Neutron diffraction and ab initio studies on the fully compensated ferrimagnetic characteristics of Mn2V1-xCoxGa Heusler alloys

Neutron diffraction and ab initio studies were carried out on Mn2V1-xCoxGa (x = 0, 0.25, 0.5, 0.75, 1) Heusler alloys which exhibits high TC fully compensated ferrimagnetic characteristics for x = 0.5. A combined analysis of neutron diffraction and ab initio calculations revealed the crystal structure and magnetic configuration which could not be determined from the X-ray diffraction and magnetic measurements. As reported earlier, Rietveld refinement of neutron diffraction data confirmed L21 structure for Mn2VGa and Xa structure for Mn2CoGa. The alloys with x = 0.25 and 0.5 possess L21 structure with Mn(C)-Co disorder. As the Co concentration reaches 0.75, a structural transition has been observed from disordered L21 to disordered X a. Detailed ab initio studies also confirmed this structural transition. The reason for the magnetic moment compensation in Mn2(V1-xCox)Ga was identified to be different from that of the earlier reported fully compensated ferrimagnet (MnCo)VGa. With the help of neutron diffraction and ab initio studies, it is identified that the disordered L21 structure with antiparallel coupling between the ferromagnetically aligned magnetic moments of (Mn(A)-Mn(C)) and (V-Co) atom pairs enables the compensation in Mn2V1-xCoxGa.

Independent gradient model based on Hirshfeld partition (IGMH): A new method for visual study of interactions in chemical systems

The independent gradient model (IGM) originally proposed in Phys. Chem. Chem. Phys., 19, 17928 (2017) has been increasingly popular in visual analysis of intramolecular and intermolecular interactions in recent years, and it has many clear advantages over the widely employed noncovalent interaction (NCI) method, such as intrafragment and interfragment interactions can be elegantly isolated and thus separately studied, the isosurfaces are smoother and less jaggy. However, we frequently observed that there is an evident shortcoming of IGM map in graphically studying weak interactions, that is its isosurfaces are usually too bulgy; in these cases, not only the graphical effect is poor, but also the color on some areas on the isosurfaces is inappropriate and may lead to erroneous analysis conclusions. In addition, the IGM method was originally proposed based on promolecular density, which is quite crude and does not take actual electronic structure into account. In this article, we first present a detailed overview of the IGM analysis, and then propose our new variant of IGM, namely IGM based on Hirshfeld partition of molecular density (IGMH), which replaces the free-state atomic densities involved in the IGM method with the atomic densities derived by Hirshfeld partition of actual molecular electron density. This change makes IGM have more rigorous physical background. In addition, we describe some indices defined on the top of IGM or IGMH framework to quantify contributions from various atoms or atom pairs to interaction between specific fragments. A large number of application examples in this article, including molecular and periodic systems, weak and chemical bond interactions, fully demonstrate the important value of IGMH in intuitively understanding interactions in chemical systems. Comparisons also showed that the IGMH usually has markedly better graphical effect than IGM and overcomes known problems in IGM. Currently IGMH analysis has been efficiently supported in our freely available and user-friendly wavefunction analysis code Multiwfn (http://sobereva.com/multiwfn), and a detailed tutorial is presented. We hope that IGMH will become a new popular method among chemists for exploring interactions in wide variety of chemical systems.

Independent gradient model based on Hirshfeld partition (IGMH): A new method for visual study of interactions in chemical systems

