Sylvester Zhang

McGill University

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Philippe Schwaller

École Polytechnique Fédérale de Lausanne

Ben Blaiszik

Argonne National Laboratory

Ian Foster

Argonne National Laboratory

Joshua D. Bocarsly

University of Houston

Jiale Shi

Hebei University of Technology

Alexander Al-Feghali

McGill University

Alishba Imran

University of California, Berkeley

Marcus Schwarting

University of Chicago

Ankur K. Gupta

Lawrence Berkeley National Laboratory

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Duke University

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École Polytechnique Fédérale de Lausanne

McGill University

Argonne National Laboratory

University of Cambridge

University of Chicago

University of British Columbia

University of California, Berkeley

Federal Institute For Materials Research and Testing

Humboldt-Universität zu Berlin

Chinese Academy of Sciences

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Author response for "14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon"

Kevin Maik Jablonka Qianxiang Ai Alexander Al-Feghali Shruti Badhwar Joshua D. Bocarsly

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10.1039/d3dd00113j/v3/response1

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Polystyrene-Microsphere-Assisted Patterning of ZnO Nanostructures: Growth and Characterization

Journal of Nanoscience and Nanotechnology (2013)

Jie Dong X. W. Zhang Sylvester Zhang Hairen Tan Z. G. Yin

In this work, periodic arrays of various ZnO nanostructures were fabricated on both Si and GaN substrates via a facile hydrothermal process. To realize the site-specific growth, two kinds of masks were introduced. The polystyrene (PS) microsphere self-assembled monolayer (SAM) was employed as the mask to create a patterned seed layer to guide the growth of ZnO nanostructures. However, the resulting ZnO nanostructures are non-equidistant, and the diameter of the ZnO nanostructures is uncontrollable. As an alternative, TiO2 sol was used to replicate the PS microsphere SAM, and the inverted SAM (ISAM) mask was obtained by extracting the PS microspheres with toluene. By using the ISAM mask, the hexagonal periodic array of ZnO nanostructures with high uniformity were readily produced. Furthermore, the effect of the underlying substrates on the morphology of ZnO nanostructures has been investigated. It is found that the highly ordered and vertically aligned ZnO nanorods epitaxially grow on the GaN substrate, while the ZnO nanoflowers on Si substrates are random oriented.

Nanorod

Polystyrene

Characterization

Nanosphere lithography

10.1166/jnn.2013.5980

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14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon

arXiv (Cornell University) (2023)

Kevin Maik Jablonka Qianxiang Ai Alexander Al-Feghali Shruti Badhwar Joshua D. Bocarsly

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.

Reflection

10.48550/arxiv.2306.06283

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

arXiv (Cornell University) (2024)

Yann Zimmermann Adib Bazgir Zartashia Afzal Fariha Agbere Qianxiang Ai

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 hybrid locations, resulting in 34 team submissions. The submissions spanned seven key application areas and demonstrated the diverse utility of LLMs for applications in (1) molecular and material property prediction; (2) molecular and material design; (3) automation and novel interfaces; (4) scientific communication and education; (5) research data management and automation; (6) hypothesis generation and evaluation; and (7) knowledge extraction and reasoning from scientific literature. Each team submission is presented in a summary table with links to the code and as brief papers in the appendix. Beyond team results, we discuss the hackathon event and its hybrid format, which included physical hubs in Toronto, Montreal, San Francisco, Berlin, Lausanne, and Tokyo, alongside a global online hub to enable local and virtual collaboration. Overall, the event highlighted significant improvements in LLM capabilities since the previous year's hackathon, suggesting continued expansion of LLMs for applications in materials science and chemistry research. These outcomes demonstrate the dual utility of LLMs as both multipurpose models for diverse machine learning tasks and platforms for rapid prototyping custom applications in scientific research.

10.48550/arxiv.2411.15221

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Purification and preparation of Rhodobacter sphaeroides reaction centers for photocurrent measurements and atomic force microscopy characterization

STAR Protocols (2021)

Daniel Jun Sylvester Zhang Adrian Jan Grzędowski Amita Mahey J. Thomas Beatty

The formation of defined surfaces consisting of photosynthetic reaction centers (RCs) in biohybrid solar cells is challenging. Here, we start with the production of engineered RCs for oriented binding. RCs are deposited onto gold electrodes, and 6-mercapto-1-hexanol (MCH) is used to displace multilayers and non-specifically adsorbed RCs. The resulting electrode surfaces are analyzed for photocurrent generation using an intensity-modulated light and lock-in amplifier. Atomic force microscopy (AFM) is used to characterize the surface and the formation of RC structural assemblies. For complete details on the use and execution of this profile, please refer to Jun et al. (2021).

Rhodobacter sphaeroides

Photocurrent

Characterization

10.1016/j.xpro.2021.101044

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Computational Design of Gallium Imides for Methane Activation

Sylvester Zhang Peter H. McBreen Chao‐Jun Li Rustam Z. Khaliullin

Activation of the strong non-polar C-H bonds in methane is difficult, especially in solution. In this work, computational modeling is used to modify NacNac gallium imide, which has recently been shown to cleave unactivated sp3 C-H bonds in organic substrates with the aim of making it suitable for methane activation. Density functional theory predicts that the 123 kJ mol−1 methane activation barrier for the experimentally employed gallium imide can be reduced to 93 kJ mol−1 by changing substituents around the active gallium center. Furthermore, pre-straining the gallium imide reduces the reaction barrier to just 62 kJ mol−1. Dimerization of the gallium imides can be prevented with bulky groups that do not affect the reaction barrier. Several modified NacNac gallium imides are thus shown to be viable for the homogeneous activation of methane and higher alkanes.

10.26434/chemrxiv-2024-8hv7c

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Correlating structural assemblies of photosynthetic reaction centers on a gold electrode and the photocurrent - potential response

iScience (2021)

Daniel Jun Sylvester Zhang Adrian Jan Grzędowski Amita Mahey J. Thomas Beatty

The use of biomacromolecules is a nascent development in clean alternative energies. In applications of biosensors and biophotovoltaic devices, the bacterial photosynthetic reaction center (RC) is a protein-pigment complex that has been commonly interfaced with electrodes, in large part to take advantage of the long-lived and high efficiency of charge separation. We investigated assemblies of RCs on an electrode that range from monolayer to multilayers by measuring the photocurrent produced when illuminated by an intensity-modulated excitation light source. In addition, atomic force microscopy and modeling of the photocurrent with the Marcus-Hush-Chidsey theory detailed the reorganization energy for the electron transfer process, which also revealed changes in the RC local environment due to the adsorbed conformations. The local environment in which the RCs are embedded significantly influenced photocurrent generation, which has implications for electron transfer of other biomacromolecules deposited on a surface in sensor and photovoltaic applications employing a redox electrolyte.

Photocurrent

Photoinduced electron transfer

Photoelectrochemistry

10.1016/j.isci.2021.102500

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Citations (3)

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

Digital Discovery (2023)

Kevin Maik Jablonka Qianxiang Ai Alexander Al-Feghali Shruti Badhwar Joshua D. Bocarsly

We report the findings of a hackathon focused on exploring the diverse applications of large language models in molecular and materials science.

Reflection

10.1039/d3dd00113j