Plasma A-Lab
Redefining the speed of material discovery through AI and robotics

Shortening the future of materials science

For centuries, discovering a new material has been like hunting for a needle in a haystack. At Plasma A-Lab, we no longer wait for luck. We believe the era of repetitive manual experimentation is coming to an end, paving the way for a better blend of human intuition and robotic precision. Our vision is not just to build a modern laboratory, but to create an autonomous brain - a place where AI and Robotics solve humanity’s greatest challenges, from clean energy to smart medicine. We aren't just doing science, we are pioneering a new way of thinking, where every second brings us closer to world-changing discoveries.

PROJECT OVERVIEW

• Principal investigator (PI): Prof. Dr. Nguyen Thanh Tung – Head of Plasma Technology Laboratory. Expert in computational materials science, plasma technology, nanomaterials synthesis, and materials informatics.

• Core team: Dr. Nguyen Nhat Linh and Dr. Nguyen Hoang Tung, specialists in automated experiments and physical/chemical synthesis. Dr. Nguyen Thi Mai and Mr. Nguyen Van Hue, experienced in DFT calculations, machine learning, and data analysis.

• Expected collaboration: Prof. Haiqing Yin (USTB, China) – International collaborator on FAIR data and open data publishing. Prof. Kwang‑Ryeol Lee (KIST, Korea) – Advisor on materials data standardization.

• Funding: Funded by Vietnam Academy of Science and Technology.

STRATEGIC GOALS

• Develop an autonomous system capable of conducting 100+ materials-synthesis experiments daily without human intervention.

• Accelerate the discovery-to-knowledge timeline from 10 years down to 1 year.

• Optimize resource utilization and minimize chemical waste in research.

METHODOLOGY

The project follows a multi‑disciplinary approach. First, a literature review and benchmarking of state‑of‑the‑art autonomous labs will be conducted. Next, we will design and construct the hardware: a cold plasma reactor, automated pipetting and stirring stations, a UV‑Vis spectrometer, an optical imaging system, and collaborative robots (cobots) with 6‑axis freedom. A layered software architecture (PLC/ROS, WebHMI) will control spatial‑temporal operations, synchronize all modules, and store metadata. Using design of experiments (DoE), the autonomous lab will perform end‑to‑end workflows (precursor preparation → plasma synthesis → catalytic testing → data logging) with ≥80% automation. The generated data will be FAIR‑formatted (Findable, Accessible, Interoperable, Reusable) and stored in a local server. Finally, machine learning models (Random Forest, XGBoost, neural networks) will be trained on the experimental dataset to predict particle size, catalytic activity, and optimal synthesis conditions.

CORE TECHNOLOGIES

• Closed-loop AI: Utilizing different optimization algorithms to design the next experiment based on real-time data automatically.

• Robots and Cobots: High-precision robotic arms for mixing, heating, and handling samples with absolute accuracy.

• In-situ characterization: Integrated sensors and spectroscopy for real-time assessment of synthesis results.

• Materials informatics: Storing and analyzing millions of data points to predict material properties via Big Data

EXPECTED OUTCOME

The project will deliver: (1) one fully operational autonomous laboratory for cold‑plasma synthesis and characterization of Au/Pt nanoparticles, meeting >80% automation, ≥50 samples/day, and ≥95% repeatability. (2) A FAIR‑compliant dataset containing at least 1,000 independent synthesis‑characterization records (including UV‑Vis spectra, optical images, and catalytic activity data). (3) One peer‑reviewed paper in a Q2 or higher international journal, one national journal paper, and two presentations at domestic conferences. (4) One accepted patent application for the autonomous lab system. (5) Training support for one PhD student. The system will serve as a blueprint for scaling to other material systems (oxides, 2D materials) and can be transferred to industry for rapid R&D, cutting costs and time while enhancing data‑driven innovation in Vietnam.