Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it
demands advances—at the materials, devices and systems levels—for the efficient …

In recent years, machine learning has proven to be a powerful tool for deriving insights from
data. In this review, we describe ways in which machine learning has been leveraged to …

In alignment with the rapid development of artificial intelligence in the era of data
management, the application domains for machine learning have expanded to all …

This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …

This article evaluates the present global condition of solar and wind energy adoption and
explores their benefits and limitations in meeting energy needs. It examines the historical …

Achieving the 2016 Paris agreement goal of limiting global warming below 2° C and
securing a sustainable energy future require materials innovations in renewable energy …

With the development of modern society, the requirement for energy has become
increasingly important on a global scale. Therefore, the exploration of novel materials for …

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 …

Abstract Machine learning (ML) is a versatile technique to rapidly and efficiently generate
insights from multidimensional data. It offers a much‐needed avenue to accelerate the …

The transformation of the chemical industry to renewable energy and feedstock supply
requires new paradigms for the design of flexible plants,(bio‐) catalysts, and functional …