Research Framework
Multiscale research goals define the materials behavior, evidence, and system outcomes that OA-SDL helps connect.
Open-Access Self-Driving Laboratory | Platforms | INSTITUTE…
IMMS is a platform-based research hub at Ewha Womans University advancing multiscale matter and systems research through integrated platforms, core projects, a…
The Open-Access Self-Driving Laboratory (OA-SDL) is a core IMMS research platform that implements AI-driven autonomous experimentation. Operated as shared infrastructure, OA-SDL accelerates the research lifecycle by enabling continuous, automated experimentation for a broad research community.
OA-SDL / OPEN-ACCESS SELF-DRIVING LABORATORY
The Open-Access Self-Driving Laboratory (OA-SDL) serves as the practical research engine of the IMMS framework, combining artificial intelligence-driven hypothesis generation, robotics-enabled automated experimentation, and real-time data analysis into a seamless autonomous system. This integrated environment dramatically enhances research productivity beyond traditional manual experiment workflows by enabling continuous, self-optimizing experimentation.
OA-SDL operates under an open-access model, meaning that it is not restricted to single labs. Researchers from academic institutions, industry partners, and research organizations worldwide can leverage this shared infrastructure and methodologies to pursue collaborative research. By doing so, OA-SDL fosters interdisciplinary cooperation, accelerates the translation of research outcomes, and supports a diverse range of scientific challenges.
More than a facility, OA-SDL represents a new paradigm in data-driven research, enabling researchers to focus on strategic thinking and creative discovery while routine experimentation is managed autonomously. The platform is closely integrated with IMMS's Technical Groups and Core Projects, providing a unifying base for multiscale, problem-oriented research across the institute.
ROLE IN THE IMMS FRAMEWORK
OA-SDL connects Technical Groups and Core Projects through shared autonomous experimentation infrastructure, making AI planning, robotic execution, real-time data learning, and multiscale research feedback operate as one IMMS research system.
Multiscale research goals define the materials behavior, evidence, and system outcomes that OA-SDL helps connect.
TG expertise and CP missions shape the hypotheses, constraints, and validation needs for each autonomous research cycle.
AI decision support, robotics-enabled experimentation, and real-time data capture provide the shared engine for continuous research execution.
Validated results return to the framework as publications, collaboration models, translated outcomes, and new research directions.