The static potential lattice versus perturbation theory in a renormalon-based approach
Linear sigma model at finite temperature

2 is the order of this transition, is it first–order with latent heat, or second–order, or maybe a crossover between the A. The potential at one–loop 27 phases? Lattice calculations suggest that when we consider two massless quarks, the transition is second order B. One loop mass correction 27 and the same suggest other approaches based on effective models. If we consider three massless flavours of quarks, C. The Keldysh contour 28 the transition is probably first–order [3, 6]. The aim of this work is to study the chiral phase transition. D. The pion self–energy graphs 28 1. The pion self–energy graph with one thermal pion28 Chiral symmetry breaking is a necessary ingredient for low energy hadron physics, since unbroken chiral symmetry results in massless baryons, without parity doubled 2. The pion
Interstitials, Vacancies, and Supersolid Order in Vortex Crystals

D-85747 Garching, Germany David R. Nelson and Daniel S. Fisher Lyman Laboratory of Physics Harvard University Cambridge, Massachusetts 02138
1 = exp − 2 Gi Gj ui (r⊥ , z )uj (r⊥ , z )
(1.1)
by phonons is discussed in Ref. 7. Here, G is a reciprocal lattice vector and u(r⊥ , z ) is the displacement field of a flux lattice with vortices parallel on average to the z direction. Dislocation loops are a topologically distinct excitation which, when they proliferate at a melting transition, drive ρG (T ) to zero and can lead to a hexatic flux liquid with residual bond orientation order [8]. Isolated dislocation loops are far more constrained than their counterparts in crystals of point particles: dislocation loops in fact must lie in a plane spanned by their Burgers vector and the average field direction [9]—see Fig. 1a. Vacancies and interstitials differ even more dramatically from the analogous defects in crystals of point particles. The number of flux lines is conserved, which means that these defects are lines instead of points. The point-like nature of vacancies and interstitials in conventional crystals ensures that they are present in equilibrium at all finite temperatures for entropic reasons [10]. However, because such imperfections have an energy proportional 2
硼掺杂磷酸铁锂正极材料提高倍率

Delivered by Publishing Technology to: University of New South Wales IP: 149.171.232.34 On: Wed, 27 Feb 2013 03:01:32Copyright American Scientific Publishers RESEARCH ARTICLECopyright©2013American Scientific Publishers All rights reservedPrinted in the United States of AmericaJournal of Nanoscience and Nanotechnology V ol.13,1535–1538,2013Research on High Rate CapabilitiesB-Substituted LiFePO4Fu Wang,Yun Zhang∗,and Chao ChenCollege of Materials Science and Engineering,Sichuan University,Chengdu610064,P.R.China LiFePO4is currently recognized as one of the most promising electrode materials for large-scale application of lithium ion batteries.However,the limitation of rate capability is believed to be intrinsic to this family of compounds due to the existence of larger tetrahedral(PO4 3−unit and quasi-hexagonal close-packed oxygen array.This paper report here a systematic investigation of the enhancement of rate performance by partly substitution of light small triangle oxyanion,(BO3 3−, for the larger tetrahedral(PO4 3−units in LiFePO4.Cathode electrode materials LiFeB X P 1−X O4− , in which X=0 3 6and9,mol%,were synthesized by solid-state method.The as-synthesized products were characterized by X-Ray Diffraction(XRD),Scanning Electron Microscope(SEM)and Electrochemical Measurements.The results showed that6mol%of boron substitution had no effect on the structure of LiFePO4material,but significantly improved its rate performance.The initial discharge capacity of the LiFeB0 06P0 94O4− sample was145.62mAh/g at0.1C,and the capacity retention ratios of81%at2C and76%at5C were obtained,demonstrating that a proper amount of boron substitution(lower than6mol%)could significantly improve the rate performance of LiFePO4 cathode material.Keywords:LiFePO4,High Rate Capability,Li-Ion Battery,Nano-Particles,Boron.1.INTRODUCTIONLiFePO4has recently received a great deal of attentionowing to their advantages of competitive high theoreti-cal capacity,good cycle stability,excellent thermal stabil-ity and low toxicity,1–3aimed at utilizing it as a cathodematerial for large-scale application of lithium ion batter-ies,such as electric vehicle and hybrid electric vehicle.Moreover,its voltage,about3.5V versus lithium,is com-patible with the window of a solid-polymer Li-ion elec-trolyte.However,this kind of compound is a wide-gapsemiconductor(3.7eV)and has an inherently extremelylow electronic conductivity(∼10−9S cm−1 at room tem-perature because of the existence of larger tetrahedral(PO4 3−units and quasi-hexagonal close-packed oxygen array.1Various material processing approaches have beenadopted to overcome this drawback,including methods ofcarbon coating,4reducing particle size to nano level,5 6and doping with super valence cations.7The aforemen-tioned methods for improving electronic conductivity andrate capability are not the most optimistic choice and havetheir intrinsic limitations:the shortcomings of carbon coat-ing including the lower content of active materials in thecathode material and no actual improvement in conductiv-ity for the core of LiFePO4particles.The preparation of ∗Author to whom correspondence should be addressed.nano-sized particles with a uniform size distribution areextremely difficult for industrial scale production.And thequantity of Fe3+/Fe2+redox couples is reduced by supervalence cations substitution.LiFeBO3,as a new potential cathode material with atheoretical capacity of220mAh/g which is much largerthan that of LiFePO4,has been reported to have the actualspecific capacity of over190mAh/g at1/20C.8In addi-tion,from the thermodynamic study performed in the caseof LiFeBO3,the Fe3+/Fe2+reduction couple lies between3.1V and2.9V(vs.Li/Li+ ,demonstrating an impor-tant inductive effect of BO3group,and the electrical con-ductivity of LiFeBO3is reported to be1 5×10−4S/cm,9which is also much higher than that of LiFePO4.10Thus,it is believed that partly replacing the tetrahedral anionunits,(PO4 3−,to plane triangle oxyanion,(BO3 3−,could be significantly increasing the electronic conductivity of the LiFePO4particles because of the smaller and lighter (BO3 3−and the controlled off-stoichiometry of oxygen element formed.In this regard,we proposed a new method,partly sub-stitution of boron element for phosphorus element inLiFePO4,for improving the rate capability of the cathodematerial.We report here a systematic investigation of theenhancement of capacity at high rates of charge and dis-charge by partly substitution of light small plane triangleJ.Nanosci.Nanotechnol.2013,Vol.13,No.21533-4880/2013/13/1535/004doi:10.1166/jnn.2013.59811535Delivered by Publishing Technology to: University of New South Wales IP: 149.171.232.34 On: Wed, 27 Feb 2013 03:01:32Copyright American Scientific Publishers R E S E A R C H A R T I C L Eoxyanion,(BO 3 3−,for the larger tetrahedral (PO 4 3−unit in LiFePO 4.The effects of boron content on the struc-ture and electrochemical performances of LiFePO 4were discussed and characterized by XRD,SEM and Electro-chemical Measurements.2.EXPERIMENTAL DETAILSLiFeB X P 1−X O 4− material was prepared by a solid-state reaction consisting of a mixture of Li 2CO 3,Fe(C 2O 4 ·2H 2O,NH 4H 2PO 4in the molar ratio of Li:Fe:B:P =1.01:1:X :1−X ,in which the X =0 3 6 9,mol%.All chemicals are of analytical grade from Changzheng (Chengdu,China).The synthesized samples were marked by B0,B3,B6and B9,respectively.The stoichiomet-ric precursors were mixed by ball milling in anhydrous ethanol for 4h.After some carbon source citric acid wasadded into the ball-milled precursors,it was ball-milled for another 4h.Then the resulting gel was dried at 40Cunder vacuum,thoroughly reground again.The dry mix-tures were put into a tube furnace full with purified N 2gas,and subjected initially to a lower calcination at 350C for 8h and subsequently to 700C for 14h.The X-ray diffraction (XRD)patterns were analyzed on a Bruker DX1000diffractometer,using Cu K radiation,operating at 40kV and 25mA in the angular range 10≤2theta ≤70 with an acquisition step of 0.02with 1s/step of continue time.A scanning electron microscope (Hitachi S-4800)was used to examine the particle size,microstruc-ture and morphology of the prepared products.The positive electrode slurry,with a ratio of LiFePO 4:acetylene black:poly(vinylidene difluoride)=80:15:5(wt%),was made by mixing the samples powder with acetylene black and PVDF in a solvent of N -methyl pyrrolidone (NMP).The slurry was coated on an alu-minum foil and dried at 120 C for 12h in a vacuum oven to obtain a cathode electrode.The formed cath-ode foil was assembled into a CR2032battery in an argon-filled glove box,with Li foil as anode,1M LiPF 6in ethylene carbonate (EC):dimethyl carbonate (DMC)(1:1(vol%))as electrolyte and a Celgard-2400separa-tor.The electrochemical performance of the cell samples was tested by a high precision battery performance test-ing system (Neware,Shenzhen,China).The galvanostatic charge/discharge cycling performance of the cell samples was tested at different C rates in the range of 2.5–4.3V at room temperature.3.RESULTS AND DISCUSSIONFigure 1shows the XRD pattern of the samples.All of thepeaks are indexed on the basis of an orthorhombic olivine-type structure in the Pnma space group (no.83-2092inJCPDS database).No second phase was found except forthe sample B9,of which the peak (220)wasabnormally Fig.1.XRD patterns of the samples.increased.The analysis of the abnormal peak showed that vonsenite (Fe 2Fe(BO 3 O 2 impurity could be existed in the sample,demonstrating that the substitution of boronto about 6mol%phosphorus allows for the synthesis ofsingle-phase LiFePO 4without unwanted impurity phases.The lattice parameters,calculated from the refined XRD patterns,of the