arXiv subjects

Markus Meuwly

Publications and source records attributed to Markus Meuwly.

At least 55 records · Page 3Linked to original sources

arXiv2024

CO$_2$ and NO$_2$ Formation on Amorphous Solid Water

The dynamics for molecule formation, relaxation, diffusion, and desorption on amorphous solid water is studied in a quantitative fashion. We aim at characterizing, at a quantitative level, the formation probability, stabilization, energy relaxation and diffusion dynamics of CO$_2$ and NO$_2$ on cold amorphous solid water following atom+diatom recombination reactions. Accurate machine-learned energy functions combined with fluctuating charge models were used to investigate the diffusion, interactions, and recombination dynamics of atomic oxygen with CO and NO on amorphous solid water (ASW). Energy relaxation to the ASW and into water-internal-degrees of freedom were determined from analysis of the vibrational density of states. The surface diffusion and desorption energetics was investigated from extended and nonequilibrium MD simulations. The reaction probability on the nanosecond time scale is determined in a quantitative fashion and demonstrates that surface diffusion of the reactants leads to recombination for initial separations up to 20 Å\/. After recombination both, CO$_2$ and NO$_2$, stabilize by energy transfer to water internal and surface phonon modes on the picosecond time scale. The average diffusion barriers and desorption energies agree with those reported from experiments. After recombination, the triatomic products diffuse easily which contrasts with the equilibrium situation in which both, CO$_2$ and NO$_2$, are stationary on the multi-nanosecond time scale.

physics.chem-ph↗

arXiv2024

Outlier-Detection for Reactive Machine Learned Potential Energy Surfaces

Uncertainty quantification (UQ) to detect samples with large expected errors (outliers) is applied to reactive molecular potential energy surfaces (PESs). Three methods - Ensembles, Deep Evidential Regression (DER), and Gaussian Mixture Models (GMM) - were applied to the H-transfer reaction between ${\it syn-}$Criegee and vinyl hydroxyperoxide. The results indicate that ensemble models provide the best results for detecting outliers, followed by GMM. For example, from a pool of 1000 structures with the largest uncertainty, the detection quality for outliers is $\sim 90$ \% and $\sim 50$ \%, respectively, if 25 or 1000 structures with large errors are sought. On the contrary, the limitations of the statistical assumptions of DER greatly impacted its prediction capabilities. Finally, a structure-based indicator was found to be correlated with large average error, which may help to rapidly classify new structures into those that provide an advantage for refining the neural network.

physics.chem-ph↗

arXiv2024

OH-Formation Following Vibrationally Induced Reaction Dynamics of H$_2$COO

The reaction dynamics of H$_2$COO to form linear HCOOH and dioxirane as first steps for OH-elimination is quantitatively investigated. Using a machine learned potential energy surface at the CASPT2/aug-cc-pVTZ level of theory vibrational excitation along the CH-normal mode $ν_{\rm CH}$ with energies up to 40.0 kcal/mol ($\sim 5 ν_{\rm CH}$) leads almost exclusively to linear HCOOH which further decomposes into OH+HCO. Although the barrier to form dioxirane is only 21.4 kcal/mol the reaction probability to form dioxirane is two orders of magnitude lower if the CH-stretch mode is excited. Following the dioxirane-formation pathway is facile, however, if in addition the COO-bend vibration is excited with energies equivalent to $\sim (2 ν_{\rm CH} + 4 ν_{\rm COO})$ or $\sim (3 ν_{\rm CH} + ν_{\rm COO})$. For OH-formation in the atmosphere the pathway through linear HCOOH is probably most relevant because the alternative pathways (through dioxirane or formic acid) involve several intermediates that can de-excite through collisions, relax {\it via} Intramolecular vibrational energy redistribution (IVR), or pass through very loose and vulnerable transition states (formic acid). This work demonstrates how, by selectively exciting particular vibrational modes, it is possible to dial into desired reaction channels with a high degree of specificity for a process relevant to atmospheric chemistry.

physics.chem-ph↗

arXiv2023

Numerical Accuracy Matters: Applications of Machine Learned Potential Energy Surfaces

The role of numerical accuracy in training and evaluating neural network-based potential energy surfaces is examined for different experimental observables. For observables that require third- and fourth-order derivatives of the total energy with respect to Cartesian coordinates single-precision arithmetics as is typically used in ML-based approaches is insufficient and leads to roughness of the underlying PES as is explicitly demonstrated. Increasing the numerical accuracy to double-precision yields a smooth PES with higher-order derivatives that are numerically stable and yield meaningful anharmonic frequencies and tunneling splitting as is demonstrated for H$_2$CO and malonaldehyde. For molecular dynamics simulations, which only require first-order derivatives, single-precision arithmetics appears to be sufficient, though.

