On the co-polarized phase difference for oil spill observation

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圆极化与线计划的设置

圆极化与线计划的设置

圆极化与线计划的设置英文回答:Circular polarization and linear polarization are two different settings used in various applications,particularly in the field of optics and telecommunications. Let's discuss each of them separately.Circular polarization refers to the polarization stateof an electromagnetic wave in which the electric fieldvector rotates in a circular pattern as the wave propagates. This rotation can be either clockwise or counterclockwise. Circular polarization is achieved by combining two orthogonal linearly polarized waves with a phase difference of 90 degrees. The resulting circularly polarized wave has equal amplitude in both orthogonal directions and aconstant magnitude of electric field vector.Circular polarization has several advantages overlinear polarization. One of the main advantages is itsimmunity to certain types of interference, such as reflections. This makes circularly polarized waves idealfor applications where signal degradation due toreflections is a concern, such as satellite communications. Circular polarization also allows for better penetration through obstacles, making it suitable for applications in wireless communication systems.Linear polarization, on the other hand, refers to the polarization state of an electromagnetic wave in which the electric field vector oscillates in a single plane. This can be either horizontal or vertical, or any other angle in between. Linear polarization is achieved by transmitting a wave with a specific orientation of the electric field vector.Linear polarization is commonly used in many applications, including television broadcasting, radar systems, and optical communication. It allows for efficient transmission and reception of signals, as the receiver antenna can be aligned with the same polarization as the transmitted signal. However, linearly polarized waves aremore susceptible to interference from reflections andcross-polarization effects, which can lead to signal degradation.In terms of setting up circular polarization and linear polarization, different techniques and devices can be used. For circular polarization, a combination of two orthogonal linearly polarized waves with a phase difference of 90 degrees is required. This can be achieved using devices such as quarter-wave plates or circular polarizers.For linear polarization, the orientation of theelectric field vector needs to be controlled. This can be done using devices such as polarizers or waveplates. Polarizers are commonly used to convert unpolarized light into linearly polarized light by selectively transmitting waves with a specific polarization orientation. Waveplates, on the other hand, can be used to rotate the polarization state of a wave by a desired angle.中文回答:圆极化和线极化是在光学和通信领域中使用的两种不同设置。

Diffusion and Separation of CO2 and CH4 in Silicalite, C168 Schwarzite,and IRMOF-1 A Com

Diffusion and Separation of CO2 and CH4 in Silicalite, C168 Schwarzite,and IRMOF-1 A Com

