Digital Discovery Blog

We’re pleased to announce that a new themed collection from Digital Discovery has now been published online.

Read the collection

 

This new themed collection represents a collaboration between the editors of Digital Discovery and the Acceleration Consortium, organisers of the Accelerate Conference. The goal of the conference was to explore the power of self-driving labs (SDLs), which combine AI, automation, and advanced computing to accelerate materials and molecular discovery.

This themed collection, Guest Edited by Prof. Janine George (Federal Institute for Materials Research and Testing (BAM) and Friedrich Schiller University Jena, Germany), Prof. Claudiane Ouellet-Plamondon (École de Technologie Supérieure, Canada) and Prof. Kristofer Reyes (University at Buffalo, United States), features contributions that cover various aspects of this process, whether specifically presented at the conference or not.

The papers span innovations in algorithms, decision-making, and integrated self-driving laboratories—from efficient experimental design and probabilistic programming to orchestration frameworks coordinating sensing, actuation, and learning. Collectively, they illustrate new principles for accelerating and scaling discovery.

The articles from this collection have been provided below. All articles in Digital Discovery are open access and free to read.

A new collection to feature contributors to Accelerate Conference 2025 is currently underway, and we look forward to sharing further information in the near future.

 

Editorial

Introduction to the “Accelerate Conference 2023–2024” themed collection

Janine George, Claudiane Ouellet-Plamondon and Kristofer Reyes

Digital Discovery, 2026, 5, DOI: 10.1039/D5DD90057C

 

Opinion

Autonomous laboratories for accelerated materials discovery: a community survey and practical insights

Linda Hung, Joyce A. Yager, Danielle Monteverde, Dave Baiocchi, Ha-Kyung Kwon, Shijing Sun and Santosh Suram

Digital Discovery, 2024, 3, 1273-1279, DOI: 10.1039/D4DD00059E

 

Review

Democratizing self-driving labs: advances in low-cost 3D printing for laboratory automationSayan Doloi, Maloy Das, Yujia Li, Zen Han Cho, Xingchi Xiao, John V. Hanna, Matthew Osvaldoa and Leonard Ng Wei Tat

Digital Discovery, 2025, 4, 1685-1721, DOI: 10.1039/D4DD00411F

 

Tutorial Review

Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept

Stanley Lo, Sterling G. Baird, Joshua Schrier, Ben Blaiszik, Nessa Carson, Ian Foster, Andrés Aguilar-Granda, Sergei V. Kalinin, Benji Maruyama, Maria Politi, Helen Tran, Taylor D. Sparks and Alán Aspuru-Guzik

Digital Discovery, 2024, 3, 842-868, DOI: 10.1039/D3DD00223C

 

Communication

Stability and transferability of machine learning force fields for molecular dynamics applications

Salatan Duangdangchote, Dwight S. Seferos and Oleksandr Voznyy

Digital Discovery, 2024, 3, 2177-2182, DOI: 10.1039/D4DD00140K

 

Papers

Autonomous organic synthesis for redox flow batteries via flexible batch Bayesian optimization

Clara Tamura, Heather Job, Henry Chang, Wei Wang, Yangang Liang and  Shijing Sun

Digital Discovery, 2025, 4, 2737-2751, DOI: 10.1039/D5DD00017C

 

Advancing vanadium redox flow battery analysis: a deep learning approach for high-throughput 3D visualization and bubble quantification

André Colliard-Granero, Kangjun Duan, Roswitha Zeis, Michael H. Eikerling, Kourosh Malek and Mohammad J. Eslamibidgoli

Digital Discovery, 2025, 4, 2724-2736, DOI: 10.1039/D5DD000158G

 

twa: The World Avatar Python package for dynamic knowledge graphs and its application in reticular chemistry

Jiaru Bai, Simon D. Rihm, Aleksandar Kondinski, Fabio Saluz, Xinhong Deng, George Brownbridge, Sebastian Mosbach, Jethro Akroyd and Markus Kraft

Digital Discovery, 2025, 4, 123-2135, DOI: 10.1039/ D5DD00069F

 

