Heterogeneous photo-Fenton____ degradation of polyacrylamide

Heterogeneous photo-Fenton____ degradation of polyacrylamide
Heterogeneous photo-Fenton____ degradation of polyacrylamide

Journal of Hazardous Materials 162(2009)860–865

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Journal of Hazardous

Materials

j o u r n a l h o m e p a g e :w w w.e l s e v i e r.c o m /l o c a t e /j h a z m a

t

Heterogeneous photo-Fenton degradation of polyacrylamide in aqueous solution over Fe(III)–SiO 2catalyst

Ting Liu,Hong You ?,Qiwei Chen

Department of Environmental Science and Engineering,Harbin Institute of Technology,P.O.Box 2606,202Haihe Road,Harbin 150090,PR China

a r t i c l e i n f o Article history:

Received 29December 2007

Received in revised form 8April 2008Accepted 22May 2008

Available online 28May 2008Keywords:Photo-Fenton Polyacrylamide

Fe(III)–SiO 2catalyst

Heterogeneous catalysis

a b s t r a c t

This article presents preparation,characterization and evaluation of heterogeneous Fe(III)–SiO 2catalysts for the photo-Fenton degradation of polyacrylamide (PAM)in aqueous solution.Fe(III)–SiO 2catalysts are prepared by impregnation method with two iron salts as precursors,namely Fe(NO 3)3and FeSO 4,and are characterized by Brunauer–Emmett–Teller (BET),X-ray diffraction (XRD)and X-ray photoelectron spectroscopy (XPS)methods.The irradiated Fe(III)–SiO 2is complexed with 1,10-phenanthroline,then is measured by UV–vis-diffuse re?ectance spectroscopy (UV–vis-DRS)and XPS to con?rm the oxidation state of Fe in solid state.By investigating the photo-Fenton degradation of PAM in aqueous solution,the results indicate that Fe(III)–SiO 2catalysts exhibit an excellent photocatalytic activity in the degradation of PAM.Moreover,the precursor species and the OH ?/Fe mole ratio affect the photocatalytic activity of Fe(III)–SiO 2catalysts to a certain extent.Finally,the amount of Fe ions leaching from the Fe(III)–SiO 2catalysts is much low.

?2008Elsevier B.V.All rights reserved.

1.Introduction

“Produced water”is the largest volume of waste generated by the oil industry.In particular,with the application of polymer ?ood-ing technology in tertiary oil recovery processes in China,a kind of new produced water containing polyacrylamide (PAM),a high molecular weight polymer,have been produced.The conventional method to dispose of such produced water is either re-injected into the subsurface for permanent disposal or discharged directly to the marine environment.However,both methods have caused serious contamination to the ground water and surface water.On the other hand,the current physical treatment processes (settling separation and ?ltration)can not satisfy the treatment requirement.Hence,the treatment technologies of produced water containing PAM have become a key problem in oil industry in China.

Physical [1,2],biological [3,4]and chemical methods [5]are presently used for treatment of PAM.It was found that the degrada-tion ratio of PAM in aqueous solution was slow by using biological methods.Recently,some investigators have reported the successful application of advanced oxidation processes for PAM degradation [6,7].One of advanced oxidation processes,Fenton (a powerful source of oxidative HO ?generated from H 2O 2in the presence of Fe 2+ions)or photo-Fenton reaction has been used in the degradation of

?Corresponding author.Tel.:+8645186283118;fax:+8645186283118.E-mail address:youhong@https://www.360docs.net/doc/566119004.html, (H.You).many organic compounds [8,9].Even though these systems are con-sidered as a very effective approach to remove organic compounds,it should be pointed out that there is a major drawback because the post-treatment of Fe sludge is an expensive process.This short-coming can be overcome by using heterogeneous photo-Fenton reaction.Therefore,a lot of effort has been made in developing heterogeneous photo-Fenton catalysts.For example,Parra et al.pre-pared Na?on/Fe structured membrane catalyst and used it in the photo-assisted immobilized Fenton degradation of 4-chorophenol [10].However,Na?on/Fe structured membrane catalyst is much expensive for practical use.Thus,the low cost supports such as the C structured fabric [11,12],activated carbon [13],mesoporous silica SBA-15[14–16],zeolite [17,18]and clay [19–21],have been used for the immobilization of active iron species.Remirez et al.prepared the catalysts using four iron salts as precursors for the heteroge-neous Fenton-like oxidation of Orange II solutions [22].The results showed that the nature of the iron salt had a signi?cant effect on the process performance.So,it is necessary to discuss the photo-catalytic activities of the catalysts by using different iron salts as precursors.

