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We are delighted to announce a special collection at the RSC to celebrate the International Year of Quantum in 2025 by highlighting Quantum Research across our journal portfolios. If you think you have any suitable work or want more info, please visit: blogs.rsc.org/dd/iyqst

In this week's first featured article, Pratiush, Kalinin et al. investigate the design of deep kernel learning workflows for STEM-EELS and present a human-in-the-loop approach to address challenges. Read the open access paper here: doi.org/10.1039/D5DD00…

In our next featured article, Higashi, Fujigaya, Kato et al. use persistent homology to extract features from DPD simulations of microphase-separated polymer materials, and use these for the prediction of materials properties such as proton conductivity. doi.org/10.1039/D4DD00…

Registration is open for the 8th RSC-CICAG / RSC-BMCS Artificial Intelligence in Chemistry meeting❗ 📅 22nd-24th September 2025 📍 Churchill College, Cambridge Artificial intelligence is increasingly revolutionizing chemistry. We are witnessing the impact of new methods and

In today's first featured article, Chilkunda, Kitchin, and Tilton present a high-throughput method for ibnary surfactant mixture property determination, using design of experiments and physics-based binary classification. Read the open access article here: doi.org/10.1039/D5DD00…

We're pleased to feature an article from Associate Editor Milad Abolhasani and colleagues. The paper shares a self-driving fluidic lab (SDFL) for autonomous optimisation of metal halid perovskite nanoparticle synthesis. Read the paper: doi.org/10.1039/D5DD00…

Gaurav Chopra Chopra Laboratory introduces our next article, by Beck, Iyer, Fine and Chopra: Introducing Paddy! A new evolutionary algorithm for chemical optimization—faster, smarter, and more versatile than traditional Bayesian and genetic methods. Read more👉 doi.org/10.1039/D4DD00…

Looking forward to the 8th MABC conference? Early bird registration, and talk and poster submissions, close this Friday 16th May. Find out more: mabc-cambridge.ai Digital Discovery and Reaction Chemistry & Engineering are proud to sponsor prizes for the best talk and poster this year!

Congratulations to all of the winners, and in particular Rei Oshima, from Digital Discovery!

Qian Yang introduces our latest featured article: "We develop a data-efficient and trustworthy machine learning approach for automated inverse analysis of small angle scattering data." Read the open access paper here: doi.org/10.1039/D5DD00…

We're pleased to feature "A digital laboratory with a modular measurement system and standardized data format" by Nishio, Hitosugi et al. Read about how robotics can enable physical interconnection of instruments for automatic and autonomous science here: doi.org/10.1039/D4DD00…

Researchers in Japan have developed a digital lab system that demonstrates advanced automatic, autonomous material synthesis of thin-film samples and measures their material properties for data- and robot-driven #materialsscience. #UTokyoResearch u-tokyo.ac.jp/focus/en/press…

Digital Discovery Issue 5 is now available! pubs.rsc.org/en/journals/jo… In this issue: VR digital twin labs, PC-SAFT parameter prediction, ML potentials for transition path sampling and much more! #openaccess

Digital Discovery Issue 5 is online and #OpenAccess pubs.rsc.org/en/journals/jo… Outside cover: Hilton et al., Read: doi.org/10.1039/D4DD00… Inside cover: Bardow et al. Read: doi.org/10.1039/D4DD00…

Digital Discovery Issue 5 is now online and #openaccess! pubs.rsc.org/en/journals/jo… Back cover: Fedik et al., “Challenges and opportunities for machine learning potentials in transition path sampling: alanine dipeptide and azobenzene studies” Read: doi.org/10.1039/D4DD00…

Ju, You, et al. evaluate pretrained ML potential SevenNet-0 on liquid electrolytes. Trained on inorganic data, SevenNet-0 performs unexpectedly well on these out-of-distribution systems, showing interpolation ability and improvement with fine-tuning. doi.org/10.1039/D5DD00…

This featured Communication article from Haddadnia, Grashoff, and Strieth-Kalthoff introduces BoTier, a library for BO experiment planning that can represent a hierarchy of preferences. Read the paper: doi.org/10.1039/D5DD00… Find BoTier on Github: github.com/fsk-lab/botier

Today's featured Review article from Wei et al. explores how artificial intelligence tools can support the development of anti-addiction medications, investigating new tools and upcoming research trends. Read the open access article: doi.org/10.1039/D5DD00…

In our next featured article, Pin-Yu Chen et al propose Representation Learning via Dictionary Learning (R2DL) to reprogram English language models for cross-domain tasks that perform well on protein property prediction tasks. Read the paper: doi.org/10.1039/D4DD00…

A fun project with Ria Vinod Payel Das IBM Research using model reprogramming techniques to "translate" a pretrained English language model for protein sequence representation learning. Our method can be on par with or even better than some of the protein foundation models!