Opinion Mining by Convolutional Neural Networks for Maximizing Discoverability of Nanomaterials.

The scientific literature contains valuable information that can be used for future applications, but manual analysis presents challenges due to its size and disciplinary boundaries. The prevailing solution involves natural language processing (NLP) techniques such as information retrieval. Nonetheless, existing automated systems primarily provide either statistically based shallow information or deep information without traceability, thereby falling short of delivering high-quality and reliable insights. To address this, we propose an innovative approach of leveraging sentiment information embedded within the literature to track the opinions toward materials. In this study, we integrated material knowledge into text representation and constructed opinion data sets to hierarchically train deep learning models, named as Scientific Sentiment Network (SSNet). SSNet can effectively extract knowledge from the energy material literature and accurately categorize expert opinions into challenges and opportunities (94% and 92% accuracy, respectively). By incorporating sentiment features determined by SSNet, we can predict the ranking of emerging thermoelectric materials with a 70% correlation to experimental outcomes. Furthermore, our model achieves a commendable 68% accuracy in predicting suitable nanomaterials for atomic layer deposition (ALD) over time. These promising results offer a practical framework to extract and synthesize knowledge from the scientific literature, thereby accelerating research in the field of nanomaterials.

Designing 3d metal oxides: selecting optimal density functionals for strongly correlated materials.

Transition metal oxides (TMOs) have remarkable physicochemical properties, are non-toxic, and have low cost and high annual production, thus they are commonly studied for various technological applications. Density functional theory (DFT) can help to optimize TMO materials by providing insights into their electronic, optical and thermodynamic properties, and hence into their structure-performance relationships, over a wide range of solid-state structures and compositions. However, this is underpinned by the choice of the exchange-correlation (XC) functional, which is critical to accurately describe the highly localized and correlated 3d-electrons of the transition metals in TMOs. This tutorial review presents a benchmark study of density functionals (DFs), ranging from generalized gradient approximation (GGA) to range-separated hybrids (RSH), with the all-electron def2-TZVP basis set, comparing magneto-electro-optical properties of 3d TMOs against experimental observations. The performance of the DFs is assessed by analyzing the band structure, density of states, magnetic moment, structural static and dynamic parameters, optical properties, spin contamination and computational cost. The results disclose the strengths and weaknesses of the XC functionals, in terms of accuracy, and computational efficiency, suggesting the unprecedented PBE0-1/5 as the best candidate. The findings of this work contribute to necessary developments of XC functionals for periodic systems, and materials science modelling studies, particularly informing how to select the optimal XC functional to obtain the most trustworthy description of the ground-state electron structure of 3d TMOs.

The usefulness of energy decomposition schemes to rationalize host-guest interactions.

This perspective focuses on the crucial role that energy decomposition schemes play in elucidating the physical nature of non-covalent interactions in supramolecular systems, particularly from the point of view of host-guest systems stabilized by non-covalent interactions, which are fundamental to molecular recognition. The findings reported here reveal the robustness and practical application of methods such as EDA-NOCV in rationalizing molecular recognition situations in systems such as calixarenes, cyclophanes and other box-shaped hosts, capable of incorporating different chemical species as anions and PAHs. We expect that the discussed cases in this perspective can be viewed as an initial assessment for the multidimensional nature of the weak interactions underlying supramolecular aggregations, which can be recognized in a plethora of different structures constantly synthesized and characterized by chemists around the world.

In Silico Design of Cylindrophanes: The Role of Functional Groups in a Fluoride Selective Host.

Molecular recognition is the key driver in the formation of supramolecular complexes, enabling the selective encapsulation of specific guests. Here, we explore the delicate balance between different energetic terms in the formation of an efficient host for fluoride anions based on a cylindrophane structure, which can be achieved by the incorporation of ligand sites into a cyanuric acid based cyclophane framework, resulting a close proximity between the ammonium hydrogens and the anion. This study describes the character and contribution of different energetic and repulsive terms that favor the efficient inclusion of fluoride. Our findings are useful for further rational design and synthesis of efficient and highly selective fluoride hosts, which have been generally less well described than complexing agents for other halides.

Understanding the interplay between π-π and cation-π interactions in [janusene-Ag]+ host-guest systems: a computational approach.

Janusene is a symmetrical molecule that contains four benzene rings, with two of them forced to be in a vertical quasi-parallel face-to-face alignment. The unique physical nature of the transannular interactions and the electronic features of the region between the enforced parallel rings was tested with the complexation of Ag+ ion as a probe to evaluate the interplay between π-stacking and cation-π non-bonded interactions. The janusene framework and the [janusene-Ag]+ host-guest (H-G) system were analyzed through the introduction of substituent groups with different chemical natures and in different parts of the host framework. The janusenes were used to tune both π-stacking and cation-π interactions. Three modes of substitution (facial, lateral, and facial plus lateral) were explored to gain insight into the effects of such scaffold modifications on the dual non-bonded interactions. Our findings suggest that the η2:η2 silver coordination is the most stable interaction mode between the silver ion and the janusene parallel rings. The cation-π interaction in the host structure is stabilized by electron donating groups and destabilized by electron withdrawing groups. The stabilization effect is highlighted with substitutions on the facial and facial plus lateral modes, with the latter being due to additive cooperation between the substituent groups. The bonding analysis indicates that [janusene-Ag]+ complexes containing electron withdrawing groups in the facial and facial plus lateral substitution schemes are more stabilized by orbital interactions. Complexes with electron donating groups and the complexes with substituent groups in the lateral position are mainly stabilized by electrostatic interactions, although in all cases orbital and dispersive interactions are also essential to describe the bonding situation. We envisage that these results will guide the development of new systems with increased cation-π interaction capability.

Quest for Insight into Ultrashort C-H···π Proximities in Molecular "Iron Maidens".

Molecular iron maidens are a strained type of cyclophane in which a methine hydrogen, by the action of the bridges, is placed closer to the center of an aromatic ring. Such constrained molecular frameworks are in fact a noteworthy synthetic challenge. The present study provides a comprehensible theoretical analysis that elucidates unique structural and energetic aspects of this class of molecules, evaluating, in the light of quantum chemistry, both the influence of the aromatic moiety, from π-basic to π-acid, and the nature of the heteroatoms located at the bridges. Our results not only propose the shortest intramolecular centered C-H···π distance to date, which is supported by calculated 1H chemical shifts, but also shed light on the main factors that rationalize and justify such proximity. QTAIM, NBO, and NCI analyses allow us prematurely to conclude that the ultrashort C-H···π distance is sustained by an interplay between a large stabilizing electrostatic component with a non-negligible covalent character. However, the energetics involving such strained molecular scaffolds, addressed by means of isodesmic reactions, revealed that the C-H···π proximity is modulated mainly by the capacity of the bridges to support the strain imposed by the whole structure, hence compressing the C-H bond against the π-system.

Tuning Heterocalixarenes to Improve Their Anion Recognition: A Computational Approach.

We have explored and analyzed the physical factors through which noncovalent interactions in anion sensing based on calixarene-type hosts can be tuned, using dispersion-corrected DFT and Kohn-Sham molecular orbital (KS-MO) theory in conjunction with a canonical energy decomposition analysis (EDA). We find that the host-guest interaction can be enhanced through the introduction of strongly electron-withdrawing groups at particular positions of the arene and triazine units in the host molecule as well as by coordination of a metal complex to the arene and triazine rings. Our analyses reveal that the enhanced anion affinity is caused by increasing the electrostatic potential in the heterocalixarene cavities. This insight can be employed to further tune and improve their selectivity for chloride ions.