Author Archive

Late 2025 Newsletter

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

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Latest News

OECRA winners 2024

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.

A portrait of Dr Linda Hung

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.

 

 

Celebrating Innovation: Digital Discovery’s Outstanding Early Career Researcher Award

OECRA winners 2024

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!

 

New Associate Editor Announcement: Dr Xin Hong joins Digital Discovery

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.

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Welcoming Dr Milad Abolhasani as Associate Editor

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!

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Workshop on AI in Drug Discovery at the 34th International Conference on Artificial Neural Networks ICANN25

The 2nd Workshop on AI in Drug Discovery (https://e-nns.org/icann2025/aidd) to be held within the esteemed 34th International Conference on Artificial Neural Networks (ICANN 2025), invites cutting-edge contributions in the rapidly evolving field of AI-driven drug discovery. We are seeking submissions encompassing various facets such as generative models, eXplainable AI (XAI), uncertainty quantification, reaction informatics and synthetic route prediction, quantum machine learning for reactivity, methodologies for mining very large compound data sets, federated learning, analysis of HTS data, multimodal and equivariant neural networks, and other topics related to the use of ML in chemistry. This workshop aims to bring together machine learning experts, computational chemists and chemoinformaticians working on the development and application of ML in chemistry, environmental health and (eco)toxicology.

 

WORKSHOP TOPICS

We look forward to receiving contributions from all researchers active in the field, whether they are developing novel methodologies or expanding the scope of established methodologies. A non-exhaustive list of topics includes:

  • Big Data and Advanced Machine Learning in Chemistry
  • eXplainable AI (XAI) in Chemistry
  • Use of Deep Learning to Predict Molecular Properties
  • Cheminformatics
  • Modeling and Prediction of Chemical Reactions
  • Generative Models

 

SUBMISSION INSTRUCTIONSContributions (full papers or extended abstracts) should be submitted through the regular ICANN submission system at https://e-nns.org/icann2025/submission.  Select track “Workshop: AI in Drug Discovery”. Accepted papers/abstracts will appear in the ICANN2025 proceedings. The authors of accepted articles/abstracts will be invited to submit new or updated papers to a special issue of Digital Discovery (including 25% discount on the publication fee) before end of December 2025. Notice that all submissions for this SI should be full research papers, with an emphasis on novelty in methodology. If any of the work has been previously published as an abstract, it will not pose an issue, provided that the full paper includes all necessary details for replication, including data and code. If the full paper has been published, the journal submission should be significantly expanded or revised. A journal article should provide additional value beyond what was published in the conference proceedings and should include substantial new material or findings that were not part of the conference version.

 

IMPORTANT DATES

  • Deadline for full papers and extended abstracts via submission system: 15th of April
  • Deadline for extended abstract submission: 1th of May
  • Notification of acceptance: 15th of May
  • Conference dates: 9 – 12 September 2025

 

PROGRAM COMMITTEE

Ola Engkvist (AstraZeneca), Matteo Aldeghi (Bayer), Marc Bianciotto (Sanofi), Chris Barbel (Molecular Networks), Jan Halborg Jensen (U. Copenhagen), Alexandre Varnek (U. Strasbourg),  Mike Preuss (U. Leiden), Alessandra Roncaglioni (IRFMN), Noelia Ferruz (CRG), Fabian Theis (TUM), Francesca Grisoni (TU/e), Rodolphe Vuilleumier (ENS-PSL), Michael Wand (USI), Philippe Schwaller (EPFL), Hyun Kil Shin (KIT) and Jürgen Schmidhuber (USI)

The workshop will be organized in connection with the Horizon Europe Marie Skłodowska-Curie Actions Doctoral Network EID grant agreement No. 101120466 “Explainable AI for Molecules” (AiChemist) https://aichemist.eu.

 

ORGANIZERS

Dr. Igor V. Tetko

Group Leader Chemoinformatics

Institute of Structural Biology, Helmholtz Munich, Germany

Contact: aidd@aichemist.eu

Dr. Djork-Arné Clevert

VP Machine Learning Research
Pfizer, Berlin, Germany

Contact: Djork-Arne.Clevert@pfizer.com

Welcoming New Advisory Board Members to Digital Discovery

New advisory board members left to right: Jehad Abed, Matteo Aldeghi, Jan Bandenburg, Kenichi Shimmei, Seiji Takeda

 

We are pleased to announce the appointment of six new members to the Digital Discovery advisory board!

We are pleased to announce the expansion of our Advisory Board to include researchers with extensive industry experience. This strategic addition brings valuable perspectives and expertise from the forefront of industry innovations, ensuring that our work remains at the cutting edge of both academic and practical applications.

