Author Archive

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 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 and to the exciting developments that lie ahead with Dr Degroote on board!

Digital Discovery is an international gold open-access journal.

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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.

Sign up now to get updates on all articles as they are published on Twitter and in our e-alerts.

Professor Cesar de la Fuente joins the team as an Associate Editor

Welcome to Digital Discovery!

We are delighted to welcome Professor Cesar de la Fuente-Nunez from the University of Pennsylvania, USA, as a new Associate Editor for Digital Discovery.

Cesar de la Fuente's picture

Cesar de la Fuente is a Presidential Assistant Professor at the University of Pennsylvania, where he leads the Machine Biology Group whose goal is to combine the power of machines and biology to help prevent, detect, and treat infectious diseases. Specifically, he pioneered the development of the first antibiotic designed by a computer with efficacy in animals, designed algorithms for antibiotic discovery, reprogrammed venoms into antimicrobials, created novel resistance-proof antimicrobial materials, and invented rapid low-cost diagnostics for COVID-19 and other infections.

De la Fuente is an NIH MIRA investigator and has received recognition and research funding from numerous other groups. Prof. de la Fuente has received over 50 awards. He was recognized by MIT Technology Review as one of the world’s top innovators for “digitizing evolution to make better antibiotics”. He was selected as the inaugural recipient of the Langer Prize, an ACS Kavli Emerging Leader in Chemistry, and received the AIChE’s 35 Under 35 Award and the ACS Infectious Diseases Young Investigator Award.

In 2021, he received the Thermo Fisher Award, and the EMBS Academic Early Career Achievement Award “For the pioneering development of novel antibiotics designed using principles from computation, engineering, and biology.” Most recently, Prof. de la Fuente was awarded the prestigious Princess of Girona Prize for Scientific Research, the ASM Award for Early Career Applied and Biotechnological Research and has been named a Highly Cited Researcher by Clarivate several times.

Professor de la Fuente has given over 200 invited lectures and his scientific discoveries have yielded over 110 publications, including papers in Nature Biomedical Engineering, Nature Communications, PNAS, ACS Nano, Cell, Nature Chemical Biology, Advanced Materials, and multiple patents.


Read some of Cesar’s recent papers below.

Deep generative models for peptide design

Fangping Wan, Daphne Kontogiorgos-Heintz and Cesar de la Fuente-Nunez

Digital Discovery, 2022, 1, 195-208

AI and drug discovery

Morgan Craig, Juan Caicedo, Payel Das, James Collins, Francesca Grisoni, Cesar de la Fuente-Núñez, Yu-Shan Lin, Jian Tang

Cell Reports Physical Science, 2022, 3, 101142


Submit your work to Cesar here.

Digital Discovery cover imagePlease join us in welcoming Professor Cesar de la Fuente to Digital Discovery!

Introducing our new advisory board

We are delighted to introduce our Advisory Board for Digital Discovery!

The Digital Discovery Advisory Board is made up of outstanding researchers from chemistry, materials science, and biotechnology who contribute to the journal as reviewers and writers, provide strategic feedback, and act as community advocates. Learn more about our entire Editorial and Advisory Boards on our website and get to know our newest Advisory Board members and some of their research samples below

Meet our new Advisory Board members:




Abigail Doyle

University of California, Los Angeles, USA

The Doyle lab conducts research at the interface of organic, organometallic, physical organic, and computational chemistry.





Alexandre Tkatchenko, University of Luxembourg, Luxemburg

Dr Tkatchenko develops first-principles computational models to study a wide range of complex materials.







Berend Smit , EPFL, Switzerland

Professor Smit’s focuses on the application and development of novel molecular simulation techniques.







Cecilia Clementi, Freie Universität Berlin, Germany

Dr Clementi’s research focuses on the development and application of methods for the modelling of complex biophysical processes.







Conor Coley, MIT, USA

Professor Coley develops new methods at the intersection of data science, chemistry, and laboratory automation.







Koji Tsuda, The University of Tokyo, Japan

Dr Tsuda’s research background and current interests involve machine learning, computational biology, and computational materials science.








Marwin Segler, Microsoft, Germany

Dr Segler pioneered modern machine learning for molecular design, and chemical synthesis planning.






Heather Kulik, MIT, USA

Professor Kulik completed postdoctoral training at Lawrence Livermore and Stanford, prior to joining MIT as a faculty member.






Jan Jensen, University of Copenhagen, Denmark

Dr Jensen works in molecular discovery and reactivity prediction in the University of Copenhagen.






Isao Tanaka, Kyoto University, Japan

Professor Isao Tanaka is working on first principles calculations and data-centric science with special interests on issues in materials science and engineering.







Ola Engkvist, AstraZeneca and Chalmers University of Technology, Sweden

Professor Engkvist main research interests are deep learning based molecular de novo design, synthetic route prediction and large scale molecular property predictions.







Silvana Botti, Friedrich Schiller University Jena, Germany

Dr Botti’s research focuses on computational materials design, as well as on the development and application of many-body treatments for theoretical spectroscopy.







Shuye Ping Ong, University of California San Diego, USA

Professor Shuye leads the Materials Virtual Lab at UCSD, focusing on the interdisciplinary application of materials science, computer science, and data science to accelerate materials design.







Pablo Carbonell, University of Valencia, Spain

Dr Carbonell’s research interests are in automated design for metabolic engineering and synthetic biology.






Please join us in welcoming all of our new Advisory Board members to Digital Discovery!

Digital Discovery is open for submissions. Find out more on the journal webpage, sign up for email alerts or submit your manuscript now.


Digital Discovery Desktop Seminar

We are pleased to announce free desktop seminar to introduce Digital Discovery and share interesting new work in the journal’s scope. In this 100-minute seminar, meet the authors and editors of Digital Discovery and learn about the exciting experimental and computational work being performed to accelerate scientific progress.

If you’re interested in either seminar but can’t make the date, register your interest and we’ll send you a link to the recording afterwards.

(Update 20 October 2022 – The recording of this webinar is now available to view at this link.)

Wednesday 12 October, 1700 JST / 1600 CST / 1330 IST / 1000 CEST / 0900 BST


Professor Yuya Oaki


Keio University, Japan

Title: “Sparse modeling for small data toward digital discovery.”

Professor Xi Zhu


The Chinese University of Hong Kong, China

Title: “Towards the digitalization of chemical experiments.”


Dr Sukriti Singh


University of Cambridge, United Kingdom

Title: “Transfer learning for reaction outcome prediction with limited data.”

Prof. Emma Schymanski


University of Luxembourg, Luxembourg

Title: “Extraction of chemical structures from literature and patent documents using open access chemistry toolkits: a case study with PFAS.”


Further information