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The discovery of carbon fullerene cages and their solids opened a new avenue to build materials from stable cage clusters as "artificial atoms"or "superatoms"instead of atoms. However, cage clusters of other elements are generally not stable. In 2001, ab initio calculations showed that endohedral doping of Zr and Ti atoms leads to highly stable Zr@Si16 fullerene and Ti@Si16 Frank-Kasper polyhedral clusters with large HOMO-LUMO gaps. In 2002, Zr@Ge16 was shown to form a Frank-Kasper polyhedron, suggesting the possibility of designing novel clusters by tuning endohedral and cage atoms. These results were subsequently confirmed from experiments. In the past nearly two decades, many experimental and theoretical studies have been carried out on different clusters, and many very stable cage clusters with possibly high abundance have been found by endohedral doping. Indeed in 2017, Ta@Si16 and Ti@Si16 cage clusters have been synthesized in bulk quantity of about 100 mg using a dry-chemistry method, giving rise to a new hope of developing cluster-based materials in macroscopic quantity besides the well-known C60 fullerene solid. Also, wet-chemistry methods have been used to synthesize endohedrally doped clusters as well as ligated clusters and their solids, which auger well for the development of novel nanostructured materials using atomically precise clusters with unique properties. In this comprehensive review, we present results of many such developments in this fast-growing field including (i) endohedrally doped Al, Ga, and In clusters, (ii) small endohedral carbon fullerene cages with ≤ 28 carbon atoms, (iii) metal doped boron cages, (iv) endohedrally doped cages of group 14 elements (Si, Ge, Sn, and Pb), (v) coinage metal (Cu, Ag, Au) cages doped with a transition metal atom as well as their ligated clusters and crystals, (vi) endohedrally doped cages of compound semiconductors, and (vii) multilayer Matryoshka cages and core-shell structures. In a large number of cases, we have performed ab initio calculations to present updated results of the most stable atomic structures and fundamental electronic properties of the endohedrally doped cage clusters. We discuss electronic, magnetic, optical, and catalytic properties in order to shed light on their potential applications. The stability of the doped cage clusters has been correlated to the concept of filling the electronic shells for superatoms such as within a spherical potential model and also using various electron counting rules including Wade-Mingos rules, systems with 18 and 32 electrons, and the spherical aromaticity rule. We also discuss cluster-cluster interaction in cluster dimers and assemblies of some of the promising doped cage clusters in different dimensions. Finally, we give a perspective of this field with a bright future. © 2020 American Chemical Society.

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Fulltext

Chemical Reviews

Endohedrally Doped Cage Clusters

Thin films of β-W are the most interesting for manipulating magnetic moments using spin–orbit torques, and a clear understanding of α to β phase transition in W by doping impurity, especially oxygen, is needed. Here we present a combined experimental and theoretical study using grazing incidence X-ray diffraction, photoelectron spectroscopy, electron microscopy, and ab initio calculations to explore atomic structure, bonding, and oxygen content for understanding the formation of β-W. It is found that the W films on SiO2/Si have 13–22 at.\% oxygen in A15 β structure. Ab initio calculations show higher solution energy of oxygen in β-W, and a tendency to transform locally from α to β phase with increasing oxygen concentration. X-ray absorption spectroscopy also revealed local geometry of oxygen in β-W, in agreement with the simulated one. These results offer an opportunity for a fundamental understanding of the structural transition in α-W and further development of β-W phase for device applications. © 2020, The Author(s).

Physics

(SoNS) School of Natural Sciences

Scientific Reports

Unravelling oxygen driven α to β phase transformation in tungsten

A novel lead-free 2D perovskite, namely PEA2SnBr4, shows impressive water-resistance by retaining its original crystal structure and optical properties when placed in contact with water. Such key properties have been advantageously used for the fabrication of a novel co-catalytic system by coupling PEA2SnBr4 with graphitic carbon nitride. PEA2SnBr4/g-C3N4 composites at different metal halide perovskite loadings (5 and 15 wt\%) have been prepared and tested in hydrogen photogeneration in an aqueous environment and organic dye degradation (methylene blue). The results show an impressive enhancement of H2 production of the composite with respect to the two separate components with hydrogen evolution rates up to 1600 μmol g-1 h-1 and analogous improvements in the efficiency of methylene blue degradation. The present results, providing a novel water-resistant perovskite and co-catalytic system, pave the way towards the safe, efficient and real use of metal halide perovskites in catalysis. This journal is © The Royal Society of Chemistry.

