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7 results on '"Gastellu, Nicolas"'

1. Disentangling morphology and conductance in amorphous graphene

Author

Gastellu, Nicolas, Madanchi, Ata, and Simine, Lena

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Disordered Systems and Neural Networks, Physics - Chemical Physics
Abstract

Amorphous graphene or amorphous monolayer carbon (AMC) is a family of carbon films that exhibit a surprising sensitivity of electronic conductance to morphology. We combine deep learning-enhanced simulation techniques with percolation theory to analyze three morphologically distinct mesoscale AMCs. Our approach avoids the pitfalls of applying periodic boundary conditions to these fundamentally aperiodic systems or equating crystalline inclusions with conducting sites. We reproduce the previously reported dependence of charge conductance on morphology and explore the limitations of partial morphology descriptors in witnessing conductance properties. Finally, we perform crystallinity analysis of conductance networks along the electronic energy spectrum and show that they metamorphose from being localized on crystallites at band edges to localized on defects around the Fermi energy opening the possibility of control through gate voltage.

Published
2024

2. 14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon

Author

Jablonka, Kevin Maik, Ai, Qianxiang, Al-Feghali, Alexander, Badhwar, Shruti, Bocarsly, Joshua D, Bran, Andres M, Bringuier, Stefan, Brinson, L Catherine, Choudhary, Kamal, Circi, Defne, Cox, Sam, de Jong, Wibe A, Evans, Matthew L, Gastellu, Nicolas, Genzling, Jerome, Gil, María Victoria, Gupta, Ankur K, Hong, Zhi, Imran, Alishba, Kruschwitz, Sabine, Labarre, Anne, Lála, Jakub, Liu, Tao, Ma, Steven, Majumdar, Sauradeep, Merz, Garrett W, Moitessier, Nicolas, Moubarak, Elias, Mouriño, Beatriz, Pelkie, Brenden, Pieler, Michael, Ramos, Mayk Caldas, Ranković, Bojana, Rodriques, Samuel G, Sanders, Jacob N, Schwaller, Philippe, Schwarting, Marcus, Shi, Jiale, Smit, Berend, Smith, Ben E, Van Herck, Joren, Völker, Christoph, Ward, Logan, Warren, Sean, Weiser, Benjamin, Zhang, Sylvester, Zhang, Xiaoqi, Zia, Ghezal Ahmad, Scourtas, Aristana, Schmidt, KJ, Foster, Ian, White, Andrew D, and Blaiszik, Ben

Subjects
Macromolecular and Materials Chemistry, Chemical Sciences
Abstract

Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines.

Published
2023

3. Electronic Conduction Through Monolayer Amorphous Carbon Nano-Junctions

Author

Gastellu, Nicolas, Kilgour, Michael, and Simine, Lena

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Chemical Physics
Abstract

In molecular electronic conduction, exotic lattice morphologies often give rise to exotic behaviors. Among 2D systems, graphene is a notable example. Recently, a stable amorphous version of graphene called Monolayer Amorphous Carbon (MAC) was synthesized. MAC poses a new set of questions regarding the effects of disorder on conduction. In this Letter, we perform ensemble-level computational analysis of the coherent electronic transmission through MAC nano-fragments in search of defining characteristics. Our analysis, relying on a semi-empirical Hamiltonian (Pariser-Parr-Pople) and Landauer theory, showed that states near the Fermi energy ($E_F$) in MAC inherit partial characteristics of analogous surface states in graphene nano-fragments. Away from $E_F$, current is carried by a set of delocalized states which transition into a subset of insulating interior states at the band edges. Finally, we also found that quantum interference between the frontier orbitals is a common feature among MAC nano-fragments.

Published
2021

4. 14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon

Author

National Science Foundation (US), Swiss National Science Foundation, Ministerio de Ciencia e Innovación (España), Gil Matellanes, María Victoria [0000-0002-2258-3011], Jablonka, Kevin Maik, Ai, Qianxiang, Al-Feghali, Alexander, Badhwar, Shruti, Bocarsly, Joshua D, Bran, Andres M, Bringuier, Stefan, Brinson, L Catherine, Choudhary, Kamal, Circi, Defne, Cox, Sam, de Jong, Wibe A, Evans, Matthew L, Gastellu, Nicolas, Genzling, Jerome, Gil Matellanes, María Victoria, Gupta, Ankur K, Hong, Zhi, Imran, Alishba, Kruschwitz, Sabine, Labarre, Anne, Lála, Jakub, Liu, Tao, Ma, Steven, Majumdar, Sauradeep, Merz, Garrett W, Moitessier, Nicolas, Moubarak, Elias, Mouriño, Beatriz, Pelkie, Brenden, Pieler, Michael, Ramos, Mayk Caldas, Ranković, Bojana, Rodriques, Samuel G, Sanders, Jacob N, Schwaller, Philippe, Schwarting, Marcus, Shi, Jiale, Smit, Berend, Smith, Ben E, Van Herck, Joren, Völker, Christoph, Ward, Logan, Warren, Sean, Weiser, Benjamin, Zhang, Sylvester, Zhang, Xiaoqi, Zia, Ghezal Ahmad, Scourtas, Aristana, Schmidt, K J, Foster, Ian, White, Andrew D, Blaiszik, Ben, National Science Foundation (US), Swiss National Science Foundation, Ministerio de Ciencia e Innovación (España), Gil Matellanes, María Victoria [0000-0002-2258-3011], Jablonka, Kevin Maik, Ai, Qianxiang, Al-Feghali, Alexander, Badhwar, Shruti, Bocarsly, Joshua D, Bran, Andres M, Bringuier, Stefan, Brinson, L Catherine, Choudhary, Kamal, Circi, Defne, Cox, Sam, de Jong, Wibe A, Evans, Matthew L, Gastellu, Nicolas, Genzling, Jerome, Gil Matellanes, María Victoria, Gupta, Ankur K, Hong, Zhi, Imran, Alishba, Kruschwitz, Sabine, Labarre, Anne, Lála, Jakub, Liu, Tao, Ma, Steven, Majumdar, Sauradeep, Merz, Garrett W, Moitessier, Nicolas, Moubarak, Elias, Mouriño, Beatriz, Pelkie, Brenden, Pieler, Michael, Ramos, Mayk Caldas, Ranković, Bojana, Rodriques, Samuel G, Sanders, Jacob N, Schwaller, Philippe, Schwarting, Marcus, Shi, Jiale, Smit, Berend, Smith, Ben E, Van Herck, Joren, Völker, Christoph, Ward, Logan, Warren, Sean, Weiser, Benjamin, Zhang, Sylvester, Zhang, Xiaoqi, Zia, Ghezal Ahmad, Scourtas, Aristana, Schmidt, K J, Foster, Ian, White, Andrew D, and Blaiszik, Ben

Abstract

Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines.

Published
2023

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