02576nas a2200277 4500008004100000022001400041245008200055210006900137260009900206300001200305490000700317520157600324653003001900653003201930653003601962100002401998700001802022700002202040700001902062700001602081700002202097700002002119700002302139700002602162856011002188 2007 eng d a0016-236100aEstimation of gross calorific value of coals using artificial neural networks0 aEstimation of gross calorific value of coals using artificial ne aTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLANDbELSEVIER SCI LTDcFEB a334-3440 v863 a

The gross calorific value (GCV) is an important property defining the energy content and thereby efficiency of fuels, such as coals. There exist a number of correlations for estimating the GCV of a coal sample based upon its proximate and/or ultimate analyses. These correlations are mainly linear in character although there are indications that the relationship between the GCV and a few constituents of the proximate and ultimate analyses could be nonlinear. Accordingly, in this paper a total of seven nonlinear models have been developed using the artificial neural networks (ANN) methodology for the estimation of GCV with a special focus on Indian coals. The comprehensive ANN model developed here uses all the major constituents of the proximate and ultimate analyses as inputs while the remaining six sub-models use different combinations of the constituents of the stated analyses. It has been found that the GCV prediction accuracy of all the models is excellent with the comprehensive model being the most accurate GCV predictor. Also, the performance of the ANN models has been found to be consistently better than that of their linear counterparts. Additionally, a sensitivity analysis of the comprehensive ANN model has been performed to identify the important model inputs, which significantly affect the GCV. The ANN-based modeling approach illustrated in this paper is sufficiently general and thus can be gainfully extended for estimating the GCV of a wide spectrum of solid, liquid and gaseous fuels. (c) 2006 Elsevier Ltd. All rights reserved.

10aArtificial neural network10agross calorific value (GCV)10aproximate and ultimate analyses1 aPatel, Shagufta, U.1 aKumar, Jeevan1 aBadhe, Yogesh, P.1 aSharma, B., K.1 aSaha, Sujan1 aBiswas, Subhasish1 aChaudhury, Asim1 aTambe, Sanjeev, S.1 aKulkarni, Bhaskar, D. uhttp://library.ncl.res.in/content/estimation-gross-calorific-value-coals-using-artificial-neural-networks01975nas a2200253 4500008004100000022001400041245013800055210006900193260008000262300001200342490000700354520098200361653001201343653002401355653003001379653003301409653002901442100002801471700002401499700002201523700002101545700002601566856012901592 2009 eng d a1367-543500aEnhanced production of amidase from Rhodococcus erythropolis MTCC 1526 by medium optimisation using a statistical experimental design0 aEnhanced production of amidase from Rhodococcus erythropolis MTC aTIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANYbSPRINGER HEIDELBERGcMAY a671-6780 v363 a

In the present work, statistical experimental methodology was used to enhance the production of amidase from Rhodococcus erythropolis MTCC 1526. R. erythropolis MTCC 1526 was selected through screening of seven strains of Rhodococcus species. The Placket-Burman screening experiments suggested that sorbitol as carbon source, yeast extract and meat peptone as nitrogen sources, and acetamide as amidase inducer are the most influential media components. The concentrations of these four media components were optimised using a face-centred design of response surface methodology (RSM). The optimum medium composition for amidase production was found to contain sorbitol (5 g/L), yeast extract (4 g/L), meat peptone (2.5 g/L), and acetamide (12.25 mM). Amidase activities before and after optimisation were 157.85 units/g dry cells and 1,086.57 units/g dry cells, respectively. Thus, use of RSM increased production of amidase from R. erythropolis MTCC 1526 by 6.88-fold.

10aAmidase10aMedium optimisation10aPlackett-Burman screening10aResponse surface methodology10aRhodococcus erythropolis1 aVaidya, Bhalchandra, K.1 aMutalik, Snehal, R.1 aJoshi, Renuka, M.1 aNene, Sanjay, N.1 aKulkarni, Bhaskar, D. uhttp://library.ncl.res.in/content/enhanced-production-amidase-rhodococcus-erythropolis-mtcc-1526-medium-optimisation-using-001617nas a2200229 4500008004100000022001400041245006800055210006800123260009900191300001200290490000800302520081600310653004201126653000801168653000901176653001101185653000801196100003201204700002101236700002601257856010401283 2012 eng d a0960-852400aEfficient lipase purification using reverse micellar extraction0 aEfficient lipase purification using reverse micellar extraction aTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLANDbELSEVIER SCI LTDcMAR a224-2300 v1083 a

Reverse micellar extraction (RME) of enzyme provides an attractive option for conventional method with the potential to achieve purification and concentration in a single step with high yield. This study presents a methodology for optimization of RME with Pseudomonas lipase as model system. Fold-purification, percent recovery and extraction time were the objective functions while the type and concentration of surfactant, contact time, pH, ionic strength, and the ratio of organic to aqueous phase were the decision variables. Under optimized conditions, the AOT (Aerosol OT (bis 2-ethylhexyl) sodium sulfosuccinate)-isooctane system gave a 15-fold purification, 80% recovery and 2.5-fold concentration of the Pseudomonas lipase with process time of 45 min. (C) 2011 Elsevier Ltd. All rights reserved.