In this paper,a series of Fe(III)–SiO 2catalysts were prepared at different OH ?/Fe mole ratio and by using two iron salts as precur-sors,namely Fe(NO 3)3and FeSO 4.All catalysts were characterized by BET,XRD and XPS.The oxidation state of Fe in the solid state was detected by the UV–vis-DRS and XPS measurement.The pho-tocatalytic activity of Fe(III)–SiO 2catalyst was evaluated in the photo-assisted Fenton degradation of PAM in aqueous solution in

0304-3894/$–see front matter ?2008Elsevier B.V.All rights reserved.doi:10.1016/j.jhazmat.2008.05.110

T.Liu et al./Journal of Hazardous Materials 162(2009)860–865861

the presence of H 2O 2and UV light at an initial solution pH of 6.8.The effects of the precursor species and the OH ?/Fe mole ratio on the photocatalytic activities of Fe(III)–SiO 2catalysts were also stud-ied.In addition,the leaching behavior of Fe from the catalyst surface was discussed.2.Experimental 2.1.Materials

The analytical grade PAM,H 2O 2(30%,w/w),Fe(NO 3)3·9H 2O,FeSO 4·7H 2O,NaOH and 1,10-phenanthroline were used for this experiment without further puri?cation.The average molecular weight of PAM was 5000000Da and degree of hydrolysis of PAM was about 30%.Silica gel (40–60mesh)as a support was purchased from Qingdao Ocean Chemical Company,China.The aqueous solu-tion of PAM was prepared by dissolving a weighed quantity of PAM in distilled water.

2.2.Preparation of the catalysts

A series of catalysts were prepared by two methods as follows:(1)Two catalysts were prepared by impregnation of 20g silica

gel in aqueous solution containing 0.05mol/L Fe(NO 3)3and 0.05mol/L FeSO 4,respectively and kept stirring for 6h.After aging for 40h at 105?C,the samples were separated and washed several times with deionized water,then dried overnight at 80?C.The dried samples were calcined at 500?C for 5h in an oven.Finally,two Fe(III)–SiO 2catalysts were obtained,namely S-Fe 3+and S-Fe 2+.

(2)Twenty grams of silica gel carrier were ?rst added into the aque-ous solution containing 0.05mol/L Fe(NO 3)3and 0.05mol/L FeSO 4,respectively and kept under vigorous stirring for 2h.Then,NaOH aqueous solution with different concentration was added drop by drop under stirring until the OH ?/Fe 3+or OH ?/Fe 2+mole ratio was equal to 1and 2.After aging for 40h at 105?C,the solid product were separated and washed several times with deionized water and dried overnight at 80?C.The dried samples were calcined at 500?C for 5h in an oven and the catalysts were named as S-Fe 3+/1,S-Fe 3+/2,S-Fe 2+/1and S-Fe 2+/2,respectively.2.3.Characterization of the catalysts

The iron content of Fe(III)–SiO 2catalysts were veri?ed by an inductively coupled plasma (ICP)(Model:Perkin-Elmer 5300DV)after acidic digestion of the catalysts.

Brunauer–Emmett–Teller (BET)speci?c surface area,total pore volume and average pore size of synthesized Fe(III)–SiO 2catalysts were measured by adsorption of nitrogen at 77K,by using auto-mated volumetric adsorption instrument (model Quantachrome Autosorb-1).

X-ray diffraction (XRD)measurement was employed using a Rigaku D/max-rB system with Cu K ?radiation operating at 45kV and 40mA.The 2?ranged from 10to 90?.

X-ray photo-electron spectroscopy (XPS)measurements were performed using a PHI 5700spectrometer.The X-ray source was operated at 250W and 12.5kV and the C 1s signal was adjusted to 284.62eV as the reference.The curve ?tting was achieved by using a Physical Electronics PC-ACCESSESCA-V6.0E program with a Gaussian–Lorentzian sum function.

Finally,UV–vis-diffuse re?ectance spectroscopy (UV–vis-DRS)measurements were recorded on TU1901with a sphere re?ectance

accessory.

Fig.1.Schematic diagram of three-phase ?uidized bed photoreactor.

2.4.Catalytic activity

The photocatalytic activities of Fe(III)–SiO 2catalysts were evaluated by degradation of PAM from aqueous solutions in a three-phase ?uidized bed photoreactor (Fig.1).The light source was UV lamp (Philips,8W,254nm)?xed inside of a cylindrical quartz tube.The total volume of PAM aqueous solution was 1500mL.In order to ensure a good dispersion of Fe(III)–SiO 2catalysts and good mix-ture in solution,compressed air was bubbled from the bottom at a ?ow rate of 3.3L/min.For each experiment,the concentration of PAM and H 2O 2were 100and 200mg/L,respectively.The cata-lyst loading was ?xed at 1.0g/L.The Fe(III)–SiO 2catalyst and H 2O 2were added into the photoreactor,at the same time,UV light was turned on and this was considered as the initial time for reaction.Then,samples were withdrawn at time intervals.The concentration of PAM in solution was measured by starch-CdI 2spectrophotom-etry [23].To determine mineralization of PAM solution,the total organic carbon (TOC)of the reaction solution was measured by a TOC-V CPN Shimadzu TOC analyzer.In addition,the concentration of Fe in reaction solution was monitored by ICP.2.5.Characterization of Fe(III)–SiO 2after the reaction

In order to know the oxidation state of Fe on Fe(III)–SiO 2catalyst surface under irradiation,the 1,10-phenanthroline was used which would be complexed with Fe(II)–SiO 2in solid state [17].0.03%1,10-phenanthroline and 0.6mol/L acetate buffer (pH 8.60)was added into the photoreactor and the S-Fe 2+/1catalyst was irradiated for 2h.After reaction,the sample was ?ltered,washed several times and dried,then characterized by UV–vis-DRS and XPS measure-ment.

