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Aakash Ashok Naik

3 papers here

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

author position
  • middle author2

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • cond-mat.mtrl-sci1
  • cs.LG1
  • physics.comp-ph1
ORCID 0000-0002-6071-6786

identity via Semantic Scholar / OpenAlex

most citedReflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

5 citations · 5 across the 3 of their papers we have counts for

collaborators

3 papers

physics.comp-ph2024

An automated framework for exploring and learning potential-energy surfaces

Yuanbin Liu, Joe D. Morrow, Christina Ertural +6

Machine learning has become ubiquitous in materials modelling and now routinely enables large-scale atomistic simulations with quantum-mechanical accuracy. However, developing mach…

cs.LG2024★ 5 cited

Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Yoel Zimmermann, Adib Bazgir, Zartashia Afzal +141

Here, we present the outcomes from the second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hyb…

cond-mat.mtrl-sci2023

"Ultima Ratio": Simulating wide-range X-ray scattering and diffraction

Brian R. Pauw, Sofya Laskina, Aakash Naik +4

We demonstrate a strategy for simulating wide-range X-ray scattering patterns, which spans the small- and wide scattering angles as well as the scattering angles typically used for…

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