physics.chem-ph↗

arXiv2023

Systematic Improvement of Empirical Energy Functions in the Era of Machine Learning

The impact of targeted replacement of individual terms in empirical force fields is quantitatively assessed for pure water, dichloromethane (DCM), and solvated K$^+$ and Cl$^-$ ions. For the electrostatics, point charges (PCs) and machine learning (ML)based minimally distributed charges (MDCM) fitted to the molecular electrostatic potential are evaluated together with electrostatics based on the Coulomb integral. The impact of explicitly including second-order terms is investigated by adding a fragment molecular orbital (FMO)-derived polarization energy to an existing force field, in this case CHARMM. It is demonstrated that anisotropic electrostatics reduce the RMSE for water (by 1.6 kcal/mol), DCM (by 0.8 kcal/mol) and for solvated Cl$^-$ clusters (by 0.4 kcal/mol). An additional polarization term can be neglected for DCM but notably improves errors in pure water (by 1.1 kcal/mol) and in Cl$^-$ clusters (by 0.4 kcal/mol) and is key to describing solvated K$^+$, reducing the RMSE by 2.3 kcal/mol. A 12-6 Lennard-Jones functional form is found to perform satisfactorily with PC and MDCM electrostatics, but is not appropriate for descriptions that account for the electrostatic penetration energy. The importance of many-body contributions is assessed by comparing a strictly 2-body approach with self-consistent reference data. DCM can be approximated well with a 2-body potential while water and solvated K$^+$ and Cl$^-$ ions require explicit many-body corrections. The present work systematically quantifies which terms improve the performance of an existing force field and what reference data to use for parametrizing these terms in a tractable fashion for ML fitting of pure and heterogeneous systems.

physics.chem-ph↗

arXiv2023

Improving Potential Energy Surfaces Using Experimental Feshbach Resonance Tomography

The structure and dynamics of a molecular system is governed by its potential energy surface (PES), representing the total energy as a function of the nuclear coordinates. Obtaining accurate potential energy surfaces is limited by the exponential scaling of Hilbert space, restricting quantitative predictions of experimental observables from first principles to small molecules with just a few electrons. Here, we present an explicitly physics-informed approach for improving and assessing the quality of families of PESs by modifying them through linear coordinate transformations based on experimental data. We demonstrate this "morphing" of the PES for the He-H$_{2}^{+}$ complex for reference surfaces at three different levels of quantum chemistry and using recent comprehensive Feshbach resonance(FR) measurements. In all cases, the positions and intensities of peaks in the collision cross-section are improved. We find these observables to be mainly sensitive to the long-range part of the PES.

physics.chem-ph↗

arXiv2023

Molecular Simulation for Atmospheric Reaction Exploration and Discovery: Non-Equilibrium Dynamics, Roaming and Glycolaldehyde Formation Following Photo-Induced Decomposition of syn-Acetaldehyde Oxide

The decomposition and chemical dynamics for vibrationally excited syn-CH$_3$CHOO is followed based on statistically significant numbers of molecular dynamics simulations. Using a neural network-based reactive potential energy surface, transfer learned to the CASPT2 level of theory, the final total kinetic energy release and rotational state distributions of the OH fragment are in quantitative agreement with experiment. In particular the widths of these distributions are sensitive to the experimentally unknown strength of the O--O bond strength, for which values $D_e \in [22,25]$ kcal/mol are found. Due to the non-equilibrium nature of the process considered, the energy-dependent rates do not depend appreciably on the O--O scission energy. Roaming dynamics of the OH-photoproduct leads to formation of glycolaldehyde on the picosecond time scale with subsequent decomposition into CH$_2$OH+HCO. Atomistic simulations with global reactive machine-learned energy functions provide a viable route to quantitatively explore the chemistry and reaction dynamics for atmospheric reactions.

