Themed collection 2025 Digital Discovery Emerging Investigators

3 items

Programmable aerosol chemistry coupled to chemical imaging establishes a new arena for automated chemical synthesis and discovery
Jakub Dawid Wosik, Chaoyi Zhu, Zehua Li and S. Hessam M. Mehr
From the themed collection:
2025 Digital Discovery Emerging Investigators
The article was first published on 18 Jul 2025
Digital Discovery, 2025, Accepted Manuscript
https://doi.org/10.1039/D5DD00100E
Digital Discovery, 2025, Accepted Manuscript
https://doi.org/10.1039/D5DD00100E

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
We present a self-driving fluidic lab with a modular hardware and software for data-driven synthesis optimization of eco-friendly colloidal semiconductor nanocrystals.
From the themed collection:
2025 Digital Discovery Emerging Investigators
The article was first published on 28 Apr 2025
Digital Discovery, 2025,4, 1722-1733
https://doi.org/10.1039/D5DD00062A
Digital Discovery, 2025,4, 1722-1733
https://doi.org/10.1039/D5DD00062A

ACES-GNN: can graph neural network learn to explain activity cliffs?
Xu Chen, Dazhou Yu, Liang Zhao and Fang Liu
We introduce an activity-cliff explanation supervision training strategy to enhance both predictivity and explainability for graph neural networks in molecular structure and activity relationship modeling.
From the themed collection:
2025 Digital Discovery Emerging Investigators
The article was first published on 30 Jun 2025
Digital Discovery, 2025, Advance Article
https://doi.org/10.1039/D5DD00012B
Digital Discovery, 2025, Advance Article
https://doi.org/10.1039/D5DD00012B
3 items
About this collection
Digital Discoveryis proud to present this collection of invited contributions from early career researchers who are making significant contributions to machine learning, robotics and AI for the acceleration of discovery. Congratulations to all of the featured researchers!