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R. Thapa

6 papers hereh-index 7104 citations14 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author4

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cond-mat.mtrl-sci5
  • cond-mat.dis-nn1
same name
  • R. Thapa — 12 papers, h 8
  • R. Thapa — 5 papers, h 24
  • R. Thapa — 3 papers, h 14
  • R. Thapa — 3 papers, h 3
  • R. Thapa — 2 papers, h 41
  • R. Thapa — 2 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192022
most citedAb initio simulation of amorphous graphite

52 citations · 102 across the 6 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cond-mat.mtrl-sci2022★ 1 cited

Formation of amorphous carbon multi-walled nanotubes from random initial configurations

C. Ugwumadu, R. Thapa, Y. Al-Majali +2

Amorphous carbon nanotubes (a-CNT) with up to four walls and sizes ranging from 200 to 3200 atoms have been simulated, starting from initial random configurations and using the Gau…

cond-mat.mtrl-sci2022★ 11 cited

Atomistic Nature of Amorphous Graphite

C. Ugwumadu, K. Nepal, R. Thapa +1

This paper focuses on the structural, electronic, and vibrational features of amorphous graphite [R. Thapa et. al., Phys. Rev. Lett. 128, 236402 (2022)]. The structure o…

cond-mat.dis-nn2022★ 18 cited

Simulation of multi-shell fullerenes using Machine-Learning Gaussian Approximation Potential

C. Ugwumadu, K. Nepal, R. Thapa +4

Multi-shell fullerenes "buckyonions" were simulated, starting from initially random configurations, using a density-functional-theory (DFT)-trained machine-learning carbon potentia…

cond-mat.mtrl-sci2022★ 52 cited

Ab initio simulation of amorphous graphite

Rajendra Thapa, Chinonso Ugwumadu, Kishor Nepal +2

A disorder-order transition from amorphous carbon (aC) to layered amorphous graphene (LAG) has been predicted using ab-initio methods. Amorphous carbon at densities close to the gr…

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