Parton Densities and Fragmentation Functions from Polarized Lambda Production in Semi-Inclu

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半导体器件中英名词解释

半导体器件中英名词解释
变容二极管:电容随着外加电压的改变而改变的二极管。
carrier injection: The flow of carriers across the space charge region of a pn junction when a voltage is applied.
载流子注入:外加偏压时,pn结体内载流子穿过空间电荷区进入p区或n区的过程。
雪崩击穿:在反向偏置时,势垒区中电场较强。随着反向偏压的增加,势垒区中电场会变得 很强, 使得电子和空穴在如此强的电场加速作用下具有足够大的动能, 以至于它们与势垒区 内原子发生碰撞时能把价键上的电子碰撞出来成为导电电子, 同时产生一个空穴, 新产生的 电子、 空穴在强电场加速作用下又会与晶格原子碰撞轰击出新的导电电子和空穴„„, 如此 连锁反应好比雪崩一样。 这种载流子数迅速增加的现象称为倍增效应。 如果电压增加到一定 值引起倍增电流趋于无穷大,这种现象叫雪崩击穿。
tunneling breakdown/Zener breakdown: Maybe top of the valence band of the p region is higher than the bottom of conduction band of the n region with the reverse bias voltage increases in heavily doped pn junction. The electrons in valence band of the p region can directly reach the conduction band of the n region through the band gap by tunnel effect, to become the carrier in the conduction band. When the reverse bias voltage at the junction increases to a certain extent, tunneling current will sharply

stable diffusion 摄影术语

stable diffusion 摄影术语

stable diffusion 摄影术语稳定扩散(stable diffusion)是摄影术语中的一个概念,指的是使用特定的技术手段在摄影作品中创造出一种模糊、柔和、温暖的效果,给人一种梦幻、浪漫、温馨的感觉。

稳定扩散常常被用于人像摄影和风光摄影中,以营造出一种柔和、温暖的氛围,使照片更加有韵味、有吸引力。

稳定扩散可以通过使用滤镜、调整设备设置、后期处理等多种方式来实现。

下面将详细介绍几种常见的稳定扩散实现方法。

一、使用滤镜:1. 扩散镜(Soft Focus Filter)是一种非常常见的稳定扩散滤镜,其主要作用是增加整个图像的柔和程度。

扩散镜利用镜片表面的纹理,模糊图像的细节,同时给予整个画面一个温暖而柔和的效果。

不同的扩散镜有不同的纹理和颗粒大小,可以根据需要选择。

2. 透镜镀层滤镜(Lens Coating Filter)是另一种常见的稳定扩散滤镜,它可以改变物体的反射和折射,使光线分散并产生一个柔和的效果。

透镜镀层滤镜常常用于拍摄阳光照射的场景,可以创造出太阳光穿过树叶间隙的效果。

3. 灰度滤镜(Neutral Density Filter)是一种常用的稳定扩散滤镜,它用于平衡不同场景中的曝光差异。

灰度滤镜可以使高亮区域变得柔和,避免过曝的现象。

通过选择不同的灰度滤镜,可以调整图像的扩散程度和整体效果。

二、调整设备设置:1. 光圈设置:选择较大的光圈值(如f/1.8、f/2.8等)可以减小景深,使前景和背景更模糊,从而创造出一种柔和的效果。

2. 快门速度:使用较长的快门速度(如1/30秒、1/60秒等)可以使相机在拍摄过程中有微小的晃动,从而产生一种轻微的模糊效果,增加稳定扩散的效果。

3. ISO设置:选择较低的ISO值(如ISO 100、ISO 200等)可以降低图像噪点,使图像更加柔和。

在充足的光线条件下使用低ISO值可以得到更好的效果。

三、后期处理:1. 软化滤镜:在后期处理中,可以使用软化滤镜或模糊工具来增加图像的扩散效果。

用密度函数理论和杜比宁方程研究活性炭纤维多段充填机理

用密度函数理论和杜比宁方程研究活性炭纤维多段充填机理

密度函数理论和杜比宁方程可以用来研究活性炭纤维在多段充填过程中的吸附行为。

密度函数理论是一种分子统计力学理论,它建立在分子统计学和热力学的基础上,用来研究一种系统中分子的分布。

杜比宁方程是一种描述分子吸附行为的方程,它可以用来计算吸附层的厚度、吸附速率和吸附能量等参数。

在研究活性炭纤维多段充填过程中,可以使用密度函数理论和杜比宁方程来研究纤维表面的分子结构和吸附行为。

通过分析密度函数和杜比宁方程的解,可以得出纤维表面的分子结构以及纤维吸附的分子的种类、数量和能量。

这些信息有助于更好地理解活性炭纤维的多段充填机理。

在研究活性炭纤维的多段充填机理时,还可以使用其他理论和方法来帮助我们更好地了解这一过程。

例如,可以使用扫描电子显微镜(SEM)和透射电子显微镜(TEM)等技术来观察纤维表面的形貌和结构。

可以使用X射线衍射(XRD)和傅里叶变换红外光谱(FTIR)等技术来确定纤维表面的化学成分和结构。

还可以使用氮气吸附(BET)和旋转氧吸附(BJH)等技术来测量纤维表面的比表面积和孔结构。

通过综合运用密度函数理论、杜比宁方程和其他理论和方法,可以更全面地了解活性炭纤维的多段充填机理,从而更好地控制和优化多段充填的过程。

在研究活性炭纤维多段充填机理时,还可以使用温度敏感性测试方法来研究充填过程中纤维表面的动力学性质。

例如,可以使用动态氧吸附(DAC)或旋转杆氧吸附(ROTA)等技术来测量温度对纤维表面吸附性能的影响。

通过对比不同温度下纤维表面的吸附性能,可以更好地了解充填过程中纤维表面的动力学性质。

此外,还可以使用分子动力学模拟方法来研究纤维表面的吸附行为。

例如,可以使用拉曼光谱或红外光谱等技术来测量纤维表面的分子吸附构型。

然后,使用分子动力学模拟方法来模拟不同分子吸附构型下的纤维表面的动力学性质,帮助我们更好地了解活性炭纤维的多段充填机理。

多肽固相合成步骤英文描述

多肽固相合成步骤英文描述

多肽固相合成步骤英文描述多肽固相合成是一种合成肽链的方法,它涉及到多个步骤。

以下是多肽固相合成的步骤和英文描述:1. 准备载体:选择适当的树脂,如弱碱性丙烯酰胺树脂(Acrylamide resin)。

Prepare resin: select an appropriate resin, such as weakly basic acrylamide resin.2. 载体预处理:将树脂进行预处理,如使用二氯甲烷和二甲基甲酰胺进行交替洗涤,实现树脂表面的清洁和活化。

Pre-treatment of the resin: pre-treat the resin, such as alternating washing with dichloromethane and dimethylformamide to achieve a clean and activated resin surface.3. 防止侧反应:在肽链合成过程中,需要采取措施防止侧反应的发生,例如使用保护基。

