Themed collection Most popular 2022 physical and theoretical chemistry articles

The latest findings from theoretical investigations into TiO₂ nanoparticles are reviewed, including both realistic models from a bottom-up approach (1–3 nm diameter) and cut from bulk models (>3 nm diameter) in a top-down approach.

This review presents the recent progress of NIR TADF emitters along with their molecular design strategies and photophysical properties, as well as the electroluminescence performance data of the emitters and their OLEDs.

We present a data-driven discovery pipeline for molecular photoswitches through multitask learning with Gaussian processes. Through subsequent screening, we identify several motifs with separated and red-shifted electronic absorption bands.

Transferable selectivity profiles allow data from intermolecular reactions using iminium substrates to be applied to predict intramolecular reactions involving thioniums.

The large conformational change of topaquinone in bacterial copper amine oxidase occurs through the TPQ ring rotation and slide, which are essential to stabilize the semiquinone form.

The global minimum of SiSb₃M₃⁺ (M = Ca, Sr, Ba) is a D_3h symmetric structure containing an elusive planar hexacoordinate silicon (phSi) atom. Most importantly, the phSi core remains intact in ligand protected environment as well.

An example of a butterfly-like [Cu₁₈H₃(S-Adm)₁₂(PPh₃)₄Cl₂] cluster with vertex-sharing kernels through a Cu(0) center. Combined experimental and theoretical results correlate its photophysical properties with its unique structural architecture.

1D zinc–organic halide microcrystals exhibiting thermally assisted spectral separation of fluorescence and phosphorescence could be used as single-component standard white-light and temperature-gating active waveguides.

We demonstrate rationally designed arylazopyrazoles as MOST-PCM that can be circularly charged and discharged below 0 °C with visible light.

Transfer learning is combined with active learning to discover synthetic reaction conditions in a small-data regime. This strategy is tested on cross-coupling reactions from a high-throughput experimentation dataset and shows promising results.

This article examines the electronic structure of group 2 (E = Be and Mg) ligand stabilized compounds. We elaborate on the donor–acceptor interaction L(0) ⇆ E(0) ⇆ L(0) and diradical L(−1) → E(+2) ← L(−1) pictures to assess the oxidation state of the metal.

This report discloses a nontrivial role of the CO₂ adsorption mode in governing the CO/formate selectivity of single-atom catalysts towards two-electron CO₂ reduction.

Inverse W/O Pickering emulsions and reconfigurable microgelsomes with a well-defined bilayer structure are prepared from octanol-swollen PNIPAM-co-MAA microgels and the combination of binary microgels, which promise wider application of soft colloids.

We synthesize air-stable, p-type CaCuP thin films with high hole concentration and high hole mobility as potential p-type transparent conductors. We study their optoelectronic properties in detail by advanced experimental and computational methods.

An extension of conceptual DFT to include the influence of an external magnetic field is proposed in the context of a program set up to cope with the ever increasing variability of reaction conditions and concomitant reactivity.

Benchmarked van der Waals density functional theory calculations are used to create a force-field to describe biomolecule interactions at the aqueous MoS₂ interface, which can recover interfacial biomolecule adsorption with high structural fidelity.

We present an open-source chemoinformatic workflow to generate and analyze complex abiological chemical networks to discover novel compounds and autocatalytic processes. We demonstrate this pipeline's capabilities against a well-studied model system.

We present a data-driven approach combining deep learning-enabled active learning with coarse-grained simulations and alchemical free energy calculations to discover small molecules to selectively permeate cardiolipin membranes.

The comprehensive analysis of non-redundant PDB macromolecular structures investigating anion distributions around all aromatic molecules in available biosystems is presented.

Generating model agnostic molecular counterfactual explanations to explain model predictions.

The dominant binding mode of the QUB-00006-Int-07 main protease inhibitor during absolute binding free energy simulations.

PIGNet, a deep neural network-based drug–target interaction model guided by physics and extensive data augmentation, shows significantly improved generalization ability and model performance.

We report a quantitative model for oxidative addition reactivity in palladium-catalyzed cross-coupling, which is broadly applicable to predict reactivity and selectivity for complex substrates from simple molecular descriptors.

Synaptotagmin-1 is a low-affinity Ca²⁺ sensor that triggers synchronous vesicle fusion.

We generate 3D molecules conditioned on receptor binding sites by training a deep generative model on protein–ligand complexes. Our model uses the conditional receptor information to make chemically relevant changes to the generated molecules.

First-principles molecular dynamics simulations of imidazole-2-carboxaldehyde at the air–water interface highlight the role of surfactants in stabilising the reactive triplet state involved in photosensitisation reactions in aqueous aerosols.

The equilibria between structural states induced by pressure within the crystal structure of Ras are illustrated with different colors corresponding to different Ras substates.

Our study reveals the detailed influence of elastic and inelastic mean-free paths on the complete photoelectron spectra of liquid water, including the low-energy electron distributions and the reshaping of the primary photoelectron bands.

Contrastive pretraining of chemical reactions by matching augmented reaction representations to improve machine learning performance on small reaction datasets.

MGraphDTA is designed to capture the local and global structure of a compound simultaneously for drug–target affinity prediction and can provide explanations that are consistent with pharmacologists.