Meet the New Advisory Board Members:

  • Dr Jehad Abed (FAIR, Meta): Researcher focused on autonomous laboratories, clean energy materials, and the application of machine learning to solve energy challenges.
  • Dr Matteo Aldeghi (Bayer Research and Innovation Center): Director of Machine Learning Research, focusing on the application of digital tools to pharmaceutical R&D.
  • Dr Jan Gerit Brandenburg (Merck KGaA Darmstadt): Director for Digital Chemistry, specializing in AI-driven research and computational simulations for molecular and materials science.
  • Dr Kenichi Shimmei (Sekisui Chemical): Head of Informatics Technology Center, integrating Materials Informatics (MI) into R&D processes and leading laboratory automation initiatives.
  • Dr Seiji Takeda (IBM Research): Research Scientist and manager, developing AI frameworks and fostering collaborations across academia and industry.

By incorporating industry professionals into our Advisory Board, we aim to strengthen the collaboration between academia and industry, and enhance the relevance of the research published in Digital Discovery.

Join Us in LinkedIn to welcome our new experts in the field to the team!

 

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Welcoming Prof Demortière as New Advisory Board Member for Digital Discovery

 

We’re excited to announce that Prof Arnaud Demortière, an expert in energy materials and advanced microscopy techniques, is joining our Advisory Board for Digital Discovery. His background and  research will be a great addition to our board.

Prof Demortière has had a distinguished career, with a PhD from the Sorbonne University in Paris and five years of postdoctoral research at Argonne National Laboratory in Chicago. Since 2015, he has been conducting research at the CNRS in France, focusing on understanding the dynamics of Li-ion battery materials. His work primarily involves multi-scale and multimodal techniques, including in situ/operando methods like TEM (transmission electron microscopy) and X-ray techniques.

In addition to his research, Prof Demortière has been leading efforts to incorporate machine learning and deep learning into analysing experimental data, especially in image processing and computer vision. He also co-founded the startup PreDeeption, which focuses on predicting battery life, and he was awarded the CNRS Innovation RISE prize for this achievement.

Join Us in LinkedIn to welcome Prof Arnaud Demortière to the team!

 

Digital Discovery is an international gold open-access journal.

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Dr Matthias Degroote Joins the Editorial Board of Digital Discovery!

We are thrilled to announce that Dr Matthias Degroote, a leading expert in quantum chemistry and quantum computing, has joined the editorial board of Digital Discovery. Dr Degroote’s experience and research in the application of quantum computers in drug design will bring great insights and much needed expertise to our journal.

Dr Matthias Degroote is currently investigating the application of quantum computers in drug design at Boehringer Ingelheim. His expertise spans both classical and quantum computing approaches to the quantum many-body problem.

Matthias earned his PhD in physics from Ghent University, where his research focused on Green’s functions. His academic journey continued with postdoctoral research in method development at Ghent University and Rice University. Since 2018, his research has concentrated on the field of quantum computing. He has held prestigious postdoctoral positions at both Harvard University and the University of Toronto.

Dr Degroote’s work at the intersection of quantum computing and drug design is pioneering. By leveraging quantum computers, he aims to revolutionize the drug design process, making it more efficient and effective. His unique approach and innovative research are expected to bring fresh perspectives to Digital Discovery, enhancing the quality and scope of our publications.

We invite the scientific community to join us in welcoming Dr Matthias Degroote to the editorial board of Digital Discovery. His expertise will significantly contribute to our mission of publishing cutting-edge research in digital and computational sciences.

We look forward to your contributions in quantum computing and beyond and to the exciting developments that lie ahead with Dr Degroote on board!

 

 

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Meet the winners of the Digital Discovery Outstanding Early Career Researcher Award 2023

We are thrilled to announce our launch of the prestigious Outstanding Early Career Research Award, aimed at recognising and celebrating outstanding contributions to Digital Discovery. This initiative seeks to honour the dedication, innovation, and impactful research  of promising early career researchers.

Andrew White and Glen Hocky are two such remarkable individuals. Their paper, Assessment of chemistry knowledge in large language models that generate code, has not only shown how powerful language models can be in scientific research but has also opened doors for major advancements in chemistry and computational sciences.

In August 2021, OpenAI released the Codex model, a variant of GPT-3 specifically tailored for code generation. This development sparked the curiosity of White, Hocky, and their team, leading them to explore the model’s capabilities in the domain of chemistry. Their investigations revealed that Codex possessed an aptitude for generating code snippets relevant to chemical tasks, signalling a promising opportunity for computational chemistry.

Publishing their findings in Digital Discovery, the researchers unveiled their groundbreaking discoveries for the future landscape of computational chemistry. Their study not only highlighted Codex’s proficiency in handling diverse chemistry-related queries but also emphasized the significance of crafting effective prompts to optimize model performance.

Moreover, the team devised a sophisticated software tool, NLCC, enabling querying of language model APIs and code execution—evidence of their innovative outlook and commitment to advancing scientific inquiry. Although the advent of ChatGPT in November 2022 altered the scientific landscape by introducing a conversational interface, the enduring impact of their contributions remains indisputable.

