@article {44242,
	title = {pH dependent sophorolipid assemblies and their influence on gelation of silk fibroin protein},
	journal = {Materials Chemistry and Physics},
	volume = {203},
	year = {2018},
	month = {JAN },
	pages = {9-16},
	type = {Article},
	abstract = {<p>Sophorolipid (SL), a bio-derived surfactant is an excellent gelling agent for natural fibrous protein, silk fibroin (SF) leading to potential biomedical applications. Interaction of SF with SL has been shown to accelerate the formation of hydrogel with the rate being dependent on the form of SL used. Here, we examine the effect of pH on SL-SF interaction and gel formation by employing rheology, fluorescence spectroscopy, SANS and NMR. The results indicate that the size of SL assemblies decrease as pH increases from acidic to alkaline and significantly impacts the association of SL and SF. The association of SF and SL is mainly via hydrophobic interactions, with the SL molecules forming bead like structures along the SF chain. The increased charge on the acidic form of SL at higher pH results in greater repulsion between acidic SL molecules, which are bound to the hydrophobic sites of SF, leading to rapid chain unfolding and subsequent gelation. (C) 2017 Elsevier B.V. All rights reserved.</p>},
	keywords = {Assemblies, Nuclear magnetic resonance spectroscopy, pH, Silk fibroin, Small angle neutron scattering, Sophorolipid},
	issn = {0254-0584},
	doi = {10.1016/j.matchemphys.2017.09.045},
	author = {Dubey, Parul and Kumar, Sugam and Ravindranathan, Sapna and Vasudevan, Sahana and Aswal, Vinod K. and Rajamohanan, Pattuparambil R. and Nisal, Anuya and Prabhune, Asmita}
}
@article {46666,
	title = {Polymer nanorings with uranium specific clefts for selective recovery of uranium from acidic effluents via reductive adsorption},
	journal = {ACS Sensors},
	volume = {5},
	year = {2020},
	month = {OCT},
	pages = {3254-3263},
	type = {Article},
	abstract = {<p>Nanostructured polymeric materials, functionalized with an appropriate receptor, have opened up newer possibilities for designing a reagent that shows analyte-specific recognition and efficient scavenging of an analyte that has either a detrimental influence on human physiology and environment or on its recovery for further value addition. Higher active surface area, morphological diversity, synthetic tunability for desired surface functionalization, and the ease of regeneration of a nanostructured material for further use have provided such materials with a distinct edge over conventional reagents. The use of a biodegradable polymeric backbone has an added significance owing to the recent concern over the impact of polymers on the environment. Functionalization of biodegradable sodium alginate with AENA (6.85\% grafting) as the receptor functionality led to a unique open framework nanoring (NNRG) morphology with a favorable spatial orientation for specific recognition and efficient binding to uranyl ions (U) in an aqueous medium over a varied pH range. Nanoring morphology was confirmed by transmission electron microscopy and atomic force microscopy images. The nanoscale design maximizes the surface area for the molecular scavenger. A combination of all these features along with the reversible binding phenomenon has made NNRG a superior reagent for specific, efficient uptake of UO22+ species from an acidic (pH 3-4) solution and compares better than all existing UO22+-scavengers reported till date. This could be utilized for the recovery of uranyl species from a synthetic acidic effluent of the nuclear power. The results of the U uptake experiments reveal a maximum adsorption capacity of 268 mg of U per g of NNRG in a synthetic nuclear effluent. X-ray photoelectron spectroscopy studies revealed a reductive complexation process and stabilization of U(IV)-species in adsorbed uranium species (U@NNRG).</p>
},
	keywords = {biodegradable polymeric backbone, molecular recognition, nanostructured material, sodium alginate, uranium, uranyl-specific receptor},
	issn = {2379-3694},
	doi = {10.1021/acssensors.0c01684},
	author = {Kushwaha, Shilpi and Mane, Manoj and Ravindranathan, Sapna and Das, Amitava}
}