physics.chem-ph↗

arXiv2023

Low-Temperature Kinetics for the N + NO reaction: Experiment Guides the Way

The reaction N(4S) + NO -> O(3P) + N2 plays a pivotal role in the conversion of atomic to molecular nitrogen in dense interstellar clouds and in the atmosphere. Here we report a joint experimental and computational investigation of the N + NO reaction with the aim of providing improved constraints on its low temperature reactivity. Thermal rates were measured over the 50 to 296 K range in a continuous supersonic flow reactor coupled with pulsed laser photolysis and laser induced fluorescence for the production and detection of N(4S) atoms, respectively. With decreasing temperature, the experimentally measured reaction rate was found to monotonously increase up to a value of (6.6 +- 1.3) x 10-11 cm3 s-1 at 50 K. To confirm this finding, quasi-classical trajectory simulations were carried out on a previously validated, full-dimensional potential energy surface (PES). However, around 50 K the computed rates decreased which required re-evaluation of the reactive PES in the long-range part due to a small spurious barrier with height 40 K in the entrance channel. By exploring different correction schemes the measured thermal rates can be adequately reproduced, displaying a clear negative temperature dependence over the entire temperature range. The possible astrochemical implications of an increased reaction rate at low temperature are also discussed.

astro-ph.GA↗

arXiv2023

PhysNet Meets CHARMM: A Framework for Routine Machine Learning / Molecular Mechanics Simulations

Full dimensional potential energy surfaces (PESs) based on machine learning (ML) techniques provide means for accurate and efficient molecular simulations in the gas- and condensed-phase for various experimental observables ranging from spectroscopy to reaction dynamics. Here, the MLpot extension with PhysNet as the ML-based model for a PES is introduced into the newly developed pyCHARMM API. To illustrate conceiving, validating, refining and using a typical workflow, para-chloro-phenol is considered as an example. The main focus is on how to approach a concrete problem from a practical perspective and applications to spectroscopic observables and the free energy for the -OH torsion in solution are discussed in detail. For the computed IR spectra in the fingerprint region the computations for para-chloro-phenol in water are in good qualitative agreement with experiment carried out in CCl$_4$. Also, relative intensities are largely consistent with experimental findings. The barrier for rotation of the -OH group increases from $\sim 3.5$ kcal/mol in the gas phase to $\sim 4.1$ kcal/mol from simulations in water due to favourable H-bonding interactions of the -OH group with surrounding water molecules.

physics.chem-ph↗

arXiv2023

Conformational and state-specific effects in reactions of 2,3-dibromobutadiene with Coulomb-crystallized calcium ions

Recent advances in experimental methodology enabled studies of the quantum-state and conformational dependence of chemical reactions under precisely controlled conditions in the gas phase. Here, we generated samples of selected gauche and s-trans 2,3-dibromobutadiene (DBB) by electrostatic deflection in a molecular beam and studied their reaction with Coulomb crystals of laser-cooled $\mathrm{Ca^{+}}$ ions in an ion trap. The rate coefficients for the total reaction were found to strongly depend on both the conformation of DBB and the electronic state of $\mathrm{Ca^{+}}$. In the $\mathrm{(4p)~^{2}P_{1/2}}$ and $\mathrm{(3d)~^{2}D_{3/2}}$ excited states of $\mathrm{Ca^{+}}$, the reaction is capture-limited and faster for the gauche conformer due to long-range ion-dipole interactions. In the $\mathrm{(4s)~^{2}S_{1/2}}$ ground state of $\mathrm{Ca^{+}}$, the reaction rate for s-trans DBB still conforms with the capture limit, while that for gauche DBB is strongly suppressed. The experimental observations were analysed with the help of adiabatic capture theory, ab-initio calculations and reactive molecular dynamics simulations on a machine-learned full-dimensional potential energy surface of the system. The theory yields near-quantitative agreement for s-trans-DBB, but overestimates the reactivity of the gauche-conformer compared to the experiment. The present study points to the important role of molecular geometry even in strongly reactive exothermic systems and illustrates striking differences in the reactivity of individual conformers in gas-phase ion-molecule reactions.

physics.chem-ph↗

arXiv2023

Molecular-Level Understanding of the Ro-vibrational Spectra of N$_2$O in Gaseous, Supercritical and Liquid SF$_6$ and Xe

The transition between the gas-, supercritical-, and liquid-phase behaviour is a fascinating topic which still lacks molecular-level understanding. Recent ultrafast two-dimensional infrared spectroscopy experiments suggested that the vibrational spectroscopy of N$_2$O embedded in xenon and SF$_6$ as solvents provides an avenue to characterize the transitions between different phases as the concentration (or density) of the solvent increases. The present work demonstrates that classical molecular dynamics simulations together with accurate interaction potentials allows to (semi-)quantitatively describe the transition in rotational vibrational infrared spectra from the P-/R-branch lineshape for the stretch vibrations of N$_2$O at low solvent densities to the Q-branch-like lineshapes at high densities. The results are interpreted within the classical theory of rigid-body rotation in more/less constraining environments at high/low solvent densities or based on phenomenological models for the orientational relaxation of rotational motion. It is concluded that classical MD simulations provide a powerful approach to characterize and interpret the ultrafast motion of solutes in low to high density solvents at a molecular level.