3.Results and discussion

3.1.Characterization of the catalysts before reaction

The content of Fe in Fe(III)–SiO 2catalysts is shown in Table 1.It is observed that the Fe content in catalysts increases with the increase of OH ?/Fe mole ratio in both Fe(NO 3)3and FeSO 4used as precursor.It should be mentioned that,with the increase of OH ?/Fe mole ratio,the structure of iron species in the solution develops from the low-molecular-weight species into high polymerization degree cationic polymer [24].Therefore,with the increase of OH ?/Fe mole ratio,

862T.Liu et al./Journal of Hazardous Materials 162(2009)860–865

Table 1

The content of Fe in catalysts and the results of BET tests Samples The content of Fe (wt.%)BET surface area (m 2/g)Total pore

volume (cm 3/g)Average pore

width (?A)SiO 20

419.00.9388.9969

S-Fe 3+0.404446.00.9988.7406S-Fe 3+/10.496462.0 1.0288.4524S-Fe 3+/20.684470.0 1.0488.2624S-Fe 2+0.184442.60.9888.6380S-Fe 2+/10.534411.80.9996.5204S-Fe 2+/2

0.976

314.9

1.07

135.8424

the polymerization degree of iron which was absorbed on SiO 2car-rier increased.It indicates that increasing OH ?concentration can improve the loading of Fe in Fe(III)–SiO 2catalyst.

The BET surface area,total pore volume and average pore width of the investigated Fe(III)–SiO 2catalysts are also listed in Table 1.The surface area of S-Fe 3+and S-Fe 2+catalysts were 446.0and 442.6m 2/g,respectively,higher than the SiO 2carrier.When using Fe(NO 3)3as precursor,with the increase of OH ?/Fe mole ratio,the surface area and total pore volume of catalysts increased and the average pore width of catalysts changed a little.On the contrary,when using FeSO 4as precursor,with the increase of OH ?/Fe mole ratio,the surface area of catalysts reduced,while the total pore vol-ume of catalysts and the average pore width of catalysts increased.The results show that the pore structure of Fe(III)–SiO 2catalysts prepared by the second method are affected remarkably by the precursor species and the OH ?/Fe mole ratio.

The XRD patterns of S-Fe 3+,S-Fe 3+/2,S-Fe 2+and S-Fe 2+/2cata-lysts are illustrated in Fig.2.The pattern showed a typical broad peak,which indicated that silica gel used as a support was a pure amorphous structure.On the other hand,the XRD patterns did not show iron oxides peaks,even for catalyst with 6.2wt.%of iron (not shown in the ?gure).It may be proposed that the XRD techniques are not sensitive enough to detect little iron oxides because the higher background of XRD measurement caused by amorphous SiO 2.

The oxidation state of Fe on the surface of catalysts was charac-terized by XPS and the results are presented in Fig.3.The binding energy of Fe 2p 3/2was determined to be 710.945eV,710.595eV and 710.975eV for S-Fe 3+,S-Fe 3+/1and S-Fe 3+/2catalyst,respectively,

which was ascribable to Fe 2O 3[25].

When FeSO 4was used as the precursor,the Fe 2p 3/2peak was found at 711.195eV,711.345eV and 711.850eV for S-Fe 2+,S-Fe 2+/1and S-Fe 2+/2catalyst,respectively,strongly suggesting that the iron on the catalysts was Fe(III)[21].When FeSO 4was used as precursor,the binding energy of Fe 2p 3/2

Fig.2.XRD patterns of the Fe(III)–SiO 2catalysts.Fig.3.XPS spectra of the Fe 2p region for the Fe(III)–SiO 2catalysts.

in catalysts were higher than that of catalysts prepared by Fe(NO 3)3.It was dif?cult to give an adequate explanation of increasing in the binding energy of Fe 2p 3/2yet.O 1s survey scan further indicated the oxygen status on the catalyst surface.As shown in Fig.4,the O 1s region can be ?tted into four peaks,which are attributed to the chemisorbed oxygen,the lattice oxygen of SiO 2,the lattice oxygen of Fe 2O 3and the chemically or physically adsorbed water.Accord-ing to the reports [26,27],the chemisorbed oxygen can take an active part in the oxidation process and greatly improve the cat-alyst activity.It can be seen from Table 2that the percentage of chemisorbed oxygen of catalyst was improved when FeSO 4was used as precursor and the S-Fe 2+/1catalyst had the highest per-centage of chemisorbed oxygen.

3.2.Characterization of the catalysts after the reaction

The catalyst was characterized by UV–vis-DRS and XPS to con?rm the formation of Fe(II)–SiO 2when Fe(III)–SiO 2was irradi-ated by photon.The UV–vis diffuse re?ectance absorption spectra of Fe(III)–SiO 2catalyst before and after reaction are shown in Fig.5.The results clearly shows a new broad absorption band at 505–525nm after irradiation which is characteristic band of [Fe(1,10-phenanthroline)]2+complex [17].It is accounted for that the Fe(III)–SiO 2on irradiation with photon is

converted into Fe(II)–SiO 2that would be complexed with 1,10-phenanthroline in solid state.The binding energy of Fe 2p for the catalyst before and after reaction is shown in Fig.6.It is observed that the binding energy of Fe 2p 3/2is slightly shifted to lower BE value from 711.345to 710.600eV after irradiation,which is due to the reduction of Fe(III)–SiO 2to Fe(II)–SiO 2during the irradiation.

