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This volume presents the current status of software development in
the field of computational and theoretical chemistry and gives an
overview of the emerging trends. The challenges of maintaining the
legacy codes and their adaptation to the rapidly growing hardware
capabilities and the new programming environments are surveyed in a
series of topical reviews written by the core developers and
maintainers of the popular quantum chemistry and molecular dynamics
programs. Special emphasis is given to new computational
methodologies and practical aspects of their implementation and
application in the computational chemistry codes. Modularity of the
computational chemistry software is an emerging concept that
enables to bypass the development and maintenance bottleneck of the
legacy software and to customize the software using the best
available computational procedures implemented in the form of
self-contained modules. Perspectives on modular design of the
computer programs for modeling molecular electronic structure,
non-adiabatic dynamics, kinetics, as well as for data visualization
are presented by the researchers actively working in the field of
software development and application.Ā This volume is of
interest to quantum and computational chemists as well as
experimental chemists actively using and developing computational
software for their research. Chapters "MLatom 2: An Integrative
Platform for Atomistic Machine Learningā and āEvolution of the
Automatic Rhodopsin Modeling (ARM) Protocol" areĀ available
open access under a CC BY 4.0 License via link.springer.com.
This volume presents the current status of software development in
the field of computational and theoretical chemistry and gives an
overview of the emerging trends. The challenges of maintaining the
legacy codes and their adaptation to the rapidly growing hardware
capabilities and the new programming environments are surveyed in a
series of topical reviews written by the core developers and
maintainers of the popular quantum chemistry and molecular dynamics
programs. Special emphasis is given to new computational
methodologies and practical aspects of their implementation and
application in the computational chemistry codes. Modularity of the
computational chemistry software is an emerging concept that
enables to bypass the development and maintenance bottleneck of the
legacy software and to customize the software using the best
available computational procedures implemented in the form of
self-contained modules. Perspectives on modular design of the
computer programs for modeling molecular electronic structure,
non-adiabatic dynamics, kinetics, as well as for data visualization
are presented by the researchers actively working in the field of
software development and application. This volume is of interest to
quantum and computational chemists as well as experimental chemists
actively using and developing computational software for their
research. Chapters "MLatom 2: An Integrative Platform for Atomistic
Machine Learning" and "Evolution of the Automatic Rhodopsin
Modeling (ARM) Protocol" are available open access under a CC BY
4.0 License via link.springer.com.
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