Papers citing Making the collective knowledge of chemistry open and machine actionable
Data storage architectures to accelerate chemical discovery: data accessibility for individual laboratories and the community
Chemical Science · 2022
Rebekah Duke, Vinayak Bhat, Chad M. Risko
Read original paper ↗ ·Exploring electronic lab notebooks (ELNs) at a R1 institution in the Southeast USA
Digital Library Perspectives · 2022
Plato L. Smith II
Read original paper ↗ ·Machine Learning Yield Prediction from NiCOlit, a Small-Size Literature Data Set of Nickel Catalyzed C–O Couplings
Journal of the American Chemical Society · 2022
Jules Schleinitz, Maxime Langevin, Yanis Smail, Benjamin Wehnert, Laurence Grimaud, Rodolphe Vuilleumier
Read original paper ↗ ·Machine Learning in Tissue Engineering
Tissue Engineering Part A · 2022
Jason L. Guo, Michael Januszyk, Michael Thornton Longaker
Read original paper ↗ ·CRIPT: A Scalable Polymer Material Data Structure
ChemRxiv · 2022
Dylan J. Walsh, Weizhong Zou, Ludwig Schneider, Reid Mello, Michael E. Deagen, Joshua A. Mysona, Tzyy‐Shyang Lin, Juan Pablo, Klavs F. Jensen, Debra J. Audus, Bradley D. Olsen
Read original paper ↗ ·Into the Unknown: How Computation Can Help Explore Uncharted Material Space
Journal of the American Chemical Society · 2022
Austin M. Mroz, Víctor Posligua, Andrew Tarzia, Emma Helen Wolpert, Kim E. Jelfs
Read original paper ↗ ·Developing Catalysts via Structure‐Property Relations Discovered by Machine Learning: An Industrial Perspective
Chemie Ingenieur Technik · 2022
Hrishikesh Joshi, Nicole Wilde, Thomas S. Asche, Dorit Wolf
Read original paper ↗ ·Mindestinformationsstandards in der Chemie: Ein Appell zum besseren Umgang mit Forschungsdaten
Angewandte Chemie · 2022
Sonja Herres‐Pawlis, Felix Bach, Ian J. Bruno, Stuart J. Chalk, Nicole Jung, Johannes C. Liermann, Leah McEwen, Steffen Neumann, Christoph Steinbeck, Matthias Razum, Oliver Koepler
Read original paper ↗ ·Minimum Information Standards in Chemistry: A Call for Better Research Data Management Practices
Angewandte Chemie International Edition · 2022
Sonja Herres‐Pawlis, Felix Bach, Ian J. Bruno, Stuart J. Chalk, Nicole Jung, Johannes C. Liermann, Leah McEwen, Steffen Neumann, Christoph Steinbeck, Matthias Razum, Oliver Koepler
Read original paper ↗ ·Using genetic algorithms to systematically improve the synthesis conditions of Al-PMOF
Communications Chemistry · 2022
Nency P. Domingues, Seyed Mohamad Moosavi, Leopold Talirz, Kevin Maik Jablonka, Christopher P. Ireland, Fatmah Mish Ebrahim, Berend Smit
Read original paper ↗ ·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, Andres M Bran, Stefan A. Bringuier, L. Catherine Brinson, Kamal Kumar Choudhary, Defne Çırcı, Sam Cox, Wibe Albert de Jong, Matthew L. Evans, Nicolas Gastellu, Jérôme Genzling, M.V. Gil, Ankur Kumar Gupta, Zhi Hong, Alishba Imran, Sabine Kruschwitz, Anne Labarre, Jakub Lála, Tao Liu, Steven Ma, Sauradeep Majumdar, Garrett W Merz, Nicolas Moitessier, Elias Moubarak, Beatriz Mouriño, Brenden Galen Pelkie, Michael Pieler, Mayk Caldas Ramos, Bojana Ranković, Samuel G. Rodriques, Jacob N. Sanders, Philippe Schwaller, Marcus Schwarting, Jiale Shi, Berend Smit, Ben E. Smith, Joren Van Herck, Christoph Völker, Logan T. Ward, Sean Warren, Benjamin Weiser, Sylvester Zhang, Xiaoqi Zhang, Ghezal Ahmad Zia, Aristana Scourtas, K. J. Schmidt, Ian T Foster, Andrew Dickson White, Ben J. Blaiszik