Diffusion and Separation of CO2and CH4in Silicalite,C168Schwarzite, and IRMOF-1:A Comparative Study from Molecular DynamicsSimulationRavichandar Babarao and Jianwen Jiang*Department of Chemical&Biomolecular Engineering,National Uni V ersity of Singapore,Singapore117576Recei V ed No V ember3,2007.Re V ised Manuscript Recei V ed February28,2008Recently we have investigated the storage and adsorption selectivity of CO2and CH4in three different classes of nanoporous materials s silicalite,IRMOF-1,and C168schwarzite through Monte Carlo simulation(Babarao,R.;Hu, Z.;Jiang,ngmuir,2007,23,659).In this work,the self-,corrected,and transport diffusivities of CO2and CH4 in these materials are examined using molecular dynamics simulation.The activation energies at infinite dilution are evaluated from the Arrheniusfits to the diffusivities at various temperatures.As loading increases,the self-diffusivities in the three frameworks decrease as a result of the steric hindrance;the corrected diffusivities remain nearly constant or decrease approximately linearly depending on the adsorbate and framework;and the transport diffusivities generally increase except for CO2in IRMOF-1.The correlation effects are identified to reduce from MFI,C168to IRMOF-1, in accordance with the porosity increasing in the three frameworks.Predictions of self-,corrected,and transport diffusivities for pure CO2and CH4from the Maxwell-Stefan formulation match the simulation results well.In a CO2/CH4mixture,the self-diffusivities decreases with loading,and good agreement is found between simulated and predicted results.On the basis of the adsorption and self-diffusivity in the mixture,the permselectivity is found to be marginal in IRMOF-1,slightly enhanced in MFI,and greatest in C168schwarzite.Although IRMOF-1has the largest storage capacity for CH4and CO2,its selectivity is not satisfactory.I.IntroductionNanoporous materials have been widely utilized in catalysis, ion exchange,gas storage,and purification.1In the nanodomain,fluids diffuse significantly differently from bulkfluids because of spatial confinement and surface interaction.2Understanding such diffusion behavior is not only of fundamental interest but also of central importance for industrial applications.There have been a large number of experimental studies on the determination of diffusivities in zeolites,carbons,and other materials.3,4 Nevertheless,with ever-growing computational power,com-putationally based molecular simulation has played an increas-ingly important role in nanoscience and nanotechnology.5 Simulation on the nanoscale can provide microscopic pictures that are experimentally inaccessible or difficult,if not impossible, to obtain.As a consequence,deeper insight can be gained from molecular simulation,thus assisting the rational design of new materials of increasing complexity.We will give a brief review of simulation studies on diffusion in various nanomaterials,among which zeolites are the most commonly investigated.In the early1990s,Theodorou and co-workers examined the self-diffusion of CH4in silicalite using equilibrium molecular dynamics(MD)6and transport diffusion using both equilibrium and nonequilibrium MD.7Recently,they simulated the self-and transport diffusion of CO2and N2in silicalite over a wide range of occupancies by using various forcefields and made a comparison with experimental data.8,9 Sholl and co-workers computed the transport diffusion of CH4 and CF4in silicalite and found that the Darken approximation is valid only for CH4and deviates strongly for CF4at all temperatures.10From the self-and transport diffusion of seven light gases separately in silicalite at room temperature,they observed that the self-diffusivity decreases with increased loading as a result of steric hindrance;however,the reverse is true for transport diffusivity.11They compared the simulation and experimental results for the permeation of the CH4/CF4mixture through silicalite and found that atomistic modeling correctly predicted silicalite to be more selective for CF4.12From simulation, they investigated the effects of pore shape and connectivity on the diffusion of gases in silica zeolites13and also the effects of the sweep gas and porous support on zeolite membranes using atomic and continuum models.14Recently,Sholl published a comprehensive review on understanding diffusion in crystalline nanoporous materials using simulations.15Snurr and co-workers made thefirst comparison for the self-diffusivities of the CH4/ CF4mixture in silicate between simulation and NMR experiments, and good agreement was observed.16They inspected the structural and transport properties of CF4and n-alkane mixtures in faujasite from MD simulation and found that whereas the main-term transport diffusivities are greater than their self-diffusivity counterparts the cross-term diffusivities are1order of magnitude*Author to whom correspondence should be addressed.Tel:(65)6516 5083.Fax:(65)67791936.E-mail:chejj@.sg.(1)Macilwain,C.Nature2000,405,730.(2)Martin,C.R.;Siwy,Z.Nat.Mater.2004,3,284.(3)Karger,J.;Ruthven,D.Diffusion in Zeolites and Other Microporous Solids; Wiley:New York,1992.(4)Demontis,P.;Suffritti,G.B.Chem.Re V.1997,97,2845.(5)Drexler,put.Theor.Nanosci.2006,3,1.(6)June,R.L.;Bell,A.T.;Theodorou,D.N.J.Phys.Chem.1990,94,8232.(7)Maginn,E.J.;Bell,A.T.;Theodorou,D.N.J.Phys.Chem.1993,97,(8)Makrodimitris,K.;Papadopoulos,G.K.;Theodorou,D.N.J.Phys.Chem. B2001,105,777.(9)Papadopoulos,G.K.;Jobic,H.;Theodorou,D.N.J.Phys.Chem.B2004, 108,12748.(10)Skoulidas,A.I.;Sholl,D.S.J.Phys.Chem.B2001,105,3151.(11)Skoulidas,A.I.;Sholl,D.S.J.Phys.Chem.B2002,106,5058.(12)Skoulidas,A.I.;Bowen,T.C.;Doelling,C.M.;Falconer,J.L.;Noble, R.D.;Sholl,D.S.J.Membr.Sci.2003,227,123.(13)Skoulidas,A.I.;Sholl,D.S.J.Phys.Chem.A2003,107,10132.(14)Skoulidas,A.I.;Sholl,D.S.AIChE J.2005,51,867.(15)Sholl,D.S.Acc.Chem.Res.2006,39,403.5474Langmuir2008,24,5474-5484smaller than the main-term diffusivities.17In addition,they examined the permeances of CH4and CF4through faujasite18 and evaluated the diffusivities for a binary mixture of CH4/CF4, C3H8/CF4,n-C4H10/CF4,and C2H6/n-C4H10in faujasite at300 K.19Krishna and co-workers reported a kinetic Monte Carlo (MC)simulation for the self-diffusion of the CH4/CF4mixture in silicalite,20simulated the self-diffusion of pure CH4and CO2 and an equimolar mixture at a wide range of loading in MFI, CHA,and DDR zeolites,21and screened12different zeolites to determine the best one for separation of CO2and CH4.22 Furthermore,they investigated the correlation effects in the diffusion of CH4and CF4in the MFI zeolite from MD simulation and the Maxwell-Stefan(MS)formulation,respectively.23Jost et al.simulated the diffusion of the CH4/Xe mixture in silicalite and compared it with the pulsedfield gradient nuclear magnetic resonance and found that the simulation and experimental results were in accordance with each other.24Moulijn and co-workers investigated the separation of CH4/C2H6and CH4/C3H8mixtures in silicalite as a function of temperature,pressure,and composi-tion.25The role of adsorption in single and binary permeation of CH4and CO2through a silicalite membrane was further examined by them,in which the generalized MS formulation was adapted in combination with the ideal adsorbed solution theory(IAST)to model binary permeation.26Since its discovery in1991,carbon nanotubes(CNTs)27have stimulated considerable interest,including their potential use for membrane separation as a result of their well-defined nanoscale structures.28Sholl,Johnson,and co-workers simulated the self-and transport diffusivities of light gases such as H2,CH4,Ar,and Ne in CNTs and in two zeolites with comparable pore sizes and found that the diffusion is1-3orders of magnitude faster in CNTs than in silicalite depending on loading.29,30Similar behavior was observed by them for CO2and N2in CNTs at room temperature,in which the linear and spherical models for CO2 were found to give roughly identical diffusivity.31They examined the transport diffusivity in rigid,defect-free CNTs in which an efficient thermostat was employed to account for the influence of nanotubeflexibility.The inclusion offlexibility reduces transport diffusion by roughly1order of magnitude at a pressure close to zero;in contrast,at high pressures the transport diffusion inflexible and rigid nanotubes is very similar,differing by a factor of2on average.32Furthermore,they predicted the binary permeance of the CH4/H2mixture through defect-free CNTs acting as a membrane at room temperature and showed that the mixture diffusion is also rapid as compared to single-component diffusion.33Arora and Sandler studied the mass transport of O2, N2,and their mixture in a CNT and demonstrated that good kinetic selectivity could be achieved for air separation by carefully adjusting the upstream and downstream pressures.34They further investigated the separation of O2and N2in a CNT with a constriction,which leads to high transport resistance to N2while allowing O2to pass at a much higher rate even though these gases have very similar sizes and energetics.35Combining the configurational-bias MC method with the dual control-volume grand canonical MD simulation,Firouzi et al.examined the transport and separation of binary n-alkane mixtures as well as CO2and n-alkane mixtures in CNTs under an external potential gradient.36Jakobtorweihen et al.proposed a novel algorithm for modeling the influence of host latticeflexibility and applied it to the investigation of the diffusion of chain molecules and mixtures in CNTs.37,38Within the past few years,a new family of naonporous materials,namely,metal organic frameworks(MOFs),have been developed.39–41With the well-located metal oxide clusters and organic linkers,MOFs allow the formation of porous frameworks with a wide variety of architecture,topology,and pore size and provide almost unlimited opportunities to develop,control,and tune structures for specific pared to zeolites and CNTs,the simulation studies for diffusion in MOFs are relatively few.Skoulidas found from MD simulation that the transport diffusivity of Ar in Cu-BTC at room temperature differs from the self-diffusivity by2orders of magnitude at high loadings.42Sarkisov et al.simulated the self-diffusivities of CH4, n-C5H12,n-C6H14,n-C7H6,and cyclo-C6H14in MOF-5,which are of the same order of magnitude as in silicalite.43Skoulidas and Sholl examined the self-and transport diffusion of light gases in MOF-2,MOF-3,MOF-5,and Cu-BTC.44Yang and Zhong performed simulations for the adsorption and diffusion of H2in IRMOFs.45Stallmach et al.reported thefirst experimental data on diffusion in MOF-5and demonstrated that organic gas molecules diffuse quite rapidly in MOFs.46Amirjalayer et al. conducted MD simulations of C6H6in IRMOF-1and found that the diffusion and activation energy of C6H6are considerably smaller in theflexible framework compared to those in the rigid one.47To the best of our knowledge,however,there is no simulation work to date for mixture diffusion in MOFs.The above-mentioned studies were primarily from numerical simulations on diffusion in zeolites,CNTs,and MOFs.Analytical predictions of mixture diffusion solely from single components have been a major challenge in the past few decades.Nevertheless, the Maxwell-Stefan(MS)formulation developed by Krishna and co-workers is an advance toward this end,as recently(17)Sanborn,M.J.;Snurr,R.Q.Sep.Purif.Technol.2000,20,1.(18)Sanborn,M.J.;Snurr,R.Q.AIChE J.2001,47,2032.(19)Chempath,S.;Krishna,R.;Snurr,R.Q.J.Phys.Chem.B2004,108, 13481.(20)Paschek,D.;Krishna,ngmuir2001,17,247.(21)Krishna,R.;van Baten,J.M.;Garcia-Perez,E.;Calero,S.Chem.Phys. Lett.2006,429,219.(22)Krishna,R.;van Baten,J.M.Chem.Eng.J.2007,133,121.(23)Skoulidas,A.I.;Sholl,D.S.;Krishna,ngmuir2003,19,7977.(24)Jost,S.;Bar,N.K.;Fritzsche,S.;Haberlandt,R.;Karger,J.J.Phys. Chem.B1998,102,6375.(25)van de Graaf,J.M.;Kapteijn,F.;Moulijn,J.A.AIChE J.1999,45,497.(26)Zhu,W.D.;Hrabanek,P.;Gora,L.;Kapteijn,F.;Moulijn,J.A.Ind.Eng. Chem.Res.2006,45,767.(27)Iijima,S.Nature1991,354,56.(28)Ajayan,P.M.;Zhou,O.Z.Applications of Carbon Nanotubes.In Carbon Nanotubes;Springer-Verlag Berlin:Berlin,2001;Vol.80;p391.(29)Skoulidas,A.I.;Ackerman,D.M.;Johnson,J.K.;Sholl,D.S.Phys.Re V. Lett.2002,89.(30)Ackerman,D.M.;Skoulidas,A.I.;Sholl,D.S.;Johnson,J.K.Mol.(33)Chen,H.B.;Sholl,D.S.J.Membr.Sci.2006,269,152.(34)Arora,G.;Sandler,S.I.J.Chem.Phys.2006,124.(35)Arora,G.;Sandler,S.I.Nano Letters2007,7,565.(36)Firouzi,M.;Nezhad,K.M.;Tsotsis,T.T.;Sahimi,M.J.Chem.Phys. 2004,120,8172.(37)Jakobtorweihen,S.;Verbeek,M.G.;Lowe,C.P.;Keil,F.J.;Smit,B. Phys.Re V.Lett.2005,95,044501.(38)Jakobtorweihen,S.;Lowe,C.P.;Keil,F.J.;Smit,B.J.Chem.Phys. 2007,127,024904.(39)Yaghi,O.M.;O’Keeffe,M.;Ockwig,N.W.;Chae,H.K.;Eddaoudi,M.; Kim,J.Nature2003,423,705.(40)Eddaoudi,M.;Kim,J.;Rosi,N.;Vodak,D.;Wachter,J.;O’Keefe,M.; Yaghi,O.M.Science2002,295,469.(41)Rosi,N.L.;Eckert,J.;Eddaoudi,M.;Vodak,D.T.;Kim,J.;O’Keeffe, M.;Yaghi,O.M.Science2003,300,1127.(42)Skoulidas,A.I.J.Am.Chem.Soc.2004,126,1356.(43)Sarkisov,L.;Duren,T.;Snurr,R.Q.Mol.Phys.2004,102,211.(44)Skoulidas,A.I.;Sholl,D.S.J.Phys.Chem.B2005,109,15760.(45)Yang,Q.Y.;Zhong,C.L.J.Phys.Chem.B2005,109,11862.Diffusion and Separation of CO2and CH4Langmuir,Vol.24,No.10,20085475reviewed.48They used a generalized MS model to predict the permeationfluxes of hydrocarbon mixtures through a silicalite membrane.49,50A general analytical expression for self-diffusivity in a multicomponent mixture was proposed by them.51It has been found that the MS diffusivity in zeolites shows a variety of dependencies on occupancy.As a consequence,they further modeled the occupancy dependence of diffusivity in zeolites by taking into account various factors such as zeolite topology, connectivity,and molecular interactions.52Sholl tested this by predicting binary diffusivity in a lattice model with site heterogeneity.He found that the model is quite accurate in situations where the binding sites are relatively homogeneous but is less accurate for strongly heterogeneous energy distribu-tions.53In addition,Krishna and van Baten carried out MD simulations for pure components and binary,ternary,and quaternary mixtures in FAU at300K over a wide range of loading and found that MS diffusivity for a particular species is nearly identical whether this species is present on its own or in a mixture with other species.54Having tested the MS formulation extensively in zeolite structures for predicting mixture diffusion, they further tested the MS formulation in CNTs for various binary mixtures and found good agreement with simulations.55Whereas the MS formulation to predict mixture diffusion from single components has been tested relatively well in zeolites and CNTs, only recently has such a prediction been attempted in MOF-5 by Keskin and Sholl.56Through MC simulation,we have recently investigated the adsorption of pure CO2and CH4and the separation of their binary mixture in three different families of nanostructured materials s silicalite,C168schwarzite,and IRMOF-1.57The separation of CO2 from CH4,a major component in natural gas,is considered to be an important practical problem.Our simulated adsorption isotherms and isosteric heats closely match the available experimental data. Compared with the adsorption capacities of silicalite and C168 schwarzite,those of CH4and CO2in IRMOF-1are substantially larger.As a typical MOF,IRMOF-1could be a good candidate for gas storage,but its adsorption selectivity does not differ much from silicalite and C168particularly at high pressure.57Nevertheless,the efficacy of membrane-based separation for a gas mixture depends notonlyonthesolubilitydifference,whichisanequilibriumproperty, but also on the diffusivity difference,which is a transport property.58 As a consequence,in this work