Digital Discovery
A new #GoldOA journal from @roysocchem.bsky.social, meeting the trend towards greater automation and data-driven scientific techniques head-on. Led by EiC Alan Aspuru-Guzik
🌐 Website: rsc.li/digitaldiscovery-journal Published by @rsc.org
- ☀️ Don't miss this #DigitalDiscovery read! ✨ Leonardo Sandonas et al. introduce QUED, a hybrid QM/ML framework that integrates molecular structure and electronic information to deliver accurate predictions of physicochemical and biological properties. ➡️
- ✨ From our “Quantum Computing in Chemistry” themed collection Tianyi Li et al. introduce a practical quantum-computing non-adiabatic molecular dynamics framework. 🖥️ Read about how their work here:
- 👉 Don’t miss this Advance Article from #DigitalDiscovery featuring Megalodon 🦈, a scalable transformer-based architecture for multi-modal molecular diffusion and flow matching towards de novo 3D-molecule generation! 🖥️ Read more here! doi.org/10.1039/D5DD... #MolecularDesign
- 🎉 Registration for #RSCPoster 2026 is now OPEN! Be part of one of the largest global online poster events, bringing together researchers at every career stage and across all scientific disciplines. Register now to secure your place and join us on 4 March 2026 ➡️ rsc.li/4ppNbyo
- 📢 Today's #DigitalDiscovery read presents a multitask deep neural network model to predict the bioactivity of solute carrier transport target compounds! 🦠 Read more about how their approach is giving way an enlarged information pool of drug candidates here:
- ✨ #DigitalDiscovery is proud to be sponsoring a prize at this years RSC Analyticode happening in London on March 16! 📢 Don't miss your chance to submit an abstract by tomorrow (January 30) or to register for the conference (March 7)! 👉 registrations.hg3conferences.co.uk/hg3/frontend...
- 📢 The first issue of #DigitalDiscovery for 2026 is now online and #OpenAccess! 🔓 ⬇️In this issue read about ML-driven materials discovery, quantum computing, benchmarking self-driving labs, reaction prediction, FAIR-compliant workflows and much more! ✨ Read it here! pubs.rsc.org/en/journals/...
- ✨ In their newest #DigitalDiscovery article, Edward Lee and Daniel Salley introduce their robotic crystal search engine! 💎 Their new tool combines robotic automation, computer vision and AI making way for the autonomous discovery of new crystal polymorphs! 🖥️ Read more:
- 🔥 Fresh from Mechanical and AI Lab (MAIL) in #DigitalDiscovery: 🖥️ "What if an LLM agent could outsmart brute-force adsorption-configuration searches? Adsorb-Agent uses LLM reasoning to uncover lower-energy adsorption states with far fewer trials." 👉 Read more here!
- 📢 #DigitalDiscovery is proud to be sponsoring a poster prize at the third edition of the CAMLC workshop in Zaragoza, Spain on June 2-5 this year! 🗓️ Don't miss out! Applications are open now and close on February 4th. 👉 See here for more information: camlcworkshop.github... #CAMLC26
- ✨ In a new #DigitalDiscovery advance article, Ping Yang and her team are improving the accuracy of solubility predictions with their new neural network-based model, HASolGNN! 📢 Read more HASolGNN here:
- ✨ What if an AI agent could automate the structure generation and property analysis pipeline? 📢 Katerina Vriza and Uma Kornu introduce the newest multi-agent AI framework for autonomously preforming atomistic simulations in #DigitalDiscovery! 👉 Read it here!
- We’re pleased to welcome Professor Jun Jiang to the Advisory Board of Digital Discovery. A Professor at USTC, his work spans intelligent chemistry, AI-driven discovery, and automated robotic platforms. Read more about Jun in our blog: bit.ly/4qEkiPg
- 📢 #DigitalDiscovery's Editor in Chief Alán Aspuru-Guzik and his team are empowering experimentalists to integrate computer vision approaches within high-throughput materials research in their newest Tutorial Review! ✨ Read more here!
- 🖥️ From The University of Manchester, Artem Mishchenko and his team deliver the latest review in #DigitalDiscovery on how deep learning is transforming 2D material structure modelling! ✨ Read more about how AI is accelerating materials discovery here:
- 🧪 What if high-throughput computation could guide our hunt of chemical reactivities and synthetic strategies? ✨ New #DigitalDiscovery release features using enumerative combinatorics to map pathways between targets molecules and commercial catalogues! 👉 Read more here
- ✨ Tingzheng Hou and his team are working to bridge atomistic modeling with data-driven materials discovery in their new #DigitalDiscovery manuscript where they introduce their open-source python package, polymer electrolyte modeling and discovery (PEMD)! 👉 Read it here!