physics.chem-ph↗

arXiv2023

Transfer-Learned Potential Energy Surfaces: Towards Microsecond-Scale Molecular Dynamics Simulations in the Gas Phase at CCSD(T) Quality

The rise of machine learning has greatly influenced the field of computational chemistry, and that of atomistic molecular dynamics simulations in particular. One of its most exciting prospects is the development of accurate, full-dimensional potential energy surfaces (PESs) for molecules and clusters, which, however, often require thousands to tens of thousands of ab initio data points restricting the community to medium sized molecules and/or lower levels of theory (e.g. DFT). Transfer learning, which improves a global PES from a lower to a higher level of theory, offers a data efficient alternative requiring only a fraction of the high level data (on the order of 100 are found to be sufficient for malonaldehyde). The present work demonstrates that even with Hartree-Fock theory and a double-zeta basis set as the lower level model, transfer learning yields CCSD(T)-level quality for H-transfer barrier energies, harmonic frequencies and H-transfer tunneling splittings. Most importantly, finite-temperature molecular dynamics simulations on the sub-microsecond time scale in the gas phase are possible and the infrared spectra determined from the transfer learned PESs are in good agreement with experiment. It is concluded that routine, long-time atomistic simulations on PESs fulfilling CCSD(T)-standards become possible.

physics.chem-ph↗

arXiv2023

Tomography of Feshbach Resonance States

Feshbach resonances are fundamental to interparticle interactions and become particularly important in cold collisions with atoms, ions, and molecules. Here we present the detection of Feshbach resonances in a benchmark system for strongly interacting and highly anisotropic collisions -- molecular hydrogen ions colliding with noble gas atoms. The collisions are launched by cold Penning ionization exclusively populating Feshbach resonances that span both short- and long-range parts of the interaction potential. We resolved all final molecular channels in a tomographic manner using ion-electron coincidence detection. We demonstrate the non-statistical nature of the final state distribution. By performing quantum scattering calculations on ab initio potential energy surfaces, we show that the isolation of the Feshbach resonance pathways reveals their distinctive fingerprints in the collision outcome.

physics.atom-ph↗

arXiv2022

Neural Network Potentials for Chemistry: Concepts, Applications and Prospects

Artificial Neural Networks (ANN) are already heavily involved in methods and applications for frequent tasks in the field of computational chemistry such as representation of potential energy surfaces (PES) and spectroscopic predictions. This perspective provides an overview of the foundations of neural network-based full-dimensional potential energy surfaces, their architectures, underlying concepts, their representation and applications to chemical systems. Methods for data generation and training procedures for PES construction are discussed and means for error assessment and refinement through transfer learning are presented. A selection of recent results illustrates the latest improvements regarding accuracy of PES representations and system size limitations in dynamics simulations, but also NN application enabling direct prediction of physical results without dynamics simulations. The aim is to provide an overview for the current state-of-the-art NN approaches in computational chemistry and also to point out the current challenges in enhancing reliability and applicability of NN methods on larger scale.

physics.chem-ph↗

arXiv2022

Water Dynamics around T0 vs. R4 of Hemoglobin from Local Hydrophobicity Analysis

The local hydration around tetrameric Hb in its T$_0$ and R$_4$ conformational substates is analyzed based on molecular dynamics simulations. Analysis of the local hydrophobicity (LH) for all residues at the $α_1 β_2$ and $α_2 β_1$ interfaces, responsible for the quaternary T$\rightarrow$R transition, which is encoded in the MWC model, as well as comparison with earlier computations of the solvent accessible surface area (SASA), makes clear that the two quantities measure different aspects of hydration. Local hydrophobicity quantifies the presence and structure of water molecules at the interface whereas ``buried surface'' reports on the available space for solvent. For simulations with Hb frozen in its T$_0$ and R$_4$ states the correlation coefficient between LH and buried surface is 0.36 and 0.44, respectively, but it increases considerably if the 95 \% confidence interval is used. The LH with Hb frozen and flexible changes little for most residues at the interfaces but is significantly altered for a few select ones, which are Thr41$α$, Tyr42$α$, Tyr140$α$, Trp37$β$, Glu101$β$ (for T$_0$) and Thr38$α$, Tyr42$α$, Tyr140$α$ (for R$_4$). The number of water molecules at the interface is found to increase by $\sim 25$ \% for T$_0$$\rightarrow$R$_4$ which is consistent with earlier measurements. Since hydration is found to be essential to protein function, it is clear that hydration also plays an essential role in allostery.