we investigate the diffusion of CO2,CH4,and their mixture in the three nanostructured adsorbents using MD simulation and examine the permselectivity based on diffusion and adsorption selectivity.This is thefirst simulation study on mixture diffusion in a MOF.In section II, the models used for adsorbents and adsorbates are briefly described and followed in section III by the simulation methodology.In section IV,we present the diffusivities and activation energies at infinite dilution for CO2and CH4.Then the self-,corrected,and transport diffusivities for single component from simulation are presented as a function of loading at300K.The correlation effects are examined from the self-and corrected diffusivities and subsequentlyfitted by an empirical equation.With thefitted correlation effects,the simulated self-, corrected,and transport diffusivities are compared with the theoretical predictions from the MS formulation.Finally,the self-diffusivities in the binary mixture at300K are presented from both simulation and the MS bining the differences in adsorption and diffusion between the two components in a binary mixture,permselectivity is evaluated.In section V,the concluding remarks are summarized.II.ModelsThe atomistic models for three adsorbents(silicalite,C168 schwarzite,and IRMOF-1)and two adsorbates(CH4and CO2) are the same as in our previous study;57therefore,a brief description is given here.Silicalite(MFI)is an Al-free zeolite typically used in membrane processes because of its pore size and ease of preparation.MFI consists of two types of channels with10-membered rings s one is straight,and the other is sinusoidal.These intersecting channels have a diameter of about 5.4Å.The Lennard-Jones potential parameters and partial charges of the Si and O atoms were adapted from the work of Hirotani et al.59Experimentally synthesized nanoporous carbon is amorphous and does not have a well-defined structure;conse-quently,C168schwarzite is used to represent a nanoporous carbon.60Two types of channels exist in C168schwarzite with average diameters of approximately7and9Å.The channels in the same layer are isolated from each other,but they are connected to those in the neighboring layers by channel intersections.Carbon atoms in C168schwarzite were assumed to be neutral,and the Steele potential was used to model the disperse interactions.61 IRMOF-1is an isoreticular MOF that has one type of straight channel with sizes of15and12Åseparately along the channel.62 A universal forcefield(UFF)was used to model the Zn,C,O, and H atoms in IRMOF-1.63On the basis of a fragmented cluster, the atom-centered partial charges were estimated with B3LYP/ 6-31G(d)density-functional theory computation and subsequently fitted using the restrained electrostatic potential(RESP)method.64 CH4was mimicked by the united-atom model with the interaction potential parameters from the TraPPE forcefield developed to reproduce the critical parameters and saturated liquid densities of alkanes.65The interactions between CH4and the adsorbent were modeled using the Lennard-Jones potential,and the Lorentz–Ber-thelot mixing rules were used to calculate the cross interaction parameters.CO2was represented by a three-site moleculefitted to the experimental data of bulk CO2.59The partial charge was0.576e on the C atom and–0.288e on the O atom.The C-O bond length was assumed to be rigid,and the bond length was1.18Å.The OCO bond angle wasflexible and governed by a harmonic potential of 1/2kθ(θ-θ0)2with force constant kθ)1275kJ/mol/rad2and equilibrium angleθ0)180°.CO2-CO2and CO2-adsorbent interactions were modeled by a combination of Lennard-Jones and Coulombic potentials except for C168schwarzite,where only the Lennard-Jones potential was considered.III.MethodologyDiffusion can be characterized into self-,corrected and transport diffusion at different length scales.Self-diffusivity describes the(48)Krishna,R.;Baur,R.Sep.Purif.Technol.2003,33,213.(49)Kapteijn,F.;Moulijn,J.A.;Krishna,R.Chem.Eng.Sci.2000,55,2923.(50)Krishna,R.;Paschek,D.Sep.Purif.Technol.2000,21,111.(51)Krishna,R.;Paschek,D.Phys.Chem.Chem.Phys.2002,4,1891.(52)Krishna,R.;Paschek,D.;Baur,R.Microporous Mesoporous Mater.2004, 76,233.(53)Sholl,ngmuir2006,22,3707.(54)Krishna,R.;van Baten,J.M.J.Phys.Chem.B2005,109,6386.(55)Krishna,R.;van Baten,J.M.Ind.Eng.Chem.Res.2006,45,2084.(56)Keskin,S.;Sholl,D.S.J.Phys.Chem.C2007,111,14055.(59)Hirotani,A.;Mizukami,K.;Miura,R.;Takaba,H.;Miya,T.;Fahmi,A.; Stirling,A.;Kubo,M.;Miyamoto,A.Appl.Surf.Sci.1997,120,81.(60)Jiang,J.W.;Sandler,S.I.J.Am.Chem.Soc.2005,127,11989.(61)Steele,W.Chem.Re V.1993,93,2355.(62)Millward,A.R.;Yaghi,O.M.J.Am.Chem.Soc.2005,127,11989.(63)Rappe,A.K.;Casewit,C.J.;Colwell,K.S.;Goddard,W.A.;Skiff,5476Langmuir,Vol.24,No.10,2008Babarao and Jiangmobility of individual molecules,also called tracer diffusivity,can be estimated from the mean-squared displacement based on the Einstein relation 66D s (c ))lim t f ∞16t 〈1N ∑k )1N|r k (t )-r k (0)|2〉(1)where c is concentration,r k (t )is the position of the k th moleculeat time t ,and N is the number of molecules.This definition applies to both single and multicomponent systems.On a macroscopic scale,Fick’s law of diffusion gives the phenomenological relation between flux J and concentration gradient ∇c ,J )-D t (c )∇c(2)The transport or Fickian diffusivity D t can be evaluated from the corrected diffusivity D c (c )and thermodynamic correction factor Γ(c ),D t (c ))D c (c )Γ(c )(3)withΓ(c ))(∂ln f ⁄∂ln c )T(4)where f is the fugacity of the fluid in equilibrium with the adsorbed phase at a concentration c .Γ(c )at a given temperature T can be evaluated from the equilibrium adsorption isotherm.The corrected diffusivity D c (c ),which is also called the jump diffusivity,can be written asD c (c ))Lk B T ⁄c(5)where L is the phenomenological coefficient and k B is Boltzmann’s constant.Note that the corrected diffusivity is equal to the Maxwell -Stefan diffusivity for a system with only one species.From the linear response theory,L is related to the flux autocorrelation function by 67L )13Vk B T∫0∞〈j (0)·j (t )〉d t(6)where V is the system volume and j (t )is the microscopic current defined as the sum of molecular velocitiesj (t ))∑k )1Nv k (t )(7)The microscopic current is an equilibrium property and can be directly obtained from MD simulation.Equation 6is the Green -Kubo form,and the equivalent Einstein form can be found elsewhere.67The above expression can be extended to multicomponent systems.Self-,corrected,and transport diffu-sivities are concentration-dependent and generally not equal to each other unless at infinite dilution,D s (0))D t (0))D c (0))D (0)(8)In this work,we simulate the diffusion of pure and mixed CH 4and CO 2in MFI,IRMOF-1,and C 168using the MUSIC program.68The simulations were carried out in a canonical ensemble (NVT )with a Nose-Hoover thermostat,and the equations of motion were integrated using a sixth-order Gearpredictor-corrector algorithm.69A time step of 1fs was used for CH 4,and 0.3fs was used for CO 2and the mixture to achieve better energy conservation.A spherical cutoff length of 19.0Åwas used to evaluate the intermolecular Lennard-Jones interactions without the long-range corrections.Cou-lombic interactions between CO 2and adsorbent were calculated using the Ewald summation technique.70For CO 2molecules,Coulombic interactions were calculated directly on the basis of the center-of-mass cutoff of 19.0Åbecause the CO 2molecule is neutral with a quadrupole interaction that converges rapidly with the cutoff distance.To accelerate the simulation,the Lennard-Jones and Coulombic interactions between adsorbate and adsorbent were calculated via a pretabulated energy map that was constructed throughout a unit cell of adsorbent with a grid of 0.2×0.2×0.2Åcubic mesh.The simulation box for MFI contained 12(2×2×3)unit cells,whereas for C 168schwarzite and IRMOF-1,8(2×2×2)unit cells were used.All three adsorbents were assumed to be rigid,and the framework atoms were fixed during simulation.It is important to note,however,that diffusion can be substantially influenced by the framework flexibility.In zeolites,diffusion is usually accelerated in the flexible model by the increased possible number of pathways for the molecular jump.71Nevertheless,a reduction in diffusion is observed in flexible carbon nanotubes by taking into account the energy exchange between diffusing molecules and the nanotube.32The diffusion and activation energy of benzene in IRMOF-1are considerably smaller in the flexible framework compared to those in the rigid one.This is attributed to the correlation motion of benzene with the organic linker phenylene rings,which leads to an increases in the population of benzene in the A-cell pockets.47The final configurations of MC simula-tions for the adsorption of pure CH 4,CO 2,and the equimolar CH 4/CO 2mixture from our previous work 57were taken as the initial configurations for the MD simulations in this work.For pure CH 4and CO 2at 300K,simulations were performed for a total period of 2.5-5.0ns with an equilibration period of 1.0-3.5ns.Ten independent runs were performed at each loading to obtain the desired level of statistical accuracy.During the production run,the atomic coordinates were written to a disk every 1ps and then used to calculate the averaged D s from the Einstein relation.The molecular velocities were written to a disk every 0.1ps and then used to calculate the flux autocorrelation function and phenomenological coefficient using eq 6with an upper limit of 30ps.As demonstrated previously,17,72with an even short limit of 10ps,the flux autocorrelation function decays to zero,and the integral converges to a constant.In addition,we calculated the diffusivities at infinite dilution of CH 4and CO 2in all three adsorbents at various temperatures.To do this,we performed the MD simulation as described above with at least 40molecules in the box by turning off the adsorbate–adsorbate interactions.For the CH 4/CO 2mixture,MD simulations were performed at 300K for a total period of 8ns,with the first half left out for equilibration and the second half left out for the ensemble average.IV.Results and DiscussionFirst we present the simulation results for pure CH 4and CO 2in the three nanostructures at infinite dilution.From the(66)McQuarrie,D.A.Statistical Mechanics;University Science Books:Sausalito,CA,2000.(67)Theodorou,D.N.;Snurr,R.Q.;Bell,A.T.Molecular Dynamics and (69)Allen,M.P.;Tildesley,D.J.Oxford University Press:Oxford,U.K.,1987.Diffusion and Separation of CO 2and CH 4Langmuir,Vol.24,No.10,20085477temperature-dependent diffusivities,the activation energies for diffusion are obtained.Then as a function of loading,the simulated self-,corrected,and transport diffusivities of pure CH4and CO2 at300K are shown.The correlation effects of diffusion are examined and used in the MS formulation for predictions,which in turn are compared with the simulation results.Finally,the simulated and predicted self-diffusivities of the CH4/CO2binary mixture are presented at300K,and the permselectivity for the mixture is evaluated.Diffusivities and Activation Energies at Infinite Dilution. Figure1shows the diffusivities at infinite dilution D(0)for CH4and CO2separately in MFI,C168,and IRMOF-1as a function of the inverse temperature.The results are the average of10independent runs with a standard deviation of within 5%.As estimated in our previous study57and also given in Table1,for the three adsorbents under consideration,the porosity increases in the order of MFI<C168<IRMOF-1.In accordance with the increasing trend in porosity,D(0)generally increases in the same order for both CH4and CO2because of the increased free space for molecules to move.At temperatures lower than 300K,however,D(0)in MFI becomes slightly greater than in C168.Therefore,porosity is not the only factor influencing the diffusivity.Our simulated D(0)at300K given in Table1generally matches the reported simulation and experimental values well. For CH4in MFI,D(0)agrees well with the simulation results from a number of groups.6,7,11,21For CH4in IRMOF-1,D(0)is also in good agreement with the simulation result,44but both are almost an order of magnitude less than the measured value by Stallmach et al.46For CO2in MFI,D(0)is comparable to the measured value from QENS[(0.6-0.7)×10-8m2/s],9though a bit higher than the value simulated by Krishna et al.21For CO2 in IRMOF-1,D(0)is slightly higher than the simulated value of Skoulidas et al.44The discrepancy for CO2might be due to the different potential parameters used.C168schwarzite is a hypothetical structure for nanoporous carbons,and no experi-mental data are available for comparison with our results.In nanoporous materials,the steric effect and surface interaction play a dominant role.Diffusion is normally interpreted as an activated process and can be described by the Arrhenius relationD(0))Dfexp(-E a RT)(9) where D f is the prefactor,E a is the activation energy,and R is the gas constant.Byfitting the simulated D(0)at various temperatures using eq9,D f and E a can be correlated.The lines with CO2.As a result of the high porosity,in IRMOF-1D f for both CH4and CO2is found to be almost1order of magnitude greater than in MFI and C168.Our simulated E a for CH4in MFI(4.45kJ/mol)is in good agreement with the experimental value(5.69kJ/mol).73Stallmach et al.found E a for CH4in IRMOF-1 to be around8.5kJ/mol,46which is almost twice the simulated value(4.88kJ/mol).However,the discrepancy in both D(0)and E a in IRMOF-1may be due to the defects present in the porous structure used in experiments,which was not taken into account in simulations.Our simulated E a for CO2in MFI(3.35kJ/mol) is smaller than one available experimental value(5.8kJ/mol). However,note that the experimental condition was not at infinite dilute;instead,the loading was approximately two molecules/ unit cell.9A molecule must overcome the free-energy barrier to move from one site to another.The barrier as reflected in the activation energy is lower for either CH4or CO2in C168schwarzite compared with that in MFI and IRMOF-1.In particularly,the estimated E a for CO2in C168(1.75kJ/mol)is considerably lower. As further discussed below,this is because CO2is a slender molecule and readily mobile particularly in C168channels. Self-Diffusivities.Figure2shows the loading dependence of the self-diffusivities D s for CH4and CO2in the three adsorbents. The loadings considered here for IRMOF-1are substantially lower than the saturation loading.The error bars indicate the uncertainties in our simulation.As seen,D s for both CH4and CO2in each adsorbent decreases monotonically as loading increases.This is type I behavior as characterized by Karger and Pfeifer in whichfive types of diffusion behavior were demon-strated with increased loading.74The observed type I behavior is very common in nanoporous materials as a result of enhanced steric hindrance of the motion of a tagged particle by neighboring particles as the loading increases.At a loading of around3mmol/g for either CH4or CO2,D s in IRMOF-1is about twice of that in C168and almost1order of magnitude greater than that in MFI. The decreased rate in D s(the slope)is closely related to theFigure1.Diffusivities D(0)at infinite dilution as a function of inverse temperature for pure CH4and CO2in MFI,IRMOF-1,and C168.Symbols are from simulation,and lines are the Arrheniusfits to the symbols.Table1.Diffusivities D(0)at300K(10-8m2/s),Prefactors D f(10-8m2/s),and Activation Energies E a(kJ/mol)at InfiniteDilution for CH4and CO2in MFI,C168,and IRMOF-1adsorbent adsorbate porosity D(0)D f E aMFI CH40.37 1.569.28 4.45CO2 1.31 5.18 3.35C168CH40.67 1.51 6.24 3.50CO2 1.35 2.81 1.75IRMOF-1CH40.82 3.3722.6 4.88CO2 3.0115.4 4.05 5478Langmuir,Vol.24,No.10,2008Babarao and Jiang。