Read original paper ↗ ·Engaging with Researchers and Raising Awareness of FAIR and Open Science through the FAIR+ Implementation Survey Tool (FAIRIST)
Data Science Journal · 2023
Christine R. Kirkpatrick, Kevin Coakley, Julianne Christopher, Inês Dutra
Read original paper ↗ ·GitHub as an open electronic laboratory notebook for real-time sharing of knowledge and collaboration
Digital Discovery · 2023
Kymberley R. Scroggie, Klementine J. Burrell-Sander, Peter J. Rutledge, Alice Motion
Read original paper ↗ ·Machine learning for industrial processes: Forecasting amine emissions from a carbon capture plant
Science Advances · 2023
Kevin Maik Jablonka, Charithea Charalambous, Eva Sánchez Fernández, Georg Wiechers, Juliana Garcia Moretz‐Sohn Monteiro, Peter Moser, Berend Smit, Susana García
Read original paper ↗ ·Machine Learning and Digital Manufacturing Approaches for Solid‐State Materials Development
Venue not supplied by source · 2023
Lawson T. Glasby, Emily H. Whaites, Peyman Z. Moghadam
Read original paper ↗ ·Overview of AI in the Understanding and Design of Nanoporous Materials
Venue not supplied by source · 2023
Seyed Mohamad Moosavi, Frits F. D. Daeyaert, Michael W. Deem, Germán Sastre
Read original paper ↗ ·Is GPT-3 all you need for low-data discovery in chemistry?
ChemRxiv · 2023
Kevin Maik Jablonka, Philippe Schwaller, Andres Ortega‐Guerrero, Berend Smit
Read original paper ↗ ·Community Resource for Innovation in Polymer Technology (CRIPT): A Scalable Polymer Material Data Structure
ACS Central Science · 2023
Dylan J. Walsh, Weizhong Zou, Ludwig Schneider, Reid Mello, Michael E. Deagen, Joshua A. Mysona, Tzyy‐Shyang Lin, Juan Pablo, Klavs F. Jensen, Debra J. Audus, Bradley D. Olsen
Read original paper ↗ ·An Ecosystem for Digital Reticular Chemistry
ACS Central Science · 2023
Kevin Maik Jablonka, Andrew Rosen, Aditi S. Krishnapriyan, Berend Smit
Read original paper ↗ ·LinChemIn: SynGraph—a data model and a toolkit to analyze and compare synthetic routes
Journal of Cheminformatics · 2023
Marta Pasquini, Marco Stenta
Read original paper ↗ ·LabInform ELN: A lightweight and flexible electronic laboratory notebook for academic research based on the open-source software DokuWiki
ChemRxiv · 2023
Mirjam Schröder, Till Biskup
Read original paper ↗ ·AI4Green: An Open-Source ELN for Green and Sustainable Chemistry
Journal of Chemical Information and Modeling · 2023
Samuel Boobier, Joseph C. Davies, Ivan N. Derbenev, Christopher M. Handley, Jonathan D. Hirst
Read original paper ↗ ·Achieving Digital Catalysis: Strategies for Data Acquisition, Storage and Use
Angewandte Chemie International Edition · 2023
Clara Patricia Marshall, Julia Schumann, Annette Trunschke
Read original paper ↗ ·Achieving Digital Catalysis: Strategies for Data Acquisition, Storage and Use
Angewandte Chemie · 2023
Clara Patricia Marshall, Julia Schumann, Annette Trunschke
Read original paper ↗ ·14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
PubMed · 2023
