Themed collection Editor’s Choice Collection 2022
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![Open Access](https://www.rsc-cdn.org/pubs-core/2022.0.148/content/NewImages/open-access-icon-orange.png)
Natural language processing models that automate programming will transform chemistry research and teaching
Natural language processing models have emerged that can generate useable software and automate a number of programming tasks with high fidelity.
Digital Discovery, 2022,1, 79-83
https://doi.org/10.1039/D1DD00009H
![Open Access](https://www.rsc-cdn.org/pubs-core/2022.0.148/content/NewImages/open-access-icon-orange.png)
Robotic cell assembly to accelerate battery research
Demonstration of the first robotic battery assembly system for academia that offers superhuman reproducibility and full data lineage tracking.
Digital Discovery, 2022,1, 755-762
https://doi.org/10.1039/D2DD00046F
![Open Access](https://www.rsc-cdn.org/pubs-core/2022.0.148/content/NewImages/open-access-icon-orange.png)
Cell morphology-guided de novo hit design by conditioning GANs on phenotypic image features
Cellular morphology can be used to guide the de novo design of small molecules inducing a desired phenotype.
Digital Discovery, 2023,2, 91-102
https://doi.org/10.1039/D2DD00081D
![Open Access](https://www.rsc-cdn.org/pubs-core/2022.0.148/content/NewImages/open-access-icon-orange.png)
Bayesian optimization in continuous spaces via virtual process embeddings
Process optimization in the latent space of functions via variational autoencoder (VAE) and Bayesian Optimization (BO). We demonstrate this to optimize the curl of a kinetic ferroelectric model.
Digital Discovery, 2022,1, 910-925
https://doi.org/10.1039/D2DD00065B
![Open Access](https://www.rsc-cdn.org/pubs-core/2022.0.148/content/NewImages/open-access-icon-orange.png)
Plot2Spectra: an automatic spectra extraction tool
Scientists cannot easily make use of numerical data encoded in plot images, such as of spectroscopy data, in scientific literature. Plot2Spectra was developed to use computer vision tools to automatically digitize plot images.
Digital Discovery, 2022,1, 719-731
https://doi.org/10.1039/D1DD00036E
![Open Access](https://www.rsc-cdn.org/pubs-core/2022.0.148/content/NewImages/open-access-icon-orange.png)
A self-driving laboratory designed to accelerate the discovery of adhesive materials
This self-driving laboratory combines a robot for preparing and testing adhesive bonds with an optimizer to rapidly improve adhesive formulations.
Digital Discovery, 2022,1, 382-389
https://doi.org/10.1039/D2DD00029F
![Open Access](https://www.rsc-cdn.org/pubs-core/2022.0.148/content/NewImages/open-access-icon-orange.png)
Extraction of chemical structures from literature and patent documents using open access chemistry toolkits: a case study with PFAS
Extracting PFAS with open source cheminformatics toolkits reveals ∼1.78 million PFAS in Google Patents, ∼28 K in the CORE literature repository.
Digital Discovery, 2022,1, 490-501
https://doi.org/10.1039/D2DD00019A
![Open Access](https://www.rsc-cdn.org/pubs-core/2022.0.148/content/NewImages/open-access-icon-orange.png)
Machine learning enhanced spectroscopic analysis: towards autonomous chemical mixture characterization for rapid process optimization
A supervised machine learning algorithm is developed to determine the concentrations of chemical species in multicomponent solutions from their Fourier transform infrared (FTIR) spectra.
Digital Discovery, 2022,1, 35-44
https://doi.org/10.1039/D1DD00027F
About this collection
To celebrate one year since the first issue of Digital Discovery, this collection highlights some of the very best work, carefully chosen by our dedicated editorial team and world-renowned editorial board members.