Probing competing relaxation pathways in malonaldehyde with transient X-ray absorption spectroscopy

List, Nanna Holmgaard; Dempwolff, Adrian L.; Dreuw, Andreas; Norman, Patrick; Martı́nez, Todd J.

doi:10.1039/d0sc00840k

Cited by 39 publications

(39 citation statements)

References 103 publications

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“…As the molecular orbitals change between the two tautomers, so does the ionization potential of an oxygen 1s electron. Our calculated spectra in Figure d compare well to ground-state O K-edge calculations of a similar system, malonaldehyde, in which the CO peak was 2.7 eV red-shifted relative to the O–H peak …”

supporting

confidence: 73%

“…Our calculated spectra in Figure 1d compare well to ground-state O K-edge calculations of a similar system, malonaldehyde, in which the CO peak was 2.7 eV red-shifted relative to the O−H peak. 32 A comparison of the calculated N and O K-edge spectra of enol and keto tautomers of HBQ reveals that the position and amplitude of peaks B and C will serve as important spectroscopic observables for monitoring ultrafast ESIPT. As shown above, the blue (red) shifting of the nitrogen (oxygen) K-edge in going from enol to keto measures the overall electron density around the nitrogen (oxygen) atom, and the amplitudes of the B and C peaks are sensitive to the electronic structure of the unfilled or partially filled molecular orbitals, providing us handles to monitor the coupling of electronic and atomic degrees of freedom during and after ESIPT.…”

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confidence: 99%

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Spectral Signatures of Ultrafast Excited-State Intramolecular Proton Transfer from Computational Multi-edge Transient X-ray Absorption Spectroscopy

Loe

Liekhus-Schmaltz

Govind

et al. 2021

J. Phys. Chem. Lett.

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Excited-state intramolecular proton transfer (ESIPT) is a fundamental chemical process with several applications. Ultrafast ESIPT involves coupled electronic and atomic motions and has been primarily studied using femtosecond optical spectroscopy. X-ray spectroscopy is particularly useful because it is element-specific and enables direct, individual probes of the proton-donating and -accepting atoms. Herein, we report a computational study to resolve the ESIPT in 10-hydroxybenzo[h]quinoline (HBQ), an intramolecularly hydrogen bonded compound. We use linear-response time-dependent density functional theory (LR-TDDFT) combined with ab initio molecular dynamics (AIMD) and time-resolved X-ray absorption spectroscopy (XAS) computations to track the ultrafast excited-state dynamics. Our results reveal clear X-ray spectral signatures of coupled electronic and atomic motions during and following ESIPT at the oxygen and nitrogen K-edge, paving the way for future experiments at Xray free electron lasers.

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supporting

confidence: 73%

mentioning

confidence: 99%

Spectral Signatures of Ultrafast Excited-State Intramolecular Proton Transfer from Computational Multi-edge Transient X-ray Absorption Spectroscopy

Loe

Liekhus-Schmaltz

Govind

et al. 2021

J. Phys. Chem. Lett.

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“…As a final example, the MC-NRO method is applied to the intramolecular hydrogen transfer of malonaldehyde in the S1 state. [65][66][67][68][69] Excited state reactions are the most important target of MC-NRO analysis, since a multiconfigurational wavefunction is required to describe excited states. The S1 state of malonaldehyde is characterized by a one-electron n-π* excitation.…”

Section: E Intramolecular Hydrogen Transfer Of Malonaldehyde In the E...mentioning

confidence: 99%

“…The S1 state of malonaldehyde is characterized by a one-electron n-π* excitation. [65][66][67][68][69] Figure 16 shows the natural orbitals related to the excitation to the S1 state obtained with the S1-optimized geometry at the CASSCF(12,9)/cc-pVTZ level. The natural orbitals indicate excitation from the in-plane lone pair of the oxygen atom (hole) to the out-of-plane π* orbital (particle).…”

Section: E Intramolecular Hydrogen Transfer Of Malonaldehyde In the E...mentioning

confidence: 99%

Extension of Natural Reaction Orbital Approach to Multiconfigurational Wavefunctions