光学术语中英文对照

光学术语中英文对照

平面镜 Flat Mirrors球面凹面镜,球面凸面镜 Spherical Concave and Convex Mirrors 抛物面镜,椭圆面镜 Off-Axis Paraboloids and Ellipsoids Mirrors 非球面镜 Aspheric Mirrors多面镜 Polygonal Mirrors热镜 Hot Mirrors冷镜 Cold Mirrors玻璃,玻璃/陶瓷面镜 Glass and Glass-Ceramic Mirrors双色向面镜 Dichroic Mirror金属面镜 Metal Mirrors多层面镜 Multilayer Mirrors半涂银面镜 Half-Silvered Mirrors激光面镜 Laser Mirrors天文用面镜 Astronomical Mirrors棱镜系列术语中英文对照Nicol棱镜 Nicol PrismsGlan-Thomson棱镜 Glan-Thomson PrismsWollaston棱镜 Wollaston PrismsRochon棱镜 Rochon Prisms直角棱镜 Right-Angle; Rectangular Prisms五面棱镜 Pentagonal Prisms脊角棱镜 Roof Prisms双棱镜 Biprisms直视棱镜 Direct Vision Prisms微小棱镜 Micro Prisms滤光镜系列术语中英文对照尖锐滤光镜 Sharp Cut (off) Filters色温变换滤光镜,日光滤光镜 Colour Conversion/Daylight Filters 干涉滤光镜 Interference Filters中性密度滤光镜 Neutral Density Filters空间/光学匹配滤光镜 Spatial/Optical Matched Filters双色向滤光镜 Dichroic Filters偏光滤光镜 Polarizing Filters排除频带滤光镜 Rejection Band Filters可调式滤光镜 Turnable Filter超窄频滤光镜 Ultra Narrowband Filters色吸收滤光镜 Absorption Filters红外吸收/反射滤光镜 Infrared Absorbing/Reflecting Filters 红外透过滤光镜 Infrared Transmitting Filters紫外吸收滤光镜 Ultraviolet Absorbing Filters紫外透过滤光镜 Ultraviolet Transmitting Filters针孔滤光镜 Pinhole Filters有色玻璃滤光镜 Colored-Glass Filters塑胶滤光镜 Plastic Filters照像用滤光镜 Photographic Filters全像滤光镜 Holographic Filters微小干涉滤光镜 Micro Interference Filters光学词汇Iris – aperture stop虹膜孔径光珊retina视网膜Color Blind 色盲weak color 色弱Myopia – near-sighted 近视Sensitivity to Light感光灵敏度boost推进lag behind落后于Hyperopic – far-sighted 远视Dynamic Range 动态范围critical fusion frequency 临界融合频率CFF临界闪变频率visual sensation视觉Chromaticity Diagram色度图Color Temperature色温HSV Model色彩模型(hue色度saturation饱和度 value纯度CIE Model 相干红外能量模式Complementary Colors补色Bar Pattern条状图形Heat body 热稠化approximate近似violet紫罗兰Body Curve人体曲线Color Gamut色阶adjacent邻近的normal illumination法线照明Primary colors红黄蓝三原色Color saturation色饱和度Color Triangle颜色三角Color Notation颜色数标法Color Difference色差TV Signal Processing电视信号处理Gamma Correction图像灰度校正Conversion Tables换算表out of balance失衡wobble摇晃back and forth前后clear (white) panel白光板vibrant震动fuzzy失真quantum leap量子越迁SVGA (800x600)derive from起源自culprit犯人render呈递inhibit抑制,约束stride大幅前进blemish污点obstruction障碍物scratch刮伤substance物质实质主旨residue杂质criteria标准parameter参数adjacent邻近的接近的asynchrony异步cluster串群mutually互助得algorithm运算法则Chromatic Aberrations色差Fovea小凹Visual Acuity视觉灵敏度Contrast Sensitivity对比灵敏度Temporal (time) Response反应时间rendition表演,翻译animation活泼又生气ghost重影Parallax视差deficient缺乏的不足的Display panel显示板NG.( Narrow Gauge)窄轨距dichroic mirror二色性的双色性的Brewster Angle布鲁斯特角Polarized Light极化光Internal reflection内反射Birefringence 双折射Extinction Ratio 消光系数Misalignment 未对准Quarter Waveplates四分之一波片blemish污点瑕疵Geometric几何学的ripple波纹capacitor电容器parallel平行的他tantalum钽(金属元素)exsiccate使干燥exsiccate油管,软膏furnace炉子镕炉electrolytic电解的,由电解产生的module模数analog类似物out of the way不恰当pincushion针垫拉lateral侧面得rectangle长方形fixture固定设备control kit工具箱DVI connector DVI数局线Vertical垂直的horizontal 水平的interlace隔行扫描mullion竖框直楞sawtooth锯齿toggle套索钉keypad数字按键键盘tangential切线diagnostic tool诊断工具sagittal direction径向的cursor position光标位置ray aberration光线相差weighting factor权种因子variables变量for now暂时,目前.眼下check box复选框Airy disk艾里斑exit pupil出[射光]瞳optical path difference光称差with respect to关于diffraction limited衍射极限wavefront aberration波阵面相差spherical aberration球面象差paraxial focus傍轴焦点chromatic aberration象差local coordinate system局部坐标系统coordinate system坐标系orthogonal直角得,正交的conic sections圆锥截面account for解决,得分parabolic reflector拋物面反射镜radius of curvature曲率半径spherical mirror球面镜geometrical aberration几何相差incident radiation入射辐射global coordinate总体坐标in terms of根据按照reflected beam反射束FYI=for your information供参考Constructive interference相长干涉phase difference相差achromatic singlet消色差透镜Interferometer干涉仪boundary constraint边界约束,池壁效应radii半径Zoom lenses变焦透镜Beam splitters分束器discrete不连续的,分离的objective/eye lens物镜/目镜mainframe主机rudimentary根本的,未发展的photographic照相得摄影得taxing繁重的,费力得algebra代数学trigonometry三角学geometry几何学calculus微积分学philosophy哲学lagrange invariant拉格朗日不变量spherical球的field information场信息Standard Lens标准透镜Refracting Surface折射面astigmatism散光HDTV高清晰度电视DLV ( Digital Light Valve)数码光路真空管,简称数字光阀diffraction grating衍射光珊field angle张角paraxial ray trace equations近轴光线轨迹方称back focal length后焦距principal plane主平面vertex顶点,最高点astigmatism散光,因偏差而造成的曲解或错判medial中间的,平均的variance不一致conic圆锥的,二次曲线field of view视野collimator瞄准仪convolution回旋.盘旋,卷积fuzzy失真,模糊aberrated异常的asymmetry不对称得indicative可表示得parabolic拋物线得suffice足够,使满足specification规格,说明书straightforward易懂的,直接了当的solidify凝固,巩固.Constraints 约束,限制metrology度量衡field coverage视场,视野dictate口述, 口授, 使听写, 指令, 指示, 命令, 规定irradiance发光, 光辉,辐照度aerial空气得,空中得halide卤化物的monochromatic单色的,单频的polychromatic多色的aspherical非球面的spherical球面的alignment列队,结盟power(透镜)放大率equiconvergence 同等收敛EFL(effective focal length)有效焦距workhorse广为应用的设备biconvex两面凸的global optimization整体最优化concave凹得,凹面得cylindrical圆柱得solid model实体模型Modulation Transfer Function调制传递函数in the heat of在最激烈的时候protocol协议,规定triplet三重态sanity心智健全zinc锌,涂锌的selenide 硒化物,硒醚miscellaneous各色各样混在一起, 混杂的, 多才多艺的versus与...相对polynomial多项式的coefficient系数explicit function显函数distinct清楚的,截然不同的emanate散发, 发出, 发源rudimentary根本的,未发展的intersection角差点PRTE=paraxial ray trace equation旁轴光线轨迹方程 achromats 消色差透镜cardinal points基本方位separations分色片dashed 虚线blow up放大overlay覆盖,覆盖图 multiplayer 多层的humidity 湿度float glass浮法玻璃square one 出发点,端点square up to 准备开打,坚决地面对reflecting telescope 反射式望远镜 diagnostic tools诊断工具Layout plots规划图Modulation transfer function调制转换功能FFT快速傅里叶变换Point spread function点传播功能wavelength波长angle角度absorption吸收system aperture系统孔径lens units透镜单位wavelength range 波长范围singlet lens单业透镜spectrum光谱diffraction grating 衍射光栅asphere半球的LDE=Lens data editor Surface radius of curvature表面曲率半径surface thickness表面厚度material type 材料种类semi-diameter半径focal length焦距aperture type孔径类型aperture value孔径值field of view视场microns微米F, d, and C= blue hydrogen, yellow helium, red hydrogen lines, primary wavelength主波长sequential mode连续模式object surface物表面The front surface of the lens透镜的前表面stop 光阑The back surface of the lens透镜的后表面The image surface 像表面symmetric相对称的biconvex两面凸的The curvature is positive if the center of curvature of the surface is to the right of the vertex. It is negative if the center of curvature is to the left of the vertex.如果曲率中心在最高点的右边,曲率值为正,如果曲率中心在最高点的左边,则曲率为负image plane像平面Ray Aberration光线相差tangential direction切线方向sagittal direction径向paraxial focus旁轴的Marginal边缘的spherical aberration球面像差Optimization Setup最优化调整variable变量mathematical sense数学角度MFE= Merit Function Editor, Adding constraints增加约束focal length焦矩长度operand操作数the effective focal length有效焦矩primary wavelength主波长initiate开始spot diagram位图表Airy disk艾里斑axial chromatic aberration轴向色差with respect to关于至于exit pupil出射光瞳OPD=optical path difference光学路径差diffraction limited衍射极限chromatic aberration色差chromatic focal shift色焦距变换paraxial focus傍轴焦点axial spherical aberration轴向球差(longitudinal spherical aberration 纵向球差:沿光轴方向度量的球差)lateral spherical aberration垂轴球差(在过近轴光线像点A‵的垂轴平面内度量的球差)coma、comatic aberration彗差meridional coma子午彗差sagittal coma弧矢彗差astigmatism像散local coordinate system 本地坐标系统meridional curvature of field子午场曲sagittal curvature of field弧矢场曲decentered lens偏轴透镜orthogonal 直角的垂直的conic section圆锥截面account for说明,占有,得分stigmatic optical system无散光的光学系统Newtonian telescope牛顿望远镜parabolic reflector抛物面镜foci焦距chromatic aberration,色差superpose重迭parabola抛物线spherical mirror球面镜RMS=Root Mean Square均方根wavefront 波阵面spot size光点直径Gaussian quadrature高斯积分rectangular array矩阵列grid size磨粒度PSF=Point Spread Function点扩散函数FFT=Fast Fourier Transform Algorithm快速傅里叶变换Cross Section横截面Obscurations昏暗local coordinates局部坐标系统vignette把…印为虚光照Arrow key键盘上的箭头键refractive折射reflective反射in phase同相的协调的Ray tracing光线追迹diffraction principles衍射原理order effect式样提出的顺序效果energy distribution能量分配Constructive interference相长干涉dispersive色散的Binary optics二元光学phase advance相位提前achromatic single消色差单透镜diffractive parameter衍射参数Zoom lenses变焦透镜Athermalized lenses绝热透镜Interferometers干涉计Beam splitter分束器Switchable component systems可开关组件系统common application通用symmetry对称boundary constraint边界约束multi-configuration (MC) MC Editor (MCE) perturbation动乱,动摇index accuracy折射率准确性index homogeneity折射率同种性index distribution折射率分配abbe number离差数Residual 剩余的Establishing tolerances建立容差figure of merit质量因子tolerance criteria公差标准Modulation Transfer Function (MTF)调制传递函数boresight视轴,瞄准线Monte Carlo蒙特卡洛Tolerance operands误差操作数conic constant ]MC1"{_qT .ueg g 圆锥常数astigmatic aberration像散误差Mechanical tilt机械倾斜,机械倾角Tolerance Data Editor (TDE)公差资料编辑器compensator补偿棱镜estimated system performance预估了的系统性能iteratively反复的,重迭的statistical dependence统计相关性sequential ray trace model连续光线追迹模型imbed埋葬,埋入multiple多样的,多重的,若干的Non-Sequential Components 不连续的组件Corner cube角隅棱镜,三面直角透镜Sensitivity Analysis灵敏度分析Faceted reflector有小面的反射镜emit发射,发出nest嵌套overlap交迭outer lens外透镜brute force强力seidel像差系数aspect ratio长宽比MRA边缘光线角MRH边缘光线高度asynchronous不同时的,异步 Apodization factor变迹因子hexapolar六角形dithered高频脉冲衍射调制传递函数(DMTF),衍射实部传递函数(DRTF),衍射虚部传递函数(DITF),衍射相位传递函数(DPTF),方波传递函数(DSWM)logarithmic对数的parity 奇偶 % Uc,I e ,17]3NnoClongitudinal aberrations 纵向像差赛得系数: 球差(SPHA,SI),彗差(COMA,S2),像散(ASTI,S3),场曲(FCUR,S4),畸变(DIST,S5),轴向色差(CLA,CL)和横向色差(CTR,CT).横向像差系数:横向球差(TSPH),横向弧矢彗差(TSCO),横向子午彗差(TTCO),横向弧矢场曲(TSFC),横向子午场曲(TTFC),横向畸变(TDIS)横向轴上色差(TLAC)。

