Sandip De

4.6k citations

39 papers · 2.2k indexed · 2 hit papers · h-index 17

Impact in

Materials Chemistry top 2%
- Machine Learning in Materials Science
- X-ray Diffraction in Crystallography
- Boron and Carbon Nanomaterials Research
Computational Theory and Mathematics top 1%
- Computational Drug Discovery Methods

Papers in ⓘ

Materials Chemistry 29
- Machine Learning in Materials Science 18
- Catalytic Processes in Materials Science 4
- X-ray Diffraction in Crystallography 4
Electrical and Electronic Engineering 10
- Semiconductor materials and devices 6
- Advancements in Semiconductor Devices and Circuit Design 5

Co-authors: Michele Ceriotti (9 shared papers)Gábor Cśanyi (3 shared papers)Albert P. Bartók (2 shared papers)Noam Bernstein (1 shared paper)Carl Poelking (1 shared paper)James R. Kermode (1 shared paper)Félix Musil (3 shared papers)Stefan Goedecker (6 shared papers)
Journals: ChemCatChem (2 papers)Journal of Physics Condensed Matter (2 papers)The Journal of Physical Chemistry A (2 papers)ACS Catalysis (2 papers)Physical Review Letters (2 papers)
Partner nations: Switzerland Germany United States

In The Last Decade

Sandip De

36 papers receiving 2.1k citations

Hit Papers

align trajectories log scale

Machine learning unifies the modeling of materials and molecules 2017 · 495 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2017 Science Advances
2016 Physical Chemistry Chemical Physics

Peers

Countries citing papers authored by Sandip De

Since Specialization

Citations

This map shows the geographic impact of Sandip De'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 Sandip De with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sandip De more than expected).

Fields of papers citing papers by Sandip De

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sandip De. 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 Sandip De. The network helps show where Sandip De may publish in the future.