BayBE: a Bayesian Back End for experimental planning in the low-to-no-data regime

Martin Fitzner, Adrian Šošić, Alexander V. Hopp, Marcel Müller, Rim Rihana, Karin Hrovatin, Fabian Liebig, Mathias Winkel, Wolfgang Halter and Jan Gerit Brandenburg

Digital Discovery, 2025, 4, 1991-2000, DOI: 10.1039/D5DD00050E

 

Atomate2: modular workflows for materials science

Alex M. Ganose, Hrushikesh Sahasrabuddhe, Mark Asta, Kevin Beck, Tathagata Biswas, Alexander Bonkowski, Joana Bustamante, Xin Chen, Yuan Chiang, Daryl C. Chrzan, Jacob Clary, Orion A. Cohen, Christina Ertural, Max C. Gallant, Janine George, Sophie Gerits, Rhys E. A. Goodall, Rishabh D. Guha, Geoffroy Hautier, Matthew Horton, T. J. Inizan, Aaron D. Kaplan, Ryan S. Kingsbury, Matthew C. Kuner, Bryant Li, Xavier Linn, Matthew J. McDermott, Rohith Srinivaas Mohanakrishnan, Aakash N. Naik, Jeffrey B. Neaton, Shehan M. Parmar, Kristin A. Persson, Guido Petretto, Thomas A. R. Purcell, Francesco Ricci, Benjamin Rich, Janosh Riebesell, Gian-Marco Rignanese, Andrew S. Rosen, Matthias Scheffler, Jonathan Schmidt Jimmy-Xuan Shen, Andrei Sobolev, Ravishankar Sundararaman, Cooper Tezak, Victor Trinquet, Joel B. Varley, Derek Vigil-Fowler, Duo Wang, David Waroquiers, Mingjian Wen, Han Yang, Hui Zheng, Jiongzhi Zheng, Zhuoying Zhu and Anubhav Jain

Digital Discovery, 2025, 4, 1944-1973, DOI: 10.1039/D5DD00019J

 

Predefined attention-focused mechanism using center-environment features: a machine learning study of alloying effects on the stability of Nb₅Si₃ alloys

Yuchao Tang, Bin Xiao, Shuizhou Chen, Quan Qian and Yi Liu

Digital Discovery, 2025, 4, 1870-1883, DOI: 10.1039/D5DD00079C

 

SynCoTrain: a dual classifier PU-learning framework for synthesizability prediction

Sasan Amariamir, Janine George and Philipp Benner

Digital Discovery, 2025, 4, 2737-2751, DOI: 10.1039/D4DD00394B

 

Large language models for knowledge graph extraction from tables in materials science

Max Dreger, Kourosh Malek and Michael Eikerling

Digital Discovery, 2025, 4, 1221-1231, DOI: 10.1039/D4DD00362D

 

ADEL: an automated drop-cast electrode setup for high-throughput screening of battery materials

Maha Ismail, Maria Angeles Cabañero, Joseba Orive, Lakshmipriya Musuvadhi Babulal, Javier Garcia, Maria C. Morant-Miñana, Jean-Luc Dauvergne, Francisco Bonilla, Iciar Monterrubio, Javier Carrasco Amaia Saracibarb and  Marine Reynaud

Digital Discovery, 2025, 4, 943-953, DOI: 10.1039/D4DD00381K

 

Archerfish: a retrofitted 3D printer for high-throughput combinatorial experimentation via continuous printing

Alexander E. Siemenn, Basita Das, Eunice Aissi, Fang Sheng, Lleyton Elliott, Blake Hudspeth, Marilyn Meyers, James Serdy and Tonio Buonassisi

Digital Discovery, 2025, 4, 896-909, DOI: 10.1039/D4DD00249K

 

Opentrons for automated and high-throughput viscometry

Beatrice W. Soh, Aniket Chitre, Shu Zheng Tan, Yuhan Wang, Yinqi Yi, Wendy Soh, Kedar Hippalgaonkar and D. Ian Wilson

Digital Discovery, 2025, 4, 711-722, DOI: 10.1039/D4DD00368C

 

Preferential Bayesian optimization improves the efficiency of printing objects with subjective qualities

