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| 2. |
- Aquilante, Francesco, et al.
(författare)
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Modern quantum chemistry with [Open]Molcas
- 2020
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Ingår i: Journal of Chemical Physics. - : AIP Publishing. - 0021-9606 .- 1089-7690. ; 152:21
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Tidskriftsartikel (refereegranskat)abstract
- MOLCAS/OpenMolcas is an ab initio electronic structure program providing a large set of computational methods from Hartree-Fock and density functional theory to various implementations of multiconfigurational theory. This article provides a comprehensive overview of the main features of the code, specifically reviewing the use of the code in previously reported chemical applications as well as more recent applications including the calculation of magnetic properties from optimized density matrix renormalization group wave functions.
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| 3. |
- Eckert, Sebastian, et al.
(författare)
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T-1 Population as the Driver of Excited-State Proton-Transfer in 2-Thiopyridone
- 2019
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Ingår i: Chemistry - A European Journal. - : Wiley. - 0947-6539 .- 1521-3765. ; 25:7, s. 1733-1739
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Tidskriftsartikel (refereegranskat)abstract
- Excited-state proton transfer (ESPT) is a fundamental process in biomolecular photochemistry, but its underlying mediators often evade direct observation. We identify a distinct pathway for ESPT in aqueous 2-thiopyridone, by employing transient N1s X-ray absorption spectroscopy and multi-configurational spectrum simulations. Photoexcitations to the singlet S-2 and S-4 states both relax promptly through intersystem crossing to the triplet T-1 state. The T-1 state, through its rapid population and near nanosecond lifetime, mediates nitrogen site deprotonation by ESPT in a secondary intersystem crossing to the S-0 potential energy surface. This conclusively establishes a dominant ESPT pathway for the system in aqueous solution, which is also compatible with previous measurements in acetonitrile. Thereby, the hitherto open questions of the pathway for ESPT in the compound, including its possible dependence on excitation wavelength and choice of solvent, are resolved.
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| 4. |
- Eckert, Sebastian, et al.
(författare)
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Ultrafast Independent N-H and N-C Bond Deformation Investigated with Resonant Inelastic X-Ray Scattering
- 2017
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Ingår i: Angewandte Chemie International Edition. - : Wiley. - 1433-7851 .- 1521-3773. ; 56:22, s. 6088-6092
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Tidskriftsartikel (refereegranskat)abstract
- The femtosecond excited-state dynamics following resonant photoexcitation enable the selective deformation of N-H and N-C chemical bonds in 2-thiopyridone in aqueous solution with optical or X-ray pulses. In combination with multiconfigurational quantum-chemical calculations, the orbital-specific electronic structure and its ultrafast dynamics accessed with resonant inelastic X-ray scattering at the N 1s level using synchrotron radiation and the soft X-ray free-electron laser LCLS provide direct evidence for this controlled photoinduced molecular deformation and its ultrashort time-scale.
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| 5. |
- Galván, Ignacio Fdez., et al.
(författare)
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OpenMolcas : From Source Code to Insight
- 2019
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Ingår i: Journal of Chemical Theory and Computation. - : American Chemical Society (ACS). - 1549-9618 .- 1549-9626. ; 15:11, s. 5925-5964
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Tidskriftsartikel (refereegranskat)abstract
- In this Article we describe the OpenMolcas environment and invite the computational chemistry community to collaborate. The open-source project already includes a large number of new developments realized during the transition from the commercial MOLCAS product to the open-source platform. The paper initially describes the technical details of the new software development platform. This is followed by brief presentations of many new methods, implementations, and features of the OpenMolcas program suite. These developments include novel wave function methods such as stochastic complete active space self-consistent field, density matrix renormalization group (DMRG) methods, and hybrid multiconfigurational wave function and density functional theory models. Some of these implementations include an array of additional options and functionalities. The paper proceeds and describes developments related to explorations of potential energy surfaces. Here we present methods for the optimization of conical intersections, the simulation of adiabatic and nonadiabatic molecular dynamics, and interfaces to tools for semiclassical and quantum mechanical nuclear dynamics. Furthermore, the Article describes features unique to simulations of spectroscopic and magnetic phenomena such as the exact semiclassical description of the interaction between light and matter, various X-ray processes, magnetic circular dichroism, and properties. Finally, the paper describes a number of built-in and add-on features to support the OpenMolcas platform with postcalculation analysis and visualization, a multiscale simulation option using frozen-density embedding theory, and new electronic and muonic basis sets.
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| 6. |
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| 7. |
- Jay, Raphael M., et al.
