Mr. Lakshminarayanan Madhavkrishnan and Dr. Rajdeep Dutta (15 September 2021)

Topic: Interpretable physics-based models compared with symbolic regression for hopping transport in organic field-effect transistors

Speakers: Lakshminarayanan Madhavkrishnan (School of Electrical and Electronic Engineering, Nanyang Technological University) and Rajdeep Dutta (Institute for Infocomm Research, Agency for Science Technology and Research)

We’re excited to announce the speakers for our next seminar, Lakshminarayanan Madhavkrishnan (Madhav) from School of Electrical and Electronic Engineering, Nanyang Technological University, and Rajdeep Dutta from Institute for Infocomm Research, Agency for Science Technology and Research, to bring us:

“Interpretable physics-based models compared with symbolic regression for hopping transport in organic field-effect transistors”

Abstract

Charge transport in organic semiconductors is dominated by the extent of disorder. Several theories have been proposed to study transport, but they require numerous and often convoluted assumptions. Here, we examine the efficacy of one of the conventional models, namely the Bassler model, in describing the temperature-dependent field-effect mobility of organic field-effect transistors. Using data-driven techniques, that do not require the prior assumption of any existing theory, we propose a simplification of the complexity of not only the number, but also the nature of parameters required by the model to describe the mobility by adopting (1) a data-driven Symbolic Regression (SR) approach and (2) a physics-inspired Renormalization approach. We discuss the merits and demerits of each approach and highlight that physics-inspired fitting techniques point towards a more generalized methodology.

Bio

Lakshminarayanan Madhavkrishnan (Madhav) is a PhD student in the School of Electrical and Electronic Engineering in Nanyang Technological University, Singapore since 2017, jointly supervised by Prof. Wei Lin Leong and Prof. Kedar Hippalgaonkar. Before starting his PhD, he obtained his integrated undergraduate and Masters degrees from the Hyderabad Campus of Birla Institute of Technology and Science (BITS), Pilani. His interests lie in studying structure-property relationships in organic materials using machine learning methods.

Rajdeep Dutta received the Bachelor of Engineering degree in Electrical Engineering, the Master of Science degree in Aerospace Engineering, and the Doctor of Philosophy degree in Electrical and Computer Engineering from Bengal Engineering and Science University (BESU) at Shibpur, Indian Institute of Science (IISc) at Bangalore, and University of Texas at San Antonio (UTSA), respectively. He is currently a research Scientist at the department of Machine Intellection, Institute for Infocom Research, Agency for Science Technology and Research (A*STAR), Singapore. Previously, he worked as a software scientist at Parabole LLC and as a postdoctoral research fellow at the department of Civil Engineering, IISc, Bangalore, India.

Very much looking forward to the seminar – hope to see you all on Wednesday: (SGT) 9am, Wed, 15 September 2021!

https://mit.zoom.us/j/96231985116

Warmest regards,

@Thway @Kedar @Tonio

Prof. Taro Hitosugi (1 September 2021)

Topic: How artificial intelligence and robotics change the way of our research?

Speaker: Prof. Taro Hitosugi from Tokyo Institute of Technology

We’re excited to announce our next speaker, Prof. Taro Hitosugi from Tokyo Institute of Technology, to bring us:

“How artificial intelligence and robotics change the way of our research?”

Abstract

Future materials-science research will involve autonomous synthesis and characterization, requiring an approach that combines machine learning, robotics, and big data. Here, we highlight our recent experiments in autonomous materials exploration. We show the synthesis and resistance minimization of Nb-doped TiO2 thin films as a proof of concept. The system fully automates sample transfer, thin film deposition, and growth condition optimization—all addressing the physical aspects of fabrication. Combining Bayesian optimization with robotics illustrates how the required speed and volume of a future big-data collection in materials science will be achieved and demonstrate the potential of this approach. We briefly discuss the outlook and significance of these results and discuss a new materials research style to accelerate materials science.

Biography

Dr. Taro Hitosugi is a Professor in the School of Materials and Chemical Technology at the Tokyo Institute of Technology (Tokyo Tech). He also serves as a Deputy Director of the Tokyo Tech Academy for Convergence of Materials and Informatics (TAC-MI). His research interests involve surfaces and interfaces of materials for electronics and energy applications. He has recently succeeded in autonomous materials synthesis by machine learning and robotics, aiming to accelerate materials science research. He is an editorial advisory board member of APL Materials and an associate editor of Science and Technology of Advanced Materials (STAM). He has published more than 150 refereed papers in leading academic journals.

Very much looking forward to the seminar – hope to see you all on Wednesday: (SGT) 9am, Wed, 1 September! https://mit.zoom.us/j/96231985116

Warmest regards, @Thway @kedar @Tonio

Asst. Prof. Tan Kwan Wee (18 August 2021)

Topic: Transient Laser Heating Approaches in Synthesis and Characterization of Hybrid Nanostructures.

Speaker: Asst. Prof. Tan Kwan Wee from Nanyang Technological University

We’re excited to announce our next speaker, Asst. Prof. Tan Kwan Wee from Nanyang Technological University, to bring us:

“Transient Laser Heating Approaches in Synthesis and Characterization of Hybrid Nanostructures”

Abstract

Transient laser heating on nano- to millisecond time scales provide new pathways to generate multiscale functional materials and phases. In this talk I will describe some of our synthesis approaches to form self-assembly–directed mesoporous polymer and crystalline silicon nanostructures. We will also introduce the X-ray probed laser anneal mapping technique to study phase transitions of metastable oxides and metal alloys.

Biography

Kwan W. Tan is an assistant professor at Nanyang Technological University. He received his PhD, MEng and BEng in materials science from Cornell University, Massachusetts Institute of Technology and Nanyang Technological University. His research interests include exploring new approaches coupling self-assembly and nonequilibrium thermal annealing to generate multifunctional material structures and combinations.

Very much looking forward to the seminar – hope to see you all on Wednesday: (SGT) 9am, Wed, 18 August! https://mit.zoom.us/j/96231985116

Warmest regards, @Thway @kedar @Tonio