James R. Deneault, Woojae Kim, Jiseob Kim, Yuzhe Gu, Jorge Chang, Benji Maruyama, Jay I. Myung and Mark A. Pitt

Digital Discovery, 2025, 4, 723-737, DOI: 10.1039/D4DD00320A

 

Multi-objective Bayesian optimization: a case study in material extrusion

Jay I. Myung, James R. Deneault, Jorge Chang, Inhan Kang, Benji Maruyama and Mark A. Pitt

Digital Discovery, 2025, 4, 464-476, DOI: 10.1039/D4DD00281D

 

A materials discovery framework based on conditional generative models applied to the design of polymer electrolytes

Arash Khajeh, Xiangyun Lei, Weike Ye, Zhenze Yang, Linda Hung, Daniel Schweigert and  Ha-Kyung Kwon

Digital Discovery, 2025, 4, 11-20, DOI: 10.1039/D4DD00293H

 

Data efficiency of classification strategies for chemical and materials design

Quinn M. Gallagher and  Michael A. Webb

Digital Discovery, 2025, 4, 135-148, DOI: 10.1039/D4DD00298A

 

Agent-based learning of materials datasets from the scientific literature

Mehrad Ansari and Seyed Mohamad Moosavi

Digital Discovery, 2025, 4, 2607-2617, DOI: 10.1039/D4DD00252K

 

Combining Hammett σ constants for Δ-machine learning and catalyst discovery

Diana Rakotonirina, Marco Bragato, Stefan Heinen and O. Anatole von Lilienfeld

Digital Discovery, 2025, 4, 2487-2496, DOI: 10.1039/D4DD00228H

 

Leveraging GPT-4 to transform chemistry from paper to practice

Wenyu Zhang, Mason A. Guy, Jerrica Yang, Lucy Hao, Junliang Liu, Joel M. Hawkins, Jason Mustakis, Sebastien Monfette and Jason E. Hein

Digital Discovery, 2024, 3, 2367-2376, DOI: 10.1039/D4DD00248B

 

Pellet dispensomixer and pellet distributor: open hardware for nanocomposite space exploration via automated material compounding

Miguel Hernández-del-Valle, Jorge Ilarraza-Zuazo, Enrique Dios-Lázaro, Javier Rubio, Joris Audoux and Maciej Haranczyk

Digital Discovery, 2024, 3, 2032-2041, DOI: 10.1039/D4DD00198B

 

We hope you enjoy this new themed collection from Digital Discovery.

Welcome to the first Digital Discovery newsletter of 2026! We’re pleased to share a recap of the most important developments in 2025, and highlight some upcoming events the journal is supporting. We wish all of our readers, authors, reviewers and editors a successful new year in 2026. Get future updates directly to your inbox with our email alerts. Sign up here.

Latest News

We’re delighted to welcome Dr Indra Priyadarsini to the Editorial Board of the journal as an Associate Editor. Dr Priyadarsini is a Research Scientist at IBM Research – Tokyo, where she focuses on developing models and algorithms for foundation models in materials discovery. She earned her B.E. in Electronics and Communication Engineering from PES Institute of Technology, Bangalore, India, in 2016, followed by an M.E. and Ph.D. from Shizuoka University, Japan, in 2019 and 2022, respectively. Her doctoral research centered on optimization algorithms and deep learning. She is currently actively involved in advanced research related to AI for Math and Science, multimodal foundation models, and their application to accelerated scientific discovery. She has contributed to open-source frameworks in AI for science and has been recognized with the IPSJ Industrial Achievement Award (2024) for her impactful work in AI-based materials research.

We are very excited to announce that the 2026 #RSCPoster Conference will be taking place for 24 hours starting 3rd March 2026, 12:00 UTC.

