Corresponding Active Orbital Spaces along Chemical Reaction Paths

The accuracy of reaction energy profiles calculated with multi-configurational electronic structure methods and corrected by multi-reference perturbation theory depends crucially on consistent active orbital spaces selected along the reaction path. However, it has been challenging in all but the simplest cases to choose molecular orbitals that can be considered corresponding in different molecular structures. Here, we demonstrate how active orbital spaces can be selected consistently along reaction coordinates in a fully automatized way. The approach requires no structure interpolation between reactants and products. Instead, it emerges from a synergy of an orbital mapping ansatz [J. Chem. Phys. 2019, 150, 214106] combined with our fully automated active space selection algorithm [J. Chem. Theory Comput. 2016, 12, 1760]. The former we extend by including also virtual orbitals rather than occupied ones only. We demonstrate our algorithm for the potential energy profile of the homolytic carbon-carbon bond dissociation and rotation around the double bond of 1-pentene in the electronic ground state. However, our algorithm also applies to electronically excited Born-Oppenheimer surfaces in a straightforward manner.Comment: 16 pages, 4 figure

On the accuracy of orbital based multi-level approaches for closed-shell transition metal chemistry

In this work, we investigate the accuracy of the local molecular orbital molecular orbital (LMOMO) scheme and projection-based wave function-in-density functional theory (WF-in-DFT) embedding for the prediction of reaction energies and barriers of typical reactions involving transition metals. To analyze the dependence of the accuracy on the system partitioning, we apply a manual orbital selection for LMOMO as well as the so-called direct orbital selection (DOS) for both approaches. We benchmark these methods on 30 closed shell reactions involving 16 different transition metals. This allows us to devise guidelines for the manual selection as well as settings for the DOS that provide accurate results within an error of 2 kcal mol−1 compared to local coupled cluster. To reach this accuracy, on average 55% of the occupied orbitals have to be correlated with coupled cluster for the current test set. Furthermore, we find that LMOMO gives more reliable relative energies for small embedded regions than WF-in-DFT embedding

Corresponding Active Orbital Spaces along Chemical Reaction Paths

The accuracy of reaction energy profiles calculated with multiconfigurational electronic structure methods and corrected by multireference perturbation theory depends crucially on consistent active orbital spaces selected along the reaction path. However, it has been challenging to choose molecular orbitals that can be considered corresponding in different molecular structures. Here, we demonstrate how active orbital spaces can be selected consistently along reaction coordinates in a fully automatized way. The approach requires no structure interpolation between reactants and products. Instead, it emerges from a synergy of the Direct Orbital Selection orbital mapping ansatz combined with our fully automated active space selection algorithm autoCAS. We demonstrate our algorithm for the potential energy profile of the homolytic carbon-carbon bond dissociation and rotation around the double bond of 1-pentene in the electronic ground state. However, our algorithm also applies to electronically excited Born-Oppenheimer surfaces.ISSN:1948-718

Concentration-Flux-Steered Mechanism Exploration with an Organocatalysis Application

Investigating a reactive chemical system with automated reaction network exploration algorithms provides a more detailed picture of its chemical mechanism than what would be accessible by manual investigation. In general, exploration algorithms cannot uncover reaction networks exhaustively for feasibility reasons. They should therefore decide which part of a network is kinetically relevant under some external conditions given. Here, we propose an automated algorithm that identifies and explores kinetically accessible regions of a reaction network on the fly by explicit modeling of concentration fluxes through an (incomplete) reaction network that is emerging during automated first-principles exploration. Key compounds are automatically identified and selected for the continuation of the exploration. As an example, we explore the reaction network of the multi-component proline-catalyzed Michael addition of propanal and nitropropene. Our algorithm provides a mechanistic picture of the Michael addition in unprecedented detail.ISSN:0021-2148ISSN:1565-8187ISSN:1869-586

Uncertainty-Aware First-Principles Exploration of Chemical Reaction Networks

Exploring large chemical reaction networks with automated exploration approaches and accurate quantum chemical methods can require prohibitively large computational resources. Here, we present an automated exploration approach that focuses on the kinetically relevant part of the reaction network by interweaving (i) large-scale exploration of chemical reactions, (ii) identification of kinetically relevant parts of the reaction network through microkinetic modeling, (iii) quantification and propagation of uncertainties, and (iv) reaction network refinement. Such an uncertainty-aware exploration of kinetically relevant parts of a reaction network with automated accuracy improvement has not been demonstrated before in a fully quantum mechanical approach. Uncertainties are identified by local or global sensitivity analysis. The network is refined in a rolling fashion during the exploration. Moreover, the uncertainties are considered during kinetically steering of a rolling reaction network exploration. We demonstrate our approach for Eschenmoser-Claisen rearrangement reactions. The sensitivity analysis identifies that only a small number of reactions and compounds are essential for describing the kinetics reliably, resulting in efficient explorations without sacrificing accuracy and without requiring prior knowledge about the chemistry unfolding.ISSN:1089-5639ISSN:1520-521

