Traditional computational approaches to design chemical species are limited by the need to
compute properties for a vast number of candidates, eg, by discriminative modeling …

With the development of 5G and Internet of Things (IoT), the era of big data‐driven product
design is booming. In addition, artificial intelligence (AI) is also emerging and evolving by …

Ligand-protected noble metal nanoclusters, commonly termed 'monolayer-protected metal
clusters'(MPCs), comprise a common set of structures with an inorganic core stabilized by an …

The solar‐energy‐driven photoreduction of CO2 has recently emerged as a promising
approach to directly transform CO2 into valuable energy sources under mild conditions. As a …

Carbon capture, utilisation and storage (CCUS) will play a critical role in future
decarbonisation efforts to meet the Paris Agreement targets and mitigate the worst effects of …

Recently, a class of machine learning methods called physics-informed neural networks
(PINNs) has been proposed and gained prevalence in solving various scientific computing …

The development of a data‐driven science paradigm is greatly revolutionizing the process of
materials discovery. Particularly, exploring novel nonlinear optical (NLO) materials with the …

Large-language models (LLMs) such as GPT-4 caught the interest of many scientists.
Recent studies suggested that these models could be useful in chemistry and materials …

Materials science and chemistry have played a central and significant role in advancing
society. With the shift toward sustainable living, it is anticipated that the development of …

The screening of advanced materials coupled with the modeling of their quantitative
structural-activity relationships has recently become one of the hot and trending topics in …