Periodic Reporting for period 5 - GEMS (General Embedding Models for Spectroscopy)
Berichtszeitraum: 2024-12-01 bis 2025-11-30
Understanding and controlling light–matter interactions at the nanoscale is a central challenge in modern physics, chemistry, and materials science. In particular, plasmonic nanostructures and graphene-based systems enable extreme enhancement and confinement of electromagnetic fields, opening new opportunities for advanced spectroscopies and molecular sensing. However, a quantitative and predictive theoretical description of these phenomena, capable of treating realistic nanostructures and complex molecular environments, has long remained out of reach.
The overall objective of the project was to develop a new generation of theoretical models and computational tools for the accurate simulation of plasmonic and surface-enhanced spectroscopies in realistic systems. The project aimed to bridge the gap between quantum-mechanical descriptions of molecules and large-scale classical models of nanostructured substrates, enabling simulations of unprecedented size and realism.
By the end of the project, these objectives have been fully achieved. The project has delivered original multiscale theoretical frameworks, efficient numerical implementations, and robust software tools that allow predictive simulations of plasmonic nanostructures containing up to millions of atoms, providing a solid and lasting foundation for future developments in enhanced spectroscopy and nanophotonics.
The overall objective of the project was to develop a new generation of theoretical models and computational tools for the accurate simulation of plasmonic and surface-enhanced spectroscopies in realistic systems. The project aimed to bridge the gap between quantum-mechanical descriptions of molecules and large-scale classical models of nanostructured substrates, enabling simulations of unprecedented size and realism.
By the end of the project, these objectives have been fully achieved. The project has delivered original multiscale theoretical frameworks, efficient numerical implementations, and robust software tools that allow predictive simulations of plasmonic nanostructures containing up to millions of atoms, providing a solid and lasting foundation for future developments in enhanced spectroscopy and nanophotonics.
Throughout the project, significant effort was devoted to the development of multiscale models combining quantum-mechanical descriptions of molecular systems with classical and semiclassical representations of plasmonic substrates. Novel formulations of force-fields were developed and extended to frequency-dependent regimes, allowing the simulation of optical and spectroscopic responses of large metallic and graphene-based nanostructures.
These theoretical advances were translated into efficient and scalable computational implementations. The project resulted in the development of dedicated software tools, including stand-alone open codes and the integration of advanced methodologies into widely used computational chemistry platforms. This ensured both robustness and accessibility of the developed methods to the broader scientific community.
The models were applied to a wide range of realistic systems, including metal nanoparticles, graphene-based substrates, and hybrid molecule–nanostructure assemblies, enabling quantitative studies of plasmonic response and surface-enhanced Raman spectroscopy. The project produced a substantial body of peer-reviewed publications in high-impact journals and contributed to the training of highly qualified researchers.
Results were disseminated through international conferences, invited lectures, workshops, and software distribution, fostering strong interaction with both academic and industrial partners and promoting the uptake of the developed methodologies beyond the project itself.
These theoretical advances were translated into efficient and scalable computational implementations. The project resulted in the development of dedicated software tools, including stand-alone open codes and the integration of advanced methodologies into widely used computational chemistry platforms. This ensured both robustness and accessibility of the developed methods to the broader scientific community.
The models were applied to a wide range of realistic systems, including metal nanoparticles, graphene-based substrates, and hybrid molecule–nanostructure assemblies, enabling quantitative studies of plasmonic response and surface-enhanced Raman spectroscopy. The project produced a substantial body of peer-reviewed publications in high-impact journals and contributed to the training of highly qualified researchers.
Results were disseminated through international conferences, invited lectures, workshops, and software distribution, fostering strong interaction with both academic and industrial partners and promoting the uptake of the developed methodologies beyond the project itself.
The project has significantly advanced the state of the art in the theoretical modelling of plasmonic nanomaterials and enhanced spectroscopies. Prior to this work, realistic simulations of large nanostructured substrates coupled to molecular systems were severely limited by computational cost and methodological constraints. The models developed within this project overcome these limitations by enabling accurate, predictive, and scalable simulations that bridge quantum and classical descriptions in a unified framework.
A major breakthrough lies in the ability to treat nanostructures of realistic size and complexity, including systems containing up to millions of atoms, while retaining a quantum-mechanical description of molecular properties. This represents a qualitative leap beyond existing approaches and opens new avenues for theory-driven interpretation and design of experiments.
Although the project has formally concluded, the results obtained establish a platform for future developments. The methodologies and software tools developed are expected to enable increasingly close interaction with experimental research, facilitate the design of next-generation plasmonic and spectroscopic experiments, and support long-term advances in areas such as molecular sensing, nanomaterials, and energy-related applications.
A major breakthrough lies in the ability to treat nanostructures of realistic size and complexity, including systems containing up to millions of atoms, while retaining a quantum-mechanical description of molecular properties. This represents a qualitative leap beyond existing approaches and opens new avenues for theory-driven interpretation and design of experiments.
Although the project has formally concluded, the results obtained establish a platform for future developments. The methodologies and software tools developed are expected to enable increasingly close interaction with experimental research, facilitate the design of next-generation plasmonic and spectroscopic experiments, and support long-term advances in areas such as molecular sensing, nanomaterials, and energy-related applications.