偏振光干涉的相位差

偏振光干涉的相位差

偏振光干涉的相位差2001年9月第20卷第3期抚州师专JournalofFuzhouTeachersc姆Sept,2001V01.20N0.3偏振光干涉的相位差黄仁忠,王爱星(抚州师范专科学校物理系,江西抚州344o00)摘要:关于偏振光干涉的相住差有两类车同的算法,文章对此进行了对比讨论,指出正璃掌握两类算法中对各项取值的不同规定,避免发生错谥.关键词:偏振光;干涉;相住差中图分类号:0436文献标识码:A文章编号:1(3Ol一635X(20O1)o3一O023一位在两块偏振片P,B之间插入一块光轴平行于晶面的晶片,平行的自然光从P.垂直射人,出射光为线偏撮光,设其光矢量为EI,进入晶片后分解为.光和e光,设其光矢量为和E.再经得到两个光波场,设其光矢量为和,它们相干叠加.关于这两个光波场的相位差△的计算.主要有以下两类表述:=△朔+性(1)/"9=.△+朔+懒(2)式中△是刚进入晶片时.光和e光的相位差,△僻=竿(nu一)d,是.光和e光穿过晶片后产生的附加相位差,△是对投影时引起的相位差.(2)式比(1)式多出一项△,但两式对△伽取值的规定不同,最后结果仍然是一致的.如果不注意区别两式对伽取值的规定,必然导致错误的结果.采用(1)式时,相当于取△=O.关于△的取值,有的教材这样规定:当B,B处于不同象限时(如图1).取△性=;当P-,处于同一象限时(如图2),取△=0….有的教材则采用另一种表述:当晶片光轴位于P_,Pz之问时(即,分居e轴两侧),取△=;当晶片光轴位于,之外时(即P_,B同居e 轴一侧),取△恤=.从以上两图中不难看出.这两种表述是完全一致的其实还可以更直观地表述为:当卫和方向相反时,取△性=,当骂和方向相同时,取△=o】.若采用(2)式计算,当在一,三象限时.取△=o,当EI在二,四象限时,取△^=_|】当e轴和0轴的正方向对轴的两个投影分量方向一致时,取△性=0,当这两个投影分量方向相反时,取△=.】.图1q~Ag/.=0,△性=;图2中△=0,△=O.在这两种情况下,(2)式所得结果都与(1)式相同.然而,e轴和0轴本身并投有正负方向之分,其正负方向完全是建立坐标系时人为约定的.分析发现.这个方向的约定会同时影响在哪个象限及e轴和0轴正方向对P2轴两个投影分量的方向,也就是说.会同时影响△和△啦的取值.因而,△+△伽的值就与e轴和0轴正方向的设定无关,也就使(2)式和(1)式所得结果能始终保持一致.对于如图1所示的情况,P】,B分居e轴两侧,我们将e轴,0轴的正方向作各种不同的设定,从图3,图4,收撬日期:~0Ol一03—29作者简介:黄仁忠(1944一),男,江西临川人,抚州师范专科学校物理系副教授王爱星(1975一),男,江西东乡人,抚州师范专科学校物理系助教图5中可以看到,△和△必有一个为零,另一十为,总有△+△性=,都与(1)式的结果相同.田3中B在第二象限.图4中E在第四象限,两图中e轴,0轴正方向对的投影分量方向都相同,所以柞得到△甲^=,△靴=O;图5中B在第三象限,而t轴,o轴正方向对的投影分量方向相反,于是有△郸=0,图1图2P图3图4△蚋t.对于如图2所示的情况,PI,同居e轴一侧,可以看到,不管e轴,o轴正方向如何设定.△和△恤必同时为(如图6,图7)或同时为零(如图8),总有△+△午=0或h,也都与(1)式的结果相同.值得注意的是,(1)式和(2)式中对△慨取值的规定.是不能混淆的.有的教材采用(2)式计算,△的规定正确,但对于△的取值却是这样规定:若卫和.同方向.则△=0,反方向则△倾=,㈨这显然又采用了(1)式的规定,对于△=0的情况尚不致于出错,但对于△=的情况(如图3,4,6,7),结果却是错图5圉6固,圈B误舯.练上所述.若采用(1)式,△是指和对投影引起的相位差,由这两个投影的方向是否相同来决定取值;若采用(2)式,△是指e轴和.轴的正方向(特别要强调是正方向)对投影引起的相位差.由这两个投影的方向是否相同来决定取值,这是不容混淆的.[参考文就】[1】昊强,郭光灿.光学【M].夸肥:中国科学技术七学出版社,1996.321—322.[2]邦永康,鲍培谛.光学教程[M].成都:四川太学出版社,I992.315.[3]榘绍蒙,刘昌年.盛正华.普通拍理学(第4分册)[M].北京:高等教育出腹社,1994242.[4]赵凯华,钟蠕华.竞学(下册)[M].北京:北京戈学出版社,|984.203—2O4.[5】陈为彰,胡学瑷,刘惠国.光学[M].北京:北京师范大学出版社,1989.307—398. PhaseDifferenceofPolarizedLightInterferenceHUANGRen.z.hong,WANGAi.xing(,Fm/mu如,Fud~ou3㈣,‰)Abstract:There'retwokindsofdifferentcountingmethodsconcerningthep}1asedifference ofp0laltinterferenceinvariousopticalteachingmaterials.1l1earticlehasraisedacomoarabledisct mianaboutit,Ilgolltthe,ightgraspofallkindsofdifferentquotasofsamplingintwokindsofe0.删E llllIods.Soas10avoidthemistakes.脚1^一.s:p0lazedlight;interference;pl1asedifference24。