- New neural network methods from Ankur Gupta and Wibe A. de Jong provide a rapid and cost-effective way to accelerate the discovery of new ligands for rare-earth element extraction! 👉 Read the full article here: doi.org/10.1039/D5DD... #DigitalDiscovery #MachineLearning #NeuralNetworks
- #DigitalDiscovery and @pccp.rsc.org are proud to be sponsoring prizes at 2026's Chemical Compound Space Conference held in Munich from March 10th to 13th. Don't miss your chance to participate. Registration closes on the 15th of January! Find out more here: ccsc2026.github.io/
- Reposted by Digital DiscoveryAre you a UK or Ireland based chemistry undergraduate, postgraduate or recent graduate from a Black or minority ethnic background? Apply by 5 February 2026 to our 2026–2027 Broadening Horizons cohort to explore career opportunities in the chemical sciences: rsc.li/broadening-horizons #ChemSky
- 🖥️ Yuuya Nagata and his team combine automated synthesis and machine learning models in their new #DigitalDiscovery manuscript which works to transform chromatographic workflows through a new model relating retention time to molecular substructure! 👉 Read more here:
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- Digital Discovery & @pccp.rsc.org are pleased to announce the poster prize winners from the Uncertainty Quantification in Atomistic Modelling meeting! 🏅 Petra Navarcikova (TU Delft) - Uncertainty-Aware Protein Folding: From Classical Force Fields to Machine Learning Interatomic Potentials
- What if molecular language models have been using the wrong assumptions? This paper by Fabian P. Krüger ey al., outlines how MolEncoder uses higher masking ratios to boost accuracy while staying compute-efficient. 👉 doi.org/10.1039/D5DD...
- Our final #DigitalDiscovery newsletter of the year is now live on the blog! Catch up on new article types, award winners, research highlights, Editorial Board developments, and upcoming themed collections. Read the full update: blogs.rsc.org/dd/2025/12/0...
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- What if TS geometries could be predicted 100× faster? GoFlow uses E(3)-equivariant flow matching to generate transition states with higher accuracy and massively faster inference. paper by Esther Heid et al. 👉 doi.org/10.1039/D5DD...
- Can we decode 4D-STEM data without supervision? An NMF-based framework uses IQA metrics + decision strategies to map orientations with more stable, interpretable clustering. Paper by Arnaud Demortière, et al. 👉 bit.ly/49RzS4Q
- Kicking off very soon in Lausanne, Switzerland: Join us fo the Uncertainty quantification in atomistic modelling: From uncertainty-aware density functional theory to machine learning workshop with top minds! 📍 CECAM-HQ-EPFL 📅 Nov 25–28 🔗www.cecam.org/worksh...
- What if ML models could learn physics, not just patterns? This study by Fleck, Niels, et al., from the University of Stuttgart outlines a neural net with built-in entropy scaling predicts shear viscosity across wide T–P ranges, learning its own reference functions. 👉 bit.ly/4r55ydu
- Reposted by Digital DiscoveryOur work exploring co-folding methods for PROTAC ternary structure prediction is now accepted in @digital-discovery.rsc.org! Article: pubs.rsc.org/en/Content/A... Website: protacfold.xyz Great work led by 2 amazing students in our team, Nils and Francisco, together with @farzanejp.bsky.social! 🤩
- An automated sol–gel workflow for SiO₂ links precursor chemistry to nanostructure, accelerating discovery for separations, catalysis & drug delivery by Lilo D Pozzo from the University of Washington 👉 doi.org/10.1039/D5DD...
- New advance article! 📄 Beyond training data: how elemental features enhance ML-based formation energy predictions by Madhavi et al., @pennstateuniv.bsky.social Element features boost GNNs trained on QM data enabling strong generalization. 👉 doi.org/10.1039/D5DD...
- 🚨A new QM/MM MD workflow + ML analysis reveals reaction coordinates in supramolecular catalysts as sequences of motions. Read the full paper by @podewitzlab.bsky.social et al., from TU Wien 👉doi.org/10.1039/D5DD...
- Fresh advance article on MEMOS, an AI framework, rapidly designs molecular emitters with unmatched color purity, by Wang, Zhang, Duan, Zhou et al., from @tsinghuauniversity.bsky.social Read the full paper here 👉doi.org/10.1039/D5DD...
- This is your last chance to register for the Uncertainty quantification in atomistic modelling! 📍 CECAM-HQ-EPFL, Lausanne, Switzerland 📝 Registration deadline: October 24, 2025 🔗 www.cecam.org/worksh...
- 🚨 Digital Discovery Issue 10 is out now! Includes a new article by Nobel laureate Omar Yaghi et al.: "Comparison of LLMs in extracting synthesis conditions and generating Q&A datasets for MOFs" 🧠 🔗 Read the issue: pubs.rsc.org/en/jour... #DigitalDiscovery #OmarYaghi #LLMs #MOFs #Research #AI
- In honour of the 2025 #NobelPrize in Chemistry, we’ve curated a collection of impactful articles from across RSC journals on metal–organic frameworks (MOFs) 🏆 Free to read until the end of November 👉 pubs.rsc.org/en/jour...
