no code implementations • 18 Nov 2017 • Sheshera Mysore, Edward Kim, Emma Strubell, Ao Liu, Haw-Shiuan Chang, Srikrishna Kompella, Kevin Huang, Andrew McCallum, Elsa Olivetti
In this work, we present a system for automatically extracting structured representations of synthesis procedures from the texts of materials science journal articles that describe explicit, experimental syntheses of inorganic compounds.
no code implementations • 6 Dec 2018 • Daniel Schwalbe-Koda, Zach Jensen, Elsa Olivetti, Rafael Gomez-Bombarelli
Predicting and directing polymorphic transformations is a critical challenge in zeolite synthesis.
Graph Similarity Materials Science
1 code implementation • 31 Dec 2018 • Edward Kim, Zach Jensen, Alexander van Grootel, Kevin Huang, Matthew Staib, Sheshera Mysore, Haw-Shiuan Chang, Emma Strubell, Andrew McCallum, Stefanie Jegelka, Elsa Olivetti
Leveraging new data sources is a key step in accelerating the pace of materials design and discovery.
no code implementations • WS 2019 • Sheshera Mysore, Zach Jensen, Edward Kim, Kevin Huang, Haw-Shiuan Chang, Emma Strubell, Jeffrey Flanigan, Andrew McCallum, Elsa Olivetti
Materials science literature contains millions of materials synthesis procedures described in unstructured natural language text.
1 code implementation • 2 Jun 2022 • Hyeonsu B. Kang, Sheshera Mysore, Kevin Huang, Haw-Shiuan Chang, Thorben Prein, Andrew McCallum, Aniket Kittur, Elsa Olivetti
Exposure to ideas in domains outside a scientist's own may benefit her in reformulating existing research problems in novel ways and discovering new application domains for existing solution ideas.
no code implementations • 21 Oct 2022 • Elton Pan, Christopher Karpovich, Elsa Olivetti
A major obstacle to the realization of novel inorganic materials with desirable properties is the inability to perform efficient optimization across both materials properties and synthesis of those materials.
no code implementations • EMNLP 2021 • Tim O’Gorman, Zach Jensen, Sheshera Mysore, Kevin Huang, Rubayyat Mahbub, Elsa Olivetti, Andrew McCallum
Material science synthesis procedures are a promising domain for scientific NLP, as proper modeling of these recipes could provide insight into new ways of creating materials.