pure LiFePO 4sample were a =10.2894Å,b =5.9933Å,c =4.6720Åand volume =288.11Å.These values,which were very close to but slightly lowerthan the standard data (a =10.347Å,b =6.019Å,c =4.704Å),probably due to the sample’s single-crystal-likecharacteristics.11Figure 2shows the continuous changein lattice dimensions as a function of the substituted boron content in LiFeB X P 1−X O 4− .The lattice parame-ter of a and b decreased with the increasing substituted boron element content probably because more tetrahedral anion units,(PO 4 3−,in LiFePO 4were replaced by smaller and plane triangle oxyanion,(BO 3 3−.However,the lat-tice dimension of c increased with the increase of substi-tuted boron content,this could be explained by that the plane direction of the substituted plane triangle oxyanion,(BO 3 3−is parallel to the plane formed by a axis and b axis.Figure 3(a)shows the voltage profile of the four sam-ples in the first cycle at different C rates in voltage range of 2.5–4.3V .The observed reversible initial dis-charge capacities of 153.99mAh/g,147.78mAh/g and 145.62mAh/g at 0.1C for sample B0,B3and B6were obtained,respectively.The results revealed that the spe-cific capacities of the synthesized samples were slightlydecreased when boron element was used to partly replace the phosphorus element in the LiFePO 4.The possible rea-son of this phenomenon is that some boron element are in the lattice position of lithium,but we really believe that it would be overcame or improved by changing the solid-state method to other synthesizing method such as sol–gel method,hydrothermal method or ion exchange method.When the amount of substituted boron reached 1536J.Nanosci.Nanotechnol.13,1535–1538,2013Delivered by Publishing Technology to: University of New South Wales IP: 149.171.232.34 On: Wed, 27 Feb 2013 03:01:32Copyright American Scientific Publishers RESEARCH ARTICLEttice dimensions as a function of boron content in LiFeB X P 1−X O4−.9mol%,only an initial specific capacity of139.21mAh/g at0.1C was obtained because the second phase vonsenite (Fe2Fe(BO3 O2 impurity might be appeared in the sample from the results of XRD analysis(Fig.1).The cycling performances of all samples at the constant current density of0.1C,0.2C,0.5C,1C,2C and5C are shown in Figure3(b).We know that3mol%and6mol% of boron substitution had negligible affect on the discharge performance of the products,but significantly improved the cycling performance from the Figure3(b).At0.2C, the sample B0,B3and B6had a discharge specific capac-ity of147.47mAh/g,143.37mAh/g and142.30mAh/g,(a)(b)Fig.3.Electrochemical performances of the samples.(a)Initial charge/discharge curves of the samples at0.1C.(b)Cycling perfor-mances of the samples.respectively,and the95.77%,97.02%and97.73%of the initial discharge capacity at0.1C were retained,respec-tively.At0.5C,the discharge capacities of the sample B3 and B6can equal to that of the sample B0,with a specific capacity of about138mAh/g.The initial discharge capac-ity of the sample B3and B6at1C was136.27mAh/g and125.39mAh/g respectively,which exceeded that of the sample B0at the same discharge rate.At2C and5C, the discharge capacity of the sample B0was decreased to 108.65mAh/g and90.90mAh/g,only a capacity retention ratio of70.56%and59.03%were kept.However,the sam-ple B3and B6can retain the initial discharge capacity of 119.62mAh/g and118.79mAh/g at2C,109.98mAh/g and111.11mAh/g at5C,respectively.The capacity reten-tion ratios of81.23%at2C,74.42%at5C for sample B3 and the retention ratios of81.13%at2C,76.30%at5C for sample B6,respectively,were retained.All abovemen-tioned analysis demonstrates that appropriate amount of boron substitution for the phosphorus(less than6mol%) in LiFePO4can significantly ameliorate the rate perfor-mance of LiFePO4cathode material.The beneficial effect of proper amounts of boron substitution on rate performance of LiFePO4could be explained as follows:Firstly,a proper amount of boron substitution have no effect on the basic orthorhombic olivine-type structure of the LiFePO4material and the extraction/insertion of Li+are not impeded;Secondly, lighter small plane triangle oxyanion,(BO3 3−,with a molecular weight of58.8,replace the larger tetrahedral (PO4 3−unit with a molecular weight of95.0may facili-tate Li+transportation for more of larger Li+channels were achieved;Thirdly,the controlled off-stoichiometry of oxygen formed through the substitution of boron for phosphorus,which break the quasi-hexagonal close-packed oxygen array,significantly improve the electronic conductivity of the material.However,the lower initial charge/discharge capacity and rapid capacity fading of the sample B9at high rate demonstrates that the Fe2Fe(BO3 O2impurity not only have bad effect on the discharge capacity of LiFePO4material,but also signifi-cantly affect the material’s rate performance.Figures4(a)and(b)represent the sample B0(LiFePO4 and the sample B6(LiFeB0 06P0 94O4− composite pow-ders consisting of nanometric particles with a partially irregular morphology or quasi-spherical shapes.A very fine powder with an average size of about120–150nm for sample LiFePO4were obtained(Fig.4(a)).The particles of the LiFeB0 06P0 94O4− sample with a homogeneous parti-cle sizes between80–110nm except for a very few abnor-mal particles that are larger than150nm were smaller than that of the sample pure LiFePO4(Fig.4(b)).Com-paring with the pure LiFePO4sample which had two or more particles partly connected each other through melted substance,the particles of LiFeB0 06P0 94O4− sample were well distributed and almost with no agglomeration,indicat-ing that the adding of boron contained compound,H3BO3,J.Nanosci.Nanotechnol.13,1535–1538,20131537Delivered by Publishing Technology to: University of New South Wales IP: 149.171.232.34 On: Wed, 27 Feb 2013 03:01:32Copyright American Scientific Publishers R E S E A R C H A R T I C L EFig.4.SEM micrographs of the sample (a)B0and (b)B6.into raw material could further stop the LiFePO 4parti-cles growing to bigger size and facilitate particle distri-bution during synthesizing process.From this perspective,the excellent rate performance of the LiFeB 0 06P 0 94O 4−sample could also be explained that the average particlesize is smaller than that of the sample LiFePO 4and the particle dispersion is better.4.CONCLUSIONS The B -substituted LiFePO 4were successfully synthe-sized by solid-state method using Li 2CO 3,FeC 2O 4·2H 2O,H 3BO 3and NH 4H 2PO 4as raw material.Up to 6mol%of boron substitution had no effect on the structure of LiFePO 4material,but significantly improved the rate per-formance due to the improved electronic conductivity caused by off-stoichiometry of oxygen and the facilitated extraction/insertion of Li +channels produced by substi-tuting of lighter small plane triangle oxyanion,(BO 3 3−,for the larger tetrahedral (PO 4 3−unit.The initial dis-charge capacity of the LiFeB 0 06P 0 94O 4− sample was 145.62mAh/g at 0.1C,and the capacity retention ratios of about 81%at 2C and 76%at 5C were obtained,demon-strating that proper amount of boron substitution could improve the rate performance of LiFePO 4material.Acknowledgments:This work was financially sup-ported by The Sichuan Province Key Technology Support Program (2011GZ0131)and Innovation Fund for Technol-ogy Based Firm from Ministry of Science and Technology (11C26215103354).References and Notes1. A.K.Padhi,K.S.Nanjundaswamy,and J.B.Goodenough,J.Elec-trochem.Soc.144,1188(1997).2.J.B.Goodenough and Y .Kim,Chem.Mater.22,587(2010).3. A.Manthiram,J.Phys.Chem.Lett.2,176(2011).4.M.M.Doeff,Y .Hu,F.McLarnon,and R.Kostecki,Electrochem.Solid.State.Lett.6,A207(2003).5.S.Ferrari,vall,D.Capsoni,E.Quartarone,A.Magistris,P.Mustarelli,and P.Canton,J.Phys.Chem. C.114,12598(2010).6. B.Kang and G.Ceder,Nature 458,190(2009).7.S.Chung,J.T.Bloking,and Y .Chiang,Nat.Mater.1,123(2002).8. A.Yamada,N.Iwane,Y .Harada,S.Nishimura,Y .Koyama,and I.Tanaka,Adv.Mater.22,3583(2010).9.Y .Z.Dong,Y .M.Zhao,Z.D.Shi,X.N.An,P.Fu,and L.Chen,Electrochim.Acta 53,2339(2008).10.Y .N.Xu,S.Y .Chung,J.T.Bloking,Y .Chiang,and W.Y .Ching,Electrochem.Solid.State Lett.7,A131(2004).11. D.H.Kim and J.Kim,Electrochem.Solid.State.Lett.9,A439(2006).Received:12September 2011.Accepted:30November 2011.1538J.Nanosci.Nanotechnol.13,1535–1538,2013。
Nature Materials 9, 904-907(2010)--np-NiPt for ORR

PUBLISHED ONLINE: 17 OCTOBER 2010 | DOI: 10.1038/NMAT2878
Oxygen reduction in nanoporous metal–ionic liquid composite electrocatalysts
J. Snyder1, T. Fujita2, M. W. Chen2 and J. Erlebacher1*
The improvement of catalysts for the four-electron oxygenreduction reaction (ORR; O2 + 4H+ + 4e− → 2H2O) remains a critical challenge for fuel cells and other electrochemicalenergy technologies. Recent attention in this area has centred on the development of metal alloys with nanostructured compositional gradients (for example, core–shell structure) that exhibit higher activity than supported Pt nanoparticles (Pt–C; refs 1–7). For instance, with a Pt outer surface and Ni-rich second atomic layer, Pt3Ni(111) is one of the most active surfaces for the ORR (ref. 8), owing to a shift in the d-band centre of the surface Pt atoms that results in a weakened interaction between Pt and intermediate oxide species, freeing more active sites for O2 adsorption2,9. However, enhancements due solely to alloy structure and composition may not be sufficient to reduce the mass activity enough to satisfy the requirements for fuel-cell commercialization10, especially as the high activity of particular crystal surface facets may not easily translate to polyfaceted particles. Here we show that a tailored geometric and chemical materials architecture can further improve ORR catalysis by demonstrating that a composite nanoporous Ni–Pt alloy impregnated with a hydrophobic, high-oxygen-solubility and protic ionic liquid has extremely high mass activity. The results are consistent with an engineered chemical bias within a catalytically active nanoporous framework that pushes the ORR towards completion.
