Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …

Dye-sensitized solar cells (DSCs) are celebrating their 30th birthday and they are attracting
a wealth of research efforts aimed at unleashing their full potential. In recent years, DSCs …

Given the emergence of data science and machine learning throughout all aspects of
society, but particularly in the scientific domain, there is increased importance placed on …

We present a benchmark test suite and an automated machine learning procedure for
evaluating supervised machine learning (ML) models for predicting properties of inorganic …

Abstract “Artificial Intelligence” in all its forms has emerged as a transformative technology
that is in the process of resha** many aspects of industry and wider society at a global …

Dye-sensitized solar cells (DSCs) are a next-generation photovoltaic technology, whose
natural transparency and good photovoltaic output under ambient light conditions afford …

A database of battery materials is presented which comprises a total of 292,313 data
records, with 214,617 unique chemical-property data relations between 17,354 unique …

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

The condensation of 4-diethylaminosalicylaldehyde and 3, 5-di-tert-butyl-salicylaldehyde
with 3, 4-diaminobenzoic acid afforded two salophen type Schiff base ligands, L1 and L2 …

The ever-growing abundance of data found in heterogeneous sources, such as scientific
publications, has forced the development of automated techniques for data extraction. While …