Author Archive

Research infographic – Uncertainty-aware and explainable machine learning for early prediction of battery degradation trajectory

Our next infographic presents work from Rieger et al., using explainability and uncertainty to efficiently predict battery degradation and end-of-life.

An infographic summarising the research in the linked article.

Find out more in their full open-access article:

Uncertainty-aware and explainable machine learning for early prediction of battery degradation trajectory

Research infographic – Cell morphology-guided de novo hit design by conditioning GANs on phenotypic image features

We’re pleased to share this new infographic on work from Marin Zapata et al., showing that phenotypic features of cell images can guide a GAN to drug candidates:

An infographic summarising the research in the linked article

Read the full open access article here:

Cell morphology-guided de novo hit design by conditioning GANs on phenotypic image features

Paula A. Marin Zapata, Oscar Méndez-Lucio, Tuan Le, Carsten Jörn Beese, Jörg Wichard, David Rouquié and Djork-Arné Clevert, Digital Discovery, 2023, 2, 91–102, DOI: 10.1039/D2DD00081D

Research infographic – A fully automated platform for photoinitiated RAFT polymerization

The first infographic from Digital Discovery volume 2 highlights a paper from Gormley et al. on a fully automated system for synthesising new polymers. The automated lab includes independent control of each reaction in a well plate using a custom light box.

An infographic summarising the research in the linked paper

Read the full article, open access, here:

A fully automated platform for photoinitiated RAFT polymerization

Research infographic – Deep learning for enantioselectivity predictions in catalytic asymmetric β-C–H bond activation reactions

Machine-learning prediction of enantioselectivity of C-H bond activation reactions is the focus of this infographic, on an exciting new paper by Hoque and Sunoj:

An infographic describing the contents of the linked paper

Find out more in the full article below!

“Deep learning for enantioselectivity predictions in catalytic asymmetric β-C–H bond activation reactions”

Research infographic – Operator-independent high-throughput polymerization screening based on automated inline NMR and online SEC

Our newest research infographic shares research by Junkers et al., demonstrating the use of automation to reduce operator-to-operator inconsistencies in high-throughput RAFT screening while improving efficiency.

An infographic describing the linked article

Read the full open access article here:

Operator-independent high-throughput polymerization screening based on automated inline NMR and online SEC

Digital Discovery, 2022, 1, 519–526, DOI: 10.1039/D2DD00035K

Research infographic – Semi-supervised machine learning workflow for analysis of nanowire morphologies from transmission electron microscopy images

Nanomaterial research often involves characterising structures through microscopy which could be accelerated by automation. This new infographic describes a new workflow by Jayaraman et al. for analysing nanowire morphologies.

An infographic describing the linked article

Read the full open access article here:

Semi-supervised machine learning workflow for analysis of nanowire morphologies from transmission electron microscopy images

Shizhao Lu, Brian Montz, Todd Emrick and Arthi Jayaraman, Digital Discovery, 2022, 1, 816–833, DOI: 10.1039/D2DD00066K

Research infographic – Plot2Spectra: an automatic spectra extraction tool

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:

A research infographic describing the linked paper

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”

Our newest research infographic shares work by Brown et al. from Digital Discovery issue 5, on a crystallisation classification system and its corresponding database:

An infogrpahic describing the research in the linked paper

Read the full open-access article here:

Data mining crystallization kinetics

Research infographic – “Machine learning enabling high-throughput and remote operations at large-scale user facilities”

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:

A research infographic describing the linked paper

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”

An infographic describing the research in the linked paper

Digital Discovery issue 3 features work by Teresa Head-Gordon, et al. on NewtonNet, summarised in this new infographic!

Read the full article here:

“NewtonNet: a Newtonian message passing network for deep learning of interatomic potentials and forces”