Summary
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. 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.
Thus, to break down these barriers, we will further accelerate our cutting-edge gold standard methods up
to few 1000 atoms via concerted theoretical and algorithmic developments, and high-performance software
design. Additionally, we will take into account biochemical, crystal, and solvent environment effects via
cost-efficient embedding models. 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. 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.
Once successful, this project we will deliver groundbreaking and open access tools for the systematically
improvable and predictive quantum simulation of large molecules in realistic conditions and environments.
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. 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.
Thus, to break down these barriers, we will further accelerate our cutting-edge gold standard methods up
to few 1000 atoms via concerted theoretical and algorithmic developments, and high-performance software
design. Additionally, we will take into account biochemical, crystal, and solvent environment effects via
cost-efficient embedding models. 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. 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.
Once successful, this project we will deliver groundbreaking and open access tools for the systematically
improvable and predictive quantum simulation of large molecules in realistic conditions and environments.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101076972 |
| Start date: | 01-07-2023 |
| End date: | 30-06-2028 |
| Total budget - Public funding: | 1 175 215,00 Euro - 1 175 215,00 Euro |
Cordis data
Original description
We propose comprehensive theoretical method development targeting a long-standing dilemma in molecularquantum 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. 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.
Thus, to break down these barriers, we will further accelerate our cutting-edge gold standard methods up
to few 1000 atoms via concerted theoretical and algorithmic developments, and high-performance software
design. Additionally, we will take into account biochemical, crystal, and solvent environment effects via
cost-efficient embedding models. 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. 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.
Once successful, this project we will deliver groundbreaking and open access tools for the systematically
improvable and predictive quantum simulation of large molecules in realistic conditions and environments.
Status
SIGNEDCall topic
ERC-2022-STGUpdate Date
31-07-2023
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