海森伯格法则

J Supercond Nov Magn(2013)26:1451–1454DOI10.1007/s10948-012-2038-7O R I G I NA L PA P E RHeisenberg-Like Critical Properties and Magnetocaloric Effect in Lead Doped NdMnO3Single CrystalNilotpal GhoshReceived:4November2012/Accepted:1December2012/Published online:5January2013©Springer Science+Business Media New York2013Abstract Static magnetization for single crystals of Nd0.7Pb0.3MnO3has been studied around the ferromagnetic-to-paramagnetic transition temperature T C.The results of mea-surements carried out in the critical range|(T−T C)/T C|≤0.1are reported.The critical exponentsβandγfor thethermal behavior of magnetization and susceptibility havebeen obtained both from the modified Arrott plots and theKouvel–Fisher method.The exponentδ,independently ob-tained from the critical isotherm,was found to satisfy theWidom scaling relationδ=γ/β+1.The values of expo-nents are consistent with those expected for isotropic mag-nets belonging to the Heisenberg universality class withshort-range exchange in three dimensions.The maximummagnetic entropy change is found at around T C.We found auniversal scaling behavior in the relative change of magneticentropy( S M).The rescaled curves of the magnetic entropychange for different appliedfields are observed to collapseonto a single curve,which validates the second order natureof the phase transition in Nd0.7Pb0.3MnO3.Keywords Critical point phenomena·Magnetocaloriceffect·Universal scaling1IntroductionIn rare earth manganites,the most attractive phenomenonis the colossal magneto resistance(CMR)[1]which usu-ally appears at metal–insulator(MI)transition associatedN.Ghosh( )VIT University,Vellore,Tamilnadu,Indiae-mail:ghosh.nilotpal@N.Ghoshe-mail:nilotpal@vit.ac.in with ferromagnetic–paramagnetic(FM–PM)phase transi-tion.Hence,it is interesting to know how the interaction is renormalized near the critical point and which univer-sality class governs the magnetic phase transition.Criti-cal phenomena in the double exchange(DE)model have beenfirst described within mean-field theory[2].Later,Mo-tome and Furukawa[3]predicted that the FM–PM transi-tion in manganites should belong to the short-range Heisen-berg universality class.A number of experimental studies of critical phenomena and scaling laws across the FM–PM phase transition have been previously made on manganites [4].In this context,it should be mentioned that the FM–PM phase transition is also very important for the inves-tigation of the magnetocaloric effect(MCE)in rare earth manganites.MCE is connected to change of magnetic en-tropy( S M)and it is a parameter which achieves rela-tively high value at the PM to FM transition.The MCE is often determined for any material by measuring magnetic isotherms at different temperatures across the T C and by determining S M with the help of Maxwell relations.Re-cently,V.Franco et al.have described the universal behavior for S M in materials with a second order phase transition [5–7].Rare earth manganites(A1−x B x MnO3)are potential candidates for MCE.[8].In the perovskite manganite fam-ily,lead(Pb)doped NdMnO3is a comparatively less studied member[9,10].Nd1−x Pb x MnO3system shows a second order FM-to-PM phase transition and belongs to the univer-sality class of the three dimensional Heisenberg ferromagnet [11,12].In the present paper,we report precise estimation of the critical exponents and validity of scaling laws for an Nd0.7Pb0.3MnO3single crystal.We have reported the study of MCE from determination of magnetic entropy by record-ing the magnetization isotherms as a function of magnetic field.A universal scaling behavior in normalized magneticentropy( S M/ S peakM )with respect to rescaled temperature(θ)is also investigated.2ExperimentSingle crystals are grown by the high temperature solutiongrowth method using PbO/PbF2flux[10].The DC magne-tization measurement is carried out at H=0.3T by Quan-tum Design SQUID ter,extensive magne-tization data M(T,H)are collected in external static mag-neticfields H up to4.8T using the SQUID magnetometer[11,12].The sample has been measured in the temperaturerange135K≤T≤186K(T C∼148.5K)near the PM–FM phase transition with a step of1K.The M(T,H)ver-sus H data are corrected by a demagnetization factor thathas been determined by a standard procedure from low-fieldDC-susceptibility measurements[12].3Results and DiscussionsFigure1(a)shows the magnetic isotherms for Nd0.7Pb0.3MnO3over afield range0–4.8T at135–155K.It is seenthatFig.1(a)The magnetization isotherms of Nd0.7Pb0.3MnO3sin-gle crystal measured at temperatures between135and155K with 1K step.The inset shows magnetization as a function of tempera-ture for Nd0.7Pb0.3MnO3single crystal at0.3T.(b)Arrott plot of Nd0.7Pb0.3MnO3which shows that the system undergoes a second or-der phase transition the magnetization increases rapidly at the lowfield range ∼0.05T and then it increases steadily over thisfield.How-ever,the saturation is not achieved even at4.8T due to thepossible canted magnetic structure of Nd moments with re-spect to Mn sublattice[13].The inset shows the result ofmagnetization measurement as a function of temperature atH=0.3T.The FM-to-PM phase transition is clearly ob-served.According to the scaling hypothesis,a second-orderphase transition near the Curie point T C is characterized bya set of interrelated critical exponents,α,β,γ,δ,etc.,anda magnetic equation of state[11,12].The magnetic phasetransition has been analysed by means of the so-called Arrotplots(M2vs H/M)based on Landau theory of phase transi-tion(Fig.1(b)).The positive slope in Arrot plots means thatthe magnetic transition from the FM-to-PM phase is of thesecond order type[14].This also shows that the mean-fieldtheory does not describe the critical behavior for the presentsystem.Therefore,the magnetic phase transition is analysedwith the modified Arrott plots(Fig.2(a)).As trial values,we have chosenβ =0.365andγ =1.336,the critical ex-ponents of the3D Heisenberg model.As these plots resultin nearly straight lines,we have extracted spontaneous mag-netization M S(T)and inverse susceptibilityχ−10(T)fromthem.These values are plotted with respect to temperaturein Fig.2(b),and the continuous curves show the indepen-dent power lawfits to M S(T)andχ−10(T)[12].The valuesof T C obtained from thefits are close to the original value.Alternatively,the values of T C,βandγhave also been ob-tained by Kouvel–Fisher(KF)method(Fig.3(a))[12].TheFig.2(a)Modified Arrott plots with critical exponents of3D Heisenberg universality class.(b)Plots of M S(T)andχ−10(T)of Nd0.7Pb0.3MnO3Fig.3(a)Kouvel–Fisher plots(b)M S(T=T c,H)versus H plots ofNd1−x Pb x MnO3for x=0.3in log–log scale for Nd0.7Pb0.3MnO3value ofδhas been found directly by plotting M(T C,H)versus H on the log–log scale(Fig.3(b)).The critical ex-ponentsβ,γandδare related through the Widom ScalingRelation(δ=1+γ/β)which is verified with the values ob-tained from our measurements.In order to check whetherour data in the critical region obey the magnetic equationof state equation,M/εβas a function of H/εβ+γwhereε=T−T C/T C is plotted in Fig.4for Nd0.7Pb0.3MnO3.It can be clearly seen that all the points fall on two curves,one for T<T C and the other for T>T C.Thus the obtainedvalues of the critical exponents and T C are reliable and inagreement with the universal scaling hypothesis.The magnetic entropy change S M was calculated frommagnetization isotherms(see Fig.5(a))following the stan-dard procedure based on Maxwell equations[15,16].Fig-ure5(b)describes the variation of− S M with temperature(T)at1.2,2.2,and4.8T.The maximum of− S M is ob-served to appear at around T C,which is quite broad,indi-cating the second order transition.In order to study the uni-versal scaling behavior of S M,we have tofind a universalcurve.Hence,the peak entropy change, S peakM,has beentaken as reference in order to normalize S M(T,H)curvesforfinding equivalent points.For each value of the appliedfield,two reference temperatures T r1<T C and T r2>T C areselected.The collapse of the normalized curves ofentropyFig.4Scaled isotherms of Nd0.7Pb0.3MnO3below and above thetransition temperature usingβandγas defined in thetextFig.5(a)The magnetization isotherms of Nd0.7Pb0.3MnO3singlecrystal measured at temperatures between135and186K with1Kstep.(b)Magnetic entropy change(− S M)as a function of temper-ature at H=1.2,2.2,and4.8T for Nd0.7Pb0.3MnO3(Colorfigureonline)Fig.6Normalized entropy change ( S M / S peakM )as a function of the rescaled temperature (θ)for Nd 0.7Pb 0.3MnO 3.The existence of a universal curve shows that the phase transition is of second order (Color figure online)changes can be obtained by defining a new variable for the temperature axis,θ,given by the following expression [17]:θ=−(T −T C )/(T r 1−T C )T ≤T C ,−(T −T C )/(T r 2−T C )T >T C .(1)Figure 6describes the change of the normalized entropyS M / S peakM as a function of rescaled temperature θfor Nd 0.7Pb 0.3MnO 3.We have considered T r 1=T r 2=T rwhere S M / S peakM is approximately 0.74.It is observed that all the three experimental curves measured at 1.2,2.2,and 4.8T collapse onto a unique curve.The collapse of all these data into a unique curve in a wide range of temperature supports the validity of the second order phase transition and universal scaling for Nd 0.7Pb 0.3MnO 3.4ConclusionsWe have studied the magnetization property of Nd 0.7Pb 0.3MnO 3single crystal at low temperature.The magnetiza-tion measurement as a function of magnetic field up to 4.8T has been carried out at several constant tempera-tures around the T C .We have determined the critical expo-nents by modified Arrott plot and the K–F ing Maxwell’s relations,the magnetic entropy is calculated at H =1.2,2.2,and 4.8T.The maximum magnetic entropy change is observed at around T C .We have found a univer-sal scaling behavior in normalized S M as a function of rescaled temperature.Acknowledgements N.G.thanks the SFB 463Project funded by DFG for financial support during his work in IFW Dresden and Dr.K.Nenkov for measurements.References1.Coey,J.M.D.,Viret,M.,von Molnar,S.:Adv.Phys.48,167(1999)2.Kubo,K.,Ohata,N.:J.Phys.Soc.Jpn.33,21(1972)3.Motome,Y .,Furukawa,N.:J.Phys.Soc.Jpn.70,1487(2001)4.Ghosh,K.,Lobb,C.J.,Greene,R.L.,Karabashev,S.G.,Shulyatev,D.A.,Arsenov,A.A.,Mukovskii,Y .:Phys.Rev.Lett.81,4740(1998)5.Franco,V .,Blázquez,J.,Conde,A.:Appl.Phys.Lett.89,222512(2006)6.Dong,Q.Y .,Zhang,H.W.,Sun,J.R.,Shen,B.G.,Franco,V .:J.Appl.Phys.103,116101(2006)7.Franco,V .,Conde,C.,Blázquez,J.,Conde,A.:J.Appl.Phys.101,093903(2007)8.Phan,M.-H.,Yu,S.-C.:J.Magn.Magn.Mater.308,325(2007)9.Kusters,R.M.,Singleton,J.,Keen, D.A.,McGreevy,R.,Hayes,W.:Physica B 155,362(1989)10.Ghosh,N.,Elizabeth,S.,Bhat,H.L.,Subanna,G.N.,Sahana,M.:J.Magn.Magn.Mater.256,286(2003)11.Sahana,M.,Roessler,U.K.,Ghosh,N.,Elizabeth,S.,Bhat,H.L.,Doerr,K.,Eckert,D.,Wolf,M.:Phys.Rev.B 68,144408(2003)12.Ghosh,N.,Roessler,S.,Roessler,U.K.,Nenkov,K.,Elizabeth,S.,Bhat,H.L.,Doerr,K.,Mueller,K.-H.:J.Phys.Condens.Matter 18,557(2006)13.Ghosh,N.:J.Magn.Magn.Mater.323,405(2011)14.Banerjee,S.K.:Phys.Lett.12,16(1964)15.Amaral,J.S.,Amaral,V .S.:J.Magn.Magn.Mater.1552,322(2010)16.Pekala,M.,Pekala,K.,Drozd,V .,Fagnard,J.F.,Vanderbem-den,P.:J.Magn.Magn.Mater.322,3460(2010)17.Franco,V .,Conde,A.,Romero-Enrique,J.M.,Blazquez,J.S.:J.Phys.Condens.Matter 20,285207(2008)。
半导体物理与器件——Terms汉译英

