Reactivity scales such as nucleophilicity and electrophilicity are valuable tools for determining chemical reactivity selectivity.

The mild and selective functionalization of carbon-hydrogen (C-H) bonds remains a pivotal challenge in organic synthesis, crucial for developing complex molecular architectures pharmaceuticals, polymers, agrochemicals. Despite advancements directing group (DG) methodologies computational approaches, predicting accurate regioselectivity C-H activation poses significant difficulties due to the diversity complexity compounds. This study introduces novel quantum mechanics-based workflow tailored...

Nucleophilicity and electrophilicity are important properties for evaluating the reactivity selectivity of chemical reactions. It allows ranking nucleophiles electrophiles on scales, enabling a better understanding prediction reaction outcomes. Building upon our recent work (N. Ree, A. H. Göller J. Jensen, Automated quantum chemistry estimating nucleophilicity with applications to retrosynthesis covalent inhibitors, Digit. Discov., 2024, 3, 347-354), we introduce an atom-based machine...

Dihydroazulene (DHA) is a molecular photoswitch that undergoes ring-opening reaction upon irradiation to form vinylheptafulvene (VHF) photoisomer. This VHF isomer will in time thermally return the DHA isomer. As isomerization photo-induced only one direction, – couple has attracted interest as solar thermal energy storage device (MOST system). In this author review, we cover our systematic efforts optimize for purpose, with challenges being achieve sufficiently high densities, broad...

Active learning (AL) can significantly accelerate drug discovery by iteratively selecting informative molecules, reducing experimental workload. However, existing AL studies typically assume access to large datasets, an unrealistic scenario for most academic labs. Here, we investigate strategies tailored specifically small-scale molecular screening, using only 110 affinity evaluations approximated docking scores from realistic compound libraries: the Developmental Therapeutics Program...

Conjugates of norbornadiene (NBD) and dihydroazulene (DHA) photoswitches were synthesised subjected to isomerisation studies.

We present RegioML, an atom-based machine learning model for predicting the regioselectivities of electrophilic aromatic substitution reactions.

Abstract We present RegioSQM20, a new version of RegioSQM (Chem Sci 9:660, 2018), which predicts the regioselectivities electrophilic aromatic substitution (EAS) reactions from calculation proton affinities. The following improvements have been made: open source semiempirical tight binding program is used instead closed program. Any low energy tautomeric forms input molecule are identified and regioselectivity predictions made for each form. Finally, RegioSQM20 offers qualitative prediction...

Determining the p K a values of various C–H sites in organic molecules offers valuable insights for synthetic chemists predicting reaction sites. As molecular complexity increases, this task becomes more challenging. This paper introduces pKalculator, quantum chemistry (QM)-based workflow automatic computations values, which is used to generate training dataset machine learning (ML) model. The QM benchmarked against 695 experimentally determined DMSO. ML model trained on diverse 775 with...

Former work has improved the energy storage capacity of dihydroazulene/vinylheptafulvene photo/thermoswitch by substitution with NH2 and NO2 in vacuum. This extends former investigating solvent effects systematically using cyclohexane, toluene, dichloromethane, ethanol, acetonitrile comparing them inclusion vacuum calculations. The investigation includes more than 8000 calculations density functional theory for comparison capacities, activation energies thermal conversion vinylheptafulvene...

Molecular photoswitches based on the norbornadiene–quadricylane (NBD–QC) couple have been proposed as key elements of molecular solar thermal energy storage schemes. To characterize intrinsic properties such systems, reversible isomerization a charge-tagged NBD–QC carboxylate is investigated in tandem ion mobility mass spectrometer, using light to induce intramolecular [2 + 2] cycloaddition NBD form QC and driving back reaction with collisions. The photoisomerization action spectrum recorded...

Electrochemical processes drive many chemical and biochemical reactions. Theoretical methods to accurately predict redox potentials are therefore crucial for understanding these reactions designing new species with desired properties. We have investigated a theoretical methodology using electronic structure based on density functional theory continuum solvation models. These been validated linear correlation plots comparing experimental results the properties of series azulene derivatives....

We present a computational methodology for the screening of chemical space 1025 substituted norbornadiene molecules promising kinetically stable molecular solar thermal (MOST) energy storage systems with high densities that absorb in visible part spectrum. use semiempirical tight-binding methods to construct dataset nearly 34 000 and train graph convolutional networks predict densities, kinetic stability, absorption spectra then models together genetic algorithm search MOST systems. identify...

We present a quantum chemistry (QM)-based method that computes the relative energies of intermediates in Heck reaction relate to regioselective outcome: branched (α), linear (β), or mix two. The calculations are done for two different pathways (neutral and cationic) based on r2SCAN-3c single-point GFN2-xTB geometries that, turn, derive from GFNFF-xTB conformational search. is completely automated sufficiently efficient allow calculation thousands outcomes. can mostly reproduce systematic...

Determining the pKa values of various C-H sites in organic molecules offers valuable insights for synthetic chemists predicting reaction sites. As molecular complexity increases, this task becomes more challenging. This paper introduces pKalculator, a quantum chemical (QM)-based workflow automatic computations values, which is used to generate training dataset machine learning model (ML). The QM benchmarked against 695 experimentally determined values. ML trained on diverse 775 with 3910 Our...

Predicted bond dissociation energies (BDEs) can be used to identify C-H bonds that are most likely react in H-abstraction reactions. However, many cases, it is not clear whether the reaction oc- curs through a radical or carbocation intermediate. Thus, hydride affinity (hydricity) may more predictive of reactive sites than BDEs. In this paper, we introduce HAlator, quantum chemistry (QM)-based workflow for automatic computations C–H hydricities, bench- mark against 35 experimentally...

Abstract The gain and loss of aromaticity plays a key role in organic chemistry the prediction rate‐determining steps. Herein, we explore concept photoisomerization reactions. Benzannulated derivatives dihydroazulene‐vinylheptafulvene (DHA‐VHF) photoswitch were investigated using transient absorption spectroscopy time‐dependent density functional theory to elucidate effect built‐in on switching properties. We found that benzannulation hampered ability by enhancing an already existing barrier...

<div> <p>We present RegioSQM20, a new version of RegioSQM (<i>Chem. Sci</i>. 2018, 9, 660), which predicts the regioselectivities electrophilic aromatic substitution (EAS) re- actions from calculation proton affinities. The following improvements have been made: open source semiempirical tight binding program xtb is used instead closed MOPAC program. Any low energy tautomeric forms input molecule are identified and regioselectivity predictions made for each form....

Herein, we present an investigation of the excited state dynamics dihydroazulene photoswitch and its photoinduced reaction to vinylheptafulvene.

Nucleophilicity and electrophilicity are important properties for evaluating the reactivity selectivity of chemical reactions. It allows ranking nucleophiles electrophiles on scales, enabling a better understanding prediction reaction outcomes. Building upon our recent work (Digit. Discov., 2024, 3, 347-354), we introduce an atom-based machine learning (ML) approach predicting methyl cation affinities (MCAs) anion (MAAs) to estimate nucleophilicity electrophilicity, respectively. The ML...

Abstract The front cover artwork is provided by the Hansen and Mikkelsen groups from University of Copenhagen. image shows how excited state aromaticity affects photochemistry dihydroazulene (DHA). Inducing enhances an barrier, so DHA can no longer reach photoproduct. Read full text Article at 10.1002/cptc.201900088 .