GIUV2024-599
The Computational Neuromorphic Chemistry group conducts theoretical and computational research aimed at the study, characterization and prediction of the behaviour of complex chemical systems, with particular emphasis on systems related to neurochemical processes, functional materials and systems of interest for neuromorphic computing.
The research activity combines quantum-chemical methods, molecular modelling, molecular dynamics and multiscale approaches to establish relationships between the structure, dynamics and properties of chemical systems at different levels of description. These approaches are applied to the study of molecules, materials and complex systems, including molecular systems of neurochemical interest and materials with functional and memristive properties.
The group also develops computational methodologies for the simulation, processing and interpretation of spectroscopic information, with particular emphasis on nuclear magnetic resonance (NMR) spectroscopy and on the relationship between spectra acquired at different magnetic field strengths. Within this framework, models are developed for the generation and transformation of spectroscopic information and...The Computational Neuromorphic Chemistry group conducts theoretical and computational research aimed at the study, characterization and prediction of the behaviour of complex chemical systems, with particular emphasis on systems related to neurochemical processes, functional materials and systems of interest for neuromorphic computing.
The research activity combines quantum-chemical methods, molecular modelling, molecular dynamics and multiscale approaches to establish relationships between the structure, dynamics and properties of chemical systems at different levels of description. These approaches are applied to the study of molecules, materials and complex systems, including molecular systems of neurochemical interest and materials with functional and memristive properties.
The group also develops computational methodologies for the simulation, processing and interpretation of spectroscopic information, with particular emphasis on nuclear magnetic resonance (NMR) spectroscopy and on the relationship between spectra acquired at different magnetic field strengths. Within this framework, models are developed for the generation and transformation of spectroscopic information and for the extraction of chemical information from complex datasets.
Machine learning and artificial intelligence-based models are employed as transversal tools for the prediction of chemical properties, the generation and transformation of spectroscopic data, pattern recognition and the integration of information across different scales and sources. The combination of molecular modelling, multiscale simulation, computational spectroscopy and machine learning provides a predictive and interdisciplinary framework for addressing problems in chemistry, neurochemistry and materials science.
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- To develop theoretical and computational methodologies for the study of the structure, dynamics and properties of complex chemical systems, integrating different levels of molecular and electronic description.
- To develop and apply multiscale modelling methodologies capable of relating molecular and microscopic properties to the emergent behaviour of complex chemical systems and materials.
- To investigate functional materials and molecular systems with neuromorphic or memristive properties using theoretical and computational methods, identifying the chemical and physical mechanisms governing their behaviour and establishing criteria for their rational design.
- To develop computational tools capable of integrating information from different scales, methodologies and experimental sources, contributing to the predictive design and characterization of new chemical systems and functional materials.
- To investigate molecular systems of interest in neurochemistry using computational methods, with particular emphasis on the relationships between molecular structure, dynamics, interactions and properties relevant to neurochemical processes.
- To develop computational models and machine learning techniques for the prediction of chemical properties, the generation and transformation of spectroscopic data, and the extraction of relevant information from complex chemical datasets.
- To integrate computational simulations, spectroscopic information and machine learning techniques to develop predictive strategies for the characterization of chemical and neurochemical systems.
- To develop methodologies for the simulation, generation, processing and interpretation of spectroscopic information, particularly nuclear magnetic resonance (NMR) spectra, and to establish relationships between the molecular characteristics of chemical systems and their spectroscopic response.
- Theoretical and Computational Modelling of Chemical Systems of Neurochemical Interest.Development and application of theoretical and computational methods for the study of molecules, interactions and chemical systems involved in neurochemical processes. The research will address the characterization of structures, electronic properties, molecular interactions, reaction mechanisms and dynamic processes using quantum chemistry, molecular dynamics and other computational modelling approaches. The overall aim is to achieve a molecular-level understanding of chemical systems involved in processes of neurochemical and biological interest.
- Multiscale Modelling of Complex Chemical Systems.Development and application of multiscale modelling strategies for the study of complex chemical systems, integrating different spatial, temporal and energetic levels of description. Quantum chemistry, molecular dynamics, quantum mechanics/molecular mechanics and other computational approaches will be combined to establish connections between molecular structure and dynamics and the emergent properties of more complex systems, with particular interest in chemical and biological systems related to neurochemistry.
| Name | Nature of participation | Entity | Description |
|---|---|---|---|
| SALVADOR JOSE CARDONA SERRA | Director | Universitat de València |
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- Physical Chemistry
- MOLECULAR DYNAMICS
- MULTISCALE MODELLING
- MOLECULAR CHEMICAL THEORY
- REACTION MECHANISMS
- QUANTUM CHEMISTRY
- COMPLEX SYSTEMS
- MOLECULAR MODELLING
- NEUROCHEMISTRY
- MOLECULAR INTERACTIONS
- COMPLEX CHEMICAL SYSTEMS
- QUANTUM MECHANICS
- MOLECULAR MECHANICS
- MOLECULAR BIOPHYSICS
- COMPUTATIONAL SIMULATION