The #RSCPoster conference is an annual event that has become a staple on many scientific community calendars. Held entirely online on LinkedIn over 24 hours, the unique format removes the environmental and financial costs of attending a traditional conference, and helps scientific researchers share their work and network across disciplines, wherever they are in the world. Find out more and join in: https://rsc.li/poster

2025 in Review

Digital Discovery introduced a new article type, Commit, for incremental improvements to articles previously published in the journal. This could include improved hardware designs, new features in software, or expanded datasets. Find out more in our Editorial at DOI: 10.1039/D4DD90053G, read the first Commit in DOI: 10.1039/D5DD00089K, and contact the Editorial Office at digitaldiscovery-rsc@rsc.org with your questions or comments.

Jan Weinreich and Daniel Probst received the Digital Discovery Outstanding Early Career Researcher Award 2025 for their paper “Learning on compressed molecular representations”. Their work uses string compression to predict molecular properties, with performance competitive to state-of-the-art graph neural networks. Find out more about the winners and their work in our blog post.

We were pleased to welcome three new Associate Editors to the journal’s Editorial Board, Prof. Milad Abolhasani of North Carolina State University, United States; Prof. Xin Hong of Zhejiang University, China; and Dr Melodie Christiansen from Merck & Co., Inc., United States. We also bid farewell to Editorial Board member Dr Linda Hung of the Toyota Research Institute, United States. Her insights and support of the journal from the outset were essential to its present success, and we wish her well in her future endeavours.

Our editors were pleased to meet the community at events such as AI4AM, Pacifichem, and WATOC. We were pleased to support the Accelerate Conference, and invite the participants to contribute to a themed collection of articles in the journal. We look forward to sharing news on the launch of a further themed collection on large language models, and the line-up of accepted papers from our collection on quantum computing, in the coming months.

Upcoming events

Digital Discovery Associate Editor Prof. Joshua Schrier will be attending Chemical Compound Space Conference 2026 and presenting awards from Digital Discovery and PCCP for the best posters.

Digital Discovery will feature contributions from the second international symposium on High-Throughput Catalysis Design, in a joint collection with Reaction Chemistry & Engineering and Catalysis Science & Technology. We look forward to working with the participants in due course.

Follow our channels below to keep up to date on the events we’re supporting in 2026.

Submit your work to Digital Discovery

Find out more about Digital Discovery on our webpage, where you can also find our author guidelines. Digital Discovery has received a 2024 Impact Factor of 5.6, has an article acceptance rate of 67%, and provides a first decision on articles sent to peer review in an average of 45 days.

Publishing open access with RSC journals unlocks the full potential of your research – bringing increased visibility, wider readership and higher citation potential to your work. As a not-for-profit organisation serving the chemical sciences community, we ensure that our article processing charge (APC) remains the most competitive of major publishers. More details can be found here and the APC for Digital Discovery is £2200. You can also use our journal finder tool to check if your institution currently has an agreement with the RSC that may entitle you to a discount of the APC.

Stay Connected

Postdoc or early career researcher? Interested in building your peer review experience and helping improve open data at Digital Discovery? Consider becoming a data reviewer. Find out more on our blog post.

Follow us on LinkedIn and Bluesky for new articles and the latest news from Digital Discovery and related journals at the Royal Society of Chemistry.

 

We are pleased to welcome Professor Jun Jiang to the Advisory Board of Digital Discovery

Professor Jiang is a Professor in the School of Chemistry and Materials Science at the University of Science and Technology of China (USTC) in Hefei, China. His research lies at the intersection of intelligent chemistry, data-driven scientific discovery, and automated robotic platforms for precision science.

By integrating artificial intelligence, robotics, and high-throughput experimentation, Professor Jiang has made significant contributions to advancing materials and chemical research. He is the developer of the “Robotic AI-Chemist”, a system that autonomously designs, executes, and iterates experiments in China. The latest iteration, Robotic AI-Chemist 2.0, leverages cloud-connected infrastructure and large-language-model-driven agents to support scalable, reproducible, and collaborative scientific exploration.

On joining the Advisory Board, Professor Jiang said:

“Being part of Digital Discovery aligns with my vision of accelerating science through openness and innovation. I look forward to supporting the journal’s mission to disseminate transformative research that bridges computation, experimentation, and real-world impact.”

We are delighted to welcome Professor Jiang and look forward to his insights and contributions in supporting the mission and future direction of Digital Discovery.

