Preparation and electrochemical characterization of lithium cobalt oxide nanoparticles by modified sol-gel method - Khomane, Ramdas B.; Agrawal, Amit C.; Kulkarni, B. D.; Gopukumar, S.; Sivashanmugam, A. (Materials Research Bulletin, 2008)
Uniformly distributed nanoparticles of LiCoO2 have been synthesized through the simple sol-gel method in presence of neutral surfactant (Tween-80). The powders were characterized by X-ray diffractometry, transmission electron microscopy and electrochemical method including charge-discharge cycling performance. The powder calcined at a temperature of 900 degrees C for 5 h shows pure phase layered LiCoO2. The results show that the particle size is reduced in presence of surfactant as compared to normal sol-gel method. Also, the sample prepared in presence of surfactant and calcined at 900 degrees C for 5 h shows the highest initial discharge capacity (106 mAh g(-1)) with good cycling stability as compared to the sample prepared without surfactant which shows the specific discharge capacity of 50 mAh g(-1). (C) 2007 Elsevier Ltd. All rights reserved.
Keywords: Electrochemical properties; intercalation reactions; Layered compounds; Sol-gel chemistry; X-ray diffraction

Pharmacokinetic modeling of caco-2 cell permeability using genetic programming (GP) method - Vyas, Renu; Goel, Purva; Karthikeyan, Muthukumarasamy; Tambe, S. S.; Kulkarni, B. D. (Letters in Drug Design & Discovery, 2014)
An accurate prediction of the pharmacokinetic properties of orally administered drugs is of paramount importance in pharmaceutical industry. Caco-2 cell permeability is a well established parameter for assessing the drug absorption profiles of lead molecules. Due to the restrictions on animal testing, prohibitive in situ models and ethical issues, the development of predictive models is essential. Genetic programming (GP) is an artificial intelligence (AI)-based exclusively data driven modeling paradigm. Given an example input-output data, it searches and optimizes, both the structure and parameters of a well fitting linear/non-linear input-output model. Despite this novelty, GP has not been widely exploited in drug design. Accordingly, in this study we propose a GP based approach for the in silico prediction of Caco-2 cell permeability using a diverse set of molecules. The predictions yielded a high magnitude for the training and test set correlation coefficient with low RMSE, indicating accurate Caco-2 permeability prediction and generalization performance by the GP model. The predictions were better or comparable to artificial neural networks (ANN) and support vector regression (SVR) methods. The GP based modeling approach illustrated will find diverse applications in (QSAR, QSPR and QSTR) modeling for the virtual screening of large libraries.
Keywords: ADME modeling; Caco-2 cell permeability; genetic programming; MLP; SVR

Process of fruit peel waste biorefinery: a case study of citrus waste biorefinery, its environmental impacts and recommendations - Joglekar S.N.; Pathak, P. D.; Mandavgane, S. A.; Kulkarni, B. D. (Environmental Science and Pollution Research, 2019)
Fruit peels are a rich source of cellulose, hemicellulose, phenolic compounds, and terpenic compounds. Thus, they have the potential to be a novel renewable, sustainable, and low-cost raw material (source) for the production of several value-added products based on framework and concepts such as waste hierarchy that includes biofertilizers, dietary fiber, animal feed, industrial enzymes, substrate for the bioactive compounds production, synthesis of nanomaterials, and clean energy (from residual biomass). With a view of evaluating the environmental burden of biorefinery, a life cycle assessment (LCA) is performed for a representative citrus waste (CW) biorefinery. The functional unit used for LCA was set as 2500 kg of CW processed. The overall GWP was observed to be 937.3 kg CO2 equivalent per 2500 kg of CW processed. On further analysis of the environmental impact, it was found that different steps contributed significantly, as shown by the various environmental indicator values. Alternative advanced process intensification technologies like microwave and ultrasound-assisted steps replacing the conventional steps when implemented show considerable reduction in environmental indicator values. The variations in the contribution to environmental indicators should be considered during the design and process selection of biorefineries.