The thermopower $α$ (also known as the Seebeck coefficient) is one of the most fundamental material characteristics for understanding charge carrier transport in thermoelectric materials. Here, we rev...

Roadmap on methods and software for electronic structure based simulations in chemistry and materials, Volker Blum, Ryoji Asahi, Jochen Autschbach, Christoph Bannwarth, Gustav Bihlmayer, Stefan Blügel, Lori A Burns, T Daniel Crawford, William Dawson, Wibe Albert de Jong, Claudia Draxl, Claudia Filippi, Luigi Genovese, Paolo Giannozzi, Niranjan Govind, Sharon Hammes-Schiffer, Jeff R Hammond, Benjamin Hourahine, Anubhav Jain, Yosuke Kanai, Paul R C Kent, Ask Hjorth Larsen, Susi Lehtola, Xiaosong Li, Roland Lindh, Satoshi Maeda, Nancy Makri, Jonathan Moussa, Takahito Nakajima, Jessica A Nash, Micael J T Oliveira, Pansy D Patel, Giovanni Pizzi, Geoffrey Pourtois, Benjamin P Pritchard, Eran Rabani, Markus Reiher, Lucia Reining, Xinguo Ren, Mariana Rossi, H Bernhard Schlegel, Nicola Seriani, Lyudmila V Slipchenko, Alexander Thom, Edward F Valeev, Benoit Van Troeye, Lucas Visscher, Vojtěch Vlček, Hans-Joachim Werner, David B Williams-Young, Theresa Windus

Scientific software development takes far more than good programming abilities and scientific reasoning. Concepts such as version control, continuous integration, packaging, deployment, automatic documentation compiling, licensing, and even file structure are not traditionally taught to scientific programmers. The skill gap leads to inconsistent code quality and difficulty deploying products to the broader audience. Most of the implementation of these skills however can be constructed at project inception. The Cookiecutter for Computational Molecular Sciences generates ready-to-go Python projects that incorporate all of the concepts above from a single command. The final product is then a software project which lets developers focus on the science and minimizes worries about nonscientific and nonprogramming concepts because the best practices, as established by the Molecular Sciences Software Institute, have already been incorporated for them. This is a community driven project with widespread adoption across the computational molecular sciences. The Molecular Sciences Software Institute and Computational Molecular Sciences community also continually contribute and update the Cookiecutter for Computational Molecular Science, ensuring that the project is responsive to community needs and tool updates. All are welcome to suggest changes and contribute to making this the best starting point for Python-based scientific code.

As a crucial parameter in the determination of thermal conductivity, the heat capacity of Cu2+xZn1−xSnS4 (CZTS) has been investigated and analyzed in detail from 2 to 773 K. The effects of the Cu–Zn s...