348 citations · 1k across the 41 of their papers we have counts for
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Explainable machine learning to enable high-throughput electrical conductivity optimization and discovery of doped conjugated polymers
Ji Wei Yoon, Adithya Kumar, Pawan Kumar +3
The combination of high-throughput experimentation techniques and machine learning (ML) has recently ushered in a new era of accelerated material discovery, enabling the identifica…
Accelerated automated screening of viscous graphene suspensions with various surfactants for optimal electrical conductivity
Daniil Bash, Frederick Hubert Chenardi, Zekun Ren +5
Functional composite thin films have a wide variety of applications in flexible and/or electronic devices, telecommunications and multifunctional emerging coatings. Rapid screening…
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…