Prevent side reactions: measures need to be taken to prevent side reactions during peptide synthesis, such as using protective groups.4. 合成肽链:通过加入氨基酸单元和活化剂,将肽链逐步合成。

Synthesize the peptide chain: synthesize the peptide chain step by step by adding amino acid units and activators.5. 洗脱肽链:用酸性溶液或氢氟酸将肽链从树脂上洗脱。

Elute the peptide chain: elute the peptide chain from the resin using an acidic solution or hydrogen fluoride.6. 去保护基:使用适当的溶液去除保护基。

【高分子专业英语翻译】

【高分子专业英语翻译】

【高分子专业英语翻译】第五课乳液聚合大部分的乳液聚合都是由自由基引发的并且表现出其他自由基体系的很多特点,最主要的反应机理的不同源自小体积元中自由基增长的场所不同。

乳液聚合不仅允许在高反应速率下获得较高分子量,这在本体聚合中是无法实现或效率低下的,,同时还有其他重要的实用优点。

水吸收了大部分聚合热且有利于反应控制,产物在低粘度体系中获得,容易处理,可直接使用或是在凝聚,水洗,干燥之后很快转化成固体聚合物。

在共聚中,尽管共聚原理适用于乳液体系,单体在水相中溶解能力的不同也可能导致其与本体聚合行为不同,从而有重要的实际意义。

乳液聚合的变化很大,从包含单一单体,乳化剂,水和单一引发剂的简单体系到这些包含有2,3个单体,一次或分批添加,,混合乳化剂和助稳定剂以及包括链转移剂的复合引发体系。