Fig.4.O 1s curve ?tting of S-Fe 2+/1catalyst.

T.Liu et al./Journal of Hazardous Materials 162(2009)860–865

863

Table 2

XPS data of O element on the surface of the catalysts Catalysts

Binding energy (eV)Percentage of O ad or O L (%)

O ad a

O L b (SiO 2)O L b (Fe 2O 3)O L c (H 2O)O ad O L (SiO 2)O L (Fe 2O 3)O L (H 2O)S-Fe 3+531.80532.80529.79533.8926.9448.52 2.9521.59S-Fe 3+/1531.80532.80529.99533.8924.1644.39 3.5727.87S-Fe 3+/2531.80532.84529.79533.8927.7344.597.4820.2S-Fe 2+531.80532.80529.79533.8931.3942.28 4.3621.98S-Fe 2+/1531.81532.87529.79533.7938.4634.537.6019.41S-Fe 2+/2

531.89

532.80

529.99

533.70

32.22

30.07

11.93

25.79

a The chemisorbed oxygen.

b The latter oxygen.

c

The chemically or physically adsorbed water.

Fig.5.UV–vis diffuse re?ectance spectra of S-Fe 2+/1catalyst:(a)Fe(III)–SiO 2and (b)Fe(II)–(1,10-phenanthroline)–SiO 2sample.

3.3.Degradation and mineralization of PAM by heterogeneous photo-Fenton processes

The degradation of 100mg/L PAM in aqueous solutions under different conditions was preformed by using S-Fe 2+/1as a photo-Fenton catalyst at an initial solution pH of 6.8,and the

results are shown in Fig.7.In the presence of UV lamp,about 5%degradation of PAM in aqueous solution was observed,indicating that the degra-dation of PAM caused by direct photolysis is very limited.In the presence of 1.0g/L S-Fe 2+/1catalyst,the removal of PAM was less than 5%,which was caused by the adsorption of PAM on the catalyst.With 1.0g/L S-Fe 2+/1catalyst and 200mg/L H 2O 2in dark,the degra-dation of PAM was low,implying that the PAM degradation in the course of heterogeneous Fenton reaction is limited in neutral cir-cumstance.In the presence of UV and 200mg/L H 2O 2without any

Fig.6.XPS spectra of the Fe 2p region for the S-Fe 2+

/1catalyst:(a)Fe(III)–SiO 2and (b)Fe(II)–(1,10-phenanthroline)–SiO 2sample.

catalyst,the concentration of PAM decreased signi?cantly.It is due to the oxidation of PAM by ?OH radicals formed direct photolysis of H 2O 2.In the presence of 1.0g/L S-Fe 2+/1catalyst,UV and 200mg/L H 2O 2,the concentration of PAM decreased rapidly and about 94%PAM degradation in 90min.As the leaching of Fe from Fe(III)–SiO 2catalyst was negligible (described as follows),the degradation of PAM in aqueous solutions was almost caused by the heterogeneous photo-Fenton reaction,indicating that S-Fe 2+/1catalyst exhibits a good photocatalytic activity in PAM degradation.It is assumed that Fe(III)species on the surface of catalysts transform to Fe(II)species under irradiation of UV light,then,the Fe(II)species generate ?OH radicals by the decomposition of H 2O 2[28,29].At the same time,the UV light irradiates hydrogen peroxide to produce the ?OH radicals.Finally,PAM is oxidized by ?OH radicals.Therefore,the mechanism for the photo-Fenton degradation of PAM using Fe(III)–SiO 2catalyst as a heterogeneous catalyst is proposed below:H 2O 2+h →2?OH

(1)Fe(III)?X +H 2O +h →Fe(II)?X +?OH +H +(2)Fe(II)?X +H 2O 2→Fe(III)?X +OH ?+?OH (3)PAM +?

OH →Intermediates →CO 2+H 2O

(4)

where X represents the surface of Fe(III)–SiO 2catalyst.

The mineralization process of PAM aqueous solutions under dif-ferent conditions was measured and the results are shown in Fig.8.Only with 8W UV,there was almost no mineralization of PAM.In the present of 1.0g/L S-Fe 2+/1catalyst and 200mg/L H 2O 2in dark,about 20%TOC of PAM was removed after 180min,indicating that the mineralization of PAM by heterogeneous Fenton reaction is limited in neutral circumstance.In the presence of 8W UV and 200mg/L H 2O 2,the mineralization of PAM is signi?cant,about 40%

Fig.7.Degradation of PAM under different conditions:(a)1g/L S-Fe 2+/1catalyst,(b)8W UV,(c)1g/L S-Fe 2+/1catalyst +200mg/L H 2O 2,(d)8W UV +200mg/L H 2O 2and (e)8W UV +200mg/L H 2O 2+1g/L S-Fe 2+/1catalyst.

