Nakul Rampal

2.0k citations
28 papers · 1.1k indexed · 6 hit papers · h-index 18

Nakul Rampal

28 papers receiving 1.1k citations

Hit Papers

Large language models for r...402023202620242025255075100

Peers

Nakul Rampal
Comparison fields: 5 of 93
  • Inorganic Chemistry 510
  • Materials Chemistry 614
  • Process Chemistry and Technology 35
  • Biomaterials 107
  • Analytical Chemistry 70
Replace Weicong Liu with:
Weicong Liu China
Mehrdad Asgari Switzerland
Qisong Xu Singapore
Yong‐Qing Huang China
Yi Luan China
Orysia Zaremba Spain
En Lin China
Yufang Wu China
Nakul Rampal relative to Weicong Liu China Weicong Liu's profile →
Citations per field
00.5×4.5×
Weicong Liu · 1×
Citations per year

Countries citing papers authored by Nakul Rampal

Since Specialization
Citations

This map shows the geographic impact of Nakul Rampal's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nakul Rampal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nakul Rampal more than expected).

Fields of papers citing papers by Nakul Rampal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nakul Rampal. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nakul Rampal. The network helps show where Nakul Rampal may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Nakul Rampal, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nakul Rampal Line = papers co-authored together Nakul Rampal links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2
Large language models for reticular chemistrybreakdown →
202540
3
Image and data mining in reticular chemistry powered by GPT-4Vbreakdown →
202436
4
Harvesting Water from Air with High-Capacity, Stable Furan-Based Metal–Organic Frameworksbreakdown →
202447
5 202410
6
A GPT‐4 Reticular Chemist for Guiding MOF Discovery**breakdown →
2023101
7 202334
8 202372
9
Shaping the Water-Harvesting Behavior of Metal–Organic Frameworks Aided by Fine-Tuned GPT Modelsbreakdown →
202379
10
ChatGPT Research Group for Optimizing the Crystallinity of MOFs and COFsbreakdown →
202388
11 20234
12 202337
13 2021131
14 202112
15 202131
16 202140
17 20217
18 202051
19 202017
20 202017

About Nakul Rampal

Nakul Rampal is a scholar working on Inorganic Chemistry, Structural Biology and Analytical Chemistry, having authored 28 papers that have together received 1.1k indexed citations. Recurring topics across this work include Metal-Organic Frameworks: Synthesis and Applications (17 papers), Machine Learning in Materials Science (7 papers), Covalent Organic Framework Applications (3 papers), Petroleum Processing and Analysis (3 papers), Topic Modeling (2 papers), Supramolecular Chemistry and Complexes (2 papers), Membrane Separation and Gas Transport (2 papers) and Nanoparticle-Based Drug Delivery (2 papers). The work is most often cited by research in Inorganic Chemistry (510 citations), Materials Chemistry (614 citations) and Process Chemistry and Technology (35 citations). Nakul Rampal has collaborated with scholars based in United States, United Kingdom and Saudi Arabia. Frequent co-authors include David Fairen‐Jiménez, Omar M. Yaghi, Zhiling Zheng, Christian Borgs, Jennifer Chayes, Zichao Rong, P. Vairavel, Xu Chen, Gautham Jeppu and Ali H. Alawadhi. Their work appears in journals such as Journal of the American Chemical Society, Advanced Materials and Angewandte Chemie International Edition.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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