Autonomous Laboratory Systems · Est. 2023

Engineering
Self-Driving
Laboratories

BRAINLAB pioneers next-generation autonomous chemistry through robotic photoelectrochemical platforms, AI-driven catalysis discovery, and closed-loop experimental intelligence.

Explore Research View Platform
0+
Autonomous experiments
0
Publications
0%
Prediction accuracy
BRAINLAB · Inside the autonomous lab
See a closed-loop campaign run end to end Watch the film
3.8×
Faster discovery
12 robots
Online now
Scroll
About BRAINLAB

Where Chemistry Meets
Robotic Intelligence

BRAINLAB is an independent deep-tech research group at the intersection of autonomous robotics, electrochemical science, and machine learning. We design and deploy closed-loop laboratory systems that discover, optimize, and validate chemical processes without human intervention.

Our infrastructure combines high-throughput robotic platforms, multi-modal chemical sensing, and AI-driven experimental orchestration — enabling an entirely new paradigm for scientific discovery at the molecular scale.

0+
Publications
0
Active robots
0
Years active
Research Areas

Six Pillars of
Autonomous Discovery

All research →
01
Electrochemistry
Automated potentiostatic systems for high-throughput electrochemical characterization, synthesis, and material discovery with sub-millisecond time resolution.
02
Catalysis
Robotic exploration of heterogeneous and homogeneous catalyst design spaces. Combinatorial screening guided by ML surrogate models for electrocatalysts.
03
Laboratory Automation
End-to-end robotic orchestration: liquid handling, solid dispensing, analytical instrument integration, and autonomous sample management at scale.
04
Autonomous Experimentation
Closed-loop systems that design, execute, analyze, and iterate without human oversight. Bayesian optimization and reinforcement learning at the bench.
05
AI & Data Infrastructure
High-dimensionality chemical data pipelines, foundation models for molecular property prediction, and real-time analytics for multi-modal lab streams.
06
Chemical Discovery
Data-driven navigation of vast chemical space using generative models and active learning to accelerate functional material discovery.
Robotics Platform

The Autonomous
Laboratory OS

  • 01
    Modular Robotic Architecture

    Scalable six-axis robotic arms with custom end-effectors for liquid handling, solid sampling, and in-line analytical integration across chemistry workflows.

  • 02
    Real-time Experiment Control

    Sub-millisecond sensor fusion across electrochemical, spectroscopic, and thermal channels with adaptive feedback for closed-loop experimental control.

  • 03
    AI Experiment Orchestration

    Bayesian optimization engine with Gaussian process surrogates driving fully autonomous multi-step synthesis and characterization campaigns.

  • 04
    Digital Twin Integration

    Physics-informed digital replica of the laboratory enabling simulation-guided experiment planning and predictive maintenance.

Explore Platform
BRAINLAB OS · Campaign #4872 Active
CURRENT YIELD
87.4%
↑ +3.1% from baseline
Running
ITERATION
31
SENSORS
24/24
AI STATUS
Online
OPTIMIZATION CURVE
3.8×
Faster discovery
12 robots
Online now
0+
Experiments Executed Autonomously
0%
Prediction Accuracy on Held-out Data
0×
Faster Discovery vs. Manual Research
0+
Peer-reviewed Publications
Featured Publications

Recent Breakthroughs
from the Lab

All publications →
Nature Chemistry 2024
Autonomous electrochemical discovery of high-performance oxygen reduction catalysts using closed-loop robotic screening
Martínez, E.R.; Chen, Y.; Holmqvist, L.; et al.
Science Advances 2024
Bayesian optimization with multi-fidelity surrogates for accelerated heterogeneous catalyst design in flow chemistry systems
Nakamura, T.; Ibrahim, S.; Patel, V.; et al.
JACS 2023
Self-driving laboratories for electrochemical CO₂ reduction: Integrating robotic synthesis with operando characterization
Chen, Y.; Díaz, A.; Martínez, E.R.; et al.
ACS Nano 2023
Graph neural network potentials for reactive electrolyte interfaces trained on autonomous experimental data
Holmqvist, L.; Nakamura, T.; et al.
Supported & Partnered With
ERC Synergy
Horizon Europe
NSF DMREF
Volkswagen Foundation
BASF
Bosch Research
MIT Energy Initiative
Latest News

From the
Research Front

All news →
March 12, 2025
BRAINLAB's autonomous system discovers novel platinum-free catalyst for hydrogen evolution
A closed-loop robotic campaign spanning 8,400 experiments identified a ternary transition metal nitride exceeding state-of-the-art benchmarks by 31%.
January 28, 2025
ERC Synergy Grant awarded for multi-lab autonomous chemistry network
€15.2M grant to establish a federated network of self-driving labs across four European research institutions.
December 5, 2024
Next-generation ATLAS robotic platform v2 unveiled
The upgraded system integrates inline mass spectrometry, operando X-ray diffraction, and a 7-axis collaborative robot arm.
Contact

Ready to Build the
Future Lab?

We collaborate with industry partners, academic institutions, and funding bodies to advance autonomous chemistry infrastructure worldwide.

Get in Touch Read Research