(författare)
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Disentangling Transient Charge Density and Metal-Ligand Covalency in Photoexcited Ferricyanide with Femtosecond Resonant Inelastic Soft X-ray Scattering
- 2018
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Ingår i: The Journal of Physical Chemistry Letters. - : American Chemical Society (ACS). - 1948-7185. ; 9:12, s. 3538-3543
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Tidskriftsartikel (refereegranskat)abstract
- Soft X-ray spectroscopies are ideal probes of the local valence electronic structure of photocatalytically active metal sites. Here, we apply the selectivity of time resolved resonant inelastic X-ray scattering at the iron L-edge to the transient charge distribution of an optically excited charge-transfer state in aqueous ferricyanide. Through comparison to steady-state spectra and quantum chemical calculations, the coupled effects of valence-shell closing and ligand-hole creation are experimentally and theoretically disentangled and described in terms of orbital occupancy, metal-ligand covalency, and ligand field splitting, thereby extending established steady-state concepts to the excited-state domain. pi-Back-donation is found to be mainly determined by the metal site occupation, whereas the ligand hole instead influences sigma-donation. Our results demonstrate how ultrafast resonant inelastic X-ray scattering can help characterize local charge distributions around catalytic metal centers in short-lived charge-transfer excited states, as a step toward future rationalization and tailoring of photocatalytic capabilities of transition-metal complexes.
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| 8. |
- Jay, Raphael M., et al.
(författare)
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The nature of frontier orbitals under systematic ligand exchange in (pseudo-)octahedral Fe(II) complexes
- 2018
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Ingår i: Physical Chemistry, Chemical Physics - PCCP. - : Royal Society of Chemistry (RSC). - 1463-9076 .- 1463-9084. ; 20:44, s. 27745-27751
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Tidskriftsartikel (refereegranskat)abstract
- Understanding and controlling properties of transition metal complexes is a crucial step towards tailoring materials for sustainable energy applications. In a systematic approach, we use resonant inelastic X-ray scattering to study the influence of ligand substitution on the valence electronic structure around an aqueous iron(II) center. Exchanging cyanide with 2-2'-bipyridine ligands reshapes frontier orbitals in a way that reduces metal 3d charge delocalization onto the ligands. This net decrease of metal-ligand covalency results in lower metal-centered excited state energies in agreement with previously reported excited state dynamics. Furthermore, traces of solvent-effects were found indicating a varying interaction strength of the solvent with ligands of different character. Our results demonstrate how ligand exchange can be exploited to shape frontier orbitals of transition metal complexes in solution-phase chemistry; insights upon which future efforts can built when tailoring the functionality of photoactive systems for light-harvesting applications.
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| 9. |
- Neelakantan, Suraj, 1994-, et al.
(författare)
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Machine Learning for Lithology Analysis using a Multi-Modal Approach of Integrating XRF and XCT data
- 2024
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Ingår i: 14th Scandinavian Conference on Artificial Intelligence SCAI 2024, June 10-11, 2024, Jönköping, Sweden.
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Konferensbidrag (refereegranskat)abstract
- We explore the use of various machine learning (ML) models for classifying lithologies utilizing data from X-ray fluorescence (XRF) and X-ray computed tomography (XCT). Typically, lithologies are identified over several meters, which restricts the use of ML models due to limited training data. To address this issue, we augment the original interval dataset, where lithologies are marked over extensive sections, into finer segments of 10cm, to produce a high resolution dataset with vastly increased sample size. Additionally, we examine the impact of adjacent lithologies on building a more generalized ML model. We also demonstrate that combining XRF and XCT data leads to an improved classification accuracy compared to using only XRF data, which is the common practice in current studies, or solely relying on XCT data.
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| 10. |
- Neelakantan, Suraj, 1994-, et al.
(författare)
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Neural network approach for shape-based euhedral pyrite identification in X-ray CT data with adversarial unsupervised domain adaptation
- 2024
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Ingår i: Applied Computing and Geosciences. - : Elsevier. - 2590-1974. ; 21
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Tidskriftsartikel (refereegranskat)abstract
- We explore an attenuation and shape-based identification of euhedral pyrites in high-resolution X-ray Computed Tomography (XCT) data using deep neural networks. To deal with the scarcity of annotated data we generate a complementary training set of synthetic images. To investigate and address the domain gap between the synthetic and XCT data, several deep learning models, with and without domain adaption, are trained and compared. We find that a model trained on a small set of human annotations, while displaying over-fitting, can rival the human annotators. The unsupervised domain adaptation approaches are successful in bridging the domain gap, which significantly improves their performance. A domain-adapted model, trained on a dataset that fuses synthetic and real data, is the overall best-performing model. This highlights the possibility of using synthetic datasets for the application of deep learning in mineralogy.
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