半导体物理与器件——Terms(术语)U1 Terms:Semiconductor physics and devices半导体物理与器件,Space lattice空间晶格, unit cell晶胞, primitive cell原胞,basic crystal structures 基本晶格结构(five), Miller indices密勒指数, atomic bonding原子价键U2 Terms:quantum mechanics量子力学,energy quanta能量子, wave-particle duality波粒二象性,the uncertainty principle测不准原理/海森堡不确定原理Schrodinger's wave equation薛定谔波动方程, eletrons in free Space自由空间中的电子the infinite potential well无限深势阱, the step potential function 阶跃势函数, the potential barrier势垒.U3 Terms:Pauli exclusion principle泡利不相容原理, quantum state量子态. allowed energy band允带, forbidden energy band禁带.conduction band导带, valence band价带,hole空穴, electron 电子.effective mass有效质量.density of states function状态密度函数,the Fermi-Dirac probability function费米-狄拉克概率函数,the Boltzmann approximation波尔兹曼近似,the Fermi energy费米能级.U4 Terms:charge carriers载流子, effective density of states function有效状态密度函数,intrinsic本征的,the intrinsic carrier concentration本征载流子浓度, the intrinsic Fermi level本征费米能级.charge neutrality电中性状态, compensated semiconductor补偿半导体, degenerate简并的,non-degenerate非简并的, position of E F费米能级的位置U5 Terms:drift current漂移电流, diffusion current 扩散电流,mobility迁移率, lattice scattering晶格散射, ionized impurity scattering 电离杂质散射, velocity saturation饱和速度,conductivity电导率,resistivity电阻率.graded impurity distribution杂质梯度分布,the induced electric field感生电场, the Einstein relation爱因斯坦关系, the hall effect霍尔效应U6 Terms:nonequilibrium excess carriers非平衡过剩载流子,carrier generation and recombination载流子的产生与复合,excess minority carrier过剩少子,lifetime寿命,low-level injection小注入,ambipolar transport双极输运, quasi-Fermi energy准费米能级.U7 Terms:the space charge region空间电荷区,the built-in potential内建电势, the built-in potential barrier内建电势差,the space charge width空间电荷区宽度, zero applied bias零偏压, reverse applied bias反偏, onesided junction单边突变结.U8 Terms:the PN junction diode PN结二极管, minority carrier distribution少数载流子分布, the ideal-diode equation理想二极管方程, the reverse saturation current density反向饱和电流密度.a short diode短二极管,generation-recombination current产生-复合电流,the Zener effect齐纳效应, the avalanche effect雪崩效应, breakdown击穿.U9 Terms:Schottky barrier diode (SBD)肖特基势垒二极管,Schottky barrier height肖特基势垒高度.Ohomic contact欧姆接触,heterojunction异质结, homojunction单质结,turn-on voltage开启电压,narrow-bandgap窄带隙, wide-bandgap宽带隙,2-D electron gas二维电子气U10 Terms:bipolar transistor双极晶体管,base基极, emitter发射极, collector集电极.forward active region正向有源区, inverse active region反向有源区, cut-off截止, saturation饱和,current gain电流增益,common-base共基, common-emitter共射.base width modulation基区宽度调制效应, Early effect厄利效应, Early voltage厄利电压U11 Terms:Gate栅极, source源极, drain漏极, substrate基底.work function difference功函数差threshold voltage阈值电压, flat-band voltage平带电压enhancement mode增强型, depletion mode耗尽型strong inversion强反型, weak inversion弱反型,transconductance跨导, I-V relationship电流-电压关系。
Oscillating magnetoresistance in diluted magnetic semiconductor barrier structures

Kai Chang∗ and J. B. Xia
NLSM, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
distances (≥ 100µm) and for long time (up to nanoseconds) [16]. In this work, we report an interesting oscillating tunneling magnetoresistance (TMR) and spin polarization (SP) through NMS/DMS structures. The DMS structure is similar to the saal study of Ref. [10]. We find theoretically that the TMR for the double barrier structure oscillates with increasing magnetic field and exhibits a peculiar beat pattern. The underlying physics of the phenomena arises from the interplay of the spin-up and the spin-down channels which are split by the s-d exchange interaction. Note that bandstructure effects and spin-orbit interaction are not very efficient spin-flip processes for electrons. [17] Recently, Egues et al [12] presented results on spin filtering and magnetoresistance through ballistic tunneling junctions. These results are complementary to ours, i.e. the beat pattern in the double NMS barriers with DMS contacts is similar to what we found, but we additionally studied double DMS barriers with NMS contacts which we found to exchibit also beat patterns. Furthermore, in our calculation we used a different approach which is more easily applicable to more complicated cases, such as e.g. the case with an electric bias. In this work we prove that the beat pattern which arises from the superposition of the spin-up and the spin-down channel is a rather general phenomena and can be observed in either NMS double barrier structures with DMS contacts or DMS barriers with NMS contacts. Instead of ZnSe/Zn1−x Mnx Se structures used in the calculation of Ref. [12], we propose Cd1−y Mgy Te / Cd1−x Mnx Te structures to realize single and double NMS(Cd1−y Mgy Te) barrier structures with DMS contacts(Cd1−x Mnx Te). Consider a spin unpolarized electron injected into a NSM/DMS/NSM single or double barrier structure in the presence of a perpendicular magnetic field. Due to the s-d exchange interaction, an external magnetic field gives rise to a giant Zeeman splitting of the conduction band states which results in a striking difference of the potential profiles seen by the spin-up and the spin-down electron (see the insets of the figures) [11]. In this simple system, the electric current has contributions from spinup and spin-down channels. Since the sample dimensions are much smaller than the spin coherence length, which may reach up to 100µm in semiconductors [14,16], spin-
专业英语原文(渗透脱水制果酱)

Journal of Food EngineeringV olume 91, Issue 1, March 2009, Pages 56-63Analysis of heat transfer during ohmic processing of a solid foodF. Marra a,,, M. Zell b, J.G. Lyng b, D.J. Morgan b and D.A. Cronin ba Dipartimento de Ingegneria Chimica e Alimentare, Universitàdegli Studi di Salerno via Ponte Don Melillo,84084 Fisicano, SA, Italyb UCD School of Agriculture, Food Science and Veterinary Medicine, Agriculture and Food Science Centre,College of Life Sciences, UCD Dublin, Belfield, Dublin 4, IrelandReceived 20 December 2007;revised 26 July 2008;accepted 5 August 2008.Available online 22 August 2008.AbstractTo produce a safe cooked food product it is necessary to ensure a uniform heating process. The aim of this study was to develop a mathematical model of a solid food material undergoing heating in a cylindrical batch ohmic heating cell. Temperature profiles and temperature distribution of the ohmic heating process were simulated and analysed via experimental and mathematical modelling which incorporated appropriate electromagnetic and thermal phenomena. T emperature profiles were measured at nine different symmetrically arranged locations inside the cell. The material was ohmically heated imposing a voltage of 100 V, while electrical field and thermal equations were solved for experimental and theoretical models by the use of FEMLAB, a finite element software. Reconstituted potato was chosen to represent a uniform solid food material and physical and electrical properties were determined prior to the experiment as a function of temperature.The simulation provided a good correlation between the experimental and the mathematical model. No cold spots within the product were detected but both experimental and model data analysis showed slightly coldregions and heat losses to the electrode and cell surfaces. The designed model could be used to optimize the cell shape and electrode configurations and to validate and ensure safe pasteurisation processes for other solid food materials.Keywords:Ohmic heating; Heat transfer modelling; FEMNomenclatureSymbol Meaning (units)A e area (m2)C p specific heat (J kg−1 K−1)I intensity of current (A)K thermal conductivity (W m−1 K−1)L length (m)Q ext heat flux towards the external environment (W/m−2)Q gen heat generation due to ohmic effect (W/m−3)T time (s)T sample temperature (K)T in external temperature (K)U overall heat transfer coefficient (W m−2 K−1)V voltage (V)Ρdensity (kg m−3)Σelectrical conductivity (S m−1)Article Outline1. Introduction2. Materials and methods2.1. Sample preparation2.2. Ohmic heating system and process2.3. Measurement of physical properties2.3.1. Electrical conductivity2.3.2. Thermal conductivity2.3.3. Specific heat capacity2.3.4. Proximate analysis3. Mathematical model3.1. Transport equations3.2. Initial and boundary conditions3.3. Numerical solution of model with defined parameters4. Results and discussion5. ConclusionAcknowledgementsReferences1. IntroductionOhmic heating is a developing technology with considerable potential for the food industry. The main advantages of ohmic processing are the rapid and relatively uniform heating achieved, together wi th the lower capital cost compared to other electroheating methods such as microwave and radio frequency heating. Ohmic heating technology has been accepted by the industry for processing liquids and solid–liquid mixtures, but not to date for solid foods (Piette et al., 2004) though a number of recent publications have been produced in the area of meat pasteurisation ([Özkan et al., 2004] and [Shirsat et al., 2004]).Mathematical modelling is an invaluable aid in the development, understanding an d validation of these emerging thermal technologies (Tijskens et al., 2001). To ensure a completely safe ohmically cooked product, a model of the thermal process should first be developed to identify possible hot and cold spots, to quantify heat losses and to evaluate the influence of key variables such as electrical field strength and sample conductivity.Previous modelling work and simulations on ohmic processes were performed on liquid foods and liquid-particulate mixtures. Initial models of ohmic processes, mainly two dimensional systems, were prepared for continuous flow systems using liquid–solid mixtures (de Alwis and Fryer, 1990). One of the first 3D models was developed by Sastry and Palaniappan (1992). Such models are necessary to visualize the thermal distribution within the whole foodstuff and also to consider other possible effects, like heat loss at surfaces and electrodes and electrical field distribution, which are critical in sterilization calculations (Jun and Sastry, 2007).Ye et al. (2004) used magnetic resonance imaging temperature mapping to model the ohmic heating process ofa liquid-particulate mixture in a static ohmic heater and Jun and Sastry (2005) predicted a heat transfer modelfor pulsed ohmic heating of tomato soup within a pouch system. Recently Salengke and Sastry (2007) developed a “worst case scenario” model, based on a solid–liquid food system which was already mentioned by them at an earlier stage (Sastry and Salengke, 1998). However, there appear to be no three dimensional mathematical models on the ohmic heating of solid foodstuffs.The objective of this study was to develop a model to quantify the ohmic heating effects within a model solid food system, then to use this model to optimize heat distribution within this foodstuff and to evaluate the main parameters affecting the system.2. Materials and methods2.1. Sample preparationMashed potato was chosen as model foodstuff due to its highly uniform nature. To ensure a homogenous product 990 g of instant mashed potato flakes (Erin Foods Ltd., Thurles, Co. Tipperary, Ireland) were mixed with3.8 l of boiling water, 145 g unsalted butter (Avonmore, Glanbia Foods, Dublin, Ireland) and 65 g pure driedvacuum salt (INEOS Enterprises, Weston Point, Runcorn, Cheshire WA7 4HB, UK). The butter was first melted in the boiling water, salt was added and the mixture was thoroughly mixed in a food processor (Kenwood, Major Classic KM800 with a dough hook stirrer, Kenwood Limited, New Lane, Havant PO9 2NH, UK) for 1 min during which time the potato flakes were added. Following mixing, the formulation was transferred to a 10 l container and the sample surface was covered with cellophane film to prevent moisture loss through evaporation. The container was also sealed with a lid and allowed to cool overnight in a refrigerator at 279.15 K and stored until required for use.2.2. Ohmic heating system and processA