Kevin Maik Jablonka, Qianxiang Ai, Alexander Al‐Feghali, Shruti Badhwar, Joshua D. Bocarsly, Andres M Bran, Stefan A. Bringuier, L. Catherine Brinson, Kamal Kumar Choudhary, Defne Çırcı, Sam Cox, Wibe Albert de Jong, Matthew L. Evans, Nicolas Gastellu, Jérôme Genzling, M.V. Gil, Ankur Kumar Gupta, Zhi Hong, Alishba Imran, Sabine Kruschwitz, Anne Labarre, Jakub Lála, Tao Liu, Steven Ma, Sauradeep Majumdar, Garrett W Merz, Nicolas Moitessier, Elias Moubarak, Beatriz Mouriño, Brenden Galen Pelkie, Michael Pieler, Mayk Caldas Ramos, Bojana Ranković, Samuel G. Rodriques, Jacob N. Sanders, Philippe Schwaller, Marcus Schwarting, Jiale Shi, Berend Smit, Ben E. Smith, Joren Van Herck, Christoph Völker, Logan T. Ward, Sean Warren, Benjamin Weiser, Sylvester Zhang, Xiaoqi Zhang, Ghezal Ahmad Zia, Aristana Scourtas, K. J. Schmidt, Ian T Foster, Andrew Dickson White, Ben J. Blaiszik
Read original paper ↗ ·Artificial intelligence driven design of catalysts and materials for ring opening polymerization using a domain-specific language
Nature Communications · 2023
Nathaniel H. Park, Matteo Manica, Jannis Born, James L. Hedrick, Tim Erdmann, Dmitry Yu. Zubarev, Nil Adell Mill, Pedro L. Arrechea
Read original paper ↗ ·ML meets MLn: Machine learning in ligand promoted homogeneous catalysis
Artificial Intelligence Chemistry · 2023
Jonathan D. Hirst, Samuel Boobier, Jennifer Coughlan, Jessica Streets, Philippa L. Jacob, O. Pugh, Ender Özcan, Simon Woodward
Read original paper ↗ ·Revealing factors influencing polymer degradation with rank-based machine learning
Patterns · 2023
Weilin Yuan, Yusuke Hibi, Ryo Tamura, Masato Sumita, Yasuyuki Nakamura, Masanobu Naito, Koji Tsuda
Read original paper ↗ ·Results of a Three-Year Survey on the Implementation of Research Data Management and the Electronic Laboratory Notebook (ELN) Chemotion in an Advanced Inorganic Lab Course
Journal of Chemical Education · 2023
Fabian Fink, Alexander Hoffmann, Sonja Herres‐Pawlis
Read original paper ↗ ·FAIRifying STEM Data Ecosystem to Enhance Data Reuse
2022 IEEE Frontiers in Education Conference (FIE) · 2023
Phub Namgay, Pema Wangdi, Sangay Thinley, Thinley Namgyel
Read original paper ↗ ·Chemical Species Ontology for Data Integration and Knowledge Discovery
Journal of Chemical Information and Modeling · 2023
Laura Pascazio, Simon D. Rihm, Ali Naseri, Sebastian Mosbach, Jethro Akroyd, Markus Kraft
Read original paper ↗ ·Covalent Organic Frameworks: Opportunities for Rational Materials Design in Cancer Therapy
Angewandte Chemie · 2023
Lele Zhou, Qun Guan, Yu‐Bin Dong
Read original paper ↗ ·Covalent Organic Frameworks: Opportunities for Rational Materials Design in Cancer Therapy
Angewandte Chemie International Edition · 2023
Lele Zhou, Qun Guan, Yu‐Bin Dong
Read original paper ↗ ·Twenty years of nmrshiftdb2: A case study of an open database for analytical chemistry
Magnetic Resonance in Chemistry · 2023
Stefan Kühn, Heinz Kolshorn, Christoph Steinbeck, Nils E. Schlörer
Read original paper ↗ ·When Yield Prediction Does Not Yield Prediction: An Overview of the Current Challenges
Journal of Chemical Information and Modeling · 2023
Varvara Voinarovska, Mikhail Kabeshov, Dmytro Dudenko, Samuel Genheden, Igor V. Tetko
Read original paper ↗ ·Automated approaches, reaction parameterisation, and data science in organometallic chemistry and catalysis: towards improving synthetic chemistry and accelerating mechanistic understanding