单体和水相的比例允许变化范围很大,但是在技术做法上通常限制在30/70到60/40。

单体和水相比更高时则达到了直接聚合允许的极限,只有通过分批添加单体方法来排除聚合产生的大量的热。

更复杂的是随着胶体数的增加粘度也大大增加,尤其是当水溶性的单体和聚合物易容时,反应结束胶乳浓度降低。

这一阶段常常伴随着通过聚集作用或是在热力学不稳定时凝结作用而使胶粒尺寸增大。

第十课高分子的构型和构象本课中我们将使用根据经典有机化学术语而来的构型和构象这两个词。

构型异构是由于分子中存在一个或多个不对称中心,以最简单的C原子为例,每一碳原子的绝对构型为R型和S型,当存在双键时会有顺式和反式几何异构。

以合成聚合物为例,构型异构的典型问题和R.S型不对称碳原子在主链上的排布有关。

这些不对称碳原子要么来自不对称单体,如环氧丙烷,要么来自对称单体,如乙烯单体,,这些物质的聚合,在每个单体单元中形成至少一个不对称碳原子。

大分子中的构型异构源于侧链上存在不对称的碳原子,例如不对称乙烯单体的聚合,也是可能的,现今已经被广泛研究。

和经典有机化学术语一致,构象,旋转体,旋转异构体,构象异构体,指的是由于分子单键的内旋转而形成的空间排布的不同。

斯仑贝谢所有测井曲线英文名称解释

斯仑贝谢所有测井曲线英文名称解释

斯仑贝谢所有测井曲线英文名称解释OCEAN DRILLING PROGRAMACRONYMS USED FOR WIRELINE SCHLUMBERGER TOOLS ACT Aluminum Clay ToolAMS Auxiliary Measurement SondeAPS Accelerator Porosity SondeARI Azimuthal Resistivity ImagerASI Array Sonic ImagerBGKT Vertical Seismic Profile ToolBHC Borehole Compensated Sonic ToolBHTV Borehole TeleviewerCBL Casing Bond LogCNT Compensated Neutron ToolDIT Dual Induction ToolDLL Dual LaterologDSI Dipole Sonic ImagerFMS Formation MicroScannerGHMT Geologic High Resolution Magnetic ToolGPIT General Purpose Inclinometer ToolGR Natural Gamma RayGST Induced Gamma Ray Spectrometry ToolHLDS Hostile Environment Lithodensity SondeHLDT Hostile Environment Lithodensity ToolHNGS Hostile Environment Gamma Ray SondeLDT Lithodensity ToolLSS Long Spacing Sonic ToolMCD Mechanical Caliper DeviceNGT Natural Gamma Ray Spectrometry ToolNMRT Nuclear Resonance Magnetic ToolQSST Inline Checkshot ToolSDT Digital Sonic ToolSGT Scintillation Gamma Ray ToolSUMT Susceptibility Magnetic ToolUBI Ultrasonic Borehole ImagerVSI Vertical Seismic ImagerWST Well Seismic ToolWST-3 3-Components Well Seismic ToolOCEAN DRILLING PROGRAMACRONYMS USED FOR LWD SCHLUMBERGER TOOLSADN Azimuthal Density-NeutronCDN Compensated Density-NeutronCDR Compensated Dual ResistivityISONIC Ideal Sonic-While-DrillingNMR Nuclear Magnetic ResonanceRAB Resistivity-at-the-BitOCEAN DRILLING PROGRAMACRONYMS USED FOR NON-SCHLUMBERGER SPECIALTY TOOLSMCS Multichannel Sonic ToolMGT Multisensor Gamma ToolSST Shear Sonic ToolTAP Temperature-Acceleration-Pressure ToolTLT Temperature Logging ToolOCEAN DRILLING PROGRAMACRONYMS AND UNITS USED FOR WIRELINE SCHLUMBERGER LOGSAFEC APS Far Detector Counts (cps)ANEC APS Near Detector Counts (cps)AX Acceleration X Axis (ft/s2)AY Acceleration Y Axis (ft/s2)AZ Acceleration Z Axis (ft/s2)AZIM Constant Azimuth for Deviation Correction (deg)APLC APS Near/Array Limestone Porosity Corrected (%)C1 FMS Caliper 1 (in)C2 FMS Caliper 2 (in)CALI Caliper (in)CFEC Corrected Far Epithermal Counts (cps)CFTC Corrected Far Thermal Counts (cps)CGR Computed (Th+K) Gamma Ray (API units)CHR2 Peak Coherence, Receiver Array, Upper DipoleCHRP Compressional Peak Coherence, Receiver Array, P&SCHRS Shear Peak Coherence, Receiver Array, P&SCHTP Compressional Peak Coherence, Transmitter Array, P&SCHTS Shear Peak Coherence, Transmitter Array, P&SCNEC Corrected Near Epithermal Counts (cps)CNTC Corrected Near Thermal Counts (cps)CS Cable Speed (m/hr)CVEL Compressional Velocity (km/s)DATN Discriminated Attenuation (db/m)DBI Discriminated Bond IndexDEVI Hole Deviation (degrees)DF Drilling Force (lbf)DIFF Difference Between MEAN and MEDIAN in Delta-Time Proc. (microsec/ft) DRH HLDS Bulk Density Correction (g/cm3)DRHO Bulk Density Correction (g/cm3)DT Short Spacing Delta-Time (10'-8' spacing; microsec/ft)DT1 Delta-Time Shear, Lower Dipole (microsec/ft)DT2 Delta-Time Shear, Upper Dipole (microsec/ft)DT4P Delta- Time Compressional, P&S (microsec/ft)DT4S Delta- Time Shear, P&S (microsec/ft))DT1R Delta- Time Shear, Receiver Array, Lower Dipole (microsec/ft)DT2R Delta- Time Shear, Receiver Array, Upper Dipole (microsec/ft)DT1T Delta-Time Shear, Transmitter Array, Lower Dipole (microsec/ft)DT2T Delta-Time Shear, Transmitter Array, Upper Dipole (microsec/ft)DTCO Delta- Time Compressional (microsec/ft)DTL Long Spacing Delta-Time (12'-10' spacing; microsec/ft)DTLF Long Spacing Delta-Time (12'-10' spacing; microsec/ft)DTLN Short Spacing Delta-Time (10'-8' spacing; microsec/ftDTRP Delta-Time Compressional, Receiver Array, P&S (microsec/ft)DTRS Delta-Time Shear, Receiver Array, P&S (microsec/ft)DTSM Delta-Time Shear (microsec/ft)DTST Delta-Time Stoneley (microsec/ft)DTTP Delta-Time Compressional, Transmitter Array, P&S (microsec/ft)DTTS Delta-Time Shear, Transmitter Array, P&S (microsec/ft)ECGR Environmentally Corrected Gamma Ray (API units)EHGR Environmentally Corrected High Resolution Gamma Ray (API units) ENPH Epithermal Neutron Porosity (%)ENRA Epithermal Neutron RatioETIM Elapsed Time (sec)FINC Magnetic Field Inclination (degrees)FNOR Magnetic Field Total Moment (oersted)FX Magnetic Field on X Axis (oersted)FY Magnetic Field on Y Axis (oersted)FZ Magnetic Field on Z Axis (oersted)GR Natural Gamma Ray (API units)HALC High Res. Near/Array Limestone Porosity Corrected (%)HAZI Hole Azimuth (degrees)HBDC High Res. Bulk Density Correction (g/cm3)HBHK HNGS Borehole Potassium (%)HCFT High Resolution Corrected Far Thermal Counts (cps)HCGR HNGS Computed Gamma Ray (API units)HCNT High Resolution Corrected Near Thermal Counts (cps)HDEB High Res. Enhanced Bulk Density (g/cm3)HDRH High Resolution Density Correction (g/cm3)HFEC High Res. Far Detector Counts (cps)HFK HNGS Formation Potassium (%)HFLC High Res. Near/Far Limestone Porosity Corrected (%)HEGR Environmentally Corrected High Resolution Natural Gamma Ray (API units) HGR High Resolution Natural Gamma Ray (API units)HLCA High Res. Caliper (inHLEF High Res. Long-spaced Photoelectric Effect (barns/e-)HNEC High Res. Near Detector Counts (cps)HNPO High Resolution Enhanced Thermal Nutron Porosity (%)HNRH High Resolution Bulk Density (g/cm3)HPEF High Resolution Photoelectric Effect (barns/e-)HRHO High Resolution Bulk Density (g/cm3)HROM High Res. Corrected Bulk Density (g/cm3)HSGR HNGS Standard (total) Gamma Ray (API units)HSIG High Res. Formation Capture Cross Section (capture units) HSTO High Res. Computed Standoff (in)HTHO HNGS Thorium (ppm)HTNP High Resolution Thermal Neutron Porosity (%)HURA HNGS Uranium (ppm)IDPH Phasor Deep Induction (ohmm)IIR Iron Indicator Ratio [CFE/(CCA+CSI)]ILD Deep Resistivity (ohmm)ILM Medium Resistivity (ohmm)IMPH Phasor Medium Induction (ohmm)ITT Integrated Transit Time (s)LCAL HLDS Caliper (in)LIR Lithology Indicator Ratio [CSI/(CCA+CSI)]LLD Laterolog Deep (ohmm)LLS Laterolog Shallow (ohmm)LTT1 Transit Time (10'; microsec)LTT2 Transit Time (8'; microsec)LTT3 Transit Time (12'; microsec)LTT4 Transit Time (10'; microsec)MAGB Earth's Magnetic Field (nTes)MAGC Earth Conductivity (ppm)MAGS Magnetic Susceptibility (ppm)MEDIAN Median Delta-T Recomputed (microsec/ft)MEAN Mean Delta-T Recomputed (microsec/ft)NATN Near Pseudo-Attenuation (db/m)NMST Magnetometer Temperature (degC)NMSV Magnetometer Signal Level (V)NPHI Neutron Porosity (%)NRHB LDS Bulk Density (g/cm3)P1AZ Pad 1 Azimuth (degrees)PEF Photoelectric Effect (barns/e-)PEFL LDS Long-spaced Photoelectric Effect (barns/e-)PIR Porosity Indicator Ratio [CHY/(CCA+CSI)]POTA Potassium (%)RB Pad 1 Relative Bearing (degrees)RHL LDS Long-spaced Bulk Density (g/cm3)RHOB Bulk Density (g/cm3)RHOM HLDS Corrected Bulk Density (g/cm3)RMGS Low Resolution Susceptibility (ppm)SFLU Spherically Focused Log (ohmm)SGR Total Gamma Ray (API units)SIGF APS Formation Capture Cross Section (capture units)SP Spontaneous Potential (mV)STOF APS Computed Standoff (in)SURT Receiver Coil Temperature (degC)SVEL Shear Velocity (km/s)SXRT NMRS differential Temperature (degC)TENS Tension (lb)THOR Thorium (ppm)TNRA Thermal Neutron RatioTT1 Transit Time (10' spacing; microsec)TT2 Transit Time (8' spacing; microsec)TT3 Transit Time (12' spacing; microsec)TT4 Transit Time (10' spacing; microsec)URAN Uranium (ppm)V4P Compressional Velocity, from DT4P (P&S; km/s)V4S Shear Velocity, from DT4S (P&S; km/s)VELP Compressional Velocity (processed from waveforms; km/s)VELS Shear Velocity (processed from waveforms; km/s)VP1 Compressional Velocity, from DT, DTLN, or MEAN (km/s)VP2 Compressional Velocity, from DTL, DTLF, or MEDIAN (km/s)VCO Compressional Velocity, from DTCO (km/s)VS Shear Velocity, from DTSM (km/s)VST Stonely Velocity, from DTST km/s)VS1 Shear Velocity, from DT1 (Lower Dipole; km/s)VS2 Shear Velocity, from DT2 (Upper Dipole; km/s)VRP Compressional Velocity, from DTRP (Receiver Array, P&S; km/s) VRS Shear Velocity, from DTRS (Receiver Array, P&S; km/s)VS1R Shear Velocity, from DT1R (Receiver Array, Lower Dipole; km/s) VS2R Shear Velocity, from DT2R (Receiver Array, Upper Dipole; km/s) VS1T Shear Velocity, from DT1T (Transmitter Array, Lower Dipole; km/s) VS2T Shear Velocity, from DT2T (Transmitter Array, Upper Dipole; km/s) VTP Compressional Velocity, from DTTP (Transmitter Array, P&S; km/s) VTS Shear Velocity, from DTTS (Transmitter Array, P&S; km/s)#POINTS Number of Transmitter-Receiver Pairs Used in Sonic Processing W1NG NGT Window 1 counts (cps)W2NG NGT Window 2 counts (cps)W3NG NGT Window 3 counts (cps)W4NG NGT Window 4 counts (cps)W5NG NGT Window 5 counts (cps)OCEAN DRILLING PROGRAMACRONYMS AND UNITS USED FOR LWD SCHLUMBERGER LOGSAT1F Attenuation Resistivity (1 ft resolution; ohmm)AT3F Attenuation Resistivity (3 ft resolution; ohmm)AT4F Attenuation Resistivity (4 ft resolution; ohmm)AT5F Attenuation Resistivity (5 ft resolution; ohmm)ATR Attenuation Resistivity (deep; ohmm)BFV Bound Fluid Volume (%)B1TM RAB Shallow Resistivity Time after Bit (s)B2TM RAB Medium Resistivity Time after Bit (s)B3TM RAB Deep Resistivity Time after Bit (s)BDAV Deep Resistivity Average (ohmm)BMAV Medium Resistivity Average (ohmm)BSAV Shallow Resistivity Average (ohmm)CGR Computed (Th+K) Gamma Ray (API units)DCAL Differential Caliper (in)DROR Correction for CDN rotational density (g/cm3).DRRT Correction for ADN rotational density (g/cm3).DTAB AND or CDN Density Time after Bit (hr)FFV Free Fluid Volume (%)GR Gamma Ray (API Units)GR7 Sum Gamma Ray Windows GRW7+GRW8+GRW9-Equivalent to Wireline NGT window 5 (cps) GRW3 Gamma Ray Window 3 counts (cps)-Equivalent to Wireline NGT window 1GRW4 Gamma Ray Window 4 counts (cps)-Equivalent to Wireline NGT window 2GRW5 Gamma Ray Window 5 counts (cps)-Equivalent to Wireline NGT window 3GRW6 Gamma Ray Window 6 counts (cps)-Equivalent to Wireline NGT window 4GRW7 Gamma Ray Window 7 counts (cps)GRW8 Gamma Ray Window 8 counts (cps)GRW9 Gamma Ray Window 9 counts (cps)GTIM CDR Gamma Ray Time after Bit (s)GRTK RAB Gamma Ray Time after Bit (s)HEF1 Far He Bank 1 counts (cps)HEF2 Far He Bank 2 counts (cps)HEF3 Far He Bank 3 counts (cps)HEF4 Far He Bank 4 counts (cps)HEN1 Near He Bank 1 counts (cps)HEN2 Near He Bank 2 counts (cps)HEN3 Near He Bank 3 counts (cps)HEN4 Near He Bank 4 counts (cps)MRP Magnetic Resonance PorosityNTAB ADN or CDN Neutron Time after Bit (hr)PEF Photoelectric Effect (barns/e-)POTA Potassium (%) ROPE Rate of Penetration (ft/hr)PS1F Phase Shift Resistivity (1 ft resolution; ohmm)PS2F Phase Shift Resistivity (2 ft resolution; ohmm)PS3F Phase Shift Resistivity (3 ft resolution; ohmm)PS5F Phase Shift Resistivity (5 ft resolution; ohmm)PSR Phase Shift Resistivity (shallow; ohmm)RBIT Bit Resistivity (ohmm)RBTM RAB Resistivity Time After Bit (s)RING Ring Resistivity (ohmm)ROMT Max. Density Total (g/cm3) from rotational processing ROP Rate of Penetration (m/hr)ROP1 Rate of Penetration, average over last 1 ft (m/hr).ROP5 Rate of Penetration, average over last 5 ft (m/hr)ROPE Rate of Penetration, averaged over last 5 ft (ft/hr)RPM RAB Tool Rotation Speed (rpm)RTIM CDR or RAB Resistivity Time after Bit (hr)SGR Total Gamma Ray (API units)T2 T2 Distribution (%)T2LM T2 Logarithmic Mean (ms)THOR Thorium (ppm)TNPH Thermal Neutron Porosity (%)TNRA Thermal RatioURAN Uranium (ppm)OCEAN DRILLING PROGRAMADDITIONAL ACRONYMS AND UNITS(PROCESSED LOGS FROM GEOCHEMICAL TOOL STRING)AL2O3 Computed Al2O3 (dry weight %)AL2O3MIN Computed Al2O3 Standard Deviation (dry weight %) AL2O3MAX Computed Al2O3 Standard Deviation (dry weight %) CAO Computed CaO (dry weight %)CAOMIN Computed CaO Standard Deviation (dry weight %) CAOMAX Computed CaO Standard Deviation (dry weight %) CACO3 Computed CaCO3 (dry weight %)CACO3MIN Computed CaCO3 Standard Deviation (dry weight %) CACO3MAX Computed CaCO3 Standard Deviation (dry weight %) CCA Calcium Yield (decimal fraction)CCHL Chlorine Yield (decimal fraction)CFE Iron Yield (decimal fraction)CGD Gadolinium Yield (decimal fraction)CHY Hydrogen Yield (decimal fraction)CK Potassium Yield (decimal fraction)CSI Silicon Yield (decimal fraction)CSIG Capture Cross Section (capture units)CSUL Sulfur Yield (decimal fraction)CTB Background Yield (decimal fraction)CTI Titanium Yield (decimal fraction)FACT Quality Control CurveFEO Computed FeO (dry weight %)FEOMIN Computed FeO Standard Deviation (dry weight %) FEOMAX Computed FeO Standard Deviation (dry weight %) FEO* Computed FeO* (dry weight %)FEO*MIN Computed FeO* Standard Deviation (dry weight %) FEO*MAX Computed FeO* Standard Deviation (dry weight %) FE2O3 Computed Fe2O3 (dry weight %)FE2O3MIN Computed Fe2O3 Standard Deviation (dry weight %) FE2O3MAX Computed Fe2O3 Standard Deviation (dry weight %) GD Computed Gadolinium (dry weight %)GDMIN Computed Gadolinium Standard Deviation (dry weight %) GDMAX Computed Gadolinium Standard Deviation (dry weight %) K2O Computed K2O (dry weight %)K2OMIN Computed K2O Standard Deviation (dry weight %)K2OMAX Computed K2O Standard Deviation (dry weight %) MGO Computed MgO (dry weight %)MGOMIN Computed MgO Standard Deviation (dry weight %) MGOMAX Computed MgO Standard Deviation (dry weight %)S Computed Sulfur (dry weight %)SMIN Computed Sulfur Standard Deviation (dry weight %) SMAX Computed Sulfur Standard Deviation (dry weight %)SIO2 Computed SiO2 (dry weight %)SIO2MIN Computed SiO2 Standard Deviation (dry weight %) SIO2MAX Computed SiO2 Standard Deviation (dry weight %) THORMIN Computed Thorium Standard Deviation (ppm) THORMAX Computed Thorium Standard Deviation (ppm)TIO2 Computed TiO2 (dry weight %)TIO2MIN Computed TiO2 Standard Deviation (dry weight %) TIO2MAX Computed TiO2 Standard Deviation (dry weight %) URANMIN Computed Uranium Standard Deviation (ppm) URANMAX Computed Uranium Standard Deviation (ppm) VARCA Variable CaCO3/CaO calcium carbonate/oxide factor。