Journal of Materials Chemistry C

PEA2SnBr4: A water-stable lead-free two-dimensional perovskite and demonstration of its use as a co-catalyst in hydrogen photogeneration and organic-dye degradation

Recent experiments on Eu-doped nanocrystals of CsPbX3 (X = Cl, Br) show that Eu exists in the 3+ oxidation state even though it substitutes Pb, which is in the 2+ state in these perovskites. Therefore, the question arises, what is it that leads to the formation of Eu3+ in the nanocrystals of these materials? In order to understand this, we have studied the doping of Eu in a slab (∼1.8 nm thick) of CsPbBr3 using ab initio calculations and explored various possibilities that could lead to the formation of Eu3+ and the occurrence of f-f transitions. These include (1) the presence of a Cs vacancy, (2) the existence of H or OH due to moisture, (3) substitution of O at the surface halogen site, and (4) the possibility of excess halogen around Eu. It is found that the presence of surface oxygen is the most likely reason for the observation of Eu3+ in these nanolayers. Our results show the presence of partially occupied spin-up f states and a magnetic moment of 6.48 μB on Eu that could lead to the possibility of f-f transition in these doped systems. A similar result has also been obtained for Eu doped in CsPbCl3 nanolayers. The calculated change in energy when defects/impurities are present is a favorable indication of finding H, OH, and Br as interstitials and O as substitutional entities but Cs vacancy is unlikely. Additionally, we find that the doping of Eu in nanolayers does not affect the atomic structure, and the cost of doping is also very small, making these perovskites very promising materials for light-emitting diodes and other solid-state lighting applications. © 2020 American Chemical Society.

ACS Applied Nano Materials

A Study of Eu Doping in Nanolayers of CsPbBr3using Ab Initio Calculations to Understand f-f Transitions in Eu3+-Doped Nanocrystals for Light-Emitting Diodes

We study the stability of the rare-earth dopant, Eu, in metal-halide perovskite CsPbBr3 with cubic and orthorhombic structures from first-principles calculations. In these perovskites, Eu is substitutionally doped on Pb sites because of their comparable ionic sizes which lead to only a small strain in the doped system. Accordingly, our results show that the cost of Eu doping is quite small compared to the values in other common hosts such as GaN. This makes these perovskites excellent candidates to develop rare-earth doped semiconducting materials for bright luminescence as it has also been observed recently in the case of thin films of CH3NH3Pb1-xEuxI3, Eu-doped quantum dots of CsPbBr3, and nanocrystals of CsPbCl3 in addition to their outstanding properties for applications in solar cells. © 2019 American Chemical Society.

Journal of Physical Chemistry C

Stability of the Eu2+ Dopant in CsPbBr3 Perovskites: A First-Principles Study

In this paper we propose a simple way for structural modification of graphene yielding a non-zero band gap which is mandatory for prospective electronics applications. This can be achieved by creating a buffer layer graphene (BuLG) upon deposition on different crystalline silicon surfaces. Previous calculations have shown that the formation of such buffer layer on 4H-SiC results in lattice deformation of BuLG, due to the 8% mismatch between the (0001)Si crystal surface of SiC and the graphene lattices. Here, for elimination of the lattice deformation, we propose a replacement of the (0001)Si surface of SiC by hydrogen atoms. Using density functional simulations we show that the band gap of the corrugated graphene sheet is $\Delta$E = 1.94 eV (hydrogenated system) or $\Delta$E = 1.21 eV SiC/graphene system. Height of corrugation is equal to h = 35.0 ± 5.0 pm. Two effects are responsible for the band gap opening: corrugation of the sheet, caused by the covalently bonded carbon atoms and removal of electrons from the bonding $\pi$ orbitals of graphene.

Bulgarian Chemical Communications

Semiconducting graphene

Traditionally, lead and heavy metal containing inorganic oxides dominate the area of ferroelectricity. Although, recently, lightweight non-toxic organic ferroelectrics have emerged as excellent alternatives, achieving higher temperature up to which the ferroelectric phase can persist has remained a challenge. Moreover, only a few of those are single-component molecular ferroelectrics and were discovered upon revisiting their crystal structures. Here we report a novel phenanthroimidazole derivative, which not only displays notable spontaneous and highly stable remnant polarizations with a low coercive field but also retains its ferroelectric phase up to a record-high temperature of ∼521 K. Subsequently, the crystal undergoes phase transition to form non-polar and centrosymmetric polymorphs, the first study of its kind in a single-component ferroelectric crystal. Moreover, the compound exhibits a significantly high thermal stability. Given the excellent figures-of-merit for ferroelectricity, this material is likely to find potential applications in microelectronic devices pertaining to non-volatile memory. © The Royal Society of Chemistry 2019.

