The chart shows the distribution of publications by all Research.com ranked scientists in the field of Materials Science in 2026. The highlighted bar marks where Aiichiro Nakano sits on this spectrum.
This scientist: 476 publications — 85th percentile
85% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 1,163 publications or more.
The chart shows the D-index (discipline H-index) distribution of Materials Science scientists ranked by Research.com in 2026. The highlighted bar marks where Aiichiro Nakano sits on this spectrum.
This scientist: 66 D-Index — 59th percentile
59% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 165 D-Index or more.
Aiichiro Nakano is affiliated with the University of Southern California in the United States. Their research primarily spans the fields of Materials Science, Engineering, and Physics and Astronomy. Within these broader disciplines, Nakano's work focuses on several subfields, including Materials Chemistry, Electrical and Electronic Engineering, Atomic and Molecular Physics and Optics, Artificial Intelligence, and Biomedical Engineering.
Nakano's contributions cover a diverse range of topics such as Machine Learning in Materials Science, 2D Materials and Applications, Chalcogenide Semiconductor Thin Films, Spectroscopy and Quantum Chemical Studies, Electronic and Structural Properties of Oxides, Phase-change materials and chalcogenides, and Quantum Dots Synthesis and Properties.
The researcher has numerous publications in notable venues, including:
Among recent papers authored by Nakano are:
Frequent collaborators in Nakano's research include Priya Vashishta, Rajiv K. Kalia, Ken-ichi Nomura, Fuyuki Shimojo, and Aravind Krishnamoorthy. These collaborative efforts have resulted in extensive literature contributions, with many coauthored works.
Nakano has also authored books, including a publication titled Simulation with Python released in 2022 by Apress eBooks.
Honors include being named a Fellow of the American Physical Society (APS) in 2009-an award citing contributions to the development and implementation of scalable parallel and distributed algorithms for large-scale atomistic simulations. These simulations aim to predict, visualize, and analyze reaction processes related to novel nanomechanochemical phenomena spanning multiple spatiotemporal scales.
Timothy Campbell;Rajiv K. Kalia;Aiichiro Nakano;Priya Vashishta
Priya Vashishta;Rajiv K. Kalia;Aiichiro Nakano;José Pedro Rino
Izabela Szlufarska;Izabela Szlufarska;Aiichiro Nakano;Aiichiro Nakano;Priya Vashishta;Priya Vashishta
José P. Rino;Ingvar Ebbsjö;Rajiv K. Kalia;Aiichiro Nakano
Aiichiro Nakano
Cindy L. Rountree;Rajiv K. Kalia;Elefterios Lidorikis;Aiichiro Nakano
Vidya Kochat;Amey Apte;Jordan A. Hachtel;Hiroyuki Kumazoe;Hiroyuki Kumazoe
Fuyuki Shimojo;Fuyuki Shimojo;Ingvar Ebbsjö;Rajiv K. Kalia;Aiichiro Nakano
Priya Vashishta;Rajiv K. Kalia;Aiichiro Nakano;José Pedro Rino
Shuji Ogata;Elefterios Lidorikis;Fuyuki Shimojo;Aiichiro Nakano
Ken Ichi Nomura;Rajiv K. Kalia;Aiichiro Nakano;Priya Vashishta
A. Nakano;M.E. Bachlechner;R.K. Kalia;E. Lidorikis
Lindsay Bassman;Pankaj Rajak;Rajiv K. Kalia;Aiichiro Nakano
Chenfei Shen;Yihang Liu;Jiangbin Wu;Chi Xu
Aiichiro Nakano;Rajiv K. Kalia;Priya Vashishta
Yue Jiang;Sili Deng;Sungwook Hong;Jiheng Zhao
Hideaki Kikuchi;Rajiv K. Kalia;Aiichiro Nakano;Priya Vashishta
Fuyuki Shimojo;Fuyuki Shimojo;Satoshi Ohmura;Satoshi Ohmura;Rajiv K. Kalia;Aiichiro Nakano
Ken-ichi Nomura;Rajiv K. Kalia;Aiichiro Nakano;Priya Vashishta
Timothy J. Campbell;Timothy J. Campbell;Gurcan Aral;Shuji Ogata;Rajiv K. Kalia
Aiichiro Nakano;Rajiv K. Kalia;Ken ichi Nomura;Ashish Sharma
Rajiv K. Kalia;Aiichiro Nakano;Andrey Omeltchenko;Kenji Tsuruta
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