Wide Angle Dynamically Tunable Enhanced Infrared Absorption on Large Area Nanopatterned Graphene

Enhancing light-matter interaction by exciting Dirac plasmons on nanopatterned monolayer graphene is an efficient route to achieve high infrared absorption. Here, we designed and fabricated the hexagonal planar arrays of nanohole and nanodisk with and without optical cavity to excite Dirac plasmons on the patterned graphene and investigated the role of plasmon lifetime, extinction cross-section, incident light polarization, the angle of incident of light and pattern dimensions on the light absorption spectra

FORMULATION OF FAST-DISSOLVING TABLETS OF DOXAZOSIN MESYLATE DRUG BY DIRECT COMPRESSION METHOD

Objective: The rationale of the current research work was to formulate and evaluate fast-dissolving tablets of doxazosin mesylate with minimum disintegration time and improved dissolution efficiency using solid dispersion method.Methods: Solid dispersions of doxazosin mesylate and polyethylene glycol 8000 in different ratios were prepared using the kneading method. The prepared solid dispersions were subjected to drug interaction and dissolution studies to select the effective solid dispersion for the formulation of fast-dissolving tablets. Fast dissolving tablets containing drug-polyethylene glycol 8000 solid dispersion (1:3) were prepared using various super-disintegrants such as crospovidone, croscarmellose sodium, mixture and coprocessed crospovidone and croscarmellose sodium in concentration range of 2% and 5% by direct compression technique. The prepared formulations (F1–F16) were evaluated for post compression parameters; hardness, thickness, friability, wetting time, disintegration time, and in–vitro drug release.Results: Drug doxazosin mesylate showed enhanced aqueous solubility of 13.3µg/ml in the presence of polyethylene glycol 8000. Differential scanning calorimetery and Fourier transform infrared spectroscopy studies confirmed no interaction between drug and polyethylene glycol 8000and, drug-polyethylene glycol 8000 solid dispersion showed cumulative drug release of 44.48% in 60 min. Formulated FDT of drug-polyethylene glycol 8000 solid dispersion, containing coprocessed mixture of crospovidone and croscarmellose sodium (5%) exhibited disintegration time of 14.5s with percentage cumulative release of 92.46% in 60 min.Conclusion: The work reasonably concludes that for the formulated doxazosin mesylate-fast dissolving tablets, disintegration time was effectively reduced by the presence of coprocessed mixture of crospovidone and croscarmellose sodium and dissolution efficiency was improved by preparation of solid dispersion with polyethylene glycol 8000

Exchange Bias Effect in Au-Fe3O4 Nanocomposites

We report exchange bias (EB) effect in the Au-Fe3O4 composite nanoparticle system, where one or more Fe3O4 nanoparticles are attached to an Au seed particle forming dimer and cluster morphologies, with the clusters showing much stronger EB in comparison with the dimers. The EB effect develops due to the presence of stress in the Au-Fe3O4 interface which leads to the generation of highly disordered, anisotropic surface spins in the Fe3O4 particle. The EB effect is lost with the removal of the interfacial stress. Our atomistic Monte-Carlo studies are in excellent agreement with the experimental results. These results show a new path towards tuning EB in nanostructures, namely controllably creating interfacial stress, and open up the possibility of tuning the anisotropic properties of biocompatible nanoparticles via a controllable exchange coupling mechanism.Comment: 28 pages, 6 figures, submitted to Nanotechnolog

Discovering Symbolic Laws Directly from Trajectories with Hamiltonian Graph Neural Networks

The time evolution of physical systems is described by differential equations, which depend on abstract quantities like energy and force. Traditionally, these quantities are derived as functionals based on observables such as positions and velocities. Discovering these governing symbolic laws is the key to comprehending the interactions in nature. Here, we present a Hamiltonian graph neural network (HGNN), a physics-enforced GNN that learns the dynamics of systems directly from their trajectory. We demonstrate the performance of HGNN on n-springs, n-pendulums, gravitational systems, and binary Lennard Jones systems; HGNN learns the dynamics in excellent agreement with the ground truth from small amounts of data. We also evaluate the ability of HGNN to generalize to larger system sizes, and to hybrid spring-pendulum system that is a combination of two original systems (spring and pendulum) on which the models are trained independently. Finally, employing symbolic regression on the learned HGNN, we infer the underlying equations relating the energy functionals, even for complex systems such as the binary Lennard-Jones liquid. Our framework facilitates the interpretable discovery of interaction laws directly from physical system trajectories. Furthermore, this approach can be extended to other systems with topology-dependent dynamics, such as cells, polydisperse gels, or deformable bodies

StriderNET: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes

Optimization of atomic structures presents a challenging problem, due to their highly rough and non-convex energy landscape, with wide applications in the fields of drug design, materials discovery, and mechanics. Here, we present a graph reinforcement learning approach, StriderNET, that learns a policy to displace the atoms towards low energy configurations. We evaluate the performance of StriderNET on three complex atomic systems, namely, binary Lennard-Jones particles, calcium silicate hydrates gel, and disordered silicon. We show that StriderNET outperforms all classical optimization algorithms and enables the discovery of a lower energy minimum. In addition, StriderNET exhibits a higher rate of reaching minima with energies, as confirmed by the average over multiple realizations. Finally, we show that StriderNET exhibits inductivity to unseen system sizes that are an order of magnitude different from the training system

2,4-dihydroxy benzaldehyde derived Schiff bases as small molecule Hsp90 inhibitors: rational identification of a new anticancer lead

Hsp90 is a molecular chaperone that heals diverse array of biomolecules ranging from multiple oncogenic proteins to the ones responsible for development of resistance to chemotherapeutic agents. Moreover they are over-expressed in cancer cells as a complex with co-chaperones and under-expressed in normal cells as a single free entity. Hence inhibitors of Hsp90 will be more effective and selective in destroying cancer cells with minimum chances of acquiring resistance to them. In continuation of our goal to rationally develop effective small molecule azomethines against Hsp90, we designed few more compounds belonging to the class of 2,4-dihydroxy benzaldehyde derived imines (1-13) with our validated docking protocol. The molecules exhibiting good docking score were synthesized and their structures were confirmed by IR, (1)H NMR and mass spectral analysis. Subsequently, they were evaluated for their potential to suppress Hsp90 ATPase activity by Malachite green assay. The antiproliferative effect of the molecules were examined on PC3 prostate cancer cell lines by adopting 3-(4,5-dimethythiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay methodology. Finally, schiff base 13 emerged as the lead molecule for future design and development of Hsp90 inhibitors as anticancer agents.Fil: Dutta Gupta, Sayan. Osmania University; India. Jawaharlal Nehru Technological University; IndiaFil: Revathi, B.. Osmania University; IndiaFil: Mazaira, Gisela Ileana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Galigniana, Mario Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; ArgentinaFil: Subrahmanyam, C. V. S.. Osmania University; IndiaFil: Gowrishankar, N. L.. Swami Vivekananda Institute of Pharmaceutical Sciences; IndiaFil: Raghavendra, N. M.. Osmania University; Indi

Exact solutions in two-dimensional string cosmology with back reaction

We present analytic cosmological solutions in a model of two-dimensional dilaton gravity with back reaction. One of these solutions exhibits a graceful exit from the inflationary to the FRW phase and is nonsingular everywhere. A duality related second solution is found to exist only in the ``pre-big-bang'' epoch and is singular at $\tau = 0$. In either case back reaction is shown to play a crucial role in determining the specific nature of these geometries.Comment: Shortened slightly, references added, to appear in Physical Review D (Rapid Communications). 16 pages, RevTex, 3 PostScript figure