As we enter the last quarter of 2025, we are excited to share our latest updates from Digital Discovery with the community.

Get future updates directly to your inbox with our email alerts. Sign up here.

Latest News

Digital Discovery has introduced a new article type, Commit, for incremental improvements to articles previously published in the journal. This could include improved hardware designs, new features in software, or expanded datasets. Find out more in our Editorial at DOI: 10.1039/D4DD90053G, read the first Commit in DOI: 10.1039/D5DD00089K, and contact the Editorial Office at digitaldiscovery-rsc@rsc.org with your questions or comments.

Jan Weinreich and Daniel Probst have received the Digital Discovery Outstanding Early Career Researcher Award 2025 for their paper “Learning on compressed molecular representations”. Their work uses string compression to predict molecular properties, with performance competitive to state-of-the-art graph neural networks. Our congratulations to the winners! Find out more about the winners and their work in our blog post.

 

Research Spotlight

We were delighted to feature a manuscript by Omar M. Yaghi et al. on the journal’s cover on the same day that Professor Yaghi received a Nobel Prize for his work on metal-organic frameworks. Read our October front cover article here: “Comparison of LLMs in extracting synthesis conditions and generating Q&A datasets for metal–organic frameworks”.

Data-driven accelerated science depends on well-organised, accessible datasets. In “A FAIR research data infrastructure for high-throughput digital chemistry”, Cousty et al. discuss the research data infrastructure of SwissCat+, which transforms experimental metadata in to RDF graphs using an ontology-driven semantic model.

 

We’re pleased to share the first article from our collaboration with the AI in Drug Discovery workshop at ICANN 2025: “MARCUS: molecular annotation and recognition for curating unravelled structures”.  This web-based tool from Steinbeck et al. provides a human-in-the-loop approach to extracting and curating data from the natural product literature. Access MARCUS at https://marcus.decimer.ai/.

Digital Discovery in the Community

We were proud to offer our support to a number of events and awards in the busy 2025 conference season. Our congratulations to all of the winners!

We were pleased to again sponsor a prize for the best talk at the Machine Learning and AI in Bio(Chemical) Engineering Conference, won by Calvin Yu (University of Bristol, UK). Our colleagues at Molecular Systems Design & Engineering also sponsored the award for best poster, won by ZhengJie Liew (University of Cambridge, UK).

Our partnership with the Accelerate Conference continues, with prizes for best posters to Florian Boser (Universität Münster, Germany), Xu Chen (University of Toronto, Canada) and Joy-Lynn Kobti (University of Windsor, Canada). We look forward to inviting all of the presenters at the meeting to contribute to a themed collection in the journal in the near future.

Finally, our new Deputy Editor Alexander Whiteside presented the People’s Prize sponsored by Digital Discovery at the 8th Artificial Intelligence in Chemistry Symposium, and was pleased to meet the winner, Sara Tanovic (University of Oxford, UK).

Editorial Board

The journal held its annual Editorial Board meeting online in October, shaping its strategy for 2026 and discussing our successes and challenges throughout the preceding year. We were pleased to welcome three new Associate Editors to the Board:

Prof. Milad Abolhasani of North Carolina State University, United States provides his expertise on self-driving labs. Prof. Abolhasani is the ALCOA Professor, a University Faculty Scholar, and the Director of the Graduate Program in the Department of Chemical and Biomolecular Engineering at North Carolina State University. He also serves as the Director of Accelerated Technologies within NC State’s Integrative Sciences Initiative.

Prof. Xin Hong of Zhejiang University, China contributes knowledge on the intersection of synthetic chemistry and data science. Prof. Hong is a tenured Associate Professor in the Department of Chemistry at Zhejiang University, and research focuses on understanding reaction mechanisms and structure–performance relationships in molecular synthesis, with a particular interest in integrating mechanistic insight with data-driven modelling.

Dr Melodie Christiansen from Merck & Co., Inc., United States, offers insights bridging chemistry, automation, and data science. Prof. Christiansen serves as Director of Data-Rich Experimentation in Process Research & Development Enabling Technologies at Merck & Co., Inc., leading the development and deployment of AI-driven automation technologies that accelerate pharmaceutical process research.

We also bid farewell to Editorial Board member Dr Linda Hung of the Toyota Research Institute, United States, whose term as an Associate Editor ends this year. Her insights and support of the journal from the outset were essential to its present success, and we wish her well in her future endeavours.

Collections

In addition to our upcoming themed collection with the Accelerate Conference 2025, Digital Discovery will feature contributions from the second international symposium on High-Throughput Catalysis Design, in a joint collection with Reaction Chemistry & Engineering and Catalysis Science and Technology. We look forward to working with the participants in due course. Follow the journal on social media or watch out for our next newsletter for information on our planned call for papers on Large Language Models, and the publication of our collection on Quantum Computing.

 

Upcoming Events

Executive Editor Anna Rulka will be representing Digital Discovery at this year’s Pacifichem symposium in Honolulu, Hawaii, on 15-20 December 2025. This year’s meeting features sessions organised by our Editor-in-Chief Alán Aspuru-Guzik and Associate Editor Yousung Jung. We look forward to meeting you there!

 

Stay Connected

Postdoc or early career researcher? Interested in building your peer review experience and helping improve open data at Digital Discovery? Consider becoming a data reviewer. Find out more on our blog post.

Follow us on LinkedIn and Bluesky for new articles and the latest news from Digital Discovery and related journals at the Royal Society of Chemistry.

 

 

We are thrilled to announce the winners of the Outstanding Early Career Researcher Award 20245: Daniel Probst and Jan Weinreich, recognized for their innovative paper published in Digital Discovery, “Learning on compressed molecular representations“

In their work, Daniel and Jan present MolZip, a simple yet powerful method that leverages string compression to predict molecular properties. By compressing concatenated SMILES and protein sequences, MolZip competes impressively with more complex graph-based methods outperforming 9 out of 10 state-of-the-art graph neural networks in predicting protein-ligand binding affinities.

Their approach is a compelling reminder that elegant, data-efficient solutions can still hold their ground even in the era of sophisticated machine learning models.

About the winners:
Daniel Probst received his PhD in Chemistry and Molecular Sciences from the University of Bern. After research roles at IBM and EPFL, he is now a tenure-track assistant professor at Wageningen University, focusing on sustainable machine learning applications in biology and chemistry.

Jan Weinreich specializes in machine learning for chemistry and materials science. He develops scalable algorithms for molecular property prediction and is co-founder of Chembricks AI, a company building AI platforms for materials discovery.

“Winning this prize is really cool and was a great surprise, especially for an article in one of my favourite journals. Of course, it is, as it is always the case, the contributions of scientific collectives rather than single groups or individuals that make a paper happen.”

– Daniel Probst

 

“We are truly honoured to receive the Outstanding Early Career Researcher Award from Digital Discovery. This recognition means a great deal to us. We hope that our work on compressed molecular representations will be of some use to the community to build AI models in chemistry that do not require huge computational resources but give quite competitive accuracy. Even with powerful GPUs at hand – sometimes being able to quickly build ML models can be helpful to “debug” data pipelines and test if allocating more attention/compute to a more “sophisticated” AI architecture”

– Jan Weinreich

🔗 Read the winner’s paper here!

 

Digital Discovery is pleased to support the SusML Workshop 2025!

The rising demand for sustainable machine learning (ML)-assisted solutions to technological and societal challenges has driven significant research and development efforts in materials science and computational chemistry. Despite notable progress, challenges remain in developing Efficient, Accurate, Scalable, and Transferable (EAST) methodologies that minimize energy consumption and data storage while creating robust ML models. The SusML workshop (https://susml.net) aims to bring together renowned scientists and emerging junior researchers pioneering advancements at the intersection of materials science, chemistry, and ML. The workshop will focus on fostering dynamic discussions and generating innovative ideas for developing EAST methodologies—a critical element for sustainable exploration (both directly and inversely) of the chemical space encompassing molecules and materials.

Deadline: Applications and abstract submissions will be accepted until June 15, 2025. See details at https://susml.net/#Application

Venue: Max Planck Institute for the Physics of Complex Systems, Dresden, Germany.