核磁共振波普仪器专业词汇英汉翻译

核磁共振波普仪器专业词汇英汉翻译

APT Attached Proton Test 质子连接实验ASIS Aromatic Solvent Induced Shift 芳香溶剂诱导位移BBDR Broad Band Double Resonance 宽带双共振BIRD Bilinear Rotation Decoupling 双线性旋转去偶(脉冲)COLOC Correlated Spectroscopy for Long Range Coupling 远程偶合相关谱COSY ( Homonuclear chemical shift ) COrrelation SpectroscopY (同核化学位移)相关谱CP Cross Polarization 交叉极化CP/MAS Cross Polarization / Magic Angle Spinning 交叉极化魔角自旋CSA Chemical Shift Anisotropy 化学位移各向异性CSCM Chemical Shift Correlation Map 化学位移相关图CW continuous wave 连续波DD Dipole-Dipole 偶极-偶极DECSY Double-quantum Echo Correlated Spectroscopy 双量子回波相关谱DEPT Distortionless Enhancement by Polarization Transfer 无畸变极化转移增强2DFTS two Dimensional FT Spectroscopy 二维傅立叶变换谱DNMR Dynamic NMR 动态NMRDNP Dynamic Nuclear Polarization 动态核极化DQ(C) Double Quantum (Coherence) 双量子(相干)DQD Digital Quadrature Detection 数字正交检测DQF Double Quantum Filter 双量子滤波DQF-COSY Double Quantum Filtered COSY 双量子滤波COSY DRDS Double Resonance Difference Spectroscopy 双共振差谱EXSY Exchange Spectroscopy 交换谱FFT Fast Fourier Transformation 快速傅立叶变换FID Free Induction Decay 自由诱导衰减H,C-COSY 1H,13C chemical-shift COrrelation SpectroscopY 1H,13C 化学位移相关谱H,X-COSY 1H,X-nucleus chemical-shift COrrelation SpectroscopY1H,X-核化学位移相关谱HETCOR Heteronuclear Correlation Spectroscopy 异核相关谱HMBC Heteronuclear Multiple-Bond Correlation 异核多键相关HMQC Heteronuclear Multiple Quantum Coherence异核多量子相干HOESY Heteronuclear Overhauser Effect Spectroscopy 异核Overhause效应谱HOHAHA Homonuclear Hartmann-Hahn spectroscopy 同核Hartmann-Hahn谱HR High Resolution 高分辨HSQCHeteronuclear Single Quantum Coherence 异核单量子相干INADEQUATE Incredible Natural Abundance Double Quantum Transfer Experiment 稀核双量子转移实验(简称双量子实验,或双量子谱)INDOR Internuclear Double Resonance 核间双共振INEPT Insensitive Nuclei Enhanced by Polarization 非灵敏核极化转移增强INVERSE H,X correlation via 1H detection 检测1H的H,X核相关IR Inversion-Recovery 反(翻)转回复JRES J-resolved spectroscopy J-分解谱LIS Lanthanide (chemical shift reagent ) Induced Shift 镧系(化学位移试剂)诱导位移LSR Lanthanide Shift Reagent 镧系位移试剂MAS Magic-Angle Spinning 魔角自旋MQ(C) Multiple-Quantum ( Coherence ) 多量子(相干)MQF Multiple-Quantum Filter 多量子滤波MQMAS Multiple-Quantum Magic-Angle Spinning 多量子魔角自旋MQS Multi Quantum Spectroscopy 多量子谱NMR Nuclear Magnetic Resonance 核磁共振NOE Nuclear Overhauser Effect 核Overhauser效应(NOE)NOESY Nuclear Overhauser Effect Spectroscopy 二维NOE谱NQR Nuclear Quadrupole Resonance 核四极共振PFG Pulsed Gradient Field 脉冲梯度场PGSE Pulsed Gradient Spin Echo 脉冲梯度自旋回波PRFT Partially Relaxed Fourier Transform 部分弛豫傅立叶变换PSD Phase-sensitive Detection 相敏检测PW Pulse Width 脉宽RCT Relayed Coherence Transfer 接力相干转移RECSY Multistep Relayed Coherence Spectroscopy 多步接力相干谱REDOR Rotational Echo Double Resonance 旋转回波双共振RELAY Relayed Correlation Spectroscopy 接力相关谱RF Radio Frequency 射频ROESY Rotating Frame Overhauser Effect Spectroscopy 旋转坐标系NOE谱ROTO ROESY-TOCSY Relay ROESY-TOCSY 接力谱SC Scalar Coupling 标量偶合SDDS Spin Decoupling Difference Spectroscopy 自旋去偶差谱SE Spin Echo 自旋回波SECSY Spin-Echo Correlated Spectroscopy自旋回波相关谱SEDOR Spin Echo Double Resonance 自旋回波双共振SEFT Spin-Echo Fourier Transform Spectroscopy (with J modulation)(J-调制)自旋回波傅立叶变换谱SELINCOR Selective Inverse Correlation 选择性反相关SELINQUATE Selective INADEQUATE 选择性双量子(实验)SFORD Single Frequency Off-Resonance Decoupling 单频偏共振去偶SNR or S/N Signal-to-noise Ratio 信 / 燥比SQF Single-Quantum Filter 单量子滤波SR Saturation-Recovery 饱和恢复TCF Time Correlation Function 时间相关涵数TOCSY Total Correlation Spectroscopy 全(总)相关谱TORO TOCSY-ROESY Relay TOCSY-ROESY接力TQF Triple-Quantum Filter 三量子滤波WALTZ-16 A broadband decoupling sequence 宽带去偶序列WATERGATE Water suppression pulse sequence 水峰压制脉冲序列WEFT Water Eliminated Fourier Transform 水峰消除傅立叶变换ZQ(C) Zero-Quantum (Coherence) 零量子相干ZQF Zero-Quantum Filter 零量子滤波T1 Longitudinal (spin-lattice) relaxation time for MZ 纵向(自旋-晶格)弛豫时间T2 Transverse (spin-spin) relaxation time for Mxy 横向(自旋-自旋)弛豫时间tm mixing time 混合时间τc rotational correlation time 旋转相关时间。