Measurement equipment null of the cross polarizati

Measurement equipment null of the cross polarizati

专利名称:Measurement equipment null of the cross polarization degradation primary factor bythe radio wave propagation发明人:ENDO SHIZUO,遠藤 静夫,OGAWA AKYOSHI,小川 明義,MATSUNAKA NAOTO,松中 直人,YOSHIKAWA YOSHIHIKO,吉川 義彦申请号:JP特願昭56-87747申请日:19810608公开号:JP特公平6-11126B2公开日:19940209专利内容由知识产权出版社提供摘要:PURPOSE:To obtain a simple cross polarized wave compensator with high reliability, by detecting the state of polarization of a system with less effect of nonuniformity of a space of a radio circuit and controlling a cross polarized wave compensator through the addition of correlativity to other systems. CONSTITUTION:A cross polarized wave compensator includes a polarized wave converter and a polarizer and consists of a feeder 9 branching a main polarized wave signal and a cross polarized wave signal, an amplitude phase detector 10 detecting the amplitude ratio and the phae difference between the main polarized wave signal and the cross polarized wave signal, an operation circuit 11 detecting a relative phase difference, a relative attenuation and their slope angle beig the causes to the degrading of polarized waves of a system A based on the detected amplitude ratio and phase difference, an operation circuit 12 generating a control signal of a cross polarized wave compensator 7 for transmission wave through the addition of the correlativity between the relative phase difference andthe relative attenuation of the systems A and B, and a controller 13 controlling the compensator 7 based on this control signal. Through the constitution like this, the degrading of an up-link can be obtained through calculation from the deterioration of cross polarization of a down link which can easily be known.申请人:KOKUSAI DENSHIN DENWA KK,国際電信電話株式会社,MITSUBISHI DENKI KK,三菱電機株式会社地址:東京都新宿区西新宿2丁目3番2号,東京都千代田区丸の内2丁目2番3号国籍:JP,JP代理人:高田 守 (外1名)更多信息请下载全文后查看。

胆甾相与蓝相液晶的布拉格反射和旋光能力研究

胆甾相与蓝相液晶的布拉格反射和旋光能力研究

胆甾相与蓝相液晶的布拉格反射和旋光能力研究窦虎;于亚楠;马红梅;孙玉宝【摘要】The Bragg reflection and optical rotatory power of cholesteric liquid crystal (ChLC)and blue phase liquid crystal (BPLC)are studied using finite-difference time-domain (FDTD)method. Firstly,the Bragg reflection of ChLC and BPLC is calculated,and the simulation results are discussed from the aspects of lattice structures and molecular arrangement.The effect of refractive index and pitch of liquid crystal on the Bragg reflection is also studied.The light leakage of the ChLC and BPLC sandwiched by the crossed polarizers is calculated,and the similar and different phenomena are ana-lyzed by the optical rotatory power of liquid crystal.%采用时域有限差分法(FDTD)研究了胆甾相液晶与蓝相液晶的旋光能力。

首先计算了圆偏振光在平面态胆甾相液晶与蓝相液晶中的布拉格反射现象,从晶格结构和分子排列的角度对模拟结果做了讨论,研究了液晶折射率和螺距对布拉格反射现象的影响。

其次研究了胆甾相与蓝相液晶夹在两正交偏振片间的漏光情况,用液晶的旋光能力对二者的相似和不同的现象进行了解释。

波片( Wave plate, 位相延迟器 )

波片( Wave plate, 位相延迟器 )

入射时 Entrance
出射时 (Exit)
线偏振光通过半波片后光矢量的转动
第七页,编辑于星期三:四点 三十二分。
3、全波片(Full-wave plate)
n o n e d m ,对 应 2 m 的
称该晶片为全波片。 性质: 1)不改变入射光的偏振状态; 2)只能增大光程差。
第八页,编辑于星期三:四点 三十二分。
性质:
1)线偏光入射时 若入射线偏光光矢量方向与快、慢轴方向一致
时,出射仍为线偏光;
若入射线偏光光矢量方向与快、慢轴都成 45度时,出射光为圆偏光。
若入射线偏光光矢量方向与快、慢轴都成 其他角度时,出射光为椭圆偏光;
第四页,编辑于星期三:四点 三十二分。
2)圆偏振光通过四分之一波片后,变为线 偏振光。
1、双折射(Birefringence)晶体作分光镜 (Optical
spectroscope)
双像元件的分束
Fe Fo
第二十五页,编辑于星期三:四点 三十二分。
S’ S’

P
A
分 干




Q


F

L
S
第二十六页,编辑于星期三:四点 三十二分。
2、偏振分光镜与/4片组合
Io/4
Io
Io/2
普通分光镜
I = a 2 c2 o s a 2 s2 is n 2 is n2 i n n 0 n e d
3、讨论
1)正交(Orthogonal)偏振器系统: 起偏器P和检偏器A的透光轴相互垂直,即:=+/2
I = a 2 s2 i2 n s2 i n n 0 n e d I0 s2 i2 n s2 i2 n