Invited speakers

• David Balcells (University of Oslo)
• Ganna Gryn’ova (University of Birmingham)
• Anatole von Lilienfeld (University of Toronto)
• Hanna Türk (École Polytechnique Fédérale de Lausanne)
• Anton Bochkarev (Ruhr-Universität Bochum)
• Veronika Juraskova (University of Oxford)
• Volker Deringer (University of Oxford)
• Jacqueline Cole (University of Cambridge)
• Johannes Margraf (Universität Bayreuth)
• Luca Ghiringhelli (Friedrich-Alexander-Universität)
• Rico Friedrich (Technische Universität Dresden)
• Janine George (Bundesanstalt für Materialforschung und -prüfung)
• Thorben Frank (Technische Universität Berlin)
• Adrian Ehrenhofer (Technische Universität Dresden)

Organizers

• Leonardo Medrano Sandonas (Technische Universität Dresden)
• Mariana Rossi (MPI for the Structure and Dynamics of Matter)
• Alexandre Tkatchenko (University of Luxembourg)
• Milica Todorović (University of Turku)
• Gianaurelio Cuniberti (Technische Universität Dresden)

Contact: susml@tu-dresden.de

We are pleased to announce that Dr Xin Hong, Associate Professor in the Department of Chemistry at Zhejiang University, has joined Digital Discovery as an Associate Editor.

Dr Hong is internationally recognised for his work at the intersection of synthetic chemistry and data science. He received his Ph.D. from UCLA in 2014 under the guidance of Prof. K. N. Houk, and continued as a postdoctoral researcher at Stanford University with Prof. Jens K. Nørskov.

His research centres on uncovering reaction mechanisms and structure–performance relationships in molecular synthesis. His group is particularly focused on integrating mechanistic understanding with data-driven approaches — including the development of chemically interpretable molecular graph models and transfer learning methods to overcome small-data limitations in organic chemistry.

These innovations have enabled practical progress in areas such as enantioselective cross-coupling and C–H activation, providing new tools for advancing digital chemistry.

“I’m thrilled to join the Editorial Board and look forward to supporting the community in embracing the transformation of chemistry in the era of AI.”

We’re proud to welcome Dr Hong to the Digital Discovery team and look forward to the contributions he’ll bring to the journal and wider community.

Follow us on LinkedIn for more Digital Discovery updates!

Digital Discovery is an international gold open-access journal. Join a community committed to impactful research and collaboration. Submit your article now Sign up now to get updates on all articles as they are published on Twitter, LinkedIn, and in our e-alerts.

This call for papers is now closed. However, we encourage you to contact us if you would like to discuss submitting your work on these topics to one of our journals.

We are delighted to announce a call for papers celebrating the UNESCO International Year of Quantum Science and Technology 2025. This collection across a selection of our materials, nanoscience, physical chemistry and interdisciplinary journals is now open for submissions.

The submission deadline is 1 October 2025.

For this broad collection of articles celebrating Quantum Science and Technology we encourage contributions on topics including, but not limited to:

• New quantum mechanical computational chemistry methods
  • Focusing on new methods to provide expanded variability (customization) to programs and algorithms applied to molecular and materials discovery.
• Studies on materials and nanostructures which exploit quantum effects
  • The engineering and investigation of materials and nanostructures that exploit QM effects. The collection seeks papers that offer insights into the understanding of Quantum effects or mechanistic insights rather than routine experimental studies that focus on material / device performance.
• Cross-disciplinary studies looking at quantum effects in molecular systems
  • Studies that bridge chemistry with adjacent disciplines to understand electronic and fundamental effects such as quantum dot cellular automata.
• Applications of quantum computing in chemistry
  • The design of new quantum algorithms, and application of existing algorithms, in the calculation, prediction and design of atomic, molecular, and materials properties.

This collection will be hosted across the following journals.