Co-authors

The 25 scholars most cited alongside Sandip De, 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 Sandip De Line = papers co-authored together Sandip De links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Comparing molecules and solids across structural and alchemical space Physical Chemistry Chemical Physics ·Sandip De, Albert P. Bartók, Gábor Cśanyi, Michele Ceriotti Hit paper breakdown →	2016	543
2	Machine learning unifies the modeling of materials and molecules Science Advances ·Albert P. Bartók, Sandip De, Carl Poelking, Noam Bernstein, James R. Kermode, Gábor Cśanyi, Michele Ceriotti Hit paper breakdown →	2017	495
3	Chemical shifts in molecular solids by machine learning Nature Communications ·Federico M. Paruzzo, Albert Hofstetter, Félix Musil, Sandip De, Michele Ceriotti, Lyndon Emsley	2018	198
4	Energy Landscape of Fullerene Materials: A Comparison of Boron to Boron Nitride and Carbon Physical Review Letters ·Sandip De, Alexander Willand, Maximilian Amsler, Pascal Pochet, Luigi Genovese, Stefan Goedecker	2011	164
5	Machine learning for the structure–energy–property landscapes of molecular crystals Chemical Science ·Félix Musil, Sandip De, Jack Yang, Joshua E. Campbell, Graeme M. Day, Michele Ceriotti	2017	153
6	Large-Scale Computational Screening of Molecular Organic Semiconductors Using Crystal Structure Prediction Chemistry of Materials ·Jack Yang, Sandip De, Josh E. Campbell, Sean Li, Michele Ceriotti, Graeme M. Day	2018	91
7	Growth and Structural Properties of Mg_N (N = 10–56) Clusters: Density Functional Theory Study The Journal of Physical Chemistry A ·Ideh Heidari, Sandip De, Seyed Mohammad Ghazi, Stefan Goedecker, D. G. Kanhere	2011	61
8	Machine Learning-Guided Approach for Studying Solvation Environments Journal of Chemical Theory and Computation ·Yasemin Basdogan, Mitchell C. Groenenboom, Ethan Henderson, Sandip De, Susan B. Rempe, John A. Keith	2019	59
9	Accurate energy barriers for catalytic reaction pathways: an automatic training protocol for machine learning force fields npj Computational Materials ·Lars L. Schaaf, Edvin Fako, Sandip De, Ansgar Schäfer, Gábor Cśanyi	2023	51
10	Trap Generation in IL and HK layers during BTI / TDDB stress in scaled HKMG N and P MOSFETs Subhadeep Mukhopadhyay, K. Joshi, Veena Chaudhary, Nilesh Goel, Sandip De, R. K. Pandey, K. V. R. M. Murali, Souvik Mahapatra	2014	40
11	Low-energy boron fullerenes: Role of disorder and potential synthesis pathways Physical Review B ·Pascal Pochet, Luigi Genovese, Sandip De, Stefan Goedecker, Damien Caliste, S. Alireza Ghasemi, Kuo Bao, Thierry Deutsch	2011	37
12	Modeling high-entropy transition metal alloys with alchemical compression Physical Review Materials ·Nataliya Lopanitsyna, Guillaume Fraux, Maximilian A. Springer, Sandip De, Michele Ceriotti	2023	35
13	Learning Design Rules for Selective Oxidation Catalysts from High-Throughput Experimentation and Artificial Intelligence ACS Catalysis ·Lucas Foppa, Christopher Sutton, Luca M. Ghiringhelli, Sandip De, Patricia Löser, Stephan A. Schunk, Ansgar Schäfer, Matthias Scheffler	2022	35
14	A comprehensive DC/AC model for ultra-fast NBTI in deep EOT scaled HKMG p-MOSFETs Nilesh Goel, Subhadeep Mukhopadhyay, N. Nanaware, Sandip De, R. K. Pandey, K. V. R. M. Murali, Souvik Mahapatra	2014	24
15	Mapping and classifying molecules from a high-throughput structural database Journal of Cheminformatics ·Sandip De, Félix Musil, Teresa Ingram, Carsten Baldauf, Michele Ceriotti	2017	24
16	Relation between the Dynamics of Glassy Clusters and Characteristic Features of their Energy Landscape Physical Review Letters ·Sandip De, Bastian Schaefer, Ali Sadeghi, Michael Sicher, D. G. Kanhere, Stefan Goedecker	2014	23
17	Understanding Process Impact of Hole Traps and NBTI in HKMG p-MOSFETs Using Measurements and Atomistic Simulations IEEE Electron Device Letters ·Souvik Mahapatra, Sandip De, K. Joshi, Subhadeep Mukhopadhyay, R. K. Pandey, K. V. R. M. Murali	2013	19
18	Stabilizing Ru in Multicomponent Alloy as Acidic Oxygen Evolution Catalysts with Machine Learning-Enabled Structural Insights and Screening Journal of the American Chemical Society ·Arifin Luthfi Maulana, Shuang Han, Shan Yu, Pengcheng Chen, Carlos Lizandara‐Pueyo, Sandip De, Kerstin Schierle‐Arndt, Peidong Yang	2025	14
19	Defect-Engineered 3D Nanostructured MoS₂ for Detection of Ammonia Gas at Room Temperature ACS Applied Nano Materials ·Manoj K. Rajbhar, Sandip De, Gopal Sanyal, Avijit Kumar, Brahmananda Chakraborty, Shyamal Chatterjee	2023	13
20	Quantification and Tuning of Surface Oxygen Vacancies for the Hydrogenation of CO₂ on Indium Oxide Catalysts Chemie Ingenieur Technik ·Robert Baumgarten, Raoul Naumann d’Alnoncourt, Stephen Lohr, Esteban Gioria, Elias Frei, Edvin Fako, Sandip De, Chiara Boscagli, Matthias Drieß, Stephan A. Schunk, Frank Rosowski	2022	13

About Sandip De

Sandip De is a scholar working on Materials Chemistry, Electrical and Electronic Engineering, Computational Theory and Mathematics, Catalysis and Physical and Theoretical Chemistry, having authored 39 papers that have together received 2.2k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (18 papers), Computational Drug Discovery Methods (6 papers), Semiconductor materials and devices (6 papers), Advancements in Semiconductor Devices and Circuit Design (5 papers), Catalysis and Oxidation Reactions (5 papers), Crystallography and molecular interactions (4 papers), Catalytic Processes in Materials Science (4 papers) and X-ray Diffraction in Crystallography (4 papers). The work is most often cited by research in Materials Chemistry (1.7k citations), Computational Theory and Mathematics (581 citations), Physical and Theoretical Chemistry (202 citations), Catalysis (147 citations) and Structural Biology (16 citations). Sandip De has collaborated with scholars based in Switzerland, Germany and United States. Frequent co-authors include Michele Ceriotti, Gábor Cśanyi, Albert P. Bartók, Noam Bernstein, Carl Poelking, James R. Kermode, Félix Musil, Stefan Goedecker, Jack Yang and Graeme M. Day. Their work appears in journals such as ChemCatChem, Journal of Physics Condensed Matter, The Journal of Physical Chemistry A, ACS Catalysis and Physical Review Letters.

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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