npj Computational Materials is a premier open-access journal dedicated to publishing high-quality research in the dynamic field of computational materials science. With a focus on bridging the gap between theoretical advancements and experimental validation, this journal aims to showcase innovative computational methods and their applications in understanding, predicting, and designing novel materials.
Key topics covered include electronic structure calculations, molecular dynamics simulations, machine learning for materials discovery, and the development of new computational algorithms. The journal welcomes submissions that address a broad range of materials, from solid-state crystals to soft matter and biological materials. Indexed in major databases like Scopus and Web of Science, npj Computational Materials provides a platform for researchers across various disciplines to share their findings and foster collaboration.
By publishing rigorously peer-reviewed research, npj Computational Materials aims to drive innovation in materials science and engineering. Authors are encouraged to submit their high-impact work and contribute to the advancement of this rapidly evolving field, enhancing our ability to design and tailor materials for specific applications. The journal supports open science principles and encourages the sharing of data and code to facilitate reproducibility and further research.