Solvation Free Energies in Subsystem Density Functional Theory

For many chemical processes the accurate description of solvent effects are vitally important. Here, we describe a hybrid ansatz for the explicit quantum mechanical description of solute-solvent and solvent-solvent interactions based on subsystem density functional theory and continuum solvation schemes. Since explicit solvent molecules may compromise the scalability of the model and transferability of the predicted solvent effect, we aim to retain both, for different solutes as well as for different solvents. The key for the transferability is the consistent subsystem decomposition of solute and solvent. The key for the scalability is the performance of subsystem DFT for increasing numbers of subsystems. We investigate molecular dynamics and stationary point sampling of solvent configurations and compare the resulting (Gibbs) free energies to experiment and theoretical methods. We can show that with our hybrid model reaction barriers and reaction energies are accurately reproduced compared to experimental data.ISSN:1549-9618ISSN:1549-962

On the accuracy of orbital based multi-level approaches for closed-shell transition metal chemistry

In this work, we investigate the accuracy of the local molecular orbital molecular orbital (LMOMO) scheme and projection-based wave function-in-density functional theory (WF-in-DFT) embedding for the prediction of reaction energies and barriers of typical reactions involving transition metals. To analyze the dependence of the accuracy on the system partitioning, we apply a manual orbital selection for LMOMO as well as the so-called direct orbital selection (DOS) for both approaches. We benchmark these methods on 30 closed shell reactions involving 16 different transition metals. This allows us to devise guidelines for the manual selection as well as settings for the DOS that provide accurate results within an error of 2 kcal mol(-1) compared to local coupled cluster. To reach this accuracy, on average 55% of the occupied orbitals have to be correlated with coupled cluster for the current test set. Furthermore, we find that LMOMO gives more reliable relative energies for small embedded regions than WF-in-DFT embedding.ISSN:1463-9084ISSN:1463-907

The subsystem quantum chemistry program Serenity

SERENITY [J Comput Chem. 2018;39:788-798] is an open-source quantum chemistry software that provides an extensive development platform focused on quantum-mechanical multilevel and embedding approaches. In this study, we give an overview over the developments done in Serenity since its original publication in 2018. This includes efficient electronic-structure methods for ground states such as multilevel domain-based local pair natural orbital coupled cluster and Moller-Plesset perturbation theory as well as the multistate frozen-density embedding quasi-diabatization method. For the description of excited states, SERENITY features various subsystem-based methods such as embedding variants of coupled time-dependent density-functional theory, approximate second-order coupled cluster theory and the second-order algebraic diagrammatic construction technique as well as GW/Bethe-Salpeter equation approaches. SERENITY's modular structure allows combining these methods with density-functional theory (DFT)-based embedding through various practical realizations and variants of subsystem DFT including frozen-density embedding, potential-reconstruction techniques and projection-based embedding.This article is categorized under:Electronic Structure Theory > Density Functional TheoryElectronic Structure Theory > Ab Initio Electronic Structure MethodsSoftware > Quantum ChemistryISSN:1759-0876ISSN:1759-088

qcserenity/serenity: Release 1.5.3

<h2>Release 1.5.3 (25.10.2023)</h2> <h3>Functionalities</h3> <ul> <li>Added two flavors of restricted open-shell HF and KS for the ground-state (Niklas Niemeyer)</li> <li>Fermi-shifted Huzinaga EO Kernel for subsystem TDDFT (Niklas Niemeyer)</li> <li>Laplace-Transform GW (Johannes Tölle, Niklas Niemeyer)</li> <li>Renamed ReadOrbitalsTask to OrbitalsIOTask (Niklas Göllmann)</li> <li>Added the functionality to write Turbomole files (Niklas Göllmann)</li> <li>Added the functionality to write Molden files for both spherical and cartesian harmonics (Niklas Göllmann)</li> <li>Added three schemes to generate complete basis function products for the Cholesky decomposition framework: Simple, First, Complete (Lars Hellmann)</li> <li>Added the functionality to control density fitting for individual contributions (Coulomb, exchange, long-range exchange, correlation)</li> </ul&gt