  The development of complex functional materials poses a multi-objective
optimization problem in a large multidimensional parameter space. Solving it
requires reproducible, user independent laboratory work and intelligent
preselection of experiments. However, experimental materials science is a field
where manual routines are still predominant, although other domains like
pharmacy or chemistry have long used robotics and automation. As the number of
publications on Materials Acceleration Platforms (MAPs) increases steadily, we
review selected systems and fit them into the stages of a general material
development process to examine the evolution of MAPs. Subsequently we present
our approach to laboratory automation in materials science. We introduce AMANDA
(Autonomous Materials and Device Application Platform), a generic platform for
distributed materials research comprising a self-developed software backbone
and several MAPs. One of them, LineOne (L1), is specifically designed to
produce and characterize solution processed thin-film devices like organic
solar cells (OSC). It is designed to perform precise closed-loop screenings of
up to 272 device variations per day yet allows further upscaling. Each
individual solar cell is fully characterized and all process steps are
comprehensively documented. We want to demonstrate the capabilities of AMANDA
L1 with OSCs based on PM6:Y6 with 13.7% efficiency when processed in air.
Further we discuss challenges and opportunities of highly automated research
platforms and elaborate on the future integration of additional techniques,
methods and algorithms in order to advance to fully autonomous self-optimizing
systems - a paradigm shift in functional materials development leading to the
laboratory of the future.