Chemistry

Chemical Communications

Record-high thermal stability achieved in a novel single-component all-organic ferroelectric crystal exhibiting polymorphism

Present research efforts coupled with improved experimental techniques have provided voluminous genomic data. To convert this data into useful knowledge, novel tools for phenomenological and data driven modelling approaches are needed. This need has spurred initiation of a lot of rigorous efforts and has resulted in development of robust artificial intelligence (AI) and machine learning (ML) based models. While these paradigms individually and in synergistic combinations have been employed in various bioinformatics applications, the viral biology discipline has particularly benefitted most. These methodologies can efficiently handle single dimensional sequence to higher dimensional protein structures, microarray data, image and text data, experimental data emanating from spectroscopy, etc. Our analysis deals with ML tools like support vector machines (SVM), neural networks, deep neural networks, random forest, and decision tree. Analysis and interpretations are provided along with ample illustrations of their relevance to real-life applications. AI and evolutionary computing based tools like Genetic Algorithms, Ant Colony optimization, Particle swarm optimization and their applicability to viral biology problems are also discussed. Hybrid combination of these tools with ML techniques have resulted in simultaneous selection of informative attributes and high performance classification. This hybrid methodology has been discussed in detail. In this chapter we describe the applications artificial intelligence and machine learning in virology. While there are AI has a multitude of tools, the focus would be on a specific aspect of Ai, known as evolutionary and heuristic computing. These are mainly employed as an alternative paradigm of optimization. They are mainly nature inspired algorithms. Although very simple and straightforward to use they have been deputed to solve several problems successfully in different domains of science and engineering. Machine learning on the other hand deals with a mountain of available data, recognize hidden patterns useful and interesting to upgrade it to structure and knowledge. We provide examples of the power of AI and Machine learning with the illustration of several examples from different subdomains of viral biology. We will also provide examples where the synergistic combination of AI and ML has a been found to be a very potent tool for solving several important problems in viral biology. © Springer Nature Switzerland AG 2019. All rights reserved.

Life Sciences

Global Virology III: Virology in the 21st Century

Applications of artificial intelligence and machine learning in viral biology

Multi-label learning has been a topic of research interest in multimedia, text speech recognitions, music, image processing, information retrieval etc. In Multi-label classification (MLC) each instance is associated with a set of multiple class labels. Like other machine learning algorithms, data preprocessing plays an key role in MLC. Feature selection is an important preprocessing step in MLC, due to high dimensionality of datasets and associated computational costs.Extracting the most informative features considerably reduces the computational loads of MLC. Most of the Multi-label feature selection algorithms available in literature involve conversions to multiple single labeled feature selection problems. We proposed an efficient modification of a recent multi-label feature selection algorithm [1] available in literature. Our algorithm consists of two steps: in the first step we decompose the output label space into lower dimensions using simple matrix factorization method; subsequently we employ feature selection process in the decoupled reduced space. Our simulations with real world datasets reveal the efficiency of proposed framework. © 2019 IEEE.

Proceedings of 2019 3rd IEEE International Conference on Electrical, Computer and Communication Technologies, ICECCT 2019

A Simple Method of Solution For Multi-label Feature Selection

We report results of the state-of-the-art ab initio calculations on two-dimensional (2D) hybrid halide perovskites capped with surface ligands to understand their effects on the stability with respect to bulk MASnBr3 (MA = CH3NH3). Considering the thinnest (one-unit-cell thick) layers R2SnBr4 with surface ligands of different lengths (R = MA, ethyl ammonium (EA), butyl ammonium (BA), and phenylethyl ammonium (PEA)), it is found that van der Waals (vdW) interactions between the long chain molecules play a crucial role in enhancing the stability of the layers. The vdW contribution in ligand-ligand interactions increases with increasing length of the ligands, and interestingly, the stability of BA2SnBr4 and PEA2SnBr4 layers becomes better than bulk MASnBr3 and comparable to that of inorganic bulk CsSnBr3. Furthermore, our calculations on the 2D-3D BA2SnBr4 system in which the surface ligands connect the neighboring perovskite layers suggest further enhancement in the stability of the layers. The present study shines light on the role of H···Br bonding in deciding the structure of the inorganic part of these thinnest layers and the effect of inclusion of vdW interactions on these H···Br bond lengths. The band gap of the layers increases slightly on increasing the length of the ligands, and there is a slight blue shift of the absorption spectrum. All the studied perovskite layers are direct band gap semiconductors, and our results show that the environmentally friendly BA2SnBr4 (PEA2SnBr4) layers are good candidates for green LEDs with a band gap of 2.28 (2.36) eV as obtained by using the HSE06 hybrid exchange-correlation functional with dispersion correction. Copyright © 2019 American Chemical Society.

Design

(SoHSS) School of Humanities and Social Sciences

Role of Ligand-Ligand Interactions in the Stabilization of Thin Layers of Tin Bromide Perovskite: An Ab Initio Study of the Atomic and Electronic Structure, and Optical Properties