864T.Liu et al./Journal of Hazardous Materials 162(2009)

860–865

Fig.8.Mineralization of PAM under different conditions:(a)8W UV,(b)1g/L S-Fe 2+/1catalyst +200mg/L H 2O 2,(c)8W UV +200mg/L H 2O 2and (d)8W UV +200mg/L H 2O 2+1g/L S-Fe 2+/1catalyst.

TOC of PAM was removed after 180min.With the present 1.0g/L S-Fe 2+/1catalyst,8W UV and 200mg/L H 2O 2,the mineralization of PAM was signi?cantly accelerated.After 180min,about 70%TOC of PAM was removed,suggesting that the S-Fe 2+/1catalyst show a signi?cant photocatalytic activity for the mineralization of PAM.3.4.Effects of the precursor species and the OH ?/Fe mole ratio on the PAM degradation

To check the photocatalytic activity of catalysts prepared by different methods,degradation of PAM in aqueous solutions by Fe(III)–SiO 2catalysts was evaluated and the results are presented in Fig.9.It was observed that the catalysts prepared with two pre-cursor species and different OH ?/Fe mole ratio showed different photocatalytic activity.At the same OH ?/Fe mole ratio,catalysts prepared with FeSO 4shown a higher photocatalytic activity than Fe(NO 3)3.The most effective catalyst seems to be that prepared with FeSO 4and the OH ?/Fe mole ratio at 1.By using S-Fe 2+/1cata-lyst,98.6%of degradation was obtained after 120min.In contrast,S-Fe 3+/1catalyst gave rise to the less photocatalytic activity,which produced an ef?ciency degradation of 89.7%.The different photo-catalytic activity was observed when two precursors are used.The results are not clear,and it will be the aim of further work (iron oxidation state effect).

3.5.Fe leaching from Fe(III)–SiO 2catalysts

In addition to having a high photocatalytic activity,stability is another important factor for a catalyst prepared.The

concentra-

Fig.9.Degradation of PAM by using different Fe(III)–SiO 2

catalysts.

Fig.10.Fe concentration in solution by using different Fe(III)–SiO 2catalysts.

tion of Fe ions in solution with different catalysts was examined by ICP and the results are shown in Fig.10.It can be seen that there is no signi?cant difference in the patterns of the curves.The concentration of Fe ions increased as reaction time increased,and reached a peak value,then followed by a decrease.The same phe-nomenon has been reported by Feng et al.[30],but the reason is still not clear.At the same OH ?/Fe mole ratio,the Fe leaching from the catalysts prepared by Fe(NO 3)3was usually lower than the catalysts prepared by FeSO 4.The maximum concentration of Fe among all the catalysts was 0.17mg/L,suggesting that the Fe leach-ing from the Fe(III)–SiO 2catalysts is negligible,and the degradation of PAM aqueous solutions are almost caused by the heterogeneous photo-Fenton reaction in neutral circumstance.After 120min of the reaction,the percentage of Fe leached from the S-Fe 2+/1catalyst is only about 0.62%,the results also suggest that the catalysts have a long-term stability.4.Conclusions

Fe(III)–SiO 2catalysts have been synthesized by two methods with Fe(NO 3)3and FeSO 4as precursors,and were characterized by the BET,XRD and XPS method.The percentage of chemisorbed oxygen on the surface of catalysts prepared by FeSO 4is higher than that prepared by Fe(NO 3)3.The results con?rm the formation of Fe(II)–SiO 2when Fe(III)–SiO 2was irradiated by photon.

The photocatalytic activities of Fe(III)–SiO 2catalysts were eval-uated by the degradation of PAM from aqueous solution in the photo-Fenton reaction and all the catalysts exhibited a better photocatalytic activities.However,the precursor species and the OH ?/Fe mole ratio have in?uence on the photocatalytic activi-ties of the catalysts.At the same OH ?/Fe mole ratio,the catalysts could present the better photocatalytic activities when using FeSO 4as precursor.The best ef?ciency for the degradation of PAM in heterogeneous photo-Fenton reaction was 94%degrada-tion in 90min and 70%TOC removal in 180min at an initial pH of 6.8.

Finally,it was observed that Fe leaching from Fe(III)–SiO 2cata-lysts was negligible,indicating that the catalysts have a long-term stability and the degradation of PAM from aqueous solution are almost caused by the heterogeneous photo-Fenton reaction.Acknowledgments

The authors gratefully acknowledge the ?nancial supports from the National Basis Research Foundation of China (973Program,No.2004CB418505)and the Research Foundation of Harbin Institute of Technology (No.HIT.MD 2003.02).