如何设计高效催化剂

如何设计高效催化剂

Surface Science Reports63(2008)487–513Contents lists available at ScienceDirectSurface Science Reports journal homepage:/locate/surfrepHigh-throughput heterogeneous catalysisDavid Farrusseng∗UniversitéLyon1,CNRS,UMR5256,IRCELYON,Institut de recherches sur la catalyse et l’environnement de Lyon,2avenue Albert Einstein,F-69626Villeurbanne,Francea r t i c l e i n f o Article history:Accepted16September2008 editor:W.H.Weinberg Keywords:CatalysisCombinatorial chemistryHigh-throughputKinetic modelingQSAR a b s t r a c tThis comprehensive review of the literature(over250references)deals with high-throughput experimentation in heterogeneous catalysis.Approaches to library design for catalyst discovery and optimization are described and discussed.Special focus is placed on advanced methods for knowledge discovery such as high-throughput kinetic modeling and QSAR.An inventory of successful case studies in catalysis is reported.Finally,recent developments in relevant electronic data and knowledge management are described.©2008Published by Elsevier B.V.Contents1.Introduction (488)2.Overview (488)3.Approaches to HT library design (489)3.1.The split&pool method (489)3.2.The hierarchical approach (490)3.3.Design of experiments(DoE)methodology(See also Figs.4and5) (492)3.4.Evolutionary algorithms (493)3.5.Evolutionary optimization using data mining tools (495)3.6.Summary (496)4.HT kinetic modeling (496)4.1.Reasons for conducting HT kinetic modeling (496)4.2.Technologies for HT kinetic modeling (497)4.3.Methodologies of HT kinetic modeling (497)4.4.Spatially-and time-resolved methods (499)5.The QSAR approach to catalysis (500)5.1.Generalities (500)5.2.Homogeneous catalysis and the QSAR approach (500)5.2.1.The QSAR concept (500)5.2.2.In silico generation of a virtual catalyst library (501)5.2.3.Choice and calculation of descriptors (501)5.2.4.QSAR modeling (501)5.3.Heterogeneous catalysis and the QSAR approach (502)5.4.HT physicochemical characterization for property quantification (502)5.5.Catalyst profiling using HT kinetic modeling of model reactions (503)5.6.Virtual screening through computational chemistry (504)Abbreviations:AniML,Analytical Information Markup Language;ANN,Artificial Neural Networks;ANOVA,Analysis Of Variance;DFT,Density Functional Theory;DoE, Design of Experiments;ee,enantioselectivity;FPA,Focalplane;FTIR,Fourier Transform Infrared;GA,Genetic Algorithm;GDC,Guided Data Capture;HT,High-throughput; HTE,High-throughput Experimentation;IT,Information Technology;KFE,Kinetic Fitting Engine;LRIS,Laboratory Research Informatic System;PCA,Principal Component Analysis;QM,Quantum Mechanics;QSAR,Quantitative Structure–Activity Relationship;QSPR,Quantitative Structure–Property Relationship;SCR,Selective Catalytic Reduction;SMEs,Small and Medium Enterprises;TPD,Temperature-programmed Desorption;TOF,Turnover Frequency;TON,Turnover Number;WGS,Water-gas Shift; WHSV,Weight Hourly Space Velocity;XML,Extensible Markup Language;XRD,X-ray Diffraction;XRF,X-ray Fluorescence.∗Tel.:+33472445365;fax:+33472445399.E-mail address:david.farrusseng@ircelyon.univ-lyon1.fr.0167-5729/$–see front matter©2008Published by Elsevier B.V.doi:10.1016/j.surfrep.2008.09.001488 D.Farrusseng/Surface Science Reports63(2008)487–5136.Discovery of catalytic materials by HT (504)6.1.Electrocatalysts for fuel cells (504)6.2.Selective hydrocarbon oxidation (504)6.3.Hydrogen production and purification (505)6.4.Automotive and refinery applications (505)6.5.Other applications (505)6.6.HT experimentation for zeolite synthesis and discoveries (505)7.Electronic infrastructure (506)7.1.Why automate data treatment? (506)7.2.Electronic open architecture for tool integration (506)7.2.1.HTE AG electronic platform (506)7.2.2.The NIST vision (506)7.2.3.Academic laboratories (507)7.2.4.Workflow-based electronic infrastructure for streamline data processing and knowledge management (507)7.2.5.Data normalization and e-standards in chemistry (509)8.Conclusions (509)Acknowledgements (510)References (510)1.IntroductionOver80%of commercial chemical processes involve the use of catalysis,with products as varied as chemicals,oil products, fertilizers,plastics,drugs and pharmaceuticals being made through catalytic steps.Catalysis is probably the most important means of producing modern chemicals;Europe’s chemical industry,for example,accounts for e1.5trillion,or14%,of this continent’s e10.5 trillion GDP(Gross Domestic Product).The likelihood of innovation in this field decreases,however, as catalytic chemical processes become increasingly mature. When new active solids are developed empirically,by trial-and-error processes employed on a few selected samples,the whole procedure is highly speculative and leads to a very slow rate of discovery for the industry in question.This research strategy based on exhaustive studies and complete understanding is also very time-consuming.Therefore,new research strategies have to be developed in order to produce breakthroughs and revitalize the field of chemical research.The high-throughput(HT)approach is a pragmatic alternative. It relies on the fast and systematic screening of libraries of diverse samples.This methodology is not new,since its origins can be found at different periods of the last century.One of the most striking examples is the discovery of the first ammonia synthesis catalyst by Mittasch et al.at BASF in1909followed by a‘‘systematic investigation of the periodic table’’with about 20,000experiments[1].This approach also appealed to K.Ziegler, who in the1950s applied it to the discovery of polymerization catalysts.The pragmatic approach of that time aimed at exploring and covering the periodic table;no references to HT screening or sample libraries could yet be made.We can trace the modern HT approach back to the pioneering work of Hanak in the1970s. He prepared and applied what we now call composition-spread or gradient libraries for research and development purposes at the RCA company laboratories.His work led to the successful entry of several new products onto the market[2].His vision of the experimental approach brought materials screening into the modern age:‘‘...the present approach to the search for new materials suffers from a chronic ailment,that of handling one sample at a time in the processes of synthesis,analysis and testing of properties.It is an expensive and time-consuming approach,which prevents highly-trained personnel from taking full advantage of its talents and keeps the tempo of discovery of new materials at a low level’’[3].The combinatorial principles employed in drug development were first applied to materials research in the early1990s by physi-cists and materials scientists at the Lawrence Berkeley National Laboratory of UC Berkeley.In fact,combinatorial materials sci-ence was recognized as a bona fide discipline only a few years later,following this team’s famous search for superconductors us-ing a materials library[4–7].By1997,the recently-formed Symyx Technologies had documented the state of the art of combinato-rial chemistry by publishing a library of over25,000distinct com-pounds[8].From2000onward,HT technology has been developed for and applied to an ever-increasing variety of materials,including electronic and magnetic materials,polymer-based materials,opti-cal materials,biomaterials,paints,drug formulations,detergents, cosmetics and glues,with the number of related publications and patents exploding accordingly.Today,HT experimentation has matured and is almost regarded as commonplace,its use in the development of new materials sometimes being omitted from a publication’s title or abstract,or even from the publication rge chemical companies (such as BASF,BP,Bayer,Degussa,DOW,DuPont,Exxon,GE, and UOP LLC)now generally have their own HT tools or labs. Meanwhile,smaller companies specialized in HT experimentation (such as Avantium,Bosch Lab Systems,hte AG,Symyx Technologies and Torial)have been founded,often enjoying spectacular growth in the space of the last ten years.Specialized companies such as these have succeeded thanks to their development of cutting-edge technologies,including hardware and software as well as their tight integration,that