cylindrical heating cell was chosen because of its symmetrical nature and because it mimics container shapescommonly used in the food industry. The static cell used for the experiments (see Fig. 1) was made of stainless steel, 14.5 cm length, 11.5 cm internal length, 7.2 cm inner diameter ID and with an outer diameter OD of 7.6 cm. The inner cell surface was lined with Teflon tape (Taconic International, Mullingar Business Park, Mullingar, Ireland) and for the thermocouple inlets three threaded holes were incorporated to allow insertion of three threaded plastic thermocouple holders at the top of the cell. Thermocouples were prepared with type T thermocouple wires (Industrial T emperature Sensors, Dublin, Ireland) within a stainless steel sheath (2 mm diameter). The smallest feasible size was chosen to minimize possible interferences with the electrical field and to minimize response time (2 s). The three thermocouples in each probe were positioned in a symmetrical manner (as shown in Fig. 1) to enable the measurement of the temperature profile across the cell diameter one.Those thermocouples located near the wall were positioned as close as possible to the wall to allow accurate estimation of surface heat loss. Platinum-coated titanium electrodes (diameter 6.9 cm) were fixed at both ends of the cell which was spring loaded with screwed lids as described in Shirsat et al. (2004). Prior to each run an appropriate amount of the test material was remixed in a mixer fitted with a dough hook stirrer (Model Auto Pro, Kenwood) to ensure a uniform product. This mixture was then vacuum packed in polythene bags with a Webomatic vacuum packaging system (Model No. C10H, Webomatic, Bochum, Germa ny) to remove trapped air. Each bag was then cut at one corner and the product was expelled by hand into the cell to ensure a uniform and air free distribution within the cell and finally compacted with a plunger to remove any air incorporatedduring the filling process. For each run the cell was filled with 530 ± 0.2 g of product and allowed to equilibrate in a refrigerator at 279.15 K for 30 min. The foodstuff was subsequently heated using a custom built 3.5 kW batch ohmic heater (C-Tech Innovation Ltd., Chester, UK). The heating unit consisted of a safety chamber housing the cell during heating and a voltage control unit. The control panel was supplied with 230 V, 50 Hz alternating current and an integrated transformer was used to adjust the voltage to 100 V for all runs.Temperature, voltage and current data were monitored at 5 s intervals using a Pico ADC 11 data logger (Model No. R5.06.3, Pico Technology Ltd, St. Neots, UK). Following set up trials all heating experiments (five replicates) were standardised to 150 s duration.Full-size image (33K)Fig. 1. Stainless steel cell used for experimental tests including the nine locations of thermocouple points for evaluation of temperature distribution during heating process.2.3. Measurement of physical properties2.3.1. Electrical conductivityA Teflon conductivity cell (3.65 cm inner diameter) was designed with specially manufactured spring loadedcaps housing the stainless steel electrodes (diameter 3.6 cm) and with a central opening for the insertion of a thermocouple. Temperature, voltage and current values were recorded at 1 s intervals with a Pico data logger system. The cell was calibrated according to Levitt’s method (Levitt, 1954). This involves the use of five concentrations of KCl (Sigma Aldrich, UK) across a range from 0.5 to 0.05 M in deionised water, leading to the calculation of a conductivity cell constant. The calibration was validated with 3 NaCl (Merck, Germany) solutions with concentrations 0.02, 0.05 and 0.17 M. Measured values were compared to corresponding published values (CRC, 1996). In the case of mashed potato measurement, 50 ± 0.2 g samples were packedinto the conductivity cell ensuring the same precautions as above to avoid air incorporation. For all conductivity experiments five sample replicates were heated up from 273.15–358.15 K at 10 V/cm and a frequency of 50 Hz. Conductivity was calculated according to the following equation:(1)(2) where I is the current intensity (A), V is the voltage (V), L is the gap between the electrodes (m) and A e is the electrode surface area (m2).The best fit with temperature produced the linear function listed in Table 1.Table 1.Best fitting for measured thermo-physical properties and electrical conductivity as functions of temperaturePropertyUnits Function (T in K) R2σS/m 0.0381 T−9.36550.994kW/(mK) 0.002 T−0.1450.9973C p J/kg0.2582 T2−157.19 T+27083 0.984 12.3.2. Thermal conductivityThe thermal conductivity k of mashed potatoes was measured with a line heat source probe based on the design of Sweat et al. (1973). The stainless steel probe incorporated a constantan heater wire which ran the length of the probe and a thermocouple located midway along the probe. T o measure k plastic beakers (King Ireland, Dublin, Ireland) were uniformly filled with the experimental material and the probe was inserted axially in the sample centre. After a 30 s equilibration time the needle was heated at a constant rate and thetemperature was monitored. Three replicates of thermal conductivity measurements were made at five temperatures in the range 278.15 K to 358.15 K. To ensure the correct temperatur e of the sample prior to the measurement a sample beaker was placed in a water bath (Model No. L TD20, Grant Instruments Ltd., Barrington, Cambridge CB2 5QZ, UK). Prior to use the system was calibrated using glycerol (99.5% A.C.S.reagent, Sigma–Aldrich) and olive oil at 293.15 K. Regression coefficients (R2) for the straight line portion of the temperature against log time curve were >0.99 for all measured values. Best fitting with temperature produced the linear function listed in T able 1.2.3.3. Specific heat capacityThe measurement of specific heat of the mashed potato samples was performed using a differential scanning calorimeter (DSC) (Model No. DSC 2010, TA Instruments Inc., Newcastle, USA). The instrument was first calibrated with indium (melting point 429.75 K) and the cell constant was determined using sapphire. Mashed potato samples (15–20 mg) were weighed into aluminium pans (TA Instruments) and sealed hermetically to prevent moisture loss during the process. As a reference a hermetically sealed empty pan was used. Samples were first cooled with liquid nitrogen, equilibrated to 278.15 K and then heated isothermally from 278.15 K to 358.15 K at a heating rate of 10 K/min. Five replicates were measured and the mean values were calculated.Best fitting with temperature produced the second order polynomial function listed in Table 1.2.3.4. Proximate analysisMoisture was determined in triplicate (AOAC, 1995method No. 950.46) using a Binder drying oven (Binder GmbH, Tuttlingen, Germany) and total salt content was evaluated in duplicate using the method of Fox (1963).A total moisture content of 77.6% and a salt content of 1.35% were recorded for th e potato product.3. Mathematical modelIn order to be able to run a series of virtual experiments, a mathematical model of ohmic heating was developed for the ohmic cell described in Section 2.2. A cylinder was chosen to represent the sample domain. All phenomena outside this sample domain were taken into account by means of appropriate boundary conditions.3.1. Transport equationsThe heat transfer occurring during ohmic processing of a solid-like foodstuff, such as mashed potatoes, is described by the classical unsteady state heat equation by conduction plus a generation term, as reportedbelow(2)where T is the temperature within the sample, t is the process time, k is the thermal conductivity, ρ is the density,C p is the heat capacity and Q gen represents the ohmic power source, as in the following equation(3)where σ is the electrical conductivity, and represents the modulus of the gradient of electrical potential.According to quasi-static approach, the electrical potential distribution within the sample can be computed using the following Laplace equation:(4)Since the electrical conductivity is a function of temperature, Eqs. (2) and (4) are strictly related to each other and must be solved simultaneously (Jun and Sastry, 2007).3.2. Initial and boundary conditionsEq. (2) needs initial condition and boundary conditions to be solved, whereas Eq. (4)needs only boundary conditions, being a stationary-state equation. Prior to commencing ohmic heating it is assumed that the entire sample is at a uniform temperature T0 = 279.15 K.As boundary conditions for the heat transfer equation, two different cases were considered: the first one assumed that all the sample is thermally insulated; the second one assumed a general external heat transfer given by(5)q ext=U(T-T inf)where U is an overall heat transfer coefficient, that takes into account any possible composite resistance such as multi-layers around the ohmic cell and T inf is the external environment temperature. In this second case, four values were considered for U= 5, 10, 50 or 100 W m−2K−1. The first case (thermally insulated sample) represents the best process condition, given that no heat is lost toward the external environment. The second case represents possible conditions when heat is lost toward the external environment: particularly, 5 < U< 10 W m−2 K−1 corresponds to the expected range of values for overall heat transfer coefficient under the present experimental conditions (Singh and Heldman, 2001). For the Laplace equation the following boundary conditions were assumed: an applied voltage between the two electrodes and a complete electrical insulation of the lateral external sample surface.3.3. Numerical solution of model with defined parametersThe set of equations above introduced, with their relative initial and boundary conditions, were solved by means of a commercial software (FEMLAB 3.1, Comsol AB, Stockholm, Sweden) based on the Finite Element Method (FEM). An implicit time-stepping scheme was used to solve time-dependent problems: at each time step, the software solved a possibly nonlinear system of equations. The nonlinear system was solved using a Newtonian iteration. An arbitrary linear system solver was then used for the final resulting systems (FEMLAB 3.1 User Guide, 2004). For the purposes of this research, a direct linear system solver (UMFPACK) was used. Relative tolerance was set to 1 × 10−2 whereas absolute tolerance was set to 1 × 10−3.The simulations were performed using a PC, equipped with two Intel Xeon CPUs, at 2.00 GHz, with 2 Gb of RAM, running under Windows XP.Numerical tests were performed with different mesh parameters in order to evaluate the simulation results and to find the best mesh settings. The set providing the best spatial resolution for the considered domain and for which the solution was found to be independent of the grid size, was composed of 10217 tetrahedrons, 1396 boundary elements, 100 edge elements, with 30170 of degree of freedom.4. Results and discussionThe numerical solution of the ohmic heating model can be presented as a series of 3D plots where, in tur n, various parameters (e.g. temperature, voltage, heat flux etc.) can be shown. Fig. 2 shows two examples of atypical temperature slice plot after 150 s of ohmic heating that illustrates heat losses from the surfaces, assuming an overall heat transfer coefficient U = 5 W m−2 K−1 (Fig. 2a) and U = 10 W m−2 K−1 (Fig. 2b), having also considered a set-point value of 100 V, as applied voltage, for initial temperature of 279.15 K and external temperature