@article{PhysRevResearch.5.043083,

title = {Manifestations of local supersolidity of $^4$He around a charged molecular impurity},

author = {Fabien Brieuc and Christoph Schran and Dominik Marx},

url = {https://link.aps.org/doi/10.1103/PhysRevResearch.5.043083},

doi = {10.1103/PhysRevResearch.5.043083},

year  = {2023},

date = {2023-10-01},

urldate = {2023-10-01},

journal = {Phys. Rev. Res.},

volume = {5},

issue = {4},

pages = {043083},

publisher = {American Physical Society},

keywords = {Nuclear quantum effects, path integral molecular dynamics (PIMD), Superfluidity},

pubstate = {published},

tppubtype = {article}

}

@article{Schran2023/10.1103/PhysRevLett.130.083001,

title = {Onset of Rotational Decoupling for a Molecular Ion Solvated in Helium: From Tags to Rings and Shells},

author = {Julia A. Davies and Christoph Schran and Fabien Brieuc and Dominik Marx and Andrew M. Ellis},

doi = {10.1103/PhysRevLett.130.083001},

year  = {2023},

date = {2023-02-01},

urldate = {2023-02-01},

journal = {Phys. Rev. Lett.},

volume = {130},

issue = {8},

pages = {083001},

publisher = {American Physical Society},

keywords = {Nuclear quantum effects, path integral molecular dynamics (PIMD), Superfluidity, Water},

pubstate = {published},

tppubtype = {article}

}

@article{Duran2022/10.1063/5.0100953,

title = {Neural Network Interaction Potentials for para-Hydrogen with Flexible Molecules},

author = {Laura Durán Caballero and Christoph Schran and Fabien Brieuc and Dominik Marx},

doi = {10.1063/5.0100953},

issn = {0021-9606},

year  = {2022},

date = {2022-08-01},

urldate = {2022-08-01},

journal = {J. Chem. Phys.},

volume = {157},

number = {7},

pages = {074302},

publisher = {AIP Publishing LLCAIP Publishing},

abstract = {The study of molecular impurities in para-hydrogen (pH2) clusters is key to push forward our understanding of intra- and intermolecular interactions including their impact on the superfluid response of this bosonic quantum solvent. This includes tagging with one or very few pH2, the microsolvation regime, and matrix isolation. However, the fundamental coupling between the bosonic pH2 environment and the (ro-)vibrational motion of molecular impurities remains poorly understood. Quantum simulations can in provide the necessary atomistic insight, but very accurate descriptions of the involved interactions are required. Here, we present a data-driven approach for the generation of impurity-pH2 interaction potentials based on machine learning techniques which retain the full flexibility of the impurity. We employ the well-established adiabatic hindered rotor (AHR) averaging technique to include the impact of the nuclear spin statistics on the symmetry-allowed rotational quantum numbers of pH2. Embedding this averaging procedure within the high-dimensional neural network potential (NNP) framework enables the generation of highly-accurate AHR-averaged NNPs at coupled cluster accuracy, namely CCSD(T*)-F12a/aVTZcp in an automated manner. We apply this methodology to the water and protonated water molecules, as representative cases for quasi-rigid and highly-flexible molecules respectively, and obtain AHR-averaged NNPs that reliably describe the H2O-pH2 and H3O+-pH2 interactions. Using path integral simulations we show for the hydronium cation that umbrella-like tunneling inversion has a strong impact on the first and second pH2 microsolvation shells. The data-driven nature of our protocol opens the door to the study of bosonic pH2 quantum solvation for a wide range of embedded impurities.},

keywords = {Machine Learning Potentials, Nuclear quantum effects, Superfluidity, Water},

pubstate = {published},

tppubtype = {article}

}

@article{Brieuc2020/10.1063/5.0008309,

title = {Converged quantum simulations of reactive solutes in superfluid helium: The Bochum perspective},

author = {Fabien Brieuc and Christoph Schran and Felix Uhl and Harald Forbert and Dominik Marx},

doi = {10.1063/5.0008309},

issn = {10897690},

year  = {2020},

date = {2020-06-01},

urldate = {2020-06-01},

journal = {J. Chem. Phys.},

volume = {152},

number = {21},

pages = {210901},

abstract = {Superfluid helium has not only fascinated scientists for centuries but is also the ideal matrix for the investigation of chemical systems under ultra-cold conditions in helium nanodroplet isolation experiments. Together with related experimental techniques such as helium tagging photodissociation spectroscopy, these methods have provided unique insights into many interesting systems. Complemented by theoretical work, they were additionally able to greatly expand our general understanding of manifestations of superfluid behavior in finite sized clusters and their response to molecular impurities. However, most theoretical studies up to now have not included the reactivity and flexibility of molecular systems embedded in helium. In this perspective, the theoretical foundation of simulating fluxional molecules and reactive complexes in superfluid helium is presented in detail. Special emphasis is put on recent developments for the converged description of both the molecular interactions and the quantum nature of the nuclei at ultra-low temperatures. As a first step, our hybrid path integral molecular dynamics/bosonic path integral Monte Carlo method is reviewed. Subsequently, methods for efficient path integral sampling tailored for this hybrid coupling scheme are discussed while also introducing new developments to enhance the accurate incorporation of the solute⋯solvent coupling. Finally, highly accurate descriptions of the interactions in solute⋯helium systems using machine learning techniques are addressed. Our current automated and adaptive fitting procedures to parameterize high-dimensional neural network potentials for both the full-dimensional potential energy surface of solutes and the solute⋯solvent interaction potentials are concisely presented. They are demonstrated to faithfully represent many-body potential functions able to describe chemically complex and reactive solutes in helium environments seamlessly from one He atom up to bulk helium at the accuracy level of coupled cluster electronic structure calculations. Together, these advances allow for converged quantum simulations of fluxional and reactive solutes in superfluid helium under cryogenic conditions.},

keywords = {Nuclear quantum effects, path integral molecular dynamics (PIMD), Superfluidity},

pubstate = {published},

tppubtype = {article}

}

@article{Schran2018/10.1063/1.4996819,

title = {High-dimensional neural network potentials for solvation: The case of protonated water clusters in helium},

author = {Christoph Schran and Felix Uhl and Jörg Behler and Dominik Marx},

doi = {10.1063/1.4996819},

issn = {00219606},

year  = {2018},

date = {2018-03-01},

urldate = {2018-03-01},

journal = {J. Chem. Phys.},

volume = {148},

number = {10},

pages = {102310},

abstract = {The design of accurate helium-solute interaction potentials for the simulation of chemically complex molecules solvated in superfluid helium has long been a cumbersome task due to the rather weak but strongly anisotropic nature of the interactions. We show that this challenge can be met by using a combination of an effective pair potential for the He–He interactions and a flexible high-dimensional neural network potential (NNP) for describing the complex interaction between helium and the solute in a pairwise additive manner. This approach yields an excellent agreement with a mean absolute deviation as small as 0.04 kJ mol−1 for the interaction energy between helium and both hydronium and Zundel cations compared with coupled cluster reference calculations with an energetically converged basis set. The construction and improvement of the potential can be performed in a highly automated way, which opens the door for applications to a variety of reactive molecules to study the effect of solvation on the solu...},

keywords = {Machine Learning Potentials, Nuclear quantum effects, Superfluidity, Water},

pubstate = {published},

tppubtype = {article}

}