provide an impressive degree of throughput and productivity(number of samples screened per day and further decision making).In such a context of technological sophistication and high productivity,most academic groups have found themselves unable to compete in the race that is materials screening.Instead,public research centers can play a major role in HT by conducting fundamental research on domains as varied as synthetic methods,analytical tools,parallel in situ characterization,data mining and decision making processes and, finally–the focus of this review–screening strategies and methods.This review deals mainly with HT experimentation for hetero-geneous catalysis and also briefly discusses homogeneous cataly-sis.For other disciplines of materials science,the reader can refer to various reviews[9–19],books[20,21]and special issues[22–30]. An excellent summary of the state of the art for materials science has recently been published elsewhere[31].2.OverviewSince HT screening is a methodological approach,this review is divided into sections describing particular HT screening strategies and their associated strengths,issues,solutions,and case studies.What are the general issues affecting HT experimentation?D.Farrusseng/Surface Science Reports63(2008)487–513489Thanks to the modern screening techniques used in HT methods,dozens or even hundreds of experiments involving many variables can be performed at once.The inevitable combinatorial explosion that results leads to two urgent,fundamental questions relating to experimental design:which experiments are the most relevant to carry out,and what is the most efficient screening strategy?Data analysis is the next issue to come up after the experimental design is chosen.It is hardly possible for humans to fully evaluate results and statistical trends emanating from data sets involving more than four variables and20experiments.The issue of decision making takes on particular importance in such a scenario.In order to understand a catalytic process,one must be aware of the most relevant variables and combinations of variables affecting it.Catalysis,and chemistry in general, are matters of synergy and typically involve highly non-linear behaviors[32],as in metal–ligand or metal–support interactions for homogeneous and heterogeneous catalysis,respectively.Once the exploratory data analysis reveals whether it is possible to highlight positive interactions,and whether one can identify and quantify trends between variables and catalytic performances,a decision must be made—what is the most relevant experimental set to perform next?Computational methods employing mathematics,statistics and artificial intelligence are required for scientists to deal adequately with these three key issues influencing HT experimentation: experimental design,data analysis,and decision making.For over15years,these issues have been addressed in the field of drug discovery,leading to the emergence of a brand new domain of science with its own specialized journals.Section5deals with the application of such screening strategies and their related tools to HT catalyst design,as well as recent developments in the application of quantitative structure–activity relationship(QSAR) to homogeneous and heterogeneous catalysis,with an emphasis on the differences between organic and inorganic compounds in terms of descriptors.Kinetic modeling,on the other hand,reflects the scientist’s insight into the chemical kinetics and,therefore,provides useful information about catalyst behavior.It relates feedstock and operating conditions to reaction rates and corresponding effluent composition,thereby quantifying catalytic performances.Recent kinetic models also contain so-called catalyst descriptors,which specifically account for catalyst properties such as the number of sites and the reactant chemisorption enthalpy.Section4addresses the concepts,recent advances and limitations of kinetic modeling in HT experimentation.An appropriate electronic infrastructure for HT screening is absolutely necessary in order to prevent bottlenecks.Manual entry and cutting-and-pasting of data are to be minimized in order to limit the impact of erroneous entries and slowed-down experiments.Section7addresses these issues,with examples describing and illustrating current technology.Publications,handbooks and other documents available over the Internet,whether free of charge or at a fee,have rendered accessible a great deal of data that could possibly generate knowledge and assist in the decision-making process.That said,the direct capture of data is usually prevented due to the heterogeneity of data,as well as to a lack of standards regarding not just data format but also document format(*.pdf or*.html).The emergence of new technologies,concerted worldwide organizations for electronic standards and new business models appears to be changing this situation.This review does not deal only with catalyst design but also with the optimization of the process conditions due to the strong interplay between catalyst,reactor design and experimental testing conditions.Sections 3.1–3.3address the issues of HT strategies and library design,while Section4explores the benefits of using kinetic and transient approaches for catalyst design.3.Approaches to HT library designThe objectives of a targeted study,such as the discovery of entirely new compounds by exploring large search spaces or the fine optimization of a known catalyst[33,34],have a strong impact on the selection of an appropriate screening strategy and the associated information technology tools.Equipment constraints,synthesis feasibility and screening performances are also important factors to panies or HT departments have developed tailor-made solutions and entire workflows.The issues of HT infrastructure and tool integration as described in[35] will not be discussed here.This section describes the various screening strategies developed in industry and academia,in order from the simplest to the most complex strategies and algorithms, and to some extent from the most massive to the most qualitative screening.3.1.The split&pool methodIn the context of a primary screening aiming to identify hits in a very large search space,the split&pool approach, derived from pharmaceutical methodology,is especially well-suited.It is generally employed in ambitious catalyst discovery programs or when little is known about the target reaction and the class of materials to be studied.Even with a limited number of variables,several hundred samples can easily be obtained thanks to the combinatorial explosion.High analytical speed and overall throughput usually take precedence over the quality or density of information obtained.The split&pool approach enables the generation of every possible combination in a search space.While the generation methodology is quite simple,the major issue,due to its complexity, is the recognition of a molecule in a mixture.For this purpose, many different techniques have been developed to tag molecules, but such techniques cannot be directly applied to inorganic solids. Detailed below are two different tagging strategies,developed by UOP LLC and hte AG,that do allow tagging in the context of inorganic solids.In both strategies,one finds a massive parallel arrangement of micro-reaction chambers containing individual beads,each bead representing one catalyst as a member of a library of solid catalysts.This provides the advantages of easy catalyst handling(unlike the case of powders),very small quantities of metal precursors(typically100µg per catalyst)and a synthesis protocol that can be scaled up.At UOP,catalysts are tagged by using spatially addressable arrays such as microtiter plates(i.e.,96-well plates)[36].Each well contains a single catalyst bead which is indexed by four coordinates,namely the well-plate identity,row and column numbers and split and synthesis step.The combinatorial synthesis consists of a multi-step metal salt impregnation with intermediate drying.Once the metal salt solution is adsorbed onto the beads and dried,rows of beads from a given plate are transferred using a row-sorter to a set of receiving well plates.The sorting algorithm can be set in such a way that the sequence of row-and column-shuffling steps monitors the compositional redundancy of the resulting split–pool library.This process makes it possible for classic,inexpensive laboratory equipment to perform the synthesis of compositionally diverse libraries.The hte AG company has developed fast parallel post-analysis, an alternative to2D addressable layout tagging[37–40].The‘‘split’’step of the split&pool synthesis consists of dividing a few thousand beads into a number of equal portions placed on porcelain dishes. The beads,which are roughly1mm in diameter and are typical catalytic supports,such as alumina or titania,are impregnated with different metallic salt solutions varying by concentration or by metal nature,and then calcined.The beads are then recombined490 D.Farrusseng /Surface Science Reports 63(2008)487–513Fig.1.Split and pool synthesis (a),micro-bead reactor (b)after [39].Table 1Binary composition at the first screening.For each binary system,8different compositions are synthesized using a linear gradientapproach.