01691nas a2200205   4500008004100000022001400041245011200055210006900167260000800236300001400244490000700258520097800265100001701243700002501260700001601285700002201301700001701323700001801340856012701358       2021                        eng d  a2041-652000aPhosphite mediated asymmetric N to C migration for the synthesis of chiral heterocycles from primary amines0 aPhosphite mediated asymmetric N to C migration for the synthesis  cJUL  a8996-90030 v123 aA phosphite mediated stereoretentive C-H alkylation of N-alkylpyridinium salts derived from chiral primary amines was achieved. The reaction proceeds through the activation of the N-alkylpyridinium salt substrate with a nucleophilic phosphite catalyst, followed by a base mediated [1,2] aza-Wittig rearrangement and subsequent catalyst dissociation for an overall N to C-2 alkyl migration. The scope and degree of stereoretention were studied, and both experimental and theoretical investigations were performed to support an unprecedented aza-Wittig rearrangement-rearomatization sequence. A catalytic enantioselective version starting with racemic starting material and chiral phosphite catalyst was also established following our understanding of the stereoretentive process. This method provides efficient access to tertiary and quaternary stereogenic centers in pyridine systems, which are prevalent in drugs, bioactive natural products, chiral ligands, and catalysts.1 aRani, Soniya1 aDash, Soumya, Ranjan1 aBera, Asish1 aAlam, Md, Nirshad1 aVanka, Kumar1 aMaity, Pradip  uhttp://library.ncl.res.in/content/phosphite-mediated-asymmetric-n-c-migration-synthesis-chiral-heterocycles-primary-amines01926nas a2200205   4500008004100000022001400041245015600055210006900211260000800280300001200288490000600300520116000306100002001466700002501486700001801511700002301529700002001552700002101572856012701593       2021                        eng d  a2516-023000aProminence of Cu in a plasmonic Cu-Ag alloy decorated SiO2@S-doped C3N4 core-shell nanostructured photocatalyst towards enhanced visible light activity0 aProminence of Cu in a plasmonic CuAg alloy decorated SiO2Sdoped   cDEC  a150-1620 v43 aA series of Cu-Ag bimetal alloys decorated on SiO2 and the fabrication of few-layer S-doped graphitic carbon nitride (SC) warped over it to form a core-shell nanostructured morphology have been demonstrated and well characterized through various physiochemical techniques. HRTEM data confirmed the formation of a compact nanojunction between the SiO2 and SC, where Cu-Ag is embedded uniformly with an average particle size of 1.3 nm. The Ag : Cu (1 : 3) between SiO2 and SC produces 1730 mu mol h(-1) g(-1) of H-2 under visible light illumination. Moreover, 6.2-fold current enhancement in the case of Ag : Cu (1 : 3) as compared to the Ag-loaded core-shell nanostructured photocatalyst indicates higher electron-hole-pair separation. The excellent activity was due to the synergistic alloying and plasmonic effect of Ag and Cu. DFT studies reveal that the Cu atom in the Cu-Ag bimetal alloy plays a pivotal role in the generation of H-2, and the reaction proceeds via a 4-membered transition state. The mechanistic insight proceeds from the generation of hot electrons due to the LSPR effect and their transfer to the SC layer via a compact nanojunction.1 aBabu, Pradeepta1 aDash, Soumya, Ranjan1 aBehera, Arjun1 aVijayaraghavan, T.1 aAshok, Anuradha1 aParida, Kulamani  uhttp://library.ncl.res.in/content/prominence-cu-plasmonic-cu-ag-alloy-decorated-sio2s-doped-c3n4-core-shell-nanostructured02589nas a2200205   4500008004100000022001400041245011100055210006900166260000900235300001400244490000700258520185700265100002402122700002502146700001902171700001702190700002402207700002402231856012802255       2022                        eng d  a1528-748300aPolymorphs of green fluorescence protein chromophore analogue: fluorescence switching with thermal stimuli0 aPolymorphs of green fluorescence protein chromophore analogue fl  cMAR   a1892-19050 v223 a<p>