of 286.15 K.Full-size image (58K)Fig. 2. Slice plot of simulated temperature within the considered sample, after 150 s, for the following conditions: applied voltage set-point 100 V, initial temperature = 279.15 K, external temperature = 286.15 K, overall heat transfer coefficient (a) U= 5 W m−2 K−1; (b) U= 10 W m−2 K−1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)The two considered values for the overall heat transfer coefficient are ve ry close but while U = 5 W m−2 K−1 gives an almost even temperature distribution (Fig. 2a) with no more than 3 K of difference among hottest and coldest areas, setting U = 10 W m−2 K−1 (Fig. 2b) gives colder zones (light blue and blue) in the proximity of external surfaces and with slice corners (in proximity of cylindrical sample edges) 6 K colder than the sample core. The two lateral slices in the plot show a more diffuse temperature distribution, whereas the central slice shows a sharp change from 336.5 K to 342.5 K in a very narrow band. In any case, cold regions are expected to be located in proximity to the electrode surfaces, with temperature values lower than the sample core temperature.Simulations were run to explore the role of heat transfer boundary conditions in the development of heating patterns within the sample. Five specific values (0, 5, 10, 50 and 100 W m−2 K−1) were considered for the overall heat transfer coefficient U, appearing in the boundary condition set for the heat equation. When U is taken equal to zero, this represents perfectly insulated conditions which was one of the hypotheses discussed in section 3. Results reported in Fig. 3 as temperature plots after 150 s of heating in the ohmic cell (evaluated along the radial coordinate in the planar centre of the sample) clearly show that conditions of perfect thermal insulation result in highly uniform heating. This is better appreciated in Fig. 4, where temperature plots evaluated along the radial coordinate in the planar centre of the sample are plotted as a function of heating time(in seconds), for an applied voltage set-point of 110 V and when perfect thermal insulation (U = 0 W m−2 K−1, Fig. 4a) or some heat losses (U = 50 W m−2 K−1, Fig. 4b) are considered on the boundaries. When perfect thermal insulation is considered, it is evident that during this time progression the temperature profile is completely uniform. Under these ideal conditions the conductive effects are minimal and the heating is due only to the ohmic effects. In reality heat losses must be accounted for, including all the possible mechanisms responsible for dissipating heat from the sample to the external environment and not just ext ernal convection. In order to account for the overall heat flux from the sample we have defined a unique parameter U which will incorporate the effects of the external environment. The effect of heat losses, as a function of processing time and of radial coordinate, is shown in Fig. 4b. It can be seen that, as soon as boundary temperature exceeds the assumed external temperature (291.15 K) the outer layers start to transfer heat to the external environment. A temperature difference is established along the radial coordinate and, at the end of the process a difference of 6 K is predicted across the outer 9 mm layer of the sample. In both cases, the higher (+10 V with respect to previous discussed case) applied voltage set-point value results in a faster heating, that can be appreciated comparing, in Fig. 3 and Fig. 4, the temperature values reached by the sample centre after 150 s. Fig. 4 shows also that, as processing time passes, the increase in temperature is faster. This happens because the heating rate increases at higher temperatures: the higher is the temperature, the higher is the electrical conductivity and, assuming that the electric potential gradient is maintained at the set-point value, the heat generation within the sample will increase accordingly.Full-size image (44K)Fig. 3. Temperature plots, after 150 s of heating in ohmic cell, evaluated along the radial coordinate in the planar centre of the sample, as a function of different values of overall heat transfer coefficient U. Other conditions: applied voltage set-point 100 V, initial temperature = 279.15 K, external temperature = 286.15 K.Full-size image (121K)Fig. 4. Temperature plots, as a function of ohmic heating time, evaluated along the radial coordinate in the planar centre of the sample, when (a) perfect thermal insulation (U = 0 W m−2 K−1) or (b) heat losses (U = 50 W m−2K−1) is considered on the sample boundary. Other conditions: applied voltage set-point 110 V, initial temperature = 279.15, external temperature = 291.15 K.This is confirmed in Fig. 5, where heat generation is shown as a function of time. Given a constant potential difference and given that the electrical conductivity increases with temperature, heat generation will increase with time. It must be emphasized that, in a real system, the maintenance of a constant potential difference, while the electrical conductivity increases, implies an increasing consumption of electrical power. The mean value of heat generation is 1.8 × 106 W m−3. If this value is assumed constant for the heat source and is applied in the model, the resulting applied potential difference will assume a higher value at the beginning of theprocess and will decrease during the process as the electrical conductivity increases:(6)This is shown in Fig. 6, where applied voltage and electrical conductivity are plotted as a function of the processing time, assuming the previously quoted value for the heat source, for a thermally insulated ohmic cell.Full-size image (17K)Fig. 5. Variation of electrical conductivity and heat source Q gen during the process time, evaluated when perfect thermal insulation is considered on the sample boundary. Other conditions: applied voltage set-point 110 V, initial temperature = 279.15 K, external temperature = 291.15 K.Full-size image (16K)Fig. 6. Variation of electrical conductivity and applied voltage during the process time, for a fixed and constant value of heat source Q gen = 1.8 × 106 W m−3, evaluated when perfect thermal insulation is considered on the sample boundary.Fig. 7shows a comparison of time temperature profiles obtained in two special cases: (1) maintaining a constant applied voltage and (2) maintaining a constant heat generation. The temp erature after 150 s is virtually the same, whereas its time evolution is different. Of course, when Q gen is considered to be constant the heating rate is linear. This result means that given the linear relationship between electrical conductivity and temperature, a control system could be designed to drive the process along a predetermined path to reach the target temperature within the desired time.Full-size image (14K)Fig. 7. Comparison of heating, in terms of temperature-time evolution, when a fixed heat source (♦) or a fixed applied voltage (□) are considered in the model and when perfect thermal insulation is considered for sample boundary.In Table 2, comparison of results in terms of average deviation and greatest errors is shown. While a convective heat transfer coefficient of U = 0 W m−2 K−1 and higher values of U = 50 and 100 W m−2 K−1 gave large average deviations and greatest errors, a heat transfer coefficient of U= 5 W m−2K−1gave the best fit. In Fig. 8, measured and predicted temperature values (using U = 5 W m−2 K−1) are compared. Mean of root square error is 0.71 K, worst agreement being noted at thermocouple positions closer to the external surface at the start of the process. This was characterized by a temperature difference with respect to the simulated values of up to 2.07 K. Being 5 W m−2 K−1 the best fitting value for the overall convective heat transfer coefficient, the slice plots shown in Fig. 2a represents the expected temperature distribution within the sample at the process end. As edges appear colder, the model suggests that those areas have to be monitored during the process, since for purposes such as pasteurisation those will be critical areas. However, given the proximity to the elec trodes, this would make measurements in those areas very difficult. Colder shells could be reduced by better insulation which would lower the overall heat transfer coefficient. Fig. 4a shows that the cold areas disappeared whenperfect thermal insulation was considered.Table 2.Comparison of experimental and numerical results, as function of external heat transfer coefficient U U [W m2 K −1]A verage deviation [K] Greatest error[K] 01.312.63 50.71 2.07 100.91 2.19 501.62 3.49 1002.37 4.65Full-size image (43K)Fig. 8. Comparison of experimental (exp) and simulated (mod) results, as evaluated in the nine positions where thermocouples were placed: applied voltage set-point 100 V, initial temperature = 279.15 K, external temperature = 286.15 K, U = 5 W m −2 K −1.It may be noted that the model generally underestimated sample temperature relative to experimental values other than for the central point. Before the experiment starts, the outer layers of the sample will warm up during the preparatory phase: so, in experiments, initial temperature near the surface will be higher than the core temperature, while in our model a uniform initial temperature (279.15 K) was assumed. The incorporation of actual initial temperature conditions, as measured at initial time by a set of probes, rather than assumed values。
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a rXiv:h ep-ph/2831v223Oct22UB-ECM-PF 02/11The static potential:lattice versus perturbation theory in a renormalon-based approach Antonio Pineda 1Dept.d’Estructura i Constituents de la Mat`e ria and IFAE,U.Barcelona Diagonal 647,E-08028Barcelona,Catalonia,Spain Abstract We compare,for the static potential and at short distances,perturbation theory with the results of lattice simulations.We show that a renormalon-dominance picture explains why in the literature sometimes agreement,and another disagreement,is found between lattice simulations and perturbation theory depending on the different implementations of the latter.We also show that,within a renormalon-based scheme,perturbation theory agrees with lattice simulations.PACS numbers:12.38.Bx,12.38.Gc,12.38.Cy.1IntroductionThe static potential is the object more accurately studied by(quenched)lattice simulations. This is due to its relevance in order to understand the dynamics of QCD.On the one hand,it is a necessary ingredient in a Schr¨o dinger-like formulation of the Heavy Quarkonium.On the other hand,a linear growing behavior at long distance is signaled as a proof of confinement. Moreover,throughout the last years,lattice simulations[1,2,3]have improved their predic-tions at short distances allowing,for thefirst time ever,the comparison between perturbation theory and lattice simulations.Therefore,the static potential provides a unique place where to test lattice and/or perturbation theory(depending on the view of the reader),as well as an ideal place where to study the interplay between perturbative and non-perturbative physics.This is even more so since the accuracy of the perturbative prediction of the static potential has also improved significantly recently[4,5,6,7].Let usfirst review the status of the art nowadays.The prediction for the perturbative static potential at two loops[4]indicated the failure(non-convergence)of perturbation theory at amazingly short distances.This failure of perturbation theory is not solved by the inclusion of the leading logs at three loops computed in[5,6]nor by performing a renormalization group(RG)improvement of the static potential at next-to-next-to-leading log(NNLL)[7].1 On the other hand,it was soon realized that the static potential suffered of renormalons [10]and that the leading one(of O(ΛQCD))cancelled with the leading renormalon of twice the pole mass[11].Nevertheless,the prediction of perturbation theory for the slope of the static potential should not suffer,in principle,from this renormalon and could be compared with lattice simulations,which,indeed,only predict the potential up to a constant.This comparison was performed in Ref.