  Applying AI power to predict syntheses of novel materials requires
high-quality, large-scale datasets. Extraction of synthesis information from
scientific publications is still challenging, especially for extracting
synthesis actions, because of the lack of a comprehensive labeled dataset using
a solid, robust, and well-established ontology for describing synthesis
procedures. In this work, we propose the first Unified Language of Synthesis
Actions (ULSA) for describing ceramics synthesis procedures. We created a
dataset of 3,040 synthesis procedures annotated by domain experts according to
the proposed ULSA scheme. To demonstrate the capabilities of ULSA, we built a
neural network-based model to map arbitrary ceramics synthesis paragraphs into
ULSA and used it to construct synthesis flowcharts for synthesis procedures.
Analysis for the flowcharts showed that (a) ULSA covers essential vocabulary
used by researchers when describing synthesis procedures and (b) it can capture
important features of synthesis protocols. This work is an important step
towards creating a synthesis ontology and a solid foundation for autonomous
robotic synthesis.
