Josephson et al.‘s paper “Formalizing chemical physics using the Lean theorem prover” is featured on a new episode of the Breaking Math podcast! Find it at the links below or in your favourite podcatcher.
Read the open access article here.
Archive for the ‘News’ Category
Dr Giodarno Mancini wins the mid-2023 Digital Discovery data reviewer draw!
13 Sep 2023
We’re pleased to announce that Dr Giordano Mancini is the winner of the Digital Discovery mug in our most recent data reviewer prize draw. Congratulations Giordano!
If you would like to join our data reviewer pool and have the chance of winning our next mug, please see our earlier blog post for information.
Research infographic – Plot2Spectra: an automatic spectra extraction tool
09 Jan 2023
We’re pleased to share a new research infographic describing Plot2Spectra, a tool for digitising published spectroscopy data, by Jiang, Chan et al. in issue 5:
Read the full open access article here:
Plot2Spectra: an automatic spectra extraction tool
Weixin Jiang, Kai Li, Trevor Spreadbury, Eric Schwenker, Oliver Cossairt and Maria K. Y. Chan, Digital Discovery, 2022, 1, 719–731. DOI: 10.1039/D1DD00036E
Research infographic – “Data mining crystallization kinetics”
06 Dec 2022
Our newest research infographic shares work by Brown et al. from Digital Discovery issue 5, on a crystallisation classification system and its corresponding database:
Read the full open-access article here:
Research infographic – “Machine learning enabling high-throughput and remote operations at large-scale user facilities”
19 Oct 2022
Digital Discovery issue 4 features work by Daniel Olds, et al. on machine learning approaches designed for non-ML-expert light source users. Find out more in the infographic below:
Read the full open-access article here:
“Machine learning enabling high-throughput and remote operations at large-scale user facilities”
Research infographic – “NewtonNet: a Newtonian message passing network for deep learning of interatomic potentials and forces”
08 Aug 2022
Digital Discovery issue 3 features work by Teresa Head-Gordon, et al. on NewtonNet, summarised in this new infographic!
Read the full article here:
Research infographic – “Self-learning entropic population annealing for interpretable materials design”
11 Jul 2022
Digital Discovery issue 3 features work by Ryo Tamura, Koji Tsuda, et al. on SLEPA, summarised in this new infographic!
Read the full article here:
“Self-learning entropic population annealing for interpretable materials design”
Jiawen Li, Jinzhe Zhang, Ryo Tamura and Koji Tsuda, Digital Discovery, 2022, 1, 295–302, DOI: 10.1039/D1DD00043H
Research infographic – “RegioML: predicting the regioselectivity of electrophilic aromatic substitution reactions using machine learning”
23 May 2022
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”
09 May 2022
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
Research infographic – “Convergence acceleration in machine learning potentials for atomistic simulations”
05 Apr 2022
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