- Fresh advance article from Paulson et al.: Adaptive subspace Bayesian optimization over molecular descriptor libraries for data-efficient chemical design MolDAIS uses Bayesian optimization to find optimal molecules fast, even with little data. Read the full paper👉
- We're pleased to support the upcoming Deep Matters: Foundations conference on foundation models in materials science. Participants will be invited to an upcoming themed collection on large language models for scientific research. Find out more and register: tldr-group.github.io/deep-matters/
- 🚨 New article out! Discover how AI-driven molecular representation learning is transforming drug discovery and materials design. From 3D models to hybrid learning, explore the our latest article 👉doi.org/10.1039/D5DD... #DigitalDiscovery #AI #Research
- Congrats to Sara Tanovic (@ox.ac.uk), winner of the poster prize at the 8th RSC-CICAG / RSC-BMCS AI in Chemistry meeting with her poster “How much chemistry can retrosynthesis models learn?” 🎉 Exciting work at the intersection of AI + chemistry! #AIinChemistry #DigitalDiscovery
- Yee Chit Wong of @uni-of-warwick.bsky.social has won the Digital Discovery and @pccp.rsc.org poster prize at the Materials and Molecular Modelling Hub Conference, for "First-Principles Defect and Migration Barrier Studies of Correlated Oxides with Machine Learning Perspectives". Congratulations!
- AI meets nanoparticle design! CCBO smartly hits size targets in polymer synthesis, beating traditional methods and expert guesses all with minimal data. Discover how this can reshape materials science. 👉 doi.org/10.1039/D5DD... #Nanotech #AI
- 🥳Congratulations to Daniel Probst (@skepteis.bsky.social) & Jan Weinreich, winners of Digital Discovery’s Outstanding Early Career Researcher Award with their paper! 📖Read their full paper "Learning on compressed molecular representations" here:
- New in Digital Discovery: ML + molecular dynamics used to design self-healing vitrimers with high Tg—before lab work begins. 📖 doi.org/10.1039/D5DD... #MaterialsScience #ML #Vitrimers #DigitalDiscovery
- New in Digital Discovery: A review on how flow chemistry enhances high-throughput screening—overcoming key limitations and expanding the discovery space. 📖 doi.org/10.1039/D5DD... #HTS #FlowChem #Automation
- The editors of Digital Discovery wish all of the participants at the upcoming 8th Artificial Intelligence in Chemistry Symposium an interesting and exciting meeting! The journal is proud to sponsor a poster prize for this year's conference. Find out more: www.rscbmcs.org/even...
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- Tired of quantum noise ruining your chemistry simulations? Our new MREM method brings multireference insight to error mitigation, boosting accuracy for strongly correlated molecules on near-term quantum devices. @rahmlab.bsky.social @dobrautz.bsky.social Read the paper here: doi.org/10.1039/D5DD...
- Reposted by Digital DiscoveryWhat a catch! 🎣 Huge congratulations to @boser-florian.bsky.social for winning the first place poster prize at this year’s @accelerationc.bsky.social Conference in Toronto awarded by @digital-discovery.rsc.org! 🥇 Thanks to the judges & organizers! #Accelerate2025 doi.org/10.1039/D4DD...
- Florian Boser (@boser-florian.bsky.social, @gloriusgroup.bsky.social) receives the best poster award from Digital Discovery at the 2025 Accelerate Conference for "Calibration-Free Quantification and Open Source Data Analysis for High-Throughput Reaction Screening". Join us in congratulating Florian!
- Xu Chen receives a runner-up award from Digital Discovery for "Accelerated Design of Synthetic Microbiome for Sustainable Chemical Production from Organic Waste" at the 2025 Accelerate Conference. Dr Chen works with Prof. Lawson and Prof. Moosavi at U. Toronto. Please join us in congratulating Xu!
- Joy-Lynn Kobti of the University of Windsor receives a runner-up award from #DigitalDiscovery for the poster "Accelerated Discovery of Therapeutic Coordination Polymers for Controlled Drug Release" at the 2025 Accelerate Conference. Please join us in congratulating Joy!
- Florian Boser (@boser-florian.bsky.social, @gloriusgroup.bsky.social) receives the best poster award from Digital Discovery at the 2025 Accelerate Conference for "Calibration-Free Quantification and Open Source Data Analysis for High-Throughput Reaction Screening". Join us in congratulating Florian!
- Dr Yuchen Wang of Kansas State University is the latest data reviewer to selected in our prize draw for the exclusive Digital Discovery mug. Interested in becoming a data review for Digital Discovery? Find out more on our blog: blogs.rsc.org/dd/data-revi...
