Molecular Dynamics Techniques in the Artificial Intelligence Era
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 92
Special Issue Editors
Interests: molecular dynamics; quantum chemistry; density functional theory; computational chemistry; nanomaterials; energy storage; carbon dioxide conversion; ionic liquids; metal-organic frameworks
Special Issues, Collections and Topics in MDPI journals
Interests: thermodynamics; phase-equilibrium; molecular simulation; separation processes
Special Issues, Collections and Topics in MDPI journals
Interests: computational chemistry; carbon dioxide capture and conversion; lithium-ion batteries; machine learning; quantum chemistry
Special Issue Information
Dear Colleagues,
From its origins in the mid-20th century as a computational tool to understand the dynamic behavior of atoms and molecules, molecular dynamics (MD) simulations have become indispensable for investigating a vast range of phenomena, from the intricate folding of proteins to the design of novel materials and drug therapies. Crucial to the accuracy of these simulations are robust force fields, and this Special Issue features significant developments in force field methodologies, critically important for achieving reliable results. The issue also explores statistical mechanics for insightful MD analysis and the transformative potential of machine learning in accelerating MD approaches. By providing unprecedented atomic-level insights, MD simulations are poised to drive innovation across diverse scientific disciplines, and this collection offers a focused overview of its current advancements and future promise. Topics:
- Force field developments for classical MD simulations.
- Statistical mechanics applied to MD analysis and post-processing.
- Molecular dynamics based on machine learning developments.
- New insights and perspectives on molecular dynamics simulations.
- Molecular dynamics applied in drug delivery.
- Free energy methods applied in molecular dynamics simulations.
- Advances in molecular dynamics: embracing the artificial intelligence revolution.
- Bridging the divide: molecular dynamics and artificial intelligence for future discoveries.
- New tools and developments in molecular dynamics simulations.
Dr. Luciano Tavares Costa
Dr. Andrew S. Paluch
Prof. Dr. Itamar Borges Junior
Guest Editors
Manuscript Submission Information
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Keywords
- molecular dynamics
- machine learning
- force field
- free energy
- statistical mechanics
- algorithm development
- artificial intelligence
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