T.Liu et al./Journal of Hazardous Materials162(2009)860–865865

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BS_EN_ISO_10582_2012[1] (Heterogeneous PVC)

24February2012 CSO COPYRIGHT INFORMATION Dear Committee Member, Thank you for your valuable contributions in the preparation of this British Standards publication. Please find attached an electronic copy, retain one copy for yourself and kindly provide your nominating organization with a hard copy or an electronic copy. Please note that you are not permitted to share this document within your place of employment unless that is your nominating organization. Dear Nominating Organization, We would like to take this opportunity of thanking you for nominating a representative to participate in the development of this British Standards publication. With regard to the electronic copy emailed to you, we request that you note the following:·the document has been sent to you for the sole purpose of reproducing a hard copy version to be used internally by your members, ·only one copy must be made, ·where a hard copy is not reproduced, the document may be viewed from one system e.g. a computer but must not be transferred or held on more than one system, ·the document may not be transferred internally or externally in any way, ·the document may not be uploaded to the organization’s website nor on its internal network-to share the document within the organization please contact the BSI Multi-User Licensing Department at cservices@https://www.360docs.net/doc/566119004.html, or by calling 020 8996 7071. In relation to the reproduced hard copy kindly note that: ·the document must not be copied, ·you may place the hard copy standard in your library for reference purposes only. For any reproduction of the publication (electronic or hard copy), for instance use of extracts, you should contact the BSI Licensing Department at copyright@https://www.360docs.net/doc/566119004.html, or by calling 0208996 7070. BSI reserves the right to permit only certain standards for uploading on internal networks, the BSI Multi-User Licensing department will advise if the current standard may be uploaded. Yours Sincerely, Deborah Stead Head of Committee Services and International Secretariat

1980Phenomenological model of shock initiation in heterogeneous explosives

Phenomenological model of shock initiation in heterogeneous explosives E. L. Lee and C. M. Tarver Citation: Phys. Fluids 23, 2362 (1980); doi: 10.1063/1.862940 View online: https://www.360docs.net/doc/566119004.html,/10.1063/1.862940 View Table of Contents: https://www.360docs.net/doc/566119004.html,/resource/1/PFLDAS/v23/i12 Published by the American Institute of Physics. Related Articles Thermal imaging of nickel-aluminum and aluminum-polytetrafluoroethylene impact initiated combustion J. Appl. Phys. 112, 084911 (2012) Two-dimensional direct numerical simulation evaluation of the flame-surface density model for flames developing from an ignition kernel in lean methane/air mixtures under engine conditions Phys. Fluids 24, 105108 (2012) Experimental and theoretical studies of the O(3P) + C2H4 reaction dynamics: Collision energy dependence of branching ratios and extent of intersystem crossing J. Chem. Phys. 137, 22A532 (2012) Effect of soot microstructure on its ozonization reactivity J. Chem. Phys. 137, 084507 (2012) High-resolution spectroscopy for Doppler-broadening ion temperature measurements of implosions at the National Ignition Facility Rev. Sci. Instrum. 83, 10E127 (2012) Additional information on Phys. Fluids Journal Homepage: https://www.360docs.net/doc/566119004.html,/ Journal Information: https://www.360docs.net/doc/566119004.html,/about/about_the_journal Top downloads: https://www.360docs.net/doc/566119004.html,/features/most_downloaded Information for Authors: https://www.360docs.net/doc/566119004.html,/authors Downloaded 06 Dec 2012 to 211.68.3.254. Redistribution subject to AIP license or copyright; see https://www.360docs.net/doc/566119004.html,/about/rights_and_permissions

Demo Abstract Cascades An Extensible Heterogeneous Sensor Networking Framework

Demo Abstract: Cascades: An Extensible Heterogeneous Sensor Networking Framework Phillip Sitbon, Nirupama Bulusu, Wu-Chi Feng Portland State University {sitbon, nbulusu, wuchi}@https://www.360docs.net/doc/566119004.html, ABSTRACT This demonstration shows a powerful high-level, heterogeneous sensor networking framework, Cascades. We intend to demonstrate how, with this framework, application designers have great control over implementation designs without the requirement of in-depth development. Several key components and example applications will be demonstrated, along with some important concepts used in this Python-based framework. The emphasis will be on video sensing and application control in heterogeneous sensor networks consisting of Crossbow Stargate (PC-class) and MicaZ (mote-class) devices. Categories and Subject Descriptors D.0 [Software]: General. J.0 [Computer Applications]: General. General Terms Management, Design. Keywords Frameworks, Heterogeneous Sensor Networking 1.CASCADES OVERVIEW Heterogeneous, or hybrid, sensor networks are becoming more common for the purpose of easing constraints on homogeneous sensor networks while increasing scalability. More capable devices, such as the Stargate Gateway[2] for example, can be used as fixed and reliable communication, storage and processing points in a sensor network in order to expand its abilities. More capable sensors such as video cameras add ability to high-level sensor network devices, especially in enabling robust event detection. The availability of an extensible and intuitive set of tools and concepts has the potential to fulfill a wide variety of application and system needs in hybrid sensor networks. Some of the key challenges to network organization and management due to increased scale and heterogeneity include deployability, programmability, management, and retaskability. These challenges are especially unique in hybrid sensor networks because devices can no longer be treated the same, meaning that applications will only be effective when exploiting specific differences of a system. There are inherent tradeoffs in meeting these challenges. For example, programmability is achieved through abstraction, which inevitably compromises performance. Designing a system for performance hinders deployability and retaskability. Cascades, a modular framework in the scripted language Python[1], gives application designers great control over implementation designs without the requirement of in-depth development. Cascades combines highly optimized code segments together in the form of Python modules. This architecture has a number of useful properties. First, it allows us to create highly-optimized, efficient code segments for computationally expensive tasks such as JPEG compression, MPEG compression, or image processing. Second, the Python scripting language allows us to seamlessly stitch code segments together. Third, because the system is scripted and modular, modifying or retasking the sensor system requires us to simply update the parts of the system that have changed, reducing network bandwidth required for management. Finally, the scripting language is at a high enough layer such that it allows us to hide many computer science specific optimizations (e.g. video buffering and adaptation or basic networking) from non-computer scientists. We consider hierarchical sensor organization in the context of event detection in order to introduce the concept of Logical Disassociation (LD): the process of creating automatic disassociations between different types of sensors by generating a known event and observing differences in their responses. This allows sensor devices that would normally use network connectivity for determining association to refine the conditions under which events should be considered related. This concept is implemented as an integrated semi-transparent component. Figure 1 gives an example scenario that will be used in the demonstration. Mote-class devices such as the MicaZ[3] typically have lower wireless communication power as a result of their low-power design. To augment their limited range, we