[12],where they compared the RG improved predictions (without including ultrasoft log resummation)of perturbation theory up to next-to-next-to-leading order(NNLO)with lattice simulations.They indeed found that the discrepancies with lattice simulations and the lack of convergence of the perturbative series remained.They also found that the difference between perturbation theory and lattice could be parameterized by a linear potential in a certain range.Therefore,it seemed to support the claims of some groups[13,14]of the possible existence of a linear potential at short distances.Such claims contradict the predictions of the operator product expansion(OPE),which state that the leading non-perturbative corrections are quadratic in distance at short distances2.On the other hand,driven by the analysis of Refs.[15],it has been argued[16]that, within a renormalon based picture,perturbation theory agrees with the phenomenological potentials aimed to describe Heavy Quarkonium.For his study,he used the static version of the1S mass and the upsilon expansion[17],which cancels the leading renormalon and relate the1S mass to the1There also exists a computation of the running of the Coulomb potential in vNRQCD[8]with the same precision that disagrees with the one obtained in pNRQCD[7].At this respect,we would like to report on a recent computation[9]of the4-loop double log term of the Coulomb potential proportional to C3Aβ0that agrees with the pNRQCD result and disagrees with the vNRQCD one.2This contradiction is indeed so only if one believes that perturbation theory can be applied for the shortest distances available in lattice simulations∼1−4GeV.We thank V.I.Zakharov for stressing this point to us.by lattice simulations at short distances by using the force instead of the potential as the basic tool without the need to talk about renormalons.In this paper,we would like to try to clarify further the above issues and support the renormalon dominance picture by comparing the potential computed in lattice with the RS static potential(a renormalon free definition of the potential obtained in Ref.[20]).2On-shell schemeThe energy of two static sources in a singlet configuration reads(in the on-shell(OS)scheme)iE(r)=2m OS+limT→∞n f 0246227116376β0α3s (r −1)log αs (r −1)3N c r 2 ∞0dte −t (V o,OS −V s,OS ) g E a (t )φ(t,0)adj ab g E b (0) (νus ).(7)At the order of interest V o,OS ≡1r and V s,OS is approximated to its leading order value:−C F αs MS =0.602(48)r −10[23],since our aimwill be to compare with lattice simulations.r 0V OS (r )0.150.20.250.30.350.40.450.5-4-3-2-1r/r 0Figure 1:Plot of r 0V OS (r )at tree (dashed line),one-loop (dash-dotted line),two-loops (dotted line)and three loops (estimate)plus the leading single ultrasoft log (solid line).For the scale of αs (ν),we set ν=1/0.15399r −10.νus =2.5r −10.Now,we want to check the convergence of the series within perturbation theory.We first consider the perturbative static potential without trying to resum ln rνlogs,ie.for a fixed scale νfor αs (ν)(Eq.(3)).We show our results in Fig.1,where we have chosen ν=1/0.15399r −10.We see that it does not converge to a value.We next try with ln rνresummation (Eq.(5)),since these logs could be large.We show our results in Fig.2.We find the same problem and moreover the slope appears to be different in both cases.The situation appears to be puzzling.Let us now compare with lattice simulations.These predict the energy of an static quark-antiquark system up to an r -independent constant 4:E latt .(r )=k latt .+lim T →∞i3However,it remains to be seen whether,once V 3is exactly computed and the O (r 2)renormalon were also subtracted,the ultrasoft logs would be a subleading effect compared with finite pieces.4Therefore,due to the unknown constant it can not be related with the underlying theory (QCD)and,for instance,obtain the mass.r 0V OS (r )0.150.20.250.30.350.40.450.5-7-6-5-4-3-2r/r 0Figure 2:Plot of r 0V OS (r )at tree (dashed line),one-loop (dash-dotted line),two-loops (dotted line)and three loops (estimate)plus the RG expression for the ultrasoft logs (solid line).For the scale of αs (ν),we set ν=1/r .νus =2.5r −10.The value of this constant varies according to the order the perturbative computation has been done,ie.k pert .(r ′)=k 0(r ′)+k 1αs (r ′)+k 2α2s (r ′)+ (11)We will consider the lattice data of Refs.[1,2].They both appear to be perfectly compatible with each other for finite lattice spacings.In any case,the lattice data of Ref.[2],being more recent,appears to have smaller errors with a very small spread of the points around the fitted curve.Here,in order to get the highest possible precision,we will use the lattice data of Ref.[2]for which the continuum limit has been reached.For comparison with the lattice points at finite lattice spacing of Ref.[1]and for a somewhat a larger range,we refer to the 1st version of this paper sent to the web.The physical outcome is,in any case,the same.The comparison with lattice is performed in Fig.3for the perturbative result without ln(rν)resummation (νconstant)and in Fig.4for the perturbative result with ln(rν)resummation (ν=1/r ).As explained above,we have added a constant to the perturbative potential (different at each order)as to make it equal to the lattice potential at r =0.15399r 0.We see a completely different behavior in both cases.Whereas for the latter,the agreement goes worse as we increase the order of our calculation,for the former the agreement with lattice improves 5.Indeed,it is quite remarkable that lattice simulations are precise enough to see the log behavior of αs predicted by asymptotic freedom.In the next section we will explain the above behavior (why sometimes perturbation theory can describe lattice data and some others not)within an controlled framework where the renormalon is taken into account.r 0(V OS (r )−V OS (r ′)+E latt.(r ′))0.150.20.250.30.350.40.450.5-1.5-1.25-1-0.75-0.5-0.25r/r 0Figure 3:Plot of r 0(V OS (r )−V OS (r ′)+E latt.(r ′))versus r at tree (dashed line),one-loop (dash-dotted line),two-loops (dotted line)and three loops (estimate)plus the leading single ultrasoft log (solid line)compared with the lattice simulations [2]E latt.(r ).For the scale of αs (ν),we set ν=1/0.15399r −10.νus =2.5r −10and r ′=0.15399r 0.3RS schemeThe RS scheme was defined in Ref.[20]aiming to eliminate the renormalons of the matching coefficients appearing in Heavy Quarkonium calculations.In particular,the leading renor-malon of the heavy quark mass and the static potential.We refer to Ref.[20]for details.Here,we just write the relevant formulas needed for our analysis.Analogously to the OS scheme,the energy of two static sources in a singlet configuration reads E s (r )=2m RS (νf )+ lim T →∞i 2π n αn +1s (νf )∞ k =0c k Γ(n +1+b −k )6Actually,we are going to use in this paper the RS’scheme defined in Ref.[20]instead of the RS scheme,since we believe it has a more physical interpretation.Nevertheless,we will denote it in this paper as RS scheme in order to simplify the notation.In any case,the physical picture does not change.The results would also converge towards the result predicted by lattice simulations but with a different pattern.r 0(V OS (r )−V OS (r ′)+E latt.(r ′))0.150.20.250.30.350.40.450.5-2.5-2-1.5-1-0.5r/r 0Figure 4:Plot of r 0(V OS (r )−V OS (r ′)+E latt.(r ′))versus r at tree (dashed line),one-loop (dash-dotted line),two-loops (dotted line)and three loops (estimate)plus the RG expression for the ultrasoft logs (solid line)compared with the lattice simulations [2]E latt.(r ).For the scale of αs (ν),we set ν=1/r .νus =2.5r −10and r ′=0.15399r 0.The result reads (for n f =0)N m =0.424413+0.174732+0.0228905=0.622036,(14)where each term corresponds to a different power in u (in the Borel plane)of the calculation (see Ref.[20]for details).We see a nice convergence.This number will be the one we will use in the following.This number should be equal to −2N V ,where N V is the normalization factor of the renormalon of the static potential.N V was also approximately computed in Ref.[20].For n f =0,it readsN V =−1.33333+0.499433−0.338437=−1.17234.(15)In this case the convergence is not so good but we have an alternating series.In any case,we see that both values appear to be quite close:22N m +N VV s,RS(r)≡V s,RS(r;νus;νf)was defined in Ref.[20](note that we expand V s andδm RS with the sameαs):V s,RS(r)=V s+2δm RS=∞n=1(V n+2δm RS,n)αn s=∞ n=0V(0)RS,nαn+1s.(18)Due to the leading renormalon,the behavior of the perturbative expansion at large orders of V n reads[24,20]V n n→∞=N Vν β0Γ(1+b) 1+b(n+b)(n+b−1)c2+··· .(19)Therefore,by addingδm RS to V s we expect to cancel the renormalon of the static potential. Indeed,what we want is to obtain the renormalon cancellation order by order in perturbation theory.This means to kill the O(n!)behavior of the coefficient multiplying the O(αn s)term of V s with the O(n!)behavior that appears inδm RS such that V RS enjoys nicer convergence properties.In principle,this cancellation should hold for an arbitraryνand,in particular, forν=1/r.This,indeed,is the key observation of this paper and it will become relevant later on in order to explain the results in the previous section as well as in the literature.In principle,anyνf should cancel the renormalon of the static potential(we have the constraint,though,thatνf should be large enough to fulfillαs(νf)≪1).If we re-expand δm RS(νf)in terms ofαs(ν),the renormalon is still kept inδm RS(νf)but new terms are generated,which,nevertheless,should not belong to the renormalon.In other wordsδm RS(νf)=δm RS(ν)+F(ν;νf),(20) where the Borel transform of F(ν;νf)should be analytic at u=1/2in the Borel plane.This can be easily seen in the largeβ0limit.In more formal terms what we have isΛMS=constant Im[δm RS(ν)]with the same constant by definition(indeed this is what defines the renormalon).Therefore, the conclusion is thatIm[F(ν;νf)]=0to the order of interest,concluding that F does not have the closest singularity in the Borel plane.Note that in order to have the structure of Eq.(20)is necessary to have the complete renormalon contribution,ie.to all orders in perturbation theory.If we have the renormalon to some given order in perturbation theory,a change of the scale will produce large(renormalon-related)terms that would not cancel since we do not have the complete sum.Indeed,this is the explanation why infixed order perturbation theory one has to expand onαs at the very same scale for the renormalon and the OS result in order to achieve the renormalon cancellation order by order inαs.On the other hand,νf can not be arbitrarily large.Otherwise the power counting is broken.This restrictsνf<∼1/r in order to ensure the counting V RS∼O(αs/r).In our case, we will setνf=2.5r−10∼1GeV.In any case,when studying the slope of the potential,the result should be independent onνf,asδm RS(νf)is just an r-independent constant.At thisrespect,we should say that this is indeed so to a large extent.If we take νf =5r −10∼2GeVagreement with lattice is also obtained 7.One could also think of setting νf =1/r .This would mean to subtract an r -dependent constant to the static potential.This is not what it is done in lattice simulations since they are arbitrary up to a r -independent constant.Therefore,this would not agree with lattice simulations.r 0V RS (r )0.150.20.250.30.350.40.450.5-2.25-2-1.75-1.5-1.25-1-0.75-0.5r/r 0Figure 5:Plot of r 0V RS (r )at tree (dashed line),one-loop (dash-dotted line),two-loops (dotted line)and three loops (estimate)plus the RG expression for the ultrasoft logs (solid line).For the scale of αs (ν),we set ν=1/r .