MultiXC-QM9: Large dataset of molecular and reaction energies from multi-level quantum chemical methods.

Well curated extensive datasets have helped spur intense molecular machine learning (ML) method development activities over the last few years, encouraging nonchemists to be part of the effort as well. QM9 dataset is one of the benchmark databases for small molecules with molecular energies based on B3LYP functional. G4MP2 based energies of these molecules were published later. To enable a wide variety of ML tasks like transfer learning, delta learning, multitask learning, etc. with QM9 molecules, in this article, we introduce a new dataset with QM9 molecule energies estimated with 76 different DFT functionals and three different basis sets (228 energy numbers for each molecule). We additionally enumerated all possible A ↔ B monomolecular interconversions within the QM9 dataset and provided the reaction energies based on these 76 functionals, and basis sets. Lastly, we also provide the bond changes for all the 162 million reactions with the dataset to enable structure- and bond-based reaction energy prediction tools based on ML.

Cheap Turns Superior: A Linear Regression-Based Correction Method to Reaction Energy from the DFT.

Workflows to predict chemical reaction networks based on density functional theory (DFT) are prone to systematic errors in reaction energy due to the extensive use of cheap DFT exchange-correlation functionals to limit computational cost. Recently, machine learning-based models are increasingly applied to mitigate this problem. However, machine learning models require systems similar to trained data, and the models often perform poorly for out-of-distribution systems. Here, we present a simple bond-based correction method that improves the accuracy of DFT-derived reaction energies. It is based on linear regression, and the correction terms for each bond are derived from reactions among the QM9 data set. We demonstrate the effectiveness of this method with three DFT functionals in three different rungs of Jacob's ladder. The simple correction method is effective for all rungs but especially so for the cheapest PBE functional. Finally, we applied the correction method to a few reactions with molecules significantly different from those in the QM9 data set that was used to fit the linear regression model. Once corrected by this method, we found that the DFT reaction energies for such out-of-distribution reactions are within 0.05 eV of the G4MP2 method.

Alteration of Electronic Band Structure via a Metal-Semiconductor Interfacial Effect Enables High Faradaic Efficiency for Electrochemical Nitrogen Fixation.

The interface engineering strategy has been an emerging field in terms of material improvisation that not only alters the electronic band structure of a material but also induces beneficial effects on electrochemical performances. Particularly, it is of immense importance for the environmentally benign electrochemical nitrogen reduction reaction (NRR), which is potentially impeded by the competing hydrogen evolution reaction (HER). The main problem lies in the attainment of the desired current density at a negotiable potential where the NRR would dominate over the HER, which in turn hampers the Faradaic efficiency for the NRR. To circumvent this issue, catalyst development becomes necessary, which would display a weak affinity for H-adsorption suppressing the HER at the catalyst surface. Herein, we have adopted the interfacial engineering strategy to synthesize our electrocatalyst NPG@SnS2, which not only suppressed the HER on the active site but yielded 49.3% F.E. for the NRR. Extensive experimental work and DFT calculations regarded that due to the charge redistribution, the Mott-Schottky effect, and the band bending of SnS2 across the contact layer at the interface of NPG, the d-band center for the surface Sn atoms in NPG@SnS2 lowered, which resulted in favored adsorption of N2 on the Sn active site. This phenomenon was driven even forward by the upshift of the Fermi level, and eventually, a decrease was seen in the work function of the heterostructure that increased the conductivity of the material as compared to pristine SnS2. This strategy thus provides a field to methodically suppress the HER in the realm of improving the Faradaic efficiency for the NRR.

Chemical bonding in cuprous complexes with simple nitriles: octet rule and resonance concepts versus quantitative charge-redistribution analysis.

Chemical bonding in a set of six cuprous complexes with simple nitriles (CN-, HNC, HCN, CH3NC, and CH3CN) is investigated by means of a recently devised analysis scheme framed in density-functional theory and quantitatively singling out concurrent charge flows such as σ donation and π backdonation. The results of our analysis are comparatively assessed against qualitative models for charge redistribution based on the popular concepts of octet rule and resonance structures, and the relative importance of different charge-flow channels relating to σ donation, π back-donation, polarization, and hyperconjugation is discussed on a quantitative basis.

Chemical promenades: Exploring potential-energy surfaces with immersive virtual reality.