Ebisawa

Tsutsumi

Taketsugu

2022

Preprint

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Recently, we proposed a new orbital analysis method, natural reaction orbital (NRO), which automatically extracts orbital pairs that characterize electron transfer in reaction processes by singular value decomposition (SVD) of the first-order orbital response matrix to the nuclear coordinate displacements (Phys. Chem. Chem. Phys. 24, 3532 (2022)). NRO analysis along the intrinsic reaction coordinate (IRC) for several typical chemical reactions demonstrated that electron transfer occurs mainly in the vicinity of transition states and in regions where the energy profile along the IRC shows shoulder features, allowing the reaction mechanism to be explained in terms of electron motion based on orbital pairs that represent electron transfer. However, its application has been limited to single configuration theories such as Hartree-Fock theory and density functional theory (DFT). In this work, the concept of NRO is extended to multiconfigurational wavefunctions and formulated as the multiconfiguration NRO (MC-NRO). The MC-NRO method is applicable to various types of electronic structure theories, including multiconfigurational theory and linear response theory, and is expected to be a practical tool for extracting the qualitative essence of a broad range of chemical reactions, including covalent bond dissociation and chemical reactions in electronically excited states. In this paper, we calculate the IRC for five basic chemical reaction processes at the level of the complete active space self-consistent field (CASSCF) theory and discuss the electron transfer by performing MC-NRO analysis along each IRC. Finally, issues and future prospects of the MC-NRO method are discussed.

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“…multiple scattering theory, multiplet theory, and Bethe-Salpeter k-space approaches, plus extensions of popular ab initio quantum chemical strategies), 106 machine learning models for fast "forward" XAS mappings are well placed to unlock affordable analyses in particularly challenging cases, e.g. coupling to ultrafast dynamics simulations, [107][108][109][110][111][112][113][114][115][116][117][118] and describing accurately disordered/amorphous materials. [119][120][121][122][123][124] In these cases, many configurations need to be sampled to simulate XAS with even qualitative accuracy, but the time-and resource-intensiveness of the individual computational calculations presently makes such treatments challenging.…”

Section: Introductionmentioning

confidence: 99%

Accurate, Affordable, and Generalisable Machine Learning Simulations of Transition Metal X-ray Absorption Spectra using the XANESNET Deep Neural Network

Rankine

Penfold

2022

Preprint

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The affordable, accurate, and reliable prediction of spectroscopic observables plays a key role in the analysis of increasingly-complex experiments. In this Article, we develop and deploy a deep neural network (DNN) – XANESNET – for predicting the lineshape of first-row transition metal K-edge X-ray absorption near-edge structure (XANES) spectra. XANESNET predicts the spectral intensities using only information about the local coordination geometry ofthe transition metal complexes encoded in a feature vector of weighted atom-centred symmetry functions (wACSF). We address in detail the calibration of the feature vector for the particularities of the problem at hand, and we explore the individual feature importances to reveal the physical insight that XANESNET obtains at the Fe K-edge. XANESNET relies on only a few judiciously-selected features – radial information on the first and second coordination shells suffices, along with angular information sufficient to separate satisfactorily key coordination geometries. The feature importance is found to reflect the XANES spectral window under consideration and is consistent with the expected underlying physics. We subsequently apply XANESNET at nine first-row transition metal (Ti–Zn) K-edges. It can be optimised in as little as a minute, predicts instantaneously, and provides K-edge XANES spectra with an average accuracy of ca. ± 2–4% in which the positions of prominent peaks are matched with a > 90% hit rate to sub-eV (ca.0.8 eV) error.

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Probing competing relaxation pathways in malonaldehyde with transient X-ray absorption spectroscopy

Abstract: Resolving competing hydrogen-transfer mediated internal conversion and relaxation processes in a prototype ESIHT-system with transient X-ray absorption.

Cited by 39 publications

References 103 publications

Spectral Signatures of Ultrafast Excited-State Intramolecular Proton Transfer from Computational Multi-edge Transient X-ray Absorption Spectroscopy

Spectral Signatures of Ultrafast Excited-State Intramolecular Proton Transfer from Computational Multi-edge Transient X-ray Absorption Spectroscopy

Extension of Natural Reaction Orbital Approach to Multiconfigurational Wavefunctions

Accurate, Affordable, and Generalisable Machine Learning Simulations of Transition Metal X-ray Absorption Spectra using the XANESNET Deep Neural Network

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