Meet the winners:

Andrew White is currently a Founder and Head of Science at FutureHouse and an Associate Professor of Chemical Engineering at the University of Rochester. Glen Hocky is an Assistant Professor in the Department of Chemistry and Simons Centre for Computational Physical Chemistry at New York University. They overlapped as postdocs at the University of Chicago and have been collaborating since.

Authors Heta Gandhi, Sam Cox, Geemi Wellawatte, and Ziyue Yang were graduate students at the University of Rochester. Mehrad Ansari was a PhD student at the University of Rochester. Subarna Sasmal, Kangxin Liu, Yuvraj Singh, and William Peña Ccoa were graduate students at NYU at the time of this work.

In the light of receiving this award, the winners commented: “We are honoured to receive this recognition for our work. We have been very gratified to see that our study has resonated with other researchers at a time when the scientific community has rapidly taken up LLMs as tools in their own research. Our work led directly to Prof White’s founding of FutureHouse which is at the forefront of leveraging language models to advance scientific discovery, and we are excited to participate in driving this field forward!”

Join us in celebrating the winners on LinkedIn!

Digital Discovery Outstanding Paper Award 2022: Recognizing Excellence in 3D Concrete Printing

In the fast-paced world of scientific research, staying abreast of the latest breakthroughs and innovations is crucial. The RSC, with journals like Digital Discovery, play a vital role in disseminating cutting-edge knowledge, and one of the ways we do so is by recognizing and celebrating outstanding contributions from the global research community. We are thrilled to unveil the winners of the Digital Discovery Outstanding Paper 2022 Award.

The selection process is rigorous, with the Editorial Board carefully evaluating each paper’s scientific merit and its potential to shape future research.

Without further ado, we are proud to introduce the winners of the Digital Discovery Outstanding Paper 2022 Award:

 

 Automating mix design for 3D concrete printing using optimization methods

 

Vasileios Sergis and Claudiane M. Ouellet-Plamondon

Digital Discovery, 2022, 1, 645-657

DOI 10.1039/D2DD00040G

Winning this prestigious award is a remarkable achievement for Vasileios Sergis and Claudiane M. Ouellet-Plamondon, the authors of the winning paper. Their work on automating mix design for 3D concrete printing using optimization methods has not only garnered recognition but has also demonstrated its potential to advance 3D concrete printing technology.

In response to the news, Vasileios Sergis expressed his enthusiasm, stating, “Winning the Outstanding Paper Award 2022 is a moment of great importance, honour, and a deeply meaningful achievement for me.” He added, “This award serves as a strong motivator for continuous exploration and commitment to excellence in my academic journey. I am genuinely thankful for this award.”

Claudiane Ouellet-Plamondon echoed the excitement, emphasizing the timeliness of their research, stating, “The timing is great as we want to solve more challenges with machine learning (ML).” She highlighted the potential of ML in designing binder and concrete with a lower CO2 impact, emphasizing its importance in mitigating climate change.

Meet the Authors

 

 

 

 

  • Vasileios Sergis, PhD: A mechanical engineer specializing in automation, additive manufacturing, and artificial intelligence. He earned his bachelor’s degree in “Production Engineering and Management” from the Technical University of Crete, followed by a master’s degree in “Automation Systems” from the Technical University of Athens, where he delved into control system design, mechatronics, and robotics. His academic journey continued with a PhD in engineering at École de Technologie Supérieure – Université du Québec in Montreal, Canada, focusing on automating the development process of mortar mixtures and the quality monitoring of the layer deposition in 3D concrete printing technology by integrating statistics, artificial intelligence, optimization, and computer vision techniques.
  • Claudiane Ouellet-Plamondon is a full professor in the Department of Construction Engineering at the École de technologie supérieure (ÉTS) in Montreal, Canada. She holds the Canada Research Chair in Sustainable Multifunctional Materials in the perspective of the ecological transition and the circular economy. She studied a bachelor of engineering at Dalhousie University, a master’s degree in biological sciences at the University of Montreal, a PhD in geoenvironmental engineering from the University of Cambridge. She was a postdoctoral fellow at ETH Zurich. Her research is on functional materials, robotic 3D printing of mortars, bio-based materials, earth construction, valorisation of industrial by-products in cement, concrete and other value-added materials, materials in a circular economy perspective, as well as the sustainability of buildings and cities. She firmly believes that modelling and artificial intelligence have become indispensable tools for designing advanced materials and understanding their behaviour.

For those eager to delve deeper into the award-winning research, Vasileios Sergis and Claudiane M. Ouellet-Plamondon will be presenting their findings in a webinar series scheduled for October. The exact date is yet to be defined, so be sure to follow @digital_rsc on Twitter for updates and details on how to join these insightful sessions.

The Outstanding Paper 2022 Award recognizes and celebrates excellence in digital science. We extend our heartfelt congratulations to Vasileios Sergis and Claudiane M. Ouellet-Plamondon for their outstanding achievement, and we look forward to the insights they will share in their upcoming webinar series. Stay tuned for more exciting discoveries in the world of digital science!

 

Digital Discovery is an international gold open-access journal. All article processing charges until mid-2024.

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