A Dynamic MapReduce Scheduler for Heterogeneous Workloads

A Dynamic MapReduce Scheduler for Heterogeneous Workloads Chao Tian12, Haojie Zhou1,Yongqiang He 12, Li Zha1 1Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China 2 Graduate University of the Chinese Academy of Sciences, Beijing 100039, China tianchao@https://www.360docs.net/doc/566119004.html,, zhouhaojie@https://www.360docs.net/doc/566119004.html,, heyongqiang@https://www.360docs.net/doc/566119004.html,, char@https://www.360docs.net/doc/566119004.html, Abstract—MapReduce is an important programming model for building data centers containing ten of thousands of nodes. In a practical data center of that scale, it is a common case that I/O-bound jobs and CPU-bound jobs, which demand different resources, run simultaneously in the same cluster. In the MapReduce framework, parallelization of these two kinds of job has not been concerned. In this paper, we give a new view of the MapReduce model, and classify the MapReduce workloads into three categories based on their CPU and I/O utilization. With workload classification, we design a new dynamic MapReduce workload predict mechanism, MR-Predict, which detects the workload type on the fly. We propose a Triple-Queue Scheduler based on the MR-Predict mechanism. The Triple-Queue scheduler could improve the usage of both CPU and disk I/O resources under heterogeneous workloads. And it could improve the Hadoop throughput by about 30% under heterogeneous workloads. Keywords-component; MapReduce; Schdule; heterogeneous workloads; I.I NTRODUCTION As the Internet scale keeps growing up, enormous data needs to be processed in many Internet Service Providers. MapReduce framework is now becoming a leading example solution for this. MapReduce is designed for building large commodity cluster, which consists of thousands of nodes by using commodity hardware. Hadoop, a popular open source implementation of MapReduce framework, developed primarily by Yahoo, is already used for processing hundreds of terabytes of data on at least 10,000 cores [3]. In this environment, many people share the same cluster for different purpose. This situation led that different kinds of workloads need to run on the same data center. For example, these clusters could be used for mining data from logs which mostly depends on CPU capability. At the same time, they also could be used for processing web text which mainly depends on I/O bandwidth. The performance of a parallel system like MapReduce system closely ties to its task scheduler. Many researchers have shown their interest in the schedule problem. Current scheduler in Hadoop uses a single queue for scheduling jobs with a FCFS method. Yahoo’s capacity scheduler [4] as well as Facebook’s fair scheduler [5] uses multiple queues for allocating different resources in the cluster. Using these scheduler, people could assign jobs to queues which could manually guarantee their specific resource share. In this work, we concentrate on the problem that how to improve the hardware utilization rate when different kinds of workloads run on the clusters in MapReduce framework. In practical, different kinds of jobs often simultaneously run in the data center. These different jobs make different workloads on the cluster, including the I/O-bound and CPU-bound workloads. But currently, the characters of workloads are not aware by Hadoop’s scheduler which prefers to simultaneously run map tasks from the same job on the top of queue. This may reduce the throughput of the whole system which seriously influences the productivity of data center, because tasks from the same job always have the same character. However, the usage of I/O and CPU are actually complementary [7]. A task that performs I/O is blocked, and is prevented from utilizing the CPU until the I/O completes. When diverse workloads run on this environment, machines could contribute different part of resource for different kinds of work. We design a new triple-queue scheduler which consist of a workload predict mechanism MR-Predict and three different queues (CPU-bound queue, I/O-bound queue and wait queue). We classify MapReduce workloads into three types, and our workload predict mechanism automatically predicts the class of a new coming job based on this classification. Jobs in the CPU-bound queue or I/O-bound queue are assigned separately to parallel different type of workloads. Our experiments show that our approach could increase the system throughput up to 30% in the situation of co-exiting diverse workloads. The rest of the paper is organized as follows. Section 2 describes the related work of this article. Section 3 shows our analysis on MapReduce schedule procedure and give a classification of MapReduce workloads. Section 4 introduces our new scheduler. Section 5 validates the performance increase of our new scheduler through a suit of experiments. II.R ELATED WORK The scheduling of a set of tasks in a parallel system has been investigated by many researchers. Many schedule algorithms has been proposed [11, 12, 13, 16, 17]. [16, 17] focus on scheduling tasks on heterogeneous hardware, and [11, This work is supported in part by the National Science Foundation of China (Grant No. 90412010),the Hi-Tech Research and Development (863) Program of China (Grant No. 2006AA01A106, 2006AA01Z121), and the National Basic Research (973) Program of China (Grant No. 2005CB321807). 2009 Eighth International Conference on Grid and Cooperative Computing

