Selective Hydrogenation Promotes Anisotropic Thermoelectric Properties of TPDH-Graphene

We have combined DFT calculations with the Boltzmann semiclassical transport theory to investigate the effect of selective hydrogenation on the thermoelectric properties of tetra-penta-deca-hexagonal graphene (TPDH-gr), a recently proposed new 2D carbon allotrope. Our results show that the Seebeck coefficient is enhanced after hydrogenation. The conductivity along the x direction is increased almost eight times while being almost suppressed along the y direction. This behavior can be understood in terms of the electronic structure changes due to the appearance of a Dirac-like cone after the selective hydrogenation. Consistent with the literature, the electronic contribution to thermal conductivity displays the same qualitative behavior as the conductivity, as expected from the Wiedemann-Franz law. The increase in thermal conductivity with temperature limits the material's power factor. The significant increase in the Seebeck coefficient and conductivity increases also contribute to the thermal conductivity increase. These results show that hydrogenation is an effective method to improve the TPDH-gr thermoelectric properties, and this carbon allotrope can be an effective material for thermoelectric applications.Comment: submitted to JPC

Machine Learning-based Analysis of Electronic Properties as Predictors of Anticholinesterase Activity in Chalcone Derivatives

In this study, we investigated the correlation between the electronic properties of anticholinesterase compounds and their biological activity. While the methodology of such correlation is well-established and has been effectively utilized in previous studies, we employed a more sophisticated approach: machine learning. Initially, we focused on a set of $22$ molecules sharing a common chalcone skeleton and categorized them into two groups based on their IC50 indices: active and inactive. Utilizing the open-source software Orca, we conducted calculations to determine the geometries and electronic structures of these molecules. Over a hundred parameters were collected from these calculations, serving as the foundation for the features used in machine learning. These parameters included the Mulliken and Lowdin electronic populations of each atom within the skeleton, molecular orbital energies, and Mayer's free valences. Through our analysis, we developed numerous models and identified several successful candidates for effectively distinguishing between the two groups. Notably, the most informative descriptor for this separation relied solely on electronic populations and orbital energies. By understanding which computationally calculated properties are most relevant to specific biological activities, we can significantly enhance the efficiency of drug development processes, saving both time and resources.Comment: to be submitted to Journal of Chemical Information and Modelin

Atomically locked interfaces of metal (Aluminum) and polymer (Polypropylene) using mechanical friction

Joining different parts is one of the crucial components of designing/engineering of materials. Presently, the current energy efficient low weight automotive and aerospace components consist of a different class of materials, such as metals, polymers, ceramics, etc. Joining these components remains a challenge. Here, we demonstrate metal (aluminum) and polymer (Polypropylene, pp) joining using mechanical friction. The detailed characterization clearly demonstrates that atomically locked interfaces are formed in such joining and no chemical bonds are formed during the joining. Also, a waterproof and strong interface is formed in such a process. Fully atomistic molecular dynamics simulations were also carried out in order to further gain insights on the joining process.by Arpan Rout, Prafull Pandey, Eliezer Fernando Oliveira, Pedro Alvesda Silva Autreto, Anurag Gumaste, Amit Singh, Douglas Soares Galvao, Amit Arora and Chandra Sekhar Tiwar

Morphology controlled Graphene-Alloy Nanoparticles Hybrids with Tunable carbon monooxide absorption

Selective oxidation of CO to CO2 using metallic or alloy nanoparticles as catalysts, can solve two major problems of energy requirements and environmental pollution. Achieving 100% conversion efficiency at a lower temperature is a very important goal. This requires sustained efforts to design and develop novel supported catalysts containing alloy nanoparticles. In this regard, the decoration of nanoalloys with graphene, as support for catalyst can provide a novel structure due to the synergic effect of the nanoalloys and graphene. Here, we demonstrate the effect of the nano-PdPt (Paladium-Platinum) alloys having different morphologies on the catalytic efficiency of selective oxidation of CO. Efforts were made to prepare different morphologies of PdPt alloy nanoparticles with the advantage of tuning the capping agent (PVP- polyvinyl pyrollidone) and decorating them on graphene sheets via wet-chemical route. The catalytic activity of the G-PdPt hybrids with urchin-like morphology has been found to be superior (higher % conversion at 135oC lower) to that with nanoflower morphology. The above experimental observations are further supported by molecular dynamics (MD) simulations.by M Manolata Devi, N Dolai, S Sreehala, Ygor M. Morais Jaques, R Mishra, D S Galvao, Chandra Sekhar Tiwary, Sudhanshu Sharma and K BISWA

Synthesis of Low-Density, Carbon-Doped, Porous Hexagonal Boron Nitride Solids

Here, we report the scalable synthesis and characterization of low-density, porous, three-dimensional (3D) solids consisting of two-dimensional (2D) hexagonal boron nitride (h-BN) sheets. The structures are synthesized using bottom-up, low-temperature (∼300 °C), solid-state reaction of melamine and boric acid giving rise to porous and mechanically stable interconnected h-BN layers. A layered 3D structure forms due to the formation of h-BN, and significant improvements in the mechanical properties were observed over a range of temperatures, compared to graphene oxide or reduced graphene oxide foams. A theoretical model based on Density Functional Theory (DFT) is proposed for the formation of h-BN architectures. The material shows excellent, recyclable absorption capacity for oils and organic solvents

Enhanced Mechanical Stability of Gold Nanotips through Carbon Nanocone Encapsulation

Gold is a noble metal that, in comparison with silver and copper, has the advantage of corrosion resistance. Despite its high conductivity, chemical stability and biocompatibility, gold exhibits high plasticity, which limits its applications in some nanodevices. Here, we report an experimental and theoretical study on how to attain enhanced mechanical stability of gold nanotips. The gold tips were fabricated by chemical etching and further encapsulated with carbon nanocones via nanomanipulation. Atomic force microscopy experiments were carried out to test their mechanical stability. Molecular dynamics simulations show that the encapsulated nanocone changes the strain release mechanisms at the nanoscale by blocking gold atomic sliding, redistributing the strain along the whole nanostructure. The carbon nanocones are conducting and can induce magnetism, thus opening new avenues on the exploitation of transport, mechanical and magnetic properties of gold covered by sp(2) carbon at the nanoscale.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP