recent Materials Horizons Communication reports two novel transport descriptors for the rapid screening of potential thermoelectric materials with high mobility and power factors. How has your research evolved from your first article to this most recent article and where do you see your research going in the future?

KH: My first research article was centered around the study of the reduction of thermal conductivity in nanostructured silicon nanowires. In the last 7 years, my team, along with so many wonderful collaborators from around the globe, have continued to plug away at a fundamental understanding of the charge and heat transport in semiconducting thermoelectrics – both organic and inorganic materials. In 2017, I started to look into how data-driven approaches could augment our methods and techniques. The present work is a result of using first author Deng Tianqi's EPIC STAR methodology of fast first principles calculations of charge scattering,¹ where we used a fantastic technique that can speed up the search for new compounds with desired functionalities – this was useful to unravel new physics of scattering in doped semiconductors, where the dielectric constant is important, in addition to the band effective mass. I hope to continue this work in the pursuit of new earth-abundant, high performance thermoelectric materials, where we are exploring the use of generative design and machine learning approaches with high-quality, high-throughput data. I would like to use insights from theoretical calculations and computational science, and translate this to realization through experiments in the lab. I envision the rapid discovery and synthesis of previously undetermined compounds, particularly those that are predicted to be metastable in the ternary and quaternary spaces. There is a whole library of compounds yet to be synthesized, with novel properties, creating a new world of materials and I hope to play a small role in this exciting time for materials research.

MH: What aspect of your work are you most excited about at the moment?

KH: At the moment, I am very excited about the possibility of using data-driven approaches to accelerate discovery. This takes many forms: the generation of high-quality data is the first step (both from computational studies, ensuring that accuracy is not compromised, as well as from rapid, automated ground truth experiments). Secondly, effective sampling and multi-parameter optimization is a critical tool, which allows for statistically efficient exploration and augments scientists’ intuitions. Thirdly, using such efficient techniques for guided exploration in a variety of fields will not only lead to the discovery of new materials, but also hitherto undiscovered properties and functions. Finally, the next frontier surely lies in machine intelligence for learning and the control of time-evolved functionalities under dynamical interactions between different material building blocks.

MH: In your opinion, what are the most important questions to be asked/answered in this field of research?

KH: How can we discover new functionalities in materials enabled by data-driven approaches? Here, we endeavour to go beyond the generative design of property-driven materials into non-equilibrium, metastable interactive intelligent materials, which can evolve as a function of time and space. Building the fundamentals to achieve this will require the confluence of data-driven approaches and automated materials synthesis and characterization, and is surely going to be the next important field of research.

MH: What do you find most challenging about your research?

KH: An open challenge is to extract knowledge and generalized models through a purely data-driven approach, therefore proving the efficacy of this approach for scientific discovery. Beyond science, the most challenging thing about my research, thankfully, is also the most enjoyable: the multi-disciplinary nature of the work that my team and collaborators are engaged in. I work with friends and colleagues in mathematics, physics, chemistry, materials science and engineering. Every day is a learning process.

MH: In which upcoming conferences or events may our readers meet you?

KH: I hope to travel to Boston for this year's Fall MRS meeting and to Hawaii for Pacifichem! I am involved in the organization of two virtual conferences – the Virtual Conference on Thermoelectrics (VCT) (https://vct2021.mines.edu/) and Materials for Humanity (MH-21), organized by the Materials Research Society, Singapore (https://mh21.mrs.org.sg/). I regularly muse on @nanotransport, so please do drop by the Twitterverse to say hi!

MH: How do you spend your spare time?

KH: I love sports, both watching and playing, especially outdoors. Hopefully as borders open up soon, we can resume hiking and traveling!

MH: Can you share one piece of career-related advice or wisdom with other early career scientists?

KH: Early career scientists today are under immense pressure – teaching, writing grants, peer reviewing, community building, just to name a few. I like to follow the mantra – ‘keep it simple’ – work with people you can be friends with, so that at least you are spending a whole lot of time with people you like and admire! Secondly, when things get overwhelming, I go back to doing what I’m most passionate about to re-focus – for me, it's reading about new research in related and new fields (I always have tons of tabs open in my internet browser). Building peaks of excellence with a breadth of knowledge keeps things exciting!

References

1. T. Deng, G. Wu, M. B. Sullivan, Z. M. Wong, K. Hippalgaonkar, J.-S. Wang and S.-W. Yang, npj Computational Materials, 2020, 6, 46.

---