HeteRecom A Semantic-based Recommendation System in Heterogeneous Networks

HeteRecom:A Semantic-based Recommendation System in Heterogeneous Networks Chuan Shi Beijing University of Posts and Telecommunications Beijing,China shichuan@https://www.360docs.net/doc/566119004.html, Chong Zhou Beijing University of Posts and Telecommunications Beijing,China zhouchong90@https://www.360docs.net/doc/566119004.html, Xiangnan Kong University of Illinois at Chicago IL,USA xkong4@https://www.360docs.net/doc/566119004.html, Philip S.Yu University of Illinois at Chicago,IL,USA King Abdulaziz University Jeddah,Saudi Arabia psyu@https://www.360docs.net/doc/566119004.html, Gang Liu Beijing University of Posts and Telecommunications Beijing,China liugangofbupt@https://www.360docs.net/doc/566119004.html, Bai Wang Beijing University of Posts and Telecommunications Beijing,China wangbai@https://www.360docs.net/doc/566119004.html, ABSTRACT Making accurate recommendations for users has become an important function of e-commerce system with the rapid growth of WWW.Conventional recommendation systems usually recommend similar objects,which are of the same type with the query object without exploring the semantics of di?erent similarity measures.In this paper,we organize objects in the recommendation system as a heterogeneous network.Through employing a path-based relevance mea-sure to evaluate the relatedness between any-typed objects and capture the subtle semantic containing in each path, we implement a prototype system(called HeteRecom)for semantic-based recommendation.HeteRecom has the fol-lowing unique properties:(1)It provides the semantic-based recommendation function according to the path speci?ed by users.(2)It recommends the similar objects of the same type as well as related objects of di?erent types.We demon-strate the e?ectiveness of our system with a real-world movie data set. Categories and Subject Descriptors H.2.8[Database Management]:Database applications-Data Mining General Terms Algorithms,Design,Experimentation Keywords heterogeneous information network,recommendation,simi-larity,semantic search 1.INTRODUCTION With the rapid growth of WWW,we are being surround-ed by a large amount of information on the web.Recom-mendation is an e?ective way to reduce the cost for?nding information.It has been widely used in many e-commerce applications,such as Amazon,eBay,and Taobao. Many recommendation methods have been proposed,which can be roughly classi?ed into two categories:content-based ?ltering(CB)and collaborative?ltering(CF).CB analyzes correlations between the content of the items and the user’s preferences[1].CF analyzes the similarity between users or items[2].These methods have been applied to recommen-dation systems and achieved great success.However,these recommendation systems have the following disadvantages. ?Conventional recommendation systems usually recom- mend similar products to users without exploring the semantics of di?erent similarity measures.However, the similar products are often di?erent based on simi- larity semantics.For example,in the movie recommen- dation,the similar movies based on the same actors are di?erent from those based on the same directors. Conventional systems usually give a recommendation without considering the subtle implications of similar- ity semantics.The proposed system is more appeal- ing to provide a semantic recommendation function, which will give more accurate recommendation when users know their intents. ?Conventional systems only recommend same-typed ob- jects.However,a system may be more useful if it si- multaneously recommends more related objects under di?erent semantics.For example,when users select movies,the system not only recommends the similar movies,but also suggests some related actors and di- rectors(note that they are not limited to the actors and directors of this movie).The user may?nd an interesting actor and then search the movies of the ac- tor.The relevance recommendation will provide richer information and enhance user experience. Nowadays,social networks consisting of di?erent types of information become popular.Particularly,the advent of Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. KDD’12, August 12–16, 2012, Beijing, China. Copyright 2012 ACM 978-1-4503-1462-6/12/08...$15.00.

资产定价Asset pricing with heterogeneous consumers 3

●The absence of arbitrage implies the existence for each t of a strictly positive (but not necessarily unique) M(a pricing t kernel) in the information set φ, such that, for any time t, t We call such a process M, a pricing kernel. ●Assumption 1: ?the transversality-like condition ?Pricing Kernel Condition ●Euler inequality of aggregate consumption : for every limited liability security, bond, or portfolio of securities and bonds with return R from time t to t + 1 +t 1

● Assumption 2: Consumer i has labor income it I , at time t where the "shocks" {}it η have the following properties: (a) distinct subsets of {}it η are independent and (b) for all i and t , it η is standard normal and independent of 1-t F and t y . ● PROPOSITION: Under Assumption 1, there exists an equilibrium with no trade that supports the given price processes of the securities and discount bonds. ● The Euler equation ● Special cases ? If consumers are homogeneous, then 021=+t y and equation

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