	Polymorphs of fluorescent organic materials offer significant implications in optoelectronics and advanced materials as they modulate photoluminescence properties. A slight alteration in the conformation/packing of molecules in the crystals shows variation in photoluminescence. This necessitates the polymorph screening of these materials to develop novel crystalline forms with distinct fluorescence emissions for broader application. In continuation of our work on the polymorph screening of Green Fluorescence Protein Chromophore (GFPc), we have synthesized a new imidazoline derivative, ethyl (Z)-2-(2-methyl-5-oxo-4-(3,4,5-trimethoxybenzylidene)-4,5-dihydro-1H-imi dazol-1- yl)acetate (1). Polymorph screening of 1 under different crystallization conditions revealed three polymorphs, Form I (needle), Form II (block), and Form III (polycrystalline material). Forms I and II are the outcome of solution crystallization, whereas Form III was produced from the melt crystallization of Forms I and II. DSC, HSM, and powder and single-crystal XRD studies indicate the conversion of Form I and Form III crystals to Form II crystals on thermal stimuli. The photoluminescence studies revealed cyan, yellow, and yellowish-green fluorescence emission for Forms I, II, and III crystals, respectively. The difference in photoluminescence could be due to the variance in aggregation modes like H-aggregation in Form I and J-aggregation in Form II crystals. Form I, Form II, and Form III crystals also showed irreversible thermal fluorescent switching from cyan-yellow-green due to polymorphic phase transitions. The study correlates the direct observation of the modulation of the excited-state transition under thermal stimuli in the crystalline phase. It will help augment the pace in the research of thermally responsive fluorescent materials.</p>
1 aMali, Bhupendra, P.1 aDash, Soumya, Ranjan1 aBiswas, Anupam1 aVanka, Kumar1 aManoj, Kochunnoonny1 aGonnade, Rajesh, G.  uhttp://library.ncl.res.in/content/polymorphs-green-fluorescence-protein-chromophore-analogue-fluorescence-switching-thermal02229nas a2200193   4500008004100000022001400041245009700055210006900152260000900221300001600230490000600246520156000252100002101812700002501833700001801858700001801876700001701894856012401911       2022                        eng d  a2470-134300aPredicting the redox potentials of phenazine derivatives using DFT-assisted machine learning0 aPredicting the redox potentials of phenazine derivatives using D  cAPR   a11742-117550 v73 a<p>
	This study investigates four machine-learning (ML) models to predict the redox potentials of phenazine derivatives in dimethoxyethane using density functional theory (DFT). A small data set of 151 phenazine derivatives having only one type of functional group per molecule (20 unique groups) was used for the training. Prediction accuracy was improved by a combined strategy of feature selection and hyperparameter optimization, using the external validation set. Models were evaluated on the external test set containing new functional groups and diverse molecular structures. High prediction accuracies of R2 &gt; 0.74 were obtained on the external test set. Despite being trained on the molecules with a single type of functional group, models were able to predict the redox potentials of derivatives containing multiple and different types of functional groups with good accuracies (R2 &gt; 0.7). This type of performance for predicting redox potential from such a small and simple data set of phenazine derivatives has never been reported before. Redox flow batteries (RFBs) are emerging as promising candidates for energy storage systems. However, new green and efficient materials are required for their widespread usage. We believe that the hybrid DFT-ML approach demonstrated in this report would help in accelerating the virtual screening of phenazine derivatives, thus saving computational and experimental costs. Using this approach, we have identified promising phenazine derivatives for green energy storage systems such as RFBs.</p>
1 aGhule, Siddharth1 aDash, Soumya, Ranjan1 aBagchi, Sayan1 aJoshi, Kavita1 aVanka, Kumar  uhttp://library.ncl.res.in/content/predicting-redox-potentials-phenazine-derivatives-using-dft-assisted-machine-learning