Computations have played a crucial role in understanding the physical and chemical phenomena in all fields of science and engineering. Even before modern computers became broadly available to the research community, researchers were developing algorithms and methodologies for solving various problems in science and engineering which later were the first to be transformed to computer programs. These computer programs, developed mostly in academic labs, were very specific - in many cases they were used only for a certain type of problem and even for a limited range of input parameters. This started to change by transforming these lab codes to software by generalizing them to cover a broader range of physical/chemical problems. This was accomplished by enhancing them with more sophisticated algorithms, advanced data structures and proper software design. In the 1970s some versions of the academic codes started to be commercialized, at the beginning often directly by the developers. About a decade later the first companies specializing in the development of such codes began to appear.

Nowadays, the development of software for scientific purposes is termed scientific software development. Scientific software development is far from trivial since it combines aspects from Information technology (IT) and the scientific or engineering discipline that the software is designed for. The latter calls for a bridge between IT and science/engineering fields. Informatics, physics, chemistry, materials science, astrophysics, data bases, machine learning, bioprocesses or high-performance computing are only some of the fields that can “co-exist” within a scientific software.

Scientific software is playing a crucial role in understanding the nature of most physical and chemical phenomena; from black hole representation to blood flow and electron movement. More important it becomes increasingly crucial to industry for the development of new products and processes. Particularly, in the context of soft matter, scientific software is extensively used along with experiments to shed some light on the underlying physical/chemical mechanisms in science and engineering, designing new processes and new materials. Scientific software in soft matter has been developed for various systems at the molecular level or in a coarse-grained manner. However, since new methodologies and algorithms are developed while the computational power continues to increase as well, new computational practices are needed.

Despite the importance of scientific software in soft matter, not many published works exist that connect science and engineering with IT. The aim of this research topic is to highlight scientific software development efforts in soft mater; from new methodologies, algorithms and software releases to generalization schemes, high performance computing (HPC) issues and software design (e. g., usage of design patterns).

Some themes of particular interest in scientific software development in soft matter are:
• New releases of scientific software
• Models and methodologies
• Design patterns
• Generalization schemes
• HPC
• Parallel computing algorithms
• Computer languages for scientific development
• MODA & CHADA templates
• Soft matter simulations (polymers, biomaterials, colloids, gels, granular materials)
• Multiscale modeling
• Atomistic & coarse-grained simulations
• Automatic workflows
• Nanomaterials and advanced materials simulations

Αll type of articles (original research, methods, review/mini review etc.) are welcome. Nevertheless, considering the nature of the present research topic, Technology and Code article types are highly encouraged.

Topic Editors Dr. Nikolaos Cheimarios and Dr. Antreas Afantitis are employed by NovaMechanics Ltd, a private company. Dr. Jörg-Rüdiger Hill is employed by Materials Design SARL, a private company. All other Topic Editors declare no competing interests with regards to the Research Topic subject.

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