Advances in machine learning have impacted myriad areas of materials science, such as
the discovery of novel materials and the improvement of molecular simulations, with likely …

Combinatorial synthesis of solid-state materials comprises the use of automation or
parallelization to systematically vary synthesis parameters. This approach to materials …

A bottleneck in efficiently connecting new materials discoveries to established literature has
arisen due to an increase in publications. This problem may be addressed by using named …

The number of published materials science articles has increased manyfold over the past
few decades. Now, a major bottleneck in the materials discovery pipeline arises in …

Experimental procedures for chemical synthesis are commonly reported in prose in patents
or in the scientific literature. The extraction of the details necessary to reproduce and …

Research publications are the major repository of scientific knowledge. However, their
unstructured and highly heterogenous format creates a significant obstacle to large-scale …

Digitizing large collections of scientific literature can enable new informatics approaches for
scientific analysis and meta-analysis. However, most content in the scientific literature is …

Materials science literature contains millions of materials synthesis procedures described in
unstructured natural language text. Large-scale analysis of these synthesis procedures …

This paper presents a new challenging information extraction task in the domain of materials
science. We develop an annotation scheme for marking information on experiments related …

The synthesis process is essential for achieving computational experiment design in the
field of inorganic materials chemistry. In this work, we present a novel corpus of the …