activity
20122021
most citedLight-Matter Coupling in Scalable Van der Waals Superlattices

111 citations · 529 across the 19 of their papers we have counts for

collaborators

19 papers

cond-mat.mtrl-sci2021

Scalable synthesis of 2D van der Waals superlattices

Michael J. Motala, Xiang Zhang, Pawan Kumar +23

Heterostructure materials form the basis of much of modern electronics, from transistors to lasers and light-emitting diodes. Recent years have seen a renewed focus on creating het…

physics.optics2021★ 49 cited

Self-Hybridized Polaritonic Emission from Layered Perovskites

Surendra B. Anantharaman, Christopher E. Stevens, Jason Lynch +9

Light-matter coupling in excitonic materials has been the subject of intense investigation due to emergence of new excitonic materials. Two-dimensional layered hybrid organic/inorg…

cond-mat.mtrl-sci2021★ 111 cited

Light-Matter Coupling in Scalable Van der Waals Superlattices

Pawan Kumar, Jason Lynch, Baokun Song +19

Two-dimensional (2D) crystals have renewed opportunities in design and assembly of artificial lattices without the constraints of epitaxy. However, the lack of thickness control in…

cond-mat.mes-hall2021★ 48 cited

Direct Opto-Electronic Imaging of 2D Semiconductor - 3D Metal Buried Interfaces

Kiyoung Jo, Pawan Kumar, Joseph Orr +10

The semiconductor-metal junction is one of the most critical factors for high performance electronic devices. In two-dimensional (2D) semiconductor devices, minimizing the voltage…

cond-mat.mtrl-sci2021

Electronic transport descriptors for the rapid screening of thermoelectric materials

Tianqi Deng, Jose Recatala-Gomez, Masato Ohnishi +11

The discovery of novel materials for thermoelectric energy conversion has potential to be accelerated by data-driven screening combined with high-throughput calculations. One way t…

physics.app-ph2020★ 1 cited

Machine learning and high-throughput robust design of P3HT-CNT composite thin films for high electrical conductivity

Daniil Bash, Yongqiang Cai, Vijila Chellappan +16

Combining high-throughput experiments with machine learning allows quick optimization of parameter spaces towards achieving target properties. In this study, we demonstrate that ma…