physics.chem-ph↗

arXiv2022

Local Hydration Control and Functional Implications Through S-Nitrosylation of Proteins: Kirsten rat sarcoma virus (KRAS) and Hemoglobin (Hb)

S-nitrosylation, the covalent addition of NO to the thiol side chain of cysteine, is an important post-transitional modification (PTM) that can affect the function of proteins. As such, PTMs extend and diversify protein functions and thus characterizing consequences of PTM at a molecular level is of great interest. Although PTMs can be detected through various direct/indirect methods, they lack the capabilities to investigate the modifications at the molecular level. In the present work local and global structural dynamics, their correlation, the hydration structure, and the infrared spectroscopy for WT and S-nitrosylated Kirsten rat sarcoma virus (KRAS) and Hemoglobin (Hb) are characterized from molecular dynamics simulations. It is found that for KRAS attaching NO to Cys118 rigidifies the protein in the Switch-I region which has functional implications, whereas for Hb nitrosylation at Cys93 at the $β_1$ chain increases the flexibility of secondary structural motives for Hb in its T$_{0}$ and R$_{4}$ conformational substates. Solvent water access decreased by 40\% after nitrosylation in KRAS, similar to Hb for which, however, local hydration of the R$_4$NO state is yet lower than for T$_0$NO. Finally, S-nitrosylation leads to detectable peaks for NO stretch, however, congested IR region will make experimental detection of these bands difficult.

physics.chem-ph↗

arXiv2022

Interaction at a Distance: Xenon Migration in Mb

The transport of ligands, such as NO or O$_2$, through internal cavities is essential for the function of globular proteins, including hemoglobin, myoglobin (Mb), neuroglobin, truncated hemoglobins, or cytoglobin. For Mb, several internal cavities (Xe1 through Xe4) were observed experimentally through X-ray crystallography experiments. At a functional level, they were linked to ligand storage and internal ligand diffusion. Barriers for ligand diffusion and relative stabilization energies for the ligand in the initial and final pocket linking a transition may differ depending on the occupation state of the remaining pockets. This is considered in the present work from biased (umbrella sampling) and unbiased molecular dynamics simulations. It is found that the energetics of a particular ligand migration pathway may depend on the direction in which the transition is followed (forward or reverse) and the occupation state of other cavities. Furthermore, the barrier for a particular transition can depend in a non-additive fashion on the occupation of either cavity A or B or simultaneous occupation of both cavities, A and B. Multiple repeats for the Xe1$\rightarrow$Xe2 transition reveals that the activation barrier is a distribution of barrier heights rather than one single value which is confirmed by a distribution of transition times for the same transition from unbiased simulations. Dynamic cross correlation maps for this transition demonstrate that correlated motions occur between adjacent residues or through space. Residue Phe138 is characterized as a gate between Xe1 and Xe2 for the Xe1$\rightarrow$Xe2 transition. It is also found that the volumes of the internal cavities vary along the diffusion pathway which points towards dynamic communication between the ligand and the protein. The findings are discussed in the context of protein allostery.

physics.chem-ph↗

arXiv2022

Combining Machine Learning and Spectroscopy to Model Reactive Atom + Diatom Collisions

The prediction of product translational, vibrational, and rotational energy distributions for arbitrary initial conditions for reactive atom+diatom collisions is of considerable practical interest in atmospheric re-entry. Due to the large number of accessible states, determination of the necessary information from explicit (quasi-classical or quantum) dynamics studies is impractical. Here, a machine-learned (ML) model based on translational energy and product vibrational states assigned from a spectroscopic, ro-vibrational coupled energy expression based on the Dunham expansion is developed and tested quantitatively. All models considered in this work reproduce final state distributions determined from quasi-classical trajectory (QCT) simulations with $R^2 \sim 0.98$. As a further validation, thermal rates determined from the machine-learned models agree with those from explicit QCT simulations and demonstrate that the atomistic details are retained by the machine learning which makes them suitable for applications in more coarse-grained simulations. More generally, it is found that ML is suitable for designing robust and accurate models from mixed computational/experimental data which may also be of interest in other areas of the physical sciences.

physics.chem-ph↗