Ultra-large Chemical Libraries Meeting: Poster deadline approaching!

Digital Discovery is pleased to support the Ultra-large Chemical Libraries meeting organised by RSC CICAG, to be held on the 10th of August 2022 at our headquarters in Burlington House, London, UK. If you’d like to submit a poster, please note that the abstract deadline is the 2nd of June!

Find out more about this event, and how to register, on its events page, and find the speaker list at its web site.

Research infographic – “RegioML: predicting the regioselectivity of electrophilic aromatic substitution reactions using machine learning”

An infographic describing the research in the paper at DOI 10.1039/D1DD00032B

We’re excited to share this new infographic about RegioML, work that was published in Digital Discovery issue 2. Read the entire open-access article at:

“Consideration of predicted small-molecule metabolites in computational toxicology”

Nicolai Ree, Andreas H. Göller and Jan H. Jensen, Digital Discovery, 2022, 1, 108–114, DOI:10.1039/D1DD00032B

 

Research infographic – “Consideration of predicted small-molecule metabolites in computational toxicology”

An infographic describing the paper "Consideration of predicted small-molecule metabolites in computational toxicology", DOI 10.1039/D1DD00018G

Discover more about this research in the open access article:

Consideration of predicted small-molecule metabolites in computational toxicology

Miriam Mathea, Johannes Kirchmair et al.Digital Discovery, 2022, 1, 158–172. DOI:10.1039/D1DD00018G

View the 29 March Desktop Seminar

We’re pleased to share a recording of our first Desktop Seminar, held on 29 March. View the seminar here find out more about the journal, and the research of our editors and authors! We look forward to holding further Desktop Seminars in the near future.

Research infographic – “Convergence acceleration in machine learning potentials for atomistic simulations”

An infographic describing the paper linked to in this post

Find out more in the open access article:

Convergence acceleration in machine learning potentials for atomistic simulations

Wissam A. Saidi et al.Digital Discovery, 2022, 1, 61–69. DOI:10.1039/D1DD00005E

Research infographic – “Sparse modeling for small data: case studies in controlled synthesis of 2D materials”

An infographic describing the paper linked to in the article

Find out more in the free-to-read open access article:

Sparse modeling for small data: case studies in controlled synthesis of 2D materials

Yuya Oaki et al., Digital Discovery, 2022, 1, 26–34. DOI:10.1039/D1DD00010A

Reminder: Digital Discovery desktop seminar, 29 March 2022, 1300 EDT

There’s still time to register for the Digital Discovery desktop seminar, taking place on the 29th of March 2022 at 1300 EDT! If you’re interested but can’t make the date, register your interest and we’ll send you a link to the recording afterwards.

Tuesday 29 March, 1800 BST / 1300 EDT / 1000 PDT

Professor Alán Aspuru-Guzik                                                 

University of Toronto, Canada

Editor-in-Chief, Digital Discovery

Title: “Computer Vision for Self-Driving Labs.”

Andrea Angulo and Prof. Miguel A. Modestino

New York University, USA

Title: “Leveraging Machine Learning Approaches to Optimize Organic Electrosynthesis.”

Professor Lilo D. Pozzo

University of Washington, USA

Editorial Board Member, Digital Discovery

Title: “Materials Acceleration for All through Open Hardware.”

Further information

Register

Dr Matthew Addicoat wins the Digital Discovery data reviewer draw!

We’re excited to announce that Dr Matthew Addicoat of Nottingham Trent University has won the first exclusive Digital Discovery mug in our data reviewer prize draw!

Dr Addicoat has this to say about open data: “Data is important for so many reasons: For me the most obvious reasons are that sharing data allows faster progression by reuse of data and broadening collaboration. It also allows for errors to be found and fixed, which is increasingly important as science increasingly turns to data-driven.”

Thanks to Dr Addicoat and all our other data reviewers for their support! Find out more about becoming a data reviewer in our earlier blog post.

Digital Discovery First Issue Desktop Seminars

Update 17 March 2022:

We regret to announce that the desktop seminar scheduled for 24 March has been cancelled due to exceptional circumstances. We are sorry for the inconvenience. We hope to run a similar webinar in the near future. Note that the desktop seminar on 29 March will continue as planned.

Original post:

We are pleased to announce two free desktop seminars to mark the publication of the first issue of Digital Discovery. In these 90-minute seminars, meet the authors and editors of Digital Discovery and learn about the exciting experimental and computational work being performed to accelerate scientific progress.

If you’re interested in either seminar but can’t make the date, register your interest and we’ll send you a link to the recording afterwards.

Thursday 24 March, 0900 UTC / 1000 CET / 1200 MSK / 1900 JST

Professor Yuya Oaki                                                               

Keio University, Japan

Title: “Sparse modeling for small data (SpM-S) toward digital discovery in chemistry and materials science.”

Professor Ekaterina V. Skorb

ITMO University, Russia

Editorial Board Member, Digital Discovery

Title: “Digital Discovery at Infochemistry Scientific Center of ITMO University.”

Professor Evgeny A. Pidko

Delft University of Technology, The Netherlands

Title: “High throughput computational screening and reaction network analysis for homogeneous catalysis with transition metal complexes.”

Further information

Register

Tuesday 29 March, 1800 BST / 1300 EDT / 1000 PDT

Professor Alán Aspuru-Guzik                                                 

University of Toronto, Canada

Editor-in-Chief, Digital Discovery

Title: “Computer Vision for Self-Driving Labs.”

Andrea Angulo and Prof. Miguel A. Modestino

New York University, USA

Title: “Leveraging Machine Learning Approaches to Optimize Organic Electrosynthesis.”

Professor Lilo D. Pozzo

University of Washington, USA

Editorial Board Member, Digital Discovery

Title: “Materials Acceleration for All through Open Hardware.”

Further information

Register

Digital Discovery is pleased to sponsor the AI2ASE workshop at AAAI22

Digital Discovery are pleased to announce sponsorship of the best paper prize at the 1st Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE), taking place as part of the 36th AAAI Conference on Artificial Intelligence. We are particularly pleased to be involved given this year’s theme, “AI for Chemistry”.

The annual AAAI workshop on AI to Accelerate Science and Engineering (AI2ASE) is relevant for dissemination of research at the intersection of AI/ML and Chemistry. Digital Discovery and AI2ASE are considering a special issue for selected papers in the chemistry domain; watch this space for more information.

You can find out more about the AI2ASE workshop at the event web site.