νus =2.5r −10and νf =2.5r −10.In conclusion,by using V RS ,we expect the bad perturbative behavior due to the renor-malon to disappear.Let us see that this is indeed so.Working analogously to the OS scheme,we consider the RS potential at different orders in perturbation theory with ln(rν)resummation or not.We display our results in Figs.5and 6.In the first case,the ln(rν)resummation is achieved by setting ν=1/r and the ultrasoft log resummation is also in-cluded.In the second case,we set ν=1/0.15399r −10and only the leading single ultrasoft log is included.We see that now we do not have the gap between different orders in the pertur-bative expansion (or it is dramatically reduced).Moreover,we do not have a (dramatically)different behavior of the slope of the potential;ln(rν)resummation or not converges to the same value.We can now compare with lattice simulations:Figs.3and 7.We work analogously to the OS scheme.Now,the constant we have to add is approximately αs -independent,reflecting that we have accurately achieved the renormalon cancellation.We see that our results are convergent to the same potential,which,as we can see,corresponds to the lattice potential.r 0V RS (r )0.150.20.250.30.350.40.450.5-2.25-2-1.75-1.5-1.25-1-0.75r/r 0Figure 6:Plot of r 0V RS (r )at tree (dashed line),one-loop (dash-dotted line),two-loops (dotted line)and three loops (estimate)plus the leading single ultrasoft log (solid line).For the scale of αs (ν),we set ν=1/0.15399r −10.νus =2.5r −10and νf =2.5r −10.The case without ln(rν)resummation is exactly equal to the OS case,ie.to Fig.3,since it is just equivalent to add a r-independent constant at each order in αs .This explains,within the renormalon dominance picture,the success of that specific OS scheme calculation;it is just equivalent to an specific case of the renormalon based calculation:ν=constant .Therefore,perturbation theory without log resummation can explain lattice data up to r ∼0.5r 0by subtracting a r-independent constant at each order in perturbation theory.This fact is understandable if the factorization scale chosen is not very far of 1/r so that the RG does not play a decisive role plus the fact that subtracting a constant kills the renormalon.However,now,we are not restricted to take ν=constant but we can take ν=1/r ,which allows us to resum the ln(rν)terms and yet cancel the renormalon as we can nicely see in Fig.7.Within the renormalon dominance picture,we can also explain why perturbation theory with ln(rν)resummation could not explain lattice data (see Fig.4)even if subtracting a r-independent constant at each order in perturbation theory.In particular,this would explain the disagreement found in Ref.[12].The explanation of this fact is that ln(rν)resummation is equivalent to set αs (r )as the expansion parameter.Therefore,the expansion parameter is a function of r and,consequently,the amount to be subtracted at each order in αs (r )in order to cancel the renormalon is also r -dependent.It follows that the (perturbative)renormalon cancellation can not be achieved by only subtracting a r -independent constant at each order in αs (r )as it was done in Fig.4.We would like now to understand the agreement between lattice [18](or potential models[16])and perturbation theory if the static potential is reconstructed from the force in ther 0(V RS (r )−V RS (r ′)+E latt.(r ′))0.150.20.250.30.350.40.450.5-1.5-1.25-1-0.75-0.5-0.25r/r 0Figure 7:Plot of r 0(V RS (r )−V RS (r ′)+E latt.(r ′))versus r at tree (dashed line),one-loop (dash-dotted line),two-loops (dotted line)and three loops (estimate)plus the RG expression for the ultrasoft logs (solid line)compared with the lattice simulations [2]E latt.(r ).For the scale of αs (ν),we set ν=1/r .νf =νus =2.5r −10and r ′=0.15399r 0.following way:V (r )= rr 0dr ′F (r ′)+V (r 0)= r r 0dr ′dV (r ′)r 2=C Fr ∞ n =0n ! β0αs (1/r )2π n .(23)Both terms have the renormalon (in the large β0approximation)so that they cancel each other.We expect that higher orders computations will reconstruct the QCD renormalon but yet the renormalon cancellation should remain at any order since the same (partial)piece of the renormalon appears for r dr ′F n −loops (r ′)than for r 0dr ′F n −loops (r ′).This ex-plains within a renormalon-dominance approach the convergence of computations using this framework even if no reference to renormalon was made for these calculations.It is worth stressing that within this renormalon-based scheme calculation,we can now account for the logs correctly by setting ν=1/r (see Fig.7).On the other hand,we introduce some errors when fixing ν=1/r ,since we are only able to perform an approximate computation of the renormalon,which do not exist in the calculation of the slope with ν=constant .The two things compete with each other in the final accuracy of the result (compare Figs.3and 7).Indeed,once the renormalon cancellation has been achieved,the resummation of logs does not appear to be very important.At least,if we do not choose our scale very far from the typical scales at study.If we go to scales smaller than 2.5r −10,the calculation with ν=1/r appears to give better results (compatible with lattice,although with larger errors,up to amazingly long distances (∼0.8r 0))than the calculation with fixed ν(see Fig.8).This may signal that log resummation becomes important for these scales (note that we have chosen ν=1/0.15399r −10as the starting point of the log evolution,for a smaller value of νan improvement may be obtained).It should be studied further whether perturbation theory can indeed describe lattice data in the regime 0.5−0.8r 0,since this would support the claims of Ref.[16]in this direction.r 0(V RS (r )−V RS (r ′)+E latt.(r ′))r 0(V RS (r )−V RS (r ′)+E latt.(r ′))00.20.40.60.81-1.5-1-0.50.5100.20.40.60.81-1123r/r 0r/r 0a )b )Figure 8:Figs.a)and b)correspond to Figs.3and 7respectively up to the value r =1.1r 0.The main result of this section is to show that all the different results found in the previous and this section as well as in the literature about the convergence (or not convergence)of the perturbative series can be explained by the presence of the renormalon.We have also shown that,with a renormalon-based scheme,agreement with lattice is obtained.The point is that we now know the constant to be subtracted and its dependence in αs ,therefore,we can set αs at the same scale and obtain the cancellation for any r .In this way,we obtain the log resummation and the renormalon cancellation.One potential problem is that other logs (ln(rνf ))appear (in the physical,finite mass,case this problem does not really show up because one usually sets νf <∼1/r being r the typical size of the system).4Bounds on short-distance non-perturbative poten-tialsWe now study possible non-perturbative effects in the static potential.Thefirst thing to notice is that any non-perturbative effects should be small and compatible with zero since perturbation theory is able to explain lattice data within errors.We can make this statement more quantitative by using the lattice data obtained in Ref.[2]where the continuum limit has been reached.For these lattice points the systematic and statistic errors are very small (smaller than the size of the points).Therefore,the main sources of uncertainty of our (perturbative)evaluation come from the uncertainty in the value ofΛMS whereas theouter band is meant to estimate the uncertainty due to higher orders in perturbation theory by allowing c0to change by±146.This is half its value according to the estimate in Table 1.This may seem a conservative variation if we take into account that the difference with the estimate obtained using Pade-approximats[22]isδc0∼20.r/r0 Figure9:Plot of r0(V RS(r)−V RS(r′)+E latt.(r′))versus r at three loops(estimate)plus the leading single ultrasoft log(dashed line)compared with the lattice simulations[2]E latt.(r). For the scale ofαs(ν),we setν=1/0.15399r−10.νus=2.5r−10and r′=0.15399r0.The inner and outer band are meant to estimate the errors inΛ8We have performed the estimation of the errors with the results of Fig.3(ν=constant),since they do not introduce errors due to the evaluation of the renormalon.Nevertheless,a similar conclusion had been achieved if the analysis had been done with the results of Fig.7(ν=1/r).4.1Bounds on a short-distance quadratic potentialThe non-perturbative effects should be encoded within Eq.(7).In general,this equation is a convolution of two scales:ΛQCD andαs/r.The explicit functionality is unknown since it involves the knowledge of the details of the non-perturbative dynamics.In the formal limit 1/r≫ΛQCD≫αs/r,it is possible to know the scaling of the potential inΛQCD and r based on dimensional arguments[27]:δE US(r,νus)≃T FMS.Assuming a non-perturbative potential V∼Ar2,we obtain|A|<∼0.6r−30(25) from the variation ofΛMS could be improved,they would provide oneof the most promising ways to control the errors in the determination of the bottom MSfrom the static potential data.4.2Bounds on a short-distance linear potentialThe usual confining potential,δV=σr,goes with an slopeσ=0.21GeV2.In lattice units we take:σ=1.35r−20.Can we discriminate such potential at short distances with the available lattice data?The answer is yes as we can see from Fig.10.9The introduction of a linear potential at short distances with such slope is not consistent with lattice simulations. This is even so after the errors considered in Fig.9have been included.This should not come as a surprise since this linear potential appears as an effect of long distance(not short distance)and it is not expected to appear from Eq.(7).Therefore,it follows that the use of the Cornell potential(with the perturbative static potential emanated from QCD instead of a pure1/r potential times afitted constant)as a phenomenologicalfit of the static potential introduces systematic errors if the typical inverse Bohr radius scale of the heavy quarkoniumsystem to study lye in the short distance regime as it is the case,for instance,for theΥ(1S).r/r0 Figure10:Plot of r0(V RS(r)−V RS(r′)+E latt.(r′)+σ(r−r′))versus r at three loops(estimate) plus the leading single ultrasoft log compared with the lattice simulations[2]E latt.(r).For the scale ofαs(ν),we setν=1/0.15399r−10.νus=2.5r−10and r′=0.15399r0.The dashed band is meant to estimate the combined error dueΛresult can be explained by the presence of the renormalon.In particular,we can explain why a calculation(Fig.3)within perturbation theory can agree with lattice data,if the perturbative expansion is made withαs(ν)withνconstant,without an explicit reference to the renormalon,but not if the expansion is made withαs(1/r)(Fig.4).This explanation is given in a renormalon-based approach in a unified way.Moreover,our method allows to set ν=1/r and,therefore,resum the ln(rν)logs besides of cancelling the renormalon(Fig.7).We have tried tofind bounds on possible non-perturbative potentials at short distances. 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