Turning gold standard quantum chemistry into a routine simulation tool: predictive properties for large molecular systems
This project aims to develop advanced quantum simulation methods for large molecules, enhancing predictive power and efficiency to study complex biochemical interactions and reactions.
Projectdetails
Introduction
We propose comprehensive theoretical method development targeting a long-standing dilemma in molecular quantum simulations between controllable predictive power and affordable computational time. While the outstanding reliability of quantum chemistry's gold standard model is repeatedly corroborated against experiments, its traditional form is limited to the size of an amino acid molecule.
Current Limitations
By exploiting the short-range nature of leading interaction contributions, a handful of groups, including ours, have recently extended the reach of such quantitative energy computations up to a few hundred atoms. However, these state-of-the-art models are still too demanding and are not at all equipped to compute experimentally relevant dynamic, spectroscopic, and thermodynamic molecular properties.
Proposed Solutions
Thus, to break down these barriers, we will further accelerate our cutting-edge gold standard methods up to a few thousand atoms via concerted theoretical and algorithmic developments, and high-performance software design.
Embedding Models
Additionally, we will take into account biochemical, crystal, and solvent environment effects via cost-efficient embedding models.
Observable Properties
For the first time, we will also derive and implement practical approaches to compute static and dynamic observable properties for large molecules at the gold standard level.
Impact of New Methods
The exceptional capabilities of the new methods will enable us to study challenging chemical processes of practical importance which are not accessible with chemical accuracy for any current lower-cost alternative. We aim at modeling and understanding intricate covalent- and non-covalent interactions governing supramolecular and protein-ligand binding, as well as the mechanism of organo-, organometallic, surface, and enzyme catalytic reactions.
Conclusion
Once successful, this project will deliver groundbreaking and open access tools for the systematically improvable and predictive quantum simulation of large molecules in realistic conditions and environments.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.175.215 |
Totale projectbegroting | € 1.175.215 |
Tijdlijn
Startdatum | 1-7-2023 |
Einddatum | 30-6-2028 |
Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- BUDAPESTI MUSZAKI ES GAZDASAGTUDOMANYI EGYETEMpenvoerder
Land(en)
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Predictive algorithms for simulating quantum materials
This project aims to develop advanced predictive algorithms for quantum many-body systems by integrating field-theory methods with tensor techniques and machine learning to enhance understanding of quantum materials.
Steering the Quantum Dynamics of Confined Molecular Materials
QUADYMM aims to revolutionize sustainable energy technologies by developing advanced simulations for nonequilibrium molecular dynamics, enhancing predictive capacity for electrochemistry and optoelectronics.
A quantum chemical approach to dynamic properties of real materials
This project aims to revolutionize computational materials science by developing novel, efficient methods for accurately predicting vibrational and optical properties of materials.
ab initio PRediction Of MaterIal SynthEsis
Develop a predictive framework using first-principles simulations to assess the synthesizability of novel materials, enhancing materials discovery and design efficiency.
Devising Reliable Electronic Structure Schemes through Eclectic Design
This project aims to develop an intuitive, accurate computational chemistry method for modeling large organic molecules by enhancing electron-pair states with multi-reference wave function data.
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