Periodic Reporting for period 3 - SubNano (Computational Photochemistry in the Long Timescale: Sub-ns Photoprocesses in DNA)
Período documentado: 2022-09-01 hasta 2024-02-29
I. Method developments to speed up the dynamics and increase its reliability:
* Local-pair zero-point-energy correction (LP-ZPE), a new technique to correct zero-point energy leakage during mixed quantum-classical dynamics [1].
* Time-dependent Baeck An (TD-BA) is a method to determine nonadiabatic couplings without evaluating wavefunctions [2].
* Mixed quantum-classical dynamics with pulse ensembles (MQC-PE), a method for dynamics induced by thermal light [3].
* A new theory of the microcanonical temperature of isolated molecules [4].
* Spectrum simulations with the nuclear ensemble approach with supervised machine learning (NEA-ML) [5].
II. Implementation of scientific software.
* Newton-X NS (novel series), an entirely redesigned Newton- X version to improve performance, manage big-data, and comply with open data standards [6-7].
* Ulamdyn, a program to analyze dynamics results based on unsupervised learning techniques [8].
* New version of the PySOC program to simulate phosphorescence spectra [9].
* We have also contributed to implementing a new version of the MLatom program for atomistic machine learning [10].
III. Construction of benchmarks to critically appraise features impacting the simulations. We have analyzed:
* The conditions that should be satisfied and the algorithmic limitations of long-timescale dynamics based on ab-initio, machine-learning, and model Hamiltonian dynamics up to 1 ns [6].
* The machine-learning-potentials (MLP) accuracy, offering a guide to choosing the adequate MLP for each type of simulation[11].
* The current status and perspectives of using machine learning for excited-state simulations [12].
* The effect of the direction choice of the velocity adjustment in surface hopping [13].
* The origin of the shift between vertical excitations and band maxima to control better the comparison between theory and experiment [14].
The computer programs developed by our groups are open source and freely available for download [7-9].
All data generated by the group is available in the form of public datasets [15-20].
[1] Mukherjee; Barbatti. ChemRxiv. 2022. (DOI: 10.26434/chemrxiv-2022-53g43)
[2] do Casal, et al. Open Res Europe 2021, 1, 49. (DOI: 10.12688/openreseurope.13624.1)
[3] Barbatti. JCTC 2020, 16, 4849. (DOI: 10.1021/acs.jctc.0c00501)
[4] Barbatti. J Chem Phys 2022, accepted. (DOI: 10.26434/chemrxiv-2022-5kr7s)
[5] Xue; Barbatti; Dral. J Phys Chem A 2020, 124, 7199. (DOI: 10.1021/acs.jpca.0c05310)
[6] Mukherjee, et al. Philos Trans R Soc A 2022, 380, 20200382. (DOI: 10.1098/10.1098/rsta-2020-0382)
[7] Demoulin, et al. Newton-x ns: Novel series, 2022. https://gitlab.com/light-and-molecules/newtonx
[8] Pinheiro Jr, et al. 2021. www.ulamdyn.com
[9] Bhati, et al. Pysoc 2, 2021. https://gitlab.com/light-and-molecules/pysoc
[10] Dral, et al. Top Curr Chem 2021, 379, 27. (DOI: 10.1007/s41061-021-00339-5)
[11] Pinheiro, et al. Chem Sci 2021, 12, 14396. (DOI: 10.1039/d1sc03564a)
[12] Dral; Barbatti. Nat Rev Chem 2021, 5, 388. (DOI: 10.1038/s41570-021-00278-1)
[13] Barbatti. JCTC 2021, 17, 3010. (DOI: 10.1021/acs.jctc.1c00012)
[14] Bai, et al. J Mol Model 2020, 26, 107. (DOI: 10.1007/s00894-020-04355-y)
[15] Pinheiro Jr; Mukherjee; Barbatti. Dataset 2021. (DOI: 10.1098/rsta-2020-0382)
[16] Pinheiro Jr; Mukherjee; Barbatti. Dataset 2021. (DOI: 10.6084/m9.figshare.14873094.v1)
[17] Pinheiro Jr; Mukherjee; Barbatti. Dataset 2021. (DOI: 10.6084/m9.figshare.14823126.v1)
[18] Casal, et al. Dataset. 2021. (DOI: 10.6084/m9.figshare.14446998.v1)
[19] Barbatti. Dataset. 2021. (DOI: 10.6084/m9.figshare.14010311.v1)
[20] Barbatti. Dataset. 2021. (DOI: 10.6084/m9.figshare.13522856.v2)
* Development of Newton-X NS [1-2]: this new version of the program can be 1800 times faster than the classical Newton-X, overcoming all our expectations.
* Development of the LP-ZPE correction [3]. For decades, the ZPE leakage has been a problem haunting classical molecular dynamics simulations. Every previous attempt to solve it involved the evaluation of Hessian matrices during the propagation, which is unaffordable even in short timescales when using on-the-fly computation of electronic properties. Our method is a game-change: it corrects the ZPE leakage using a collisional model based on local vibrations, with minimum computational costs and interference in the dynamics. We have shown for a test case that dissociation of water dimers induced by ZPE leakage is fully inhibited in 20 ps ab-initio dynamics when using LP-ZPE corrections.
* Development of dynamics induced by thermal light with MQC-PE [4]. This methodology has two striking features. First, it is the only technique that allows such simulations with full nuclear dimensionality. Second, the post-processing strategy to include quantum effects in pre-computed simulations is extremely promising. We are exploring it now to include other types of quantum effects in dynamics.
[1] Mukherjee, et al. Philos Trans R Soc A 2022, 380, 20200382. (DOI: 10.1098/10.1098/rsta-2020-0382)
[2] Demoulin, et al. Newton-x ns: Novel series, 2022. https://gitlab.com/light-and-molecules/newtonx
[3] Mukherjee; Barbatti. ChemRxiv. 2022. (DOI: 10.26434/chemrxiv-2022-53g43)
[4] Barbatti. JCTC 2020, 16, 4849. (DOI: 10.1021/acs.jctc.0c00501)