Chemical Science, Chemical Communications, RSC Applied Interfaces and RSC Advances

Digital Discovery and Physical Chemistry Chemical Physics

Materials Horizons, Journal Materials Chemistry A, Journal Materials Chemistry B, Journal Materials Chemistry C, and Materials Advances,

Nanoscale Horizons, Nanoscale and Nanoscale Advances

We hope you will accept our invitation to contribute to this collection. If you are interested, please contact us at journals@rsc.org and let us know which journal you would like to contribute to. If you have any questions, we would be delighted to send you more information. If you are unsure which journal would be the most suitable for your work or would like to check a topic’s suitability for a journal, we would be happy to help.

Publishing open access with RSC journals unlocks the full potential of your research – bringing increased visibility, wider readership and higher citation potential to your work. As a not-for-profit organisation serving the chemical sciences community we ensure that our article processing charge (APC) remains the most competitive of major publishers. More details can be found here. You can also use our journal finder tool to check if your institution currently has an agreement with the RSC that may entitle you to a discount or fully cover the APC.

Articles will be added to the collection as soon as they are accepted, and promotion of the collection is scheduled for the end of 2025. Please mention the collection name “Quantum Science and Technology” when you submit your manuscript. Please note that all submissions will undergo peer-review in the usual manner and must comply with each journal’s usual journal scope and standards.

We’re pleased to announce that Dr Milad Abolhasani has joined our editorial team as a new Associate Editor.

Dr. Abolhasani is an expert in autonomous chemical experimentation and currently serves as ALCOA Professor, University Faculty Scholar, and Director of the Graduate Program in Chemical and Biomolecular Engineering at North Carolina State University. He also plays a key role in NC State’s Integrative Sciences Initiative as Director of Accelerated Technologies.

His research focuses on self-driving labs—automated microfluidic platforms for accelerated discovery and manufacturing of advanced materials and molecules. Dr. Abolhasani’s work has received international recognition, including the NSF CAREER Award, AIChE Catalysis & Reaction Engineering Early Career Investigator Award, and the Dreyfus Award for Machine Learning in the Chemical Sciences & Engineering.

We’re thrilled to welcome Dr Abolhasani to our editorial team and look forward to his expertise and insight in Digital Discovery.

Join us in welcoming Milad on LinkedIn!

Digital Discovery is an international gold open-access journal. Join a community committed to impactful research and collaboration. Submit your article now Sign up now to get updates on all articles as they are published on Twitter, LinkedIn, and in our e-alerts.

Digital Discovery is delighted to welcome papers for its latest themed collection on Quantum Computing in Chemistry, Material Science and Biotechnology themed collection of Digital Discovery, led by Dr Matthias Degroote (Boehringer Ingelheim Quantum Lab), Prof. Joonho Lee (Harvard University) and Dr Pauline Ollitrault (QC Ware Corp.). If you do not directly work in this field, please do feel free to forward this email to any of your colleagues that might be interested in contributing to this themed collection.

Contributions are welcome in both theory for and applications of quantum computers in chemistry, material science and biotechnology. We would especially like to encourage manuscripts that expand the current area of applicability of quantum computers and introduce innovative ways to discover, characterize and produce new molecules. We will consider near-term and fault-tolerant algorithms as well as improvements over current algorithms and entirely new workflows.

We encourage submissions on topics including, but by no means limited to:

• Synergies between classical and quantum computers that leverage the strengths of both.
• Use of machine learning and data to bring down the cost of quantum computation.
• Tailored algorithms for specific subsets of chemical systems or types of interaction.
• Prediction of chemical properties with data that can efficiently be extracted from a quantum computer.

The deadline for submissions 11 August 2025.

If you would like to contribute to this collection, please let us know by email at digitaldiscovery-rsc@rsc.org, and we will set up a submission link for you to contribute your article.

Promotion of the collection is scheduled for promotion in late 2025, with articles published online as soon as they’re accepted. Authors are welcome to submit original research in the form of a Communication or Full Paper. Authors who would like to contribute a Review article should contact the Editorial office with their proposal. The Editorial Office reserves the right to check suitability of submissions for both the journal and the scope of the collection, and inclusion of accepted articles in the final themed collection is not guaranteed.

You can find out more detailed information about our journal scope and our valued editorial board members on our website. If you have any questions about the journal or the collection, please contact us at the above address.