ReviewACS physical chemistry Au2024
A Vision for the Future of Multiscale Modeling.
Review in ACS physical chemistry Au, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Strong light-matter interactions in hybrid polaritonic systems.Chemical communications (Cambridge, England) · 2026Review
- Quantized Plasmon Modes for Metallic Nanoparticles of Arbitrary Shape with a Generic Dielectric Function.The journal of physical chemistry letters · 2026Article
- Utility-Scale Quantum Computational Chemistry.The journal of physical chemistry letters · 2026Review
- Organic Chemistry as a Catalyst for AI Innovation: Challenges, Methods, and Emerging Paradigms.Chemical reviews · 2026Review
- Multiscale Architecture and Mechanics of the Cell Nucleus: Implications for Disease, Bioengineering and Nanomedicine.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Water-modulated conformational heterogeneity underlies multiple timescales of primary charge separation in photosystem II.Nature communications · 2026Article
- Multi-Scale Modeling and Experimental Validation of Thermo-Mechanical Responses in Femtosecond Laser Micromachining of Copper.Materials (Basel, Switzerland) · 2026Article
- Threshold-Filtered Kinetic Monte Carlo Simulation for Real-Time Simulation and Control of Biomass Fractionation.Industrial & engineering chemistry research · 2026Article
- Multiscale Computational Enzymology of CYP450 Biotransformation of Organic Halogenated Pollutants: Methods and Environmental Perspectives.ACS omega · 2026Review
- Emerging Advanced Electronic Packaging Materials for Thermal Management in Power Electronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- How Artificial Intelligence Can Advance Electrochemical Science and Identify Water Molecule Orientation on Platinum Electrodes.The journal of physical chemistry. C, Nanomaterials and interfaces · 2026Review
- Modeling molecular environment of allomorphic N-salicylidene-4-halo-aniline crystals through iterative QM/QM' structural optimization.Journal of molecular modeling · 2025Article
- A Rational Framework to Estimate the Chiroptical Activity of [6]Helicene Derivatives.The journal of physical chemistry. A · 2025Article
- Epitaxy of Emerging Materials and Advanced Heterostructures for Microelectronics and Quantum Sciences.Small methods · 2025Article
- CGsmiles: A Versatile Line Notation for Molecular Representations across Multiple Resolutions.Journal of chemical information and modeling · 2025Article
- Unravelling MnPhysical chemistry chemical physics : PCCP · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rise of modern computer science enabled physical chemistry to make enormous progresses in understanding and harnessing natural and artificial phenomena. Nevertheless, despite the advances achieved over past decades, computational resources are still insufficient to thoroughly simulate extended systems from first principles. Indeed, countless biological, catalytic and photophysical processes require ab initio treatments to be properly described, but the breadth of length and time scales involved makes it practically unfeasible. A way to address these issues is to couple theories and algorithms working at different scales by dividing the system into domains treated at different levels of approximation, ranging from quantum mechanics to classical molecular dynamics, even including continuum electrodynamics. This approach is known as multiscale modeling and its use over the past 60 years has led to remarkable results. Considering the rapid advances in theory, algorithm design, and computing power, we believe multiscale modeling will massively grow into a dominant research methodology in the forthcoming years. Hereby we describe the main approaches developed within its realm, highlighting their achievements and current drawbacks, eventually proposing a plausible direction for future developments considering also the emergence of new computational techniques such as machine learning and quantum computing. We then discuss how advanced multiscale modeling methods could be exploited to address critical scientific challenges, focusing on the simulation of complex light-harvesting processes, such as natural photosynthesis. While doing so, we suggest a cutting-edge computational paradigm consisting in performing simultaneous multiscale calculations on a system allowing the various domains, treated with appropriate accuracy, to move and extend while they properly interact with each other. Although this vision is very ambitious, we believe the quick development of computer science will lead to both massive improvements and widespread use of these techniques, resulting in enormous progresses in physical chemistry and, eventually, in our society.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.