Digital Discovery · 2024
Stuart C. Smith, Christopher S. Horbaczewskyj, Theo F. N. Tanner, Jacob J. Walder, Ian J. S. Fairlamb
Read original paper ↗ ·Chemistry in a graph: modern insights into commercial organic synthesis planning
Digital Discovery · 2024
Claudio Avila, Adam West, Anna Chiara Vicini, William Waddington, Christopher J. Brearley, James Clarke, Andrew M. Derrick
Read original paper ↗ ·Digital chemistry: navigating the confluence of computation and experimentation – definition, status quo, and future perspective
Digital Discovery · 2024
Stefan Bräse
Read original paper ↗ ·Knowledge graph representation of zeolitic crystalline materials
Digital Discovery · 2024
Aleksandar Kondinski, P. P. Rutkevych, Laura Pascazio, Dan N. Tran, Feroz Farazi, Srishti Ganguly, Markus Kraft
Read original paper ↗ ·Transforming research laboratories with connected digital twins
Nexus · 2024
Simon D. Rihm, Jiaru Bai, Aleksandar Kondinski, Sebastian Mosbach, Jethro Akroyd, Markus Kraft
Read original paper ↗ ·Leveraging large language models for predictive chemistry
Nature Machine Intelligence · 2024
Kevin Maik Jablonka, Philippe Schwaller, Andres Ortega‐Guerrero, Berend Smit
Read original paper ↗ ·Leveraging Text-to-Text Pretrained Language Models for Question Answering in Chemistry
ACS Omega · 2024
Dan N. Tran, Laura Pascazio, Jethro Akroyd, Sebastian Mosbach, Markus Kraft
Read original paper ↗ ·LinChemIn: Route Arithmetic─Operations on Digital Synthetic Routes
Journal of Chemical Information and Modeling · 2024
Marta Pasquini, Marco Stenta
Read original paper ↗ ·Digital Futures of Learning Pharmacology and Medicinal and Organic Chemistry
ACS Pharmacology & Translational Science · 2024
Fun Man Fung, Étienne Blanc, Xavier Coumoul
Read original paper ↗ ·Reaction Rebalancing: A Novel Approach to Curating Reaction Databases
ChemRxiv · 2024
Tieu-Long Phan, Klaus Weinbauer, Thomas Gärtner, Daniel Merkle, Jakob L. Andersen, Rolf Fagerberg, Peter Florian Stadler
Read original paper ↗ ·Reaction Rebalancing: A Novel Approach to Curating Reaction Databases
Research Square · 2024
Tieu-Long Phan, Klaus Weinbauer, Thomas Gärtner, Daniel Merkle, Jakob L. Andersen, Rolf Fagerberg, Peter Florian Stadler
Read original paper ↗ ·Advancing materials science through next-generation machine learning
Current Opinion in Solid State and Materials Science · 2024
Rohit Unni, Mingyuan Zhou, Peter R. Wiecha, Yuebing Zheng
Read original paper ↗ ·Artificial Intelligence for Retrosynthetic Planning Needs Both Data and Expert Knowledge
Journal of the American Chemical Society · 2024
Felix Strieth‐Kalthoff, Sara Szymkuć, Karol Molga, Alán Aspuru‐Guzik, Frank Glorius, Bartosz A. Grzybowski
Read original paper ↗ ·Promises and Perils of Big Data: Philosophical Constraints on Chemical Ontologies
Journal of the American Chemical Society · 2024
Rebekah Duke, Ryan E. McCoy, Chad M. Risko, Julia R. S. Bursten
Read original paper ↗ ·Multiscale Modeling of Physical Properties of Nanoporous Frameworks: Predicting Mechanical, Thermal, and Adsorption Behavior
Accounts of Chemical Research · 2024
Arthur Hardiagon, François‐Xavier Coudert
Read original paper ↗ ·