🚨New Advance Article from Editorial Board member Professor Yousung Jung's research lab at Seoul National University. Presenting a high-dimensional neural network potential (HDNNP) framework for accurate atomistic simulations of #OLED materials✨
👉 Read it now: doi.org/10.1039/D5DD...
#OpenAccess

Check out a round up of our latest news in our April 2026 newsletter, now available on our blog: blogs.rsc.org/dd/q2-...

Get future updates directly to your inbox with our email alerts. Sign up here: www.rsc.org/publishi...

Quantum computing meets carbon capture in this new research from #RSCDigital available now: doi.org/10.1039/D6DD...

Dario Rocca et al. develop quantum algorithm for more efficient and accurate models of metal-organic frameworks to predict properties and potential in carbon capture applications.

We're proud to join @pccp.rsc.org, @materialshorizons.rsc.org @materialsadvances.rsc.org & @nanoscale-journals.rsc.org in sponsoring poster awards at the Conference on Quantum Information and Quantum Control! Watch out for our themed collection later this year. www.fields.utoronto.ca/activities/2...

📢 Digital Discovery and PCCP are sponsoring poster prizes at the Southeastern Theoretical Chemistry Association meeting🎉
Abstract deadline is 20 April 2026 so submit yours now!
📍Georgia State University, Atlanta USA
📆 28-30 May 2026
🔗 sites.gsu.edu/setca2...

#RSCPhysical #SETCA2026 #RSCDigital

💡Looking for some weekend reading?
Explore the evolution of reaction optimization strategies! Uniting experimental design, theoretical modeling, and data science paves the way toward autonomous, data-driven reaction optimization and rational catalyst design. 👉Read it here: doi.org/10.1039/D5DD...

📢 Introducing MORGOTH, a robust and interpretable random forest for multivariate classification & regression with applications in drug sensitivity prediction, focusing on trustworthiness and outperforming existing neural network approaches.

Read it #OpenAccess now: doi.org/10.1039/D5DD...

In this week's highlighted review, Nematiaram et al. explore how AI accelerates property prediction and charge-transport modelling of molecular semiconductors, outlining strategies for scalable, autonomous optoelectronic materials discovery.
👉 Read the full Review here: doi.org/10.1039/D5DD...

How can we predictively model catalytic reactions without human guidance?
Robidas and Legault introduce a new atomic reactivity framework and neophile kinetic model to simplify reaction complexity for a practical route to less human‑dependent reaction design.
👉 Read it now: doi.org/10.1039/D5DD...

RSC Desktop Seminar: Americas Emerging Investigators - Applications of Mechanochemistry on Wednesday 8 April 2026 at 11 am EDT and 4 pm BST

Join our next Americas Emerging Investigator webinar, part of the Desktop Seminar series, next Wednesday, April 8th at 11am EDT/4pm BST. Xinle Li and Paulo de Oliveira @uspoficial.bsky.social will discuss "Applications of Mechanochemistry".

Sign up for free here: rsc.zoom.us/webinar/regi...

Can generative AI shine a light on OLED molecule discovery? 💡

D Kim, WY Kim, et al. explore a building block-based autoregressive generative model for OLED materials discovery, focusing on structural novelty, sythesizability, and key TADF properties

👉 Read the full story: doi.org/10.1039/D5DD...

Are mass spectrometry and ion-mobility spectrometry ready for an upgrade?
P Urban et al. share their perspective on the automation of these analytical tools. They discuss the integration of robotics and AI and highlight applications in single-cell analysis
Get the full story: doi.org/10.1039/D5DD...

✨ #DigitalDiscovery is proud to announce that we are sponsoring a poster prize at RSC CICAG Chemical Structure Representations 2026 on 8 April at Burlington House, London!

👉 Click the following link if you are interested in attending this meeting! registrations.hg3conferences.co.uk/hg3/360/regi...

Issue 3 back cover - Dam et al present an AI framework for accelerating high-entropy alloy discovery, integrating experimental data and scientific literature with LLMs and using Dempster-Shafer theory to evaluate candidates and quantify prediction uncertainty
👉Read it here: doi.org/10.1039/D5DD...

DD Issue 3 inside front cover - Xingran Kou, Dachuan Zhang, et al. present a comprehensive survey of plant volatiles to evaluate their sleep-promoting activity, combining large-scale data mining, computational prediction, and in vivo experimentation.
👉 Find out more now: doi.org/10.1039/D5DD...

On the front cover of Digital Discovery Issue 3, Guillermo Restrepo presents their Perspective on recent advances in hypergraph theory as well as the advantages and current limitations of hypergraph-based methods for modelling complex chemical systems.

👉 Get the full story: doi.org/10.1039/D5DD...

