Gold-nanorod-based sensing of sequence specific HIV-1 virus DNA by using hyper-Rayleigh scattering spectroscopy

Infectious diseases caused by the human immunodeficiency virus (HIV) remain the leading killers of human beings worldwide, and function to destabilize societies in Africa, Asia, and the Middle East. Driven by the need to detect the presence of HIV viral sequence, here we demonstrate that the second-order nonlinear optical (NLO) properties of gold nanorods can be used for screening HIV-1 viral DNA sequence without any modification, with good sensitivity (100 pico-molar) and selectivity (single base-pair mismatch). The hyper-Rayleigh scattering (HRS) intensity increases 45 times when a label-free 145-mer, ss-gag gene DNA, was hybridized with 100 pM target DNA. The mechanism of HRS intensity change has been discussed with experimental evidence for higher multipolar contribution to the NLO response of gold nanorods.     

Spectroscopic studies of transition metal complexes with a N-donor tetradentate(N4) 12-membered macrocylic ligand

Chromium(III), manganese(II), iron(III), cobalt(II), nickel(II), copper(II), ruthenium(III), iridium(III), palladium(II) and platinum(II) complexes were synthesized with a 12-membered 1,4,7,10-tetraazadodeca-5,6,11,12-tetraene macrocylic ligand (L) and characterized by elemental analysis, molar conductance, magnetic susceptibility, IR, electronic, EPR and M?ssbauer [Fe(III)] spectral studies. The molar conductance measurements of all the complexes in DMF solution correspond to non-electrolytic nature for M(L)Cl2 complexes [where M=Mn(II), Co(II), Ni(II), Cu(II)], 1:1 electrolytes for M'(L)Cl3 complexes [where M'=Cr(III), Fe(III), Ru(III) and Ir(III)] and 1:2 electrolytes for M'(L)Cl2 complexes [where M'=Pd(II) and Pt(II)]. Thus, the complexes may be formulated as [M(L)C1(2)], [M'(L)C1(2)]C1 and [M'(L)]C1(2), respectively [where L=ligand]. All complexes were of the high-spin type and found to have six-coordinate octahedral geometry except the Pd(II) and Pt(II) complexes which were four coordinate, square planar and diamagnetic.     

Statistically convergent difference double sequence spaces

In this article we define the notion of statistically convergent difference double sequence spaces. We examine the spaces 2l∞（△, q）, 2c（△, q）, 2cB（△, q）, 2cR（△, q）, 2cBR（△,q） etc. being symmetric, solid, monotone, etc. We prove some inclusion results too.     

Interface Design Enabling Stable Polymer/Thiophosphate Electrolyte Separators for Dendrite-Free Lithium Metal Batteries

Organic/inorganic interfaces greatly affect Li⁺ transport in composite solid electrolytes (SEs), while SE/electrode interfacial stability plays a critical role in the cycling performance of solid-state batteries (SSBs). However, incomplete understanding of interfacial (in)stability hinders the practical application of composite SEs in SSBs. Herein, chemical degradation between Li₆PS₅Cl (LPSCl) and poly(ethylene glycol) (PEG) is revealed. The high polarity of PEG changes the electronic state and structural bonding of the PS₄³⁻ tetrahedra, thus triggering a series of side reactions. A substituted terminal group of PEG not only stabilizes the inner interfaces but also extends the electrochemical window of the composite SE. Moreover, a LiF-rich layer can effectively prevent side reactions at the Li/SE interface. The results provide insights into the chemical stability of polymer/sulfide composites and demonstrate an interface design to achieve dendrite-free lithium metal batteries.     

Observation of Asymmetric Oxidation Catalysis with B20 Chiral Crystals**

The study of heterogeneous reactions for enantiomeric processes based on inorganic crystals has been resurgent in recent years. However, the question remains how homochirality develops in nature and chemical reactions. Here, the successful growth of B20 group PdGa single crystals with different chiral lattices enabled us to achieve enantioselective recognition of 3,4-dihydroxyphenylalanine (DOPA) based on a new mechanism, namely orbital angular momentum (OAM) polarization. The orbital textures of PdGa crystals indicate large OAM polarization near the Fermi level and carrying opposite signs. A positive or negative magnetization in the [111] direction is expected depending on the chiral lattice of PdGa crystals. Due to this, the adsorption energies of PdGa crystals and DOPA molecules differ depending on how well the O-2p orbital of DOPA pairs with the Pd-4d orbital of PdGa. The results provide one possible explanation for how chirality arises in nature by providing an enantioselective route with pure inorganic crystals.     

A Synergistic Approach towards Optimization of Coupled Cluster Amplitudes by Exploiting Dynamical Hierarchy

The coupled cluster iteration scheme for determining the cluster amplitudes involves a set of nonlinearly coupled difference equations. In the space spanned by the amplitudes, the set of equations are analyzed as a multivariate time-discrete map where the concept of time appears in an implicit manner. With the observation that the cluster amplitudes have difference in their relaxation timescales with respect to the distributions of their magnitudes, the coupled cluster iteration dynamics are considered as a synergistic motion of coexisting slow and fast relaxing modes, manifesting a dynamical hierarchical structure. With the identification of the highly damped auxiliary amplitudes, their time variation can be neglected compared to the principal amplitudes which take much longer time to reach the fixed points. We analytically establish the adiabatic approximation where each of these auxiliary amplitudes are expressed as unique parametric functions of the collective principal amplitudes, allowing us to study the optimization with the latter taken as the independent degrees of freedom. Such decoupling of the amplitudes significantly reduces the computational scaling without sacrificing the accuracy in the ground state energy as demonstrated by a number of challenging molecular applications. A road-map to treat higher order post-adiabatic effects is also discussed.     

Structural and Electronic Properties of Two-Dimensional Materials: A Machine-Learning-Guided Prediction

The growing number of studies and interest in two-dimensional (2D) materials has not yet resulted in a wide range of material applications. This is a result of difficulties in getting the properties, which are often determined through numerical experiments or through first-principles predictions, both of which require lots of time and resources. Here we provide a general machine learning (ML) model that works incredibly well as a predictor for a variety of electronic and structural properties such as band gap, fermi level, work function, total energy and area of unit cell for a wide range of 2D materials derived from the Computational 2D Materials Database (C2DB). Our predicted model for classification of samples works extraordinarily well and gives an accuracy of around 99 %. We are able to successfully decrease the number of studied features by employing a strict permutation-based feature selection method along with the sure independence screening and sparsifying operator (SISSO), which further supports the design recommendations for the identification of novel 2D materials with the desired properties.