The independent gradient model (IGM) originally proposed in Phys. Chem. Chem. Phys., 19, 17928 (2017) has been increasingly popular in visual analysis of intramolecular and intermolecular interactions in recent years, and it has many clear advantages over the widely employed noncovalent interaction (NCI) method, such as intrafragment and interfragment interactions can be elegantly isolated and thus separately studied, the isosurfaces are smoother and less jaggy. However, we frequently observed that there is an evident shortcoming of IGM map in graphically studying weak interactions, that is its isosurfaces are usually too bulgy; in these cases, not only the graphical effect is poor, but also the color on some areas on the isosurfaces is inappropriate and may lead to erroneous analysis conclusions. In addition, the IGM method was originally proposed based on promolecular density, which is quite crude and does not take actual electronic structure into account. In this article, we first present a detailed overview of the IGM analysis, and then propose our new variant of IGM, namely IGM based on Hirshfeld partition of molecular density (IGMH), which replaces the free-state atomic densities involved in the IGM method with the atomic densities derived by Hirshfeld partition of actual molecular electron density. This change makes IGM have more rigorous physical background. In addition, we describe some indices defined on the top of IGM or IGMH framework to quantify contributions from various atoms or atom pairs to interaction between specific fragments. A large number of application examples in this article, including molecular and periodic systems, weak and chemical bond interactions, fully demonstrate the important value of IGMH in intuitively understanding interactions in chemical systems. Comparisons also showed that the IGMH usually has markedly better graphical effect than IGM and overcomes known problems in IGM. Currently IGMH analysis has been efficiently supported in our freely available and user-friendly wavefunction analysis code Multiwfn (http://sobereva.com/multiwfn), and a detailed tutorial is presented. We hope that IGMH will become a new popular method among chemists for exploring interactions in wide variety of chemical systems.

FP-ADMET: a compendium of fingerprint-based ADMET prediction models

Motivation The absorption, distribution, metabolism, excretion, and toxicity (ADMET) of drugs plays a key role in determining which among the potential candidates are to be prioritized. In silico approaches based on machine learning methods are becoming increasing popular, but are nonetheless limited by the availability of data. With a view to making both data and models available to the scientific community, we have developed FPADMET which is a repository of molecular fingerprint-based predictive models for ADMET properties. Summary In this article, we have examined the efficacy of fingerprint-based machine learning models for a large number of ADMET-related properties. The predictive ability of a set of 20 different binary fingerprints (based on substructure keys, atom pairs, local path environments, as well as custom fingerprints such as all-shortest paths) for over 50 ADMET and ADMET-related endpoints have been evaluated as part of the study. We find that for a majority of the properties, fingerprint-based random forest models yield comparable or better performance compared with traditional 2D/3D molecular descriptors. Availability The models are made available as part of open access software that can be downloaded from https://gitlab.com/vishsoft/fpadmet.

The SN2 reaction and its relationship with the Walden inversion, the Finkelstein and Menshutkin reactions together with theoretical calculations for the Finkelstein reaction

This communication gives an overview of the relationships between four reactions that although related were not always perceived as such: SN2, Walden, Finkelstein, and Menshutkin. Binary interactions (SN2 & Walden, SN2 & Menshutkin, SN2 & Finkelstein, Walden & Menshutkin, Walden & Finkelstein, Menshutkin & Finkelstein) were reported. Carbon, silicon, nitrogen, and phosphorus as central atoms and fluorides, chlorides, bromides, and iodides as lateral atoms were considered. Theoretical calculations provide Gibbs free energies that were analyzed with linear models to obtain the halide contributions. The M06-2x DFT computational method and the 6-311++G(d,p) basis set have been used for all atoms except for iodine where the effective core potential def2-TZVP basis set was used. Concerning the central atom pairs, carbon/silicon vs. nitrogen/phosphorus, we reported here for the first time that the effect of valence expansion was known for Si but not for P. Concerning the lateral halogen atoms, some empirical models including the interaction between F and I as entering and leaving groups explain the Gibbs free energies.

Probing the Rheological Properties of Liquids Under Conditions of Elastohydrodynamic Lubrication Using Simulations and Machine Learning

In elastohydrodynamic lubrication (EHL), the lubricant experiences pressures in excess of 500 MPa and strain rates larger than $$10^5$$ 10 5 $$\text{s}^{-1}$$ s - 1 . The high pressures lead to a dramatic rise in the Newtonian viscosity and the high rates lead to large shear stresses and pronounced shear thinning. The extraction of accurate rheological properties using non-equilibrium molecular dynamics simulations (NEMD) has played a key role in improving our understanding of lubricant flow in EHL conditions. However, the high dimensionality of the output data generated by NEMD simulations often makes a deeper interrogation of the link between molecular-scale features and rheological properties challenging. In this paper, we explore the use of machine learning to analyze and visualize the high-dimensional output data generated in typical NEMD simulations. We show that dimension reduction of NEMD simulation data describing the shear flow of squalane enables a clear visualization of the transition from Newtonian to non-Newtonian shear thinning with increasing shear rate and provides a reliable assessment of the correlation between shear thinning and the evolution in molecular alignment. The end-to-end atom pairs dominate the largest variations in pair orientation tensor components for low-pressure systems (0.1, 100 MPa) and provide the clearest separation of the orientation tensors with rate. On the other hand, the side atom pairs dominate the largest variation in the tensor components for the high-pressure systems ($$P\ge 400$$ P ≥ 400 MPa) which exhibit an overall limited evolution in orientation tensors as a function of rate. Dimension reduction using all the six components of the orientation tensors of all 435 pairs associated with a squalane molecule shows that the decrease in viscosity with rate for low pressures is strongly correlated with changes in molecular alignment. However, for high pressures, shear thinning occurs at saturated orientational order.

The missing link: covalent linkages in structural models

Covalent linkages between constituent blocks of macromolecules and ligands have been subject to inconsistent treatment during the model-building, refinement and deposition process. This may stem from a number of sources, including difficulties with initially detecting the covalent linkage, identifying the correct chemistry, obtaining an appropriate restraint dictionary and ensuring its correct application. The analysis presented herein assesses the extent of problems involving covalent linkages in the Protein Data Bank (PDB). Not only will this facilitate the remediation of existing models, but also, more importantly, it will inform and thus improve the quality of future linkages. By considering linkages of known type in the CCP4 Monomer Library (CCP4-ML), failure to model a covalent linkage is identified to result in inaccurate (systematically longer) interatomic distances. Scanning the PDB for proximal atom pairs that do not have a corresponding type in the CCP4-ML reveals a large number of commonly occurring types of unannotated potential linkages; in general, these may or may not be covalently linked. Manual consideration of the most commonly occurring cases identifies a number of genuine classes of covalent linkages. The recent expansion of the CCP4-ML is discussed, which has involved the addition of over 16 000 and the replacement of over 11 000 component dictionaries using AceDRG. As part of this effort, the CCP4-ML has also been extended using AceDRG link dictionaries for the aforementioned linkage types identified in this analysis. This will facilitate the identification of such linkage types in future modelling efforts, whilst concurrently easing the process involved in their application. The need for a universal standard for maintaining link records corresponding to covalent linkages, and references to the associated dictionaries used during modelling and refinement, following deposition to the PDB is emphasized. The importance of correctly modelling covalent linkages is demonstrated using a case study, which involves the covalent linkage of an inhibitor to the main protease in various viral species, including SARS-CoV-2. This example demonstrates the importance of properly modelling covalent linkages using a comprehensive restraint dictionary, as opposed to just using a single interatomic distance restraint or failing to model the covalent linkage at all.

Understanding Topological Insulators in Real Space

A real space understanding of the Su–Schrieffer–Heeger model of polyacetylene is introduced thanks to delocalization indices defined within the quantum theory of atoms in molecules. This approach enables to go beyond the analysis of electron localization usually enabled by topological insulator indices—such as IPR—enabling to differentiate between trivial and topological insulator phases. The approach is based on analyzing the electron delocalization between second neighbors, thus highlighting the relevance of the sublattices induced by chiral symmetry. Moreover, the second neighbor delocalization index, δi,i+2, also enables to identify the presence of chirality and when it is broken by doping or by eliminating atom pairs (as in the case of odd number of atoms chains). Hints to identify bulk behavior thanks to δ1,3 are also provided. Overall, we present a very simple, orbital invariant visualization tool that should help the analysis of chirality (independently of the crystallinity of the system) as well as spreading the concepts of topological behavior thanks to its relationship with well-known chemical concepts.