📢 #DigitalDiscovery Issue 3 is out now and #OpenAccess!
Find the latest research in data-driven approaches to scientific discoveries, including molecular hypergraphs, a survey of sleep-promoting volatiles, high-entropy alloy discovery and much more👇
Get the full issue here:

What happens when #machinelearning models learn chemistry? Find out in this two part bonus👇
Part I introduces #Python-based Workflow for Interpretability Scoring using matched molecular Pairs: WISP👉doi.org/10.1039/D5DD...
Part II explores additional functionalities of WISP👉doi.org/10.1039/D5DD...

Graphical Abstract for Digital Discovery article "Accelerating catalytic advancements through the precision of high-throughput experiments & calculations"

How do we unlock faster, more sustainable catalyst discovery?
👉This #openaccess article discuses high-throughput experimental and computational methods that are transforming catalysis, highlighting persistent challenges and exciting opportunities!
🔗Read the full story: doi.org/10.1039/D5DD...

Graphical Abstract for Digital Discovery Article "ToPolyAgent: AI agents for coarse-grained bead-spring topological polymer simulations"

📢New work from Ding et al. at Oak Ridge National Laboratory introduces ToPolyAgent, the AI-agent for coarse grained bead-spring topological polymer simulations supporting both interactive and autonomous simulation workflows across diverse polymer architectures
👉Read it now: doi.org/10.1039/D5DD...

Graphical Abstract for Digital Discovery article "Statistics makes a difference: machine learning adsorption dynamics of functionalized cyclooctyne on Si(001) at DFT accuracy"

The best of both for surface experiment simulations?
Westermayr et al. introduce a “molecular-gun” workflow for modelling surface chemistries, bridging the gap between the accuracy of ab initio molecular dynamics and the computational cost of extensive sampling. Read it here doi.org/10.1039/D5DD...

Graphical Abstract of Digital Discovery article "The PPP model – a minimum viable parametrisation of conjugated chemistry for modern computing applications"

📢 New HOT article on the Pariser-Parr-Pople (PPP) Hamiltonian, its ability to minimally model conjugated π-electron systems, applications in modern computing, and current limitations.
Read it here: doi.org/10.1039/D5DD...

A part of our Quantum Computing themed collection:
pubs.rsc.org/en/jour...

The abstract submission deadline for both talks and posters on 15 March is fast approaching - make sure you don't miss your opportunity to participate!

We're proud to sponsor awards at the 11th Conference on Quantum Information and Quantum Control, Aug. 17-21 in Toronto, with @pccp.rsc.org, @materialshorizons.rsc.org, @materialsadvances.rsc.org and Nanoscale Advances @nanoscale-journals.rsc.org:

www.fields.utoronto.ca/activities/2...

For International Women’s Day 2026, we are highlighting some of the impactful work published by excellent women in accelerated science, through a collection of recent #DigitalDiscovery articles:

pubs.rsc.org/en/jour...

Please contact us if you have recent publications you would like to add.

⏳ The closing date to nominate someone for the 2026 Chemical Science Lectureship is fast approaching!
Details about eligibility and how to nominate are here: rsc.li/chemsci-lectureship26
#compchem #mlchem #AIChem #machinelearning

Digital Discovery and @rscadvances.rsc.org are proud to sponsor the lightning talk awards at the ACS Graduate Student Symposium in Fall. Look out for further information on "Advancing Chemistry with AI and Emerging Technologies: Innovation, Entrepreneurship, and Careers": www.acs.org/education/st...

FiberForge: enabling high-throughput simulations of the mechanical properties of helical fibrils The mechanical properties of amyloid-based materials are governed by fibril geometry, sequence, and polymorphism, yet systematic exploration of this vast design space has been limited by the lack of high-throughput modeling tools. Here we present FiberForge, an open-source workflow that automates constructio

📢 Zhongyue (John) Yang introduces FiberForge: an open source workflow that automates molecular modelling, design and characterisation of amyloid fibrils in new #DigitalDiscovery manuscript!

🖥️ Read more here: doi.org/10.1039/D5DD...

#EmergingInvestigators2025

Data augmentation in a triple transformer loop retrosynthesis model Reactions in the US Patent Office (USPTO) are biased towards a few over-represented reaction types, which potentially limits their usefulness for computer-assisted synthesis planning (CASP). To obtain an equilibrated dataset, we applied retrosynthesis templates to USPTO molecules as products (P) to generate

✨ A new approach in #DigitalDiscovery is providing better ways to utilise data from open-source publicly available datasets!

🔥 Read about how data augmentation can enrich reactivities in the USPTO chemical reaction dataset here: doi.org/10.1039/D5DD...

#OpenSource #CAPS

Our new Digital Discovery themed collection in collaboration with Accelerate Conference 2023–24 has now been published online!

This new themed collection represents a collaboration between #DigitalDiscovery and the Acceleration Consortium.

Read the collection here: rsc.li/DDAccel24!