光外差检测条件

光外差检测条件

展开上式 ,并舍弃合频项, 得
Expanding above formula, and discarding the sum frequency item, we have
2 2 Es0 + EL0 dip = α + Es0EL0 cos[(ωL ωs )t + kx x]dx 2
2,两光场不重合对信噪比的影响
The influence on the SNR when the two optical fields are not coincident
设:探测器光敏面为边长为d 的正方形;信号光场和本振光场 均为平面波,其中,本振光垂直入射到光敏面;二波前夹角 ,
Suppose: Detector's photosensitive surface is a square with a side length of d; both of the signal and local lights are plane waves, the local light is normally incident on the photosensitive surface of the detector; and the angle
sin(kxd 2) (1) Only when , =1 can the iIF get its maximum, this means kxd 2
that the kx should be zero: kx = 0 , i.e. k ⊥ x , and (2) When . = 0
sin(kxd 2) = 0 iIF = 0 . This means sin(kxd 2) = 0 but , kxd 2
二,外差检测的频率条件
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PLEASE SCROLL DOWN FOR ARTICLEThis article was downloaded by: [Ocean University of China]On: 20 September 2010Access details: Access Details: [subscription number 906076772]Publisher Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UKInternational Journal of Remote SensingPublication details, including instructions for authors and subscription information:/smpp/title~content=t713722504On the co-polarized phase difference for oil spill observationM. Migliaccio a ; F. Nunziata a ; A. Gambardella a aUniversità degli Studi di Napoli Parthenope, Dipartimento per le Tecnologie, Centro Direzionale,Isola C4, 80143 Napoli, ItalyTo cite this Article Migliaccio, M. , Nunziata, F. and Gambardella, A.(2009) 'On the co-polarized phase difference for oilspill observation', International Journal of Remote Sensing, 30: 6, 1587 — 1602To link to this Article: DOI: 10.1080/01431160802520741URL: /10.1080/01431160802520741Full terms and conditions of use: /terms-and-conditions-of-access.pdf This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden.The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss,actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.On the co-polarized phase difference for oil spill observationM.MIGLIACCIO*,F.NUNZIATA and A.GAMBARDELLAUniversita `degli Studi di Napoli Parthenope,Dipartimento per le Tecnologie,CentroDirezionale,Isola C4,80143Napoli,Italy(Received 11July 2007;in final form 5April 2008)In this study dual-polarized synthetic aperture radar (SAR)measurements were used to enhance oil spill observation.The co-polarized phase difference (CPD)was modelled and used to characterize the scattering return from oil spills and biogenic slicks.The model predicts,under low to moderate wind conditions,a larger CPD standard deviation (s )for oil with respect to the sea,while for biogenic slicks a s value similar to that for the sea is obtained.Experiments accomplished with multilook complex (MLC)C-and L-band SAR data show that the model predictions are confirmed and that the C-band is,as expected,to be preferred to the L-band.1.IntroductionSea oil pollution is a matter of great concern,with about 180millions of gallons of pollution estimated to be spilled every year (Delilah 2002,ITOPF 2007).Oil discharged into the sea enters into the fish life cycle,alters it and subsequently affects human health (Delilah 2002).An oil spill monitoring system,with all-weather day and night capability,is fundamental to support law enforcement and to minimize the ecosystem impact of such polluting events.For this purpose,airborne and spaceborne remote sensing is a key tool and synthetic aperture radar (SAR)is the most useful sensor for the detection of sea oil pollution,under low to moderate wind conditions (Brekke and Solberg 2005).SAR is an active,coherent,band-limited microwave high-resolution sensor that provides valuable measurements at both day-and night-time and almost independently of atmospheric conditions.Physically,oil spill detection is possible because an oil slick dampens the short gravity and capillary waves that are responsible for the backscattered electro-magnetic field at the SAR (Brekke and Solberg 2005).As a consequence,an oil spill generates a low backscatter area,that is a dark area in SAR images.However,oil spill detection in SAR images is not an easy task.Other physical phenomena can also generate dark areas and SAR images are affected by multiplicative noise known as speckle (Brekke and Solberg 2005).Dark areas not related to oil spills are known as look-alikes.Phenomena that give rise to look-alikes include biogenic films (e.g.slicks produced by animals and plankton),low-wind areas,areas of wind-shadow near coasts,rain cells,currents,zones of upwelling,internal waves and oceanic or atmospheric fronts (Brekke and Solberg 2005).Oil spill detection can be divided into three phases:dark area detection,features extraction,and oil spill/look-alike classification.Dark area detection algorithms are generally based on filtering*Corresponding author.Email:maurizio.migliaccio@uniparthenope.itInternational Journal of Remote Sensing Vol.30,No.6,20March 2009,1587–1602International Journal of Remote SensingISSN 0143-1161print/ISSN 1366-5901online #2009Taylor &Francis/journals DOI:10.1080/01431160802520741D o w n l o a d e d B y : [O c e a n U n i v e r s i t y o f C h i n a ] A t : 02:26 20 S e p t e m b e r 2010techniques accomplished on multilook single-polarization SAR data.While dark area detection algorithms yield the area location and the segmentation of suspected polluted areas,the extraction of features (e.g.geometric,radiometric and texture related)is necessary to perform the classification.On the basis of the estimated features and some a priori knowledge it is possible to assign a probability that a dark area is an oil spill (Brekke and Solberg 2005).To enhance the ability to distinguish oil spills and look-alikes,the usefulness of additional external data is nowadays recognized;for instance,optical data to identify biogenic films (Fingas and Brown 1997).Although there is a general consensus that radar polarimetry is able to provide additional information for environmental applications,the real benefit of SAR polarimetric information,which can be extracted once a suitable electromagnetic model is available,has been demonstrated only for land applications and initial investigations on sea oil spill observation were generally unsatisfactory (Gade et al.1998).Only in a recent paper (Migliaccio et al.2007)was it shown that fully polarimetric features can assist in distinguishing between oil spill and biogenic look-alikes.On similar physical guidelines,in this paper the usefulness and the significance of a dual-polarized SAR sensor is explored.Although a fully polarimetric SAR is to be desired,there may be hardware and budget considerations that require the design and implementation of a simpler polarimetric SAR configuration (Raney 2007).For instance,the SAR sensors onboard RADARSAT-2and ALOS PALSAR operate in fully dual-and single-polarization modes while the SARs onboard ENVISAT and COSMO-SkyMed operate only in single-or dual-polarization modes.The use of dual-polarized SAR sensors for oil spill observation is operationally important.Many studies on the use of partially polarimetric SAR data for geophysical remote sensing have been addressed (e.g.Lee et al.2001,Raney 2007).Among them,for the purposes of this paper,some theoretical and land application studies (Ulaby et al.1987,Boerner et al.1987,Ulaby et al.1992,Kuga and Zhao 1996,Lee et al.2001)using the co-polarized phase difference (CPD),that is the phase difference between HH and VV channels,are emphasized.Only a few preliminary studies have been published regarding sea application of the CPD (Schuler et al.1993),and none on oil spill observations.In Schuler et al.(1993)a relationship between the CPD and sea surface roughness and local incidence angle was reported using JPL AIRSAR C-,L-and P-band polarimetric data.In Lee et al.(1994)a closed form for the multilook CPD probability density function (pdf)was derived and compared successfully with JPL AIRSAR polarimetric ocean surface SAR data.In this paper a new paradigm is stated:dual-polarimetric SAR data,once properly interpreted by means of a tailored electromagnetic model,are more useful than the single polarization data for oil spill observation.A model that relates the CPD to sea surface scattering mechanisms with and without slicks is first developed.It is shown that,under low to moderate wind conditions,the broadening of the CPD pdf is sensitive to the presence of a low backscattering area.The theoretical considerations predict a different sensitivity of oil slicks and biogenic look-alikes because of their different damping effects.Thus,a novel and very effective filtering technique,based on CPD,has been implemented and tested on multilook complex (MLC)C-and L-band SAR data.The results confirm that the C-band is better than the L-band (Gade et al.1998)and that the CPD is useful both to assist oil spill observation and to distinguish between oil spills and biogenic look-alikes.This1588M.Migliaccio et al .D o w n l o a d e d B y : [O c e a n U n i v e r s i t y o f C h i n a ] A t : 02:26 20 S e p t e m b e r 2010filtering technique can be used to improve classical oil spill detection procedures.The paper is organized as follows:in section 2the theoretical background is reported;in section 3the experiments are presented and discussed;and conclusions are drawn in section 4.2.TheoryA full-polarimetric SAR measures the 262scattering matrix S ,which relates the electromagnetic field scattered by the observed scene E s to the incident one E i (Guissard 1994):E s~e {jkr rSE ið1Þwhere j is the imaginary unit,k is electromagnetic wavenumber and r is the distance.The scattering matrix,considering the horizontal and vertical linearly polarized electric fields,can be expressed by:S ~:S hh :S hv:S vh :S vv !ð2Þwhere each complex element of the scattering matrix,called the scattering amplitude,can be written as::S pq ~S pq e j Q pq p ,q ~h ,v ð3ÞThus,invoking reciprocity,equation (2)can be written as:S ~ej Q vv S hh e j Q cS hv e j Q xS hv e j Q x S vv ð4ÞwhereQ x ~Q hv {Q vv ~Q vh {Q vvð5ÞandQ c ~Q hh {Q vvð6Þare the cross-polarized phase difference (XPD)and the CPD,respectively.It is well known that in natural surface scattering the Q pq are uniformly distributed and contain no useful information (Ulaby et al.1992).This is generally untrue for the CPD and XPD.In fact,as the co-and cross-polarized scattering amplitudes are almost uncorrelated for most natural surfaces,the XPD follows approximately a uniform distribution (Ulaby et al.1992)(see also experimental pdf shown in figure 1)whereas,because of the correlation between the co-polarized scattering amplitudes,the CPD is generally non-uniformly distributed (Ulaby et al.1992)and has a mathematical expression that is given by (Joughin et al.1994,Lee et al.1994):p l Q c ðÞ~1{r 2ÀÁl C 2l ðÞ2ffiffiffip p C l ðÞ11{b l z 1=2ðÞ=2P {l {1=2l {3=2{b ðÞð7ÞwithCPD for oil spill observation 1589D o w n l o a d e d B y : [O c e a n U n i v e r s i t y o f C h i n a ] A t : 02:26 20 S e p t e m b e r 2010b ~r cos Qc {Q ðÞð8Þwhere l is the number of looks,P (?)is the associate Legendre function of the firstkind and C (?)is the gamma function.r and Q–are the modulus and the phase of the complex correlation coefficient between HH and VV channels,respectively,and :r is given by (Joughin et al.1994,Lee et al.1994)::r ~·:S hh :S Ãvv ¶ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi·hh vv Qð9ÞThe width of (7)depends on l and on :r .In particular,the pdf becomes narrowerwhen either l or r increase.The peak of the pdf is at Q c 5Q–(Joughin et al.1994,Lee et al.1994).Moreover,when r tends to 0(total decorrelation between HH and VV channels),the pdf becomes uniformly distributed between [2p ,p ),while for r approaching 1(HH and VV totally correlated)the pdf tends to a Dirac deltafunction.For 0,r ,1the pdf resembles a Gaussian bell with a mean value m 5Q–and a standard deviation s that is inversely related to r (see figure 2).It is now important to read the CPD pdf in marine physical terms.Its behaviour can be explained,under low to moderate wind conditions and for incidence angles far from the grazing angle,by considering some key reference scenarios.In the case of an oil-free sea surface,the small-scale scattering is well modelled by the Bragg scattering mechanism,which is characterized by low polarimetric entropy (Schuler and Lee 2006)and the HH–VV phase difference around 0u (Guissard 1994).Two cases must beconsidered.Figure 1.Plots of the theoretical XPD pdf (dashed line)and the experimental one relevant to a transect obtained from the C-Band.SIR-C/X SAR data acquired on 4October 1994at 04:37UTC (solid line).1590M.Migliaccio et al .D o w n l o a d e d B y : [O c e a n U n i v e r s i t y o f C h i n a ] A t : 02:26 20 S e p t e m b e r 2010When the long-wave structure is weak,the backscatter follows the SmallPerturbation Model (SPM).Because the first-order SPM does not show any depolarization,the cross-polarized scattering amplitudes vanish and the scattering matrix S is diagonal.In practice,because of the high HH–VV correlation (Van Zyl 1989),we expect a narrow CPD pdf whose width is mainly related to the system noise (Freeman 1993).When the long-wave structure is present,the backscatter calls for a two-scale model.Depolarization effects,as well as an increasing of the amount of polarimetric entropy,are expected (Schuler et al.1993,Schuler and Lee 2006),and the full S matrix needs to be considered.In practice,the cross-polarized terms are neglected because they are smaller than the co-polarized ones and very close to the noise floor (Freeman et al.1994).In real measurements,the two former oil-free sea scattering cases are almost indistinguishable in terms of CPD pdf.The main effect of an oil slick over the sea surface is to dampen the small-scale structure.A low backscattered signal and a high polarimetric entropy,which indicate that a non-Bragg scattering mechanism is in place (Schuler and Lee 2006),are experienced (Migliaccio et al.2007).As the polarimetric entropy measures the randomness of the complex polarimetric scattering processes (Cloude and Pottier 1996),a low correlation between the