10a(Hexadicetyltrimethylammoniumbromide)10aAOT10aCTAB10aLipase10aRME1 aGaikaiwari, Raghavendra, P.1 aWagh, Shilpa, A.1 aKulkarni, Bhaskar, D. uhttp://library.ncl.res.in/content/efficient-lipase-purification-using-reverse-micellar-extraction-002241nas a2200205 4500008004100000022001400041245006900055210006900124260007300193300001200266490000700278520151900285653000901804653003201813653001201845100003201857700002101889700002601910856009901936 2012 eng d a1383-586600aExtraction and purification of tannase by reverse micelle system0 aExtraction and purification of tannase by reverse micelle system aPO BOX 211, 1000 AE AMSTERDAM, NETHERLANDSbELSEVIER SCIENCE BVcMAR a288-2960 v893 a

Tannin acyl hydrolase commonly called as tannase (EC 3.1.1.20) is a commercially important enzyme. Partially purified and concentrated tannase is required for commercial applications. Typical objectives of purification process comprise high fold-purification, recovery and concentration. These objectives may be potentially conflicting. Conventional methods of purification require multiple steps which are time consuming and may cause higher loss. Reverse micellar extraction (RME) using ionic surfactants provides an attractive option for concentration and purification of tannase which is a highly hydrophilic glycoprotein. This study presents an optimized methodology for RME and purification of Aspergillus allahabadi intracellular tannase. Fold-purification, percent recovery and extraction time were the objective while the type and concentration of surfactant, contact time, pH, ionic strength, and the ratio of organic to aqueous phase were the decision variables. Some of these parameters were also studied for their effect on back-extraction. Among the surfactants tested, CTAB-isooctane system was found to be suitable. Under optimized conditions, 12.7-fold purification, 81.2% recovery and 3-fold concentration of tannase with a process time of 45 min was obtained. Conventional purification methods provided a higher fold-purification albeit at a much lower enzyme recovery. Further, the conventional method requires a process time of several hours. (c) 2012 Elsevier B.V. All rights reserved.

10aCTAB10aReverse micellar extraction10aTannase1 aGaikaiwari, Raghavendra, P.1 aWagh, Shilpa, A.1 aKulkarni, Bhaskar, D. uhttp://library.ncl.res.in/content/extraction-and-purification-tannase-reverse-micelle-system-001819nas a2200181 4500008004100000022001400041245014200055210006900197260007100266300001600337490000700353520106200360100002101422700002001443700002301463700002601486856012501512 2014 eng d a0888-588500aEfficient conversion of cellulose to levulinic acid by hydrothermal treatment using zirconium dioxide as a recyclable solid acid catalyst0 aEfficient conversion of cellulose to levulinic acid by hydrother a1155 16TH ST, NW, WASHINGTON, DC 20036 USAbAMER CHEMICAL SOCcDEC a18796-188050 v533 a

Conversion of cellulose into platform chemicals is essential for sustainable development of the chemical industry. With this aim, single step hydrothermal conversion of cellulose to industrially important levulinic acid using zirconium dioxide as a catalyst has been investigated. A remarkably high yield (53.9 mol %) of levulinic acid with excellent accountability and total conversion of cellulose has been achieved at 180 degrees C reaction temperature and reaction time of 3 h with 2 wt % of catalyst and 2 g of cellulose. The major products identified were levulinic acid (LA), formic acid (FA), 5-hydroxymethylfurfural (5-HMF), furfural, and humins. Formation of humins during cellulose hydrolysis and dehydration was observed and is also confirmed by NMR and FTIR analysis. The effect of various reaction parameters such as temperature, time, substrate concentration, and catalyst loading on conversion and selectivity has been studied. The catalyst has been regenerated and recycled several times without any loss of activity and selectivity.

1 aJoshi, Sunil, S.1 aZodge, Amit, D.1 aPandare, Kiran, V.1 aKulkarni, Bhaskar, D. uhttp://library.ncl.res.in/content/efficient-conversion-cellulose-levulinic-acid-hydrothermal-treatment-using-zirconium-002352nas a2200229 4500008004100000022001400041245006200055210006200117260000800179300001400187490000700201520163500208653002501843653002501868653000801893653002401901100003101925700002201956700002501978700002602003856009302029 2018 eng d a1877-264100aEnvironmental impact study of bagasse valorization routes0 aEnvironmental impact study of bagasse valorization routes cJAN a2067-20780 v103 aIndia is the world’s second largest sugarcane producer and a major manufacturer of molasses-derived ethanol. The sugarcane produced is widely used in the production of sugar and 1G ethanol. Though sugar and 1G ethanol are the major concerns, there is still a huge amount of bagasse waste generated in the sugar factories. This bagasse has also some end use value, as it can be utilized for production of methanol, 2G ethanol and electricity. Even though the technology for production of these value added products is well established, it is important to analyze the social, economical and environmental impacts associated with these production processes. This work compares the environmental impacts of various sugarcane conversion processes on life cycle basis. The functional unit used is one tonne of sugarcane cultivated in field. Four routes identified for bagasse conversion- conversion of bagasse to methanol (Route 1), conversion of bagasse to ethanol via 2 stage dilute acid process (Route 2), conversion of bagasse to ethanol via enzymatic process (Route 3) and electricity production from bagasse (Route 4). On comparison of these routes on midpoint indicators such as global warming potential (GWP), acidification potential (AP), eutrophication potential (EP) and ozone depletion potential (ODP) and photochemical ozone creation potential (POCP), it is observed that the methanol production is having the highest environmental indicator values. Even though ethanol production processes and cogeneration process are having nearly similar results, it can be said that cogeneration process is the more eco-friendly one.10aBagasse valorization10aEnvironmental impact10aLCA10aMidpoint indicators1 aMandavgane, Sachin, Arvind1 aJoglekar, Saurabh1 aTandulje, Akshay, P.1 aKulkarni, Bhaskar, D. uhttp://library.ncl.res.in/content/environmental-impact-study-bagasse-valorization-routes