The virtual-reality framework AVATAR (Advanced Virtual Approach to Topological Analysis of Reactivity) for the immersive exploration of potential-energy landscapes is presented. AVATAR is based on modern consumer-grade virtual-reality technology and builds on two key concepts: (a) the reduction of the dimensionality of the potential-energy surface to two process-tailored, physically meaningful generalized coordinates, and (b) the analogy between the evolution of a chemical process and a pathway through valleys (potential wells) and mountain passes (saddle points) of the associated potential energy landscape. Examples including the discovery of competitive reaction paths in simple A + BC collisional systems and the interconversion between conformers in ring-puckering motions of flexible rings highlight the innovation potential that augmented and virtual reality convey for teaching, training, and supporting research in chemistry.

Prebiotic Chemistry of HCN Tetramerization by Automated Reaction Search.

HCN oligomerization is considered to be one of the important pathways in chemical evolution. Nucleobases, aminoacids, and many other complex organic molecules can evolve through this pathway. We report an explorative study based on an automated reaction search method that avoids the cognitive bias present when searching chemical reaction space. We discuss the chemical space of the HCN dimer in detail, and the important trimers and tetramers are discussed briefly. A component-wise molecular-fingerprint-based methodology is proposed to identify molecular similarity. We present four different thermal routes to cis/trans-2,3-diaminomaleonitrile and 4-amino-1H-imidazole-5-carbonitrile, which are important intermediates in prebiotic chemistry.

ESIPT-induced fluorescent o-hydroxycinnamate: a self-monitoring phototrigger for prompt image-guided uncaging of alcohols.

o-Hydroxycinnamate derivatives are well-known phototriggers for fast and direct release of alcohols and amines without proceeding through the cleavage of carbonate or carbamate linkages. Despite these unique features, o-hydroxycinnamates lack extensive applications in biological systems mainly because of their non-fluorescent nature. To overcome this limitation, we have attached a 2-(2'-hydroxyphenyl) benzothiazole (HBT) moiety, capable of rapid excited-state intramolecular proton transfer (ESIPT) to the o-hydroxycinnamate group. The ESIPT effect induced two major advantages to the o-hydroxycinnamate group: (i) large Stokes' shifted fluorescence (orange colour) properties and (ii) distinct fluorescence colour change upon photorelease. In vitro studies exhibited an image guided, photoregulated release of bioactive molecules by the o-hydroxycinnamate-benzothiazole-methyl salicylate conjugate and real-time monitoring of the release action.

A p-Hydroxyphenacyl-Benzothiazole-Chlorambucil Conjugate as a Real-Time-Monitoring Drug-Delivery System Assisted by Excited-State Intramolecular Proton Transfer.

Among the well-known phototriggers, the p-hydroxyphenacyl (pHP) group has consistently enabled the very fast, efficient, and high-conversion release of active molecules. Despite this unique behavior, the pHP group has been ignored as a delivery agent, particularly in the area of theranostics, because of two major limitations: Its excitation wavelength is below 400 nm, and it is nonfluorescent. We have overcome these limitations by incorporating a 2-(2'-hydroxyphenyl)benzothiazole (HBT) appendage capable of rapid excited-state intramolecular proton transfer (ESIPT). The ESIPT effect also provided two unique advantages: It assisted the deprotonation of the pHP group for faster release, and it was accompanied by a distinct fluorescence color change upon photorelease. In vitro studies showed that the p-hydroxyphenacyl-benzothiazole-chlorambucil conjugate presents excellent properties, such as real-time monitoring, photoregulated drug delivery, and biocompatibility.

Viability of aromatic all-pnictogen anions.

Aromaticity in novel cyclic all-pnictogen heterocyclic anions, P2N3(-) and P3N2(-), and in their heavier analogues is studied using quantum mechanical computations. All geometrical parameters from optimized geometry, bonding, electron density analysis from quantum theory of atoms in molecules, nucleus-independent chemical shift, and ring current density plots support their aromaticity. The aromatic nature of these molecules closely resembles that of the prototypical aromatic anion, C5H5(-). These singlet C2v symmetric molecules are comprised of five distinct canonical structures and are stable up to at least 1000 fs without any significant distortion. Mechanistic study revealed a plausible synthetic pathway for P3N2(-) - a click reaction between N2 and P3(-), through a C2v symmetric transition state. Besides this, the possibility of P3N2(-) as a η(5)-ligand in metallocenes is studied and the nature of bonding in metallocenes is discussed through the energy decomposition analysis.