We invite you to read our new Digital Discovery Emerging Investigators Collection 2025.
We’re pleased to announce that a new themed collection from Digital Discovery has now been published online.
Digital Discovery is committed to supporting and recognizing the excellent work of early career researchers. We are thus proud to present our first annual Emerging Investigators collection. The collection showcases research carried out by internationally recognised, up-and-coming scientists in the early stage of their independent careers across the Digital Discovery community who are making outstanding contributions to their respective fields.
A selection of the articles has been provided below. Be sure to visit the collection the read the rest!
All articles in Digital Discovery are open access and free to read.
If you would like to nominate a colleague or yourself as an Emerging Investigator for our next collection, please contact us for further details by reply to this email.
Profile
Contributors to the Digital Discovery Emerging Investigators collection 2025
Digital Discovery, 2026, 5, DOI: 10.1039/D6DD90017H
Papers
A self-driving fluidic lab for data-driven synthesis of lead-free perovskite nanocrystals
Sina Sadeghi, Karl Mattsson, Joshua Glasheen, Victoria Lee, Christine Stark, Pragyan Jha, Nikolai Mukhin, Junbin Li Arup Ghorai, Negin Orouji, Christopher H. J. Moran, Alireza Velayati, Jeffrey A. Bennett, Richard B. Canty, Kristofer G. Reyes and Milad Abolhasani
Digital Discovery, 2025, 4, 1722-1733, DOI: 10.1039/D5DD00062A
Jakub D. Wosik, Chaoyi Zhu, Zehua Li and S. Hessam M. Mehr
Digital Discovery, 2025, 4, 2423-2430, DOI: 10.1039/D5DD00100E
Going beyond SMILES enumeration for data augmentation in generative drug discovery
Helena Brinkmann, Antoine Argante, Hugo ter Steege and Francesca Grisoni
Digital Discovery, 2025, 4, 2752-2764, DOI: 10.1039/D5DD00028A
Guanming Chen and Thijs Stuyver
Digital Discovery, 2025, 4, 3227-3237, DOI: 10.1039/D5DD00256G
Valdas Vitartas, Hanwen Zhang, Veronika Juraskova, Tristan Johnston-Wood and Fernanda Duarte
Digital Discovery, 2026, 5, 108-122, DOI: 10.1039/D5DD00261C
Babak Mahjour, Felix Katzenburg, Emil Lammi and Tim Cernak
Digital Discovery, 2026, 5, 153-160, DOI: 10.1039/D5DD00310E
FiberForge: enabling high-throughput simulations of the mechanical properties of helical fibrils
Kieran Nehil-Puleo and Zhongyue John Yang
Digital Discovery, 2026, 5, 919-930, DOI: 10.1039/D5DD00307E
shnitsel-tools: a toolkit for the full lifecycle of surface hopping trajectory data
Kevin Höllring, Theodor E. Röhrkasten and Carolin Müller
Digital Discovery, 2026, 5, DOI: 10.1039/D5DD00299K
Physics-informed machine learning for predicting temperature-dependent chemical properties
Mahyar Rajabi-Kochi, Hanie Rezaei, Sartaaj Takrim Khan Bhanu Mamillapalli, Maryam Ebrahimiazar, Haoming Ye, Rose Moosavian, Mohammad Zargartalebi, David Sinton and Seyed Mohamad Moosavi
Digital Discovery, 2026, 5, DOI: 10.1039/D5DD00489F
We hope you enjoy this new themed collection from Digital Discovery.
Sincerely,
Digital Discovery Editorial Office
Royal Society of Chemistry