Pavel Nikolaev

United States Air Force Research Laboratory

Papers

Total Citations

478

H-Index

About

Pavel Nikolaev is a pioneering figure in the autonomous experimentation of advanced nanomaterials, most notably carbon nanotubes. His research lies at the intersection of materials science and artificial intelligence, where he has fundamentally redefined how new materials are discovered and optimized. Nikolaev’s seminal 2016 paper, “Autonomy in materials research: a case study in carbon nanotube growth,” has garnered over 377 citations, establishing a foundational framework for closed-loop, self-driving laboratories. This work demonstrated that an AI system could design, conduct, and analyze experiments more rapidly than traditional human-led methods, dramatically accelerating the materials development cycle. Earlier, his 2014 study on “Discovery of Wall-Selective Carbon Nanotube Growth Conditions via Automated Experimentation” (101 citations) showcased the power of this approach to solve a long-standing challenge: precisely controlling nanotube chirality and wall number during synthesis. By integrating robotics, machine learning, and high-throughput characterization, Nikolaev has not only advanced the practical production of high-quality nanotubes for electronics and conductive wires but also inspired a new generation of researchers to embrace automation as a core tool for scientific discovery.