HH and VV backscattered signals,and thus a broadening of the CPD pdf,is expected for the oil-covered area.In other words,oil slicks,which are generally characterized by strong damping properties (Gade et al.1998),are expected to be distinguishable from the surrounding sea because of their different scattering mechanisms.The case of a biogenic slick is very different.The presence of a biogenic slick over the sea surface,because of its weak damping property (Gade et al.1998),still calls for a Bragg scattering mechanism,that is a Bragg scattering with a lower backscattered signal.Therefore,similar CPD pdfs for the biogenic-free and biogenic-covered sea surface are to beexpected.Figure 2.Plots of the theoretical CPD pdf for |r |50.1,0.7,0.9and its phase Q –50u ,with l 54.CPD for oil spill observation 1591D o w n l o a d e d B y : [O c e a n U n i v e r s i t y o f C h i n a ] A t : 02:26 20 S e p t e m b e r 20103.ExperimentsIn this section we describe and discuss the experiments used to demonstrate the capability of the CPD both to observe an oil spill and to distinguish between oil spills and biogenic look-alikes,under low to moderate wind conditions.A total of 25C-and L-band MLC SAR images were processed.In detail,seven acquisitions include scenes in which biogenic look-alikes were present,four acquisitions were relevant to oil spills and in one an oil spill and six different biogenic look-alikes were present.In total,40low backscattering areas were analysed.The data set was acquired by the sensor SIR-C/X-SAR during the missions STS-59(April 1994)and STS-68(September and October 1994).Further details on the data set can be found in table 1(Gade et al.1998).The radar was designed and built to make eight different measurements at the same time:L-and C-band backscatter at four different polarization combinations:HH,HV,VH and VV (multifrequency and fully polarimetric SAR).The noise floor at the L-band and the C-band was 236and 228dB,respectively.The incidence angle varied between 20u and 55u and the SAR swath width on the ground varied between 15km and 90km.SAR data were processed by means of a simple and effective filtering technique that,applied over the CPD image,estimated m and s through an N 6N movingTable 1.C-and L-band SIR-C/X SAR data set.Processing number Type and band Area of acquisition Date,time UTC Surfactant Wind speed (m s 21)11587MLC L-band Pacific Ocean (Japan)15April,02:14OLA 8.811588MLC C-band 41466MLC L-band Pacific Ocean (Japan)4October,04:37OLA 9.341467MLC C-band 41369MLC L-band Pacific Ocean (Japan)1October,05:33OLA 5.741370MLC C-band 11351MLC L-band Pacific Ocean (Japan)12April,03:12OLA 9.011352MLC C-band 11438MLC L-band Pacific Ocean (Japan)16April,01:53OLA 6.811439MLC C-band 11585MLC L-band Pacific Ocean (Japan)8April,21:38OLA 4.211586MLC C-band 41464MLC L-band Pacific Ocean (Japan)2October,05:15OLA 5.241465MLC C-band 12815MLC L-band Azores 12April,07:21Oil Low to moderate*12816MLC C-band 17040MLC L-band North Sea 11April,10:49Oil Low to moderate*17041MLC C-band 44326MLC L-band North Sea 1October,08:14Oil Low to moderate*44327MLC C-band 49938MLC L-band English Channel 8October,05:57Oil 4.049939MLC C-band 40385MLC L-band North Sea11October,08:12Oil and look-alikes12.040386MLCC-band*In this case no detailed information on the wind speed is available.Only the reference wind condition is given (Gade et al.1998).1592M.Migliaccio et al .D o w n l o a d e d B y : [O c e a n U n i v e r s i t y o f C h i n a ] A t : 02:26 20 S e p t e m b e r 2010window.In this study a window size equal to 7was used because it represents a good compromise between speckle smoothing and texture preservation in polarimetric SAR images (Lee et al.1997).Seven of the experiments are shown and discussed in detail.Other results are summarized in table 2.The first experiments concern the processing of SAR data in which only oil spills are present.Then,the same analysis is accomplished over SAR data in which Oley alcohol (OLA)slicks are present.OLA forms a monomolecular surface film that simulates well a biogenic surface slick (Gade et al.1998).The last experiment is with regard to a SAR acquisition,under high wind speed,in which both biogenic look-alikes and an oil spill are present.The first data set is relevant to the acquisition of 1October 1994,8:14UTC [processing number (p.n.)44326].Figure 3(a )shows an excerpt of the L-band VV power SAR image in which an oil spill is clearly visible.The estimated m and s images are shown in grey tones in figures 3(b )and 3(c ),respectively.They do not reveal any features related to the oil spill.This result can be quantitatively confirmed by analysing the measured CPD pdfs,relevant to both the oil slick and the surrounding sea surface,see figure 3(d ).In fact,the CPD approach is not able to discriminate between the oil spill and the surrounding sea surface.Similar results were obtained for all the L-band SAR images (not shown because of limited space).The results are consistent with those reported by Gade et al.(1998)and show that the CPD approach is not useful for oil spill observation when applied to L-band data.The second data set is relevant to the same acquisition but at the C-band,p.n.44327(figure 4(a )).In this case the CPD output images clearly show features related to the oil spill (figures 4(b )and 4(c )).Analysis of the m and s images shows that oil spill is clearly distinguishable,and s provides the key information.This result confirms the theoretical model proposed in section 2,which predicts a different scattering mechanism in the presence of an oil spill and this is revealed by theTable 2.C-and L-band SIR-C/X SAR data set.Processing number Surfactant Mean s slick (u )Mean s sea (u )c VV image c s image 11588OLA 4.5 3.50.3480.083241467OLA 4.0 3.60.3900.057241370OLA 5.1 4.00.3260.069111352OLA 12.310.30.3300.17211439OLA 6.3 4.70.4360.16611586OLA 5.7 4.70.2150.10941465OLA 10.48.70.1310.078412816Spill 19.311.20.3360.58317041Spill 60.011.20.4770.83344327Spill 60.017.00.3780.62049939Spill 34.318.00.2990.21740386A 17.713.80.2820.100B 19.013.80.3580.105C 17.913.80.2920.0870D 21.113.80.3760.127E 19.613.80.3670.186F 16.213.80.3860.115G16.013.80.2750.0970CPD for oil spill observation 1593D o w n l o a d e d B y : [O c e a n U n i v e r s i t y o f C h i n a ] A t : 02:26 20 S e p t e m b e r 2010analysis of the measured oil spill CPD pdf,which is much broader than the surrounding sea surface (figure 4(d )).The mean oil spill s value is 60.0u while that for the surrounding sea surface is only 17.0u .The behaviour predicted by the theoretical model is confirmed by the analysis of the polarimetric entropy,estimated according to the Cloude and Pottier (1996)eigenvector decomposition theorem.The entropy values for the oil-covered and oil-free sea surface are 0.89and 0.61,respectively.Note,however,that in this case the estimation procedure needs fully polarimetric data.It should also be noted that,because of the very different s values exhibited by the oil-covered sea surface and its surroundings,the CPD for oil spills acts as an emphasis filter.To quantitatively estimate the emphasizing capability of the CPD,the contrast parameter (c ),defined according to Blacknell (1994)as the standard deviation to mean ratio,was evaluated.This is a texture-related parameter that is largely used for choosing the adaptive threshold in dark patch detectionproceduresFigure 3.L-band SAR data relevant to the acquisition of 1October 1994at 08:14UTC (p.n.44326).(a )An excerpt of the L-band VV power SAR image in which an oil spill is clearly visible.(b ,c )The estimated m and s images,respectively,shown in grey tones.(d )The measured CPD pdfs relevant to both the oil-covered and the surrounding sea surface.1594M.Migliaccio et al .D o w n l o a d e d B y : [O c e a n U n i v e r s i t y o f C h i n a ] A t : 02:26 20 S e p t e m b e r 2010(Solberg et al.2007)and,combined with other geometrical and radiometric features,for discriminating between oil spills and look-alikes (Solberg et al.1999).The c parameter was evaluated for the VV power image and the corresponding s image.In this latter case,c was equal to 0.378and 0.620for the VV and s images,respectively.Thus,the contrast was approximately doubled after the CPD-based filtering.The third data set is relevant to the acquisition of 11April 1994,10:49UTC (p.n.17041),see figure 5(a ).The processing results are in agreement with what was experienced previously (figure 5(b )).The fourth data set is relevant to the acquisition of 8October 1994,5:57UTC (p.n.49939),see figure 6(a ).A typical oil spill pattern due to a ship (see elongated shape related to the spilling mechanism)is present.No information about the type of oil is reported in the literature (Fortuny-Guasch 2003).As in the previous cases,the output image (figure 6(b ))clearly shows features related to the oil spill.TheFigure 4.C-band SAR data relevant to the acquisition of 1October 1994at 08:14UTC (p.n.44327).(a )An excerpt of the C-band VV power SAR image in which an oil spill is clearly visible.(b ,c )The estimated m and s images,respectively,shown in grey tones.(d )The measured CPD pdfs relevant to both the oil-covered and the surrounding sea surface.CPD for oil spill observation 1595D o w n l o a d e d B y : [O c e a n U n i v e r s i t y o f C h i n a ] A t : 02:26 20 S e p t e m b e r 2010measured oil CPD pdf is broader than the sea one (figure 6(c ))and in fact the oil spill and sea mean s values are very different (34.3u ,18.0u ).Concerning c ,it is equal to 0.299and 0.217for the VV and the s images,respectively.Such an unexpected result is most probably due to the ageing and weathering processes that generate greater image heterogeneity.Before proceeding further,it is important to note that it might be thought that the ability to detect an oil slick by measuring the CPD s values is related to the low SIR-C signal-to-noise ratio (SNR).However,this is not the case as shown,for instance,in the worst case (p.n.44327),where the oil-covered CPD pdf was plotted only considering the pixel values above the noise floor (figure 7).The s values are now 17.0u and 44.0u (instead of 17.0u and 60.0u )for the oil-free and oil-covered areas,respectively.This behaviour confirms the physical consistency of the proposed approach.The following experiments were performed over SAR images in which biogenic look-alikes were present.The fifth data set is relevant to the acquisition of 15April 1994,2:14UTC (p.n.11588),in which an OLA is clearly visible (see figure 8(a )).The s image (figure 8(b))does not show any features related to the OLA,that is it is not possible to discriminate the OLA.This result confirms the proposed theoretical model that predicts,for a weaker damping,a scattering mechanism similar to the sea surface,as witnessed by the measured CPD pdfs that are almost overlapping (figure 8(c )).In detail,the mean s value relevant to the OLA is 4.5u while the surrounding sea surface one is 3.5u.Figure 5.C-band SAR data relevant to the acquisition of 11April 1994at 10:49UTC (p.n.17041).(a )An excerpt of the C-band VV power SAR image in which two oil spills are present.(b )The estimated s image shown in grey tones.1596M.Migliaccio et al .D o w n l o a d e d B y : [O c e a n U n i v e r s i t y o f C h i n a ] A t : 02:26 20 S e p t e m b e r 2010The behaviour predicted by the theoretical model is confirmed by the analysis ofthe polarimetric entropy estimated for both the slick-covered (0.54)and the surrounding sea surface (0.53).Moreover,the c values are 0.348and 0.0832for the VV power image and the s image,respectively.This shows that the CPD,for OLA,acts as a de-emphasis filter.The sixth data set is relevant to the acquisition of 1October 1994,5:33UTC (p.n.41370),in which an OLA is present (figure 9(a )).This result is in agreement with what was experienced previously (see figures 9(b )and 9(c )).The only additional comment relevant to the acquisitions made over the area of Japan (see table 1)is that in these cases a peak shift is exhibited on both the sea and the OLA CPD pdfs.Its physical meaning is not related to the presence of OLA but more insights are presently unavailable.It should be noted,however,that this does not affect the CPD filtering capabilities.The last data set concerns the experiment conducted by the University of Hamburg described in Gade et al.(1998).During this experiment artificialbiogenicFigure 6.C-band SAR data relevant to the acquisition of 8October 1994at 05:57UTC (p.n.49939).(a )An excerpt of the C-band VV power SAR image in which an oil spill is clearly visible.(b )The estimated image shown in grey tones.(c )The measured CPD pdfs relevant to both the oil-covered and the surrounding sea surface.CPD for oil spill observation 1597D o w n l o a d e d B y : [O c e a n U n i v e r s i t y o f C h i n a ] A t : 02:26 20 S e p t e m b e r 2010films and a mineral oil spill consisting of heavy fuel (IFO 180)were deployed.The corresponding SAR data were acquired on 11October 1994(p.n.40386)over the German Bight of the North Sea,under high wind conditions.The area of interest in the experiment is shown in figure 10(a ),where the seven small slick-covered areas are present.From top to bottom the surface films are due to IFO 180,OLA,oleic acid methyl ester (OLME),triolein (TOLG),TOLG spread with the help of n -hexane,OLME spread with the help of n -hexane and OLME spread with the help of ethanol,respectively (Gade et al.1998).To identify the seven slicks,they are labelled as A,B,C,D,E,F and G,from top to bottom.Analysis of the s image (figure 10(b ))and the measured CPD pdfs relevant to slicks A and B (figures 10(c )and 10(d))Figure 8.C-band SAR data relevant to the acquisition of 15April 1994at 02:14UTC (p.n.11588).(a )An excerpt of the C-band VV power SAR image in which an OLA slick is clearly visible.(b )The estimated s image shown in grey tones.(c )The measured CPD pdfs relevant to both the slick-covered and the surrounding sea surface.1598M.Migliaccio et al .D o w n l o a d e d B y : [O c e a n U n i v e r s i t y o f C h i n a ] A t : 02:26 20 S e p t e m b e r 2010。

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