(‘‘pooled’’)together and are well-mixed via shaking.Typically,the whole process is repeated several times.For example,for five different metal precursors at four different concentrations,the beads are split five times into four different containers (Fig.1).The total number of possible combinations from a mathematical perspective is 45=1024.That said,because the synthesis protocol cannot guarantee that each bead will follow a different path (making the preparation of some identical catalysts possible),it is recommended to start with a greater number of beads,with a ratio of 1.2–1.5with respect to the total theoretical number of combinations.At hte AG,up to 625beads can be tested individually by fast sequential testing methods in a specially-designed array of micro-reactors.The ‘‘hits’’identified are then post-analyzed by micro-X-ray fluorescence (or micro-XRF).In only a few minutes,commercial equipment can quantify the composition of an array of 100samples.The knowledge of the presence or absence of elements and of the range of concentration makes it possible to trace the synthesis path history for the beads.3.2.The hierarchical approachSome erroneous measurements inevitably occur during the primary screening due to the extreme miniaturization and the great number of experiments.Inactive catalysts can appear as ‘‘hits’’(false positives)and active catalysts that should be selected are missed (false negatives).In primary screening,false negatives (which would be missed forever)are far more problematic than are false positives (which would be discarded anyway following the secondary screening).With this fact in mind,Symyx has developed screening strategies to reduce the likelihood of false negatives.Over a two-week period in Symyx laboratories,a hierarchical gradient approach was used with MoVNb patented catalysts for ethane partial oxidation to acetic acid [41].This process led to the discovery of new dopants and to the successful rediscovery of existing catalysts.The primary screening is targeted to identify the best ternary combinations of redox metals from V,Mo,Cr,Mn,Fe,Co,Ni,Cu,Ag,Re,Sn,Sb,Ti and Bi.At the outset,30redox binary systems were investigated,with eight distinct samples synthesizedfor each binary system using a gradient approach consisting of a linear evolution of the composition (Table 1).Of the 30redox binaries (8-point gradients),MoV is by far the most active redox binary,while other active binaries are CrV,MnV,MnCr,CeV,CoCr,CoV,VTi and MoTi.Next,an additional element X was investigated within the MoV system,with X =Mg ,Cr ,Li ,Nb ,Mn ,Co ,Cu ,Fe ,Ni ,Zn ,Zr ,Sb ,Ag ,In or Ce,plus three proprietary dopants.For each ternary,12–15distinct compositions were screened.It was found that Nb,Ni,Sb,and Ce,as well as the three proprietary dopants,result in higher acetic acid productivity.Finally,among the 18ternary MoVX systems,eight of the most promising were tested again with 28different compositions per ternary system.In agreement with the literature,the MoVNb system was identified as very active,while several other metal dopants also produced hits.In summary,as the screening proceeds,the number of com-ponents in the catalytic system increases,formulation complexity increases and higher degrees of interactions are sought in a step-wise manner.The gradient library design approach also permits the efficient management of false negatives and false positives.The testing of similar compositions greatly reduces the risk of missing a hit,while allowing for the easy identification of false positives which afterward are not subjected to further screening.Symyx has demonstrated the value of this screening strategy for various types of catalysis,allowing the determination of the best formulations already reported in the literature and the discovery of new sys-tems [42].For example,the efficiency of Ni–Co–Nb and Ni–Ta–Nb oxide catalysts has successfully been proven for the ethane ox-idative dehydrogenation process at low temperatures [43],while supported-CoCr mixed oxide catalyst systems are proposed for VOC removal [44].Academic laboratories have also applied the gradient strategy.In a primary screening for the partial oxidation of isobutane [45–48],nine elements (V,Fe,Mo,Cr,Ta,Nb,Mn,Sb and Bi)were selected for an initial library design due to the promising partial oxidation properties reported in the literature for the associated oxides.As an alternative to a hierarchical approach,a single library was composed of the nine single oxides (AO x ),D.Farrusseng/Surface Science Reports63(2008)487–513491Fig.2.Emissivity-corrected IR-thermographic images of catalyst library during methanation of CO2at200◦C from[59].of double mixed oxides(A a B b O x)and of ternary mixed oxides (A a B b C c O x).The double mixed oxides consisted of all possible pairs with molar composition(0:1),(0.25:0.75),(0.5:0.5),(0.75:0.25) and(1:0)starting from the nine elements.The ternary mixed oxides consisted of combinations of three elements,always with a(0.33:0.33:0.33)molar composition.Most of the best dehydrogenation catalysts turned out to be Mn and Cr mixed oxides.In accordance with these results,four focused ternary systems–MoVSbO x,MoVFeO x,MoVBiO x and VBiSbO x–were studied in more detail using a dense grinding of the search space. The three elements were allowed to vary between0and100mol% in steps of10mol%,which led to the preparation of66samples per ternary.Other ternaries were investigated elsewhere[49].According to the authors,such composition-spread libraries should allow the identification of any existing local maxima. The best-performing mixed oxides among MoVSbO x,MoVFeO x, MoVBiO x and VBiSbO x were scaled up and tested in a secondary screening.The result was that the optimized composition, Mo10V10Sb80O x,surpassed the best reference catalyst in the literature.Several screening devices have been developed for the mapping of composition-spread libraries.Infrared(IR)thermography is an appropriate choice for the identification of active components in primary screening because,in principle,thousands of samples can be analyzed at the same time[11,50–61].This system records the temperature change arising from the exothermicity or endothermicity of the reaction(Fig.2).In principle,theselectivity Fig.3.Cross-section of the assembled reactor(left)and magnification of reaction chambers(right)from[70].Fig.4.Experimental planning for catalyst design(left).Headers correspond to the element names on the right;M,O,D and S stand for noble Metal,metal Oxides,Dopants and Supports,respectively.Main effects of catalyst compositions on the CO conversion(right),in the absence of H2(a)and in the presence of H2(b).492 D.Farrusseng /Surface Science Reports 63(2008)487–513Fig.5.Blocking structure of 19×19metal binary library (left).Results of 19×19metal binary study (right);synergy was calculated as the difference between the observed TON for the combination minus the sum of the TONs for the individual metals [77].can be measured using an IR focal plane detector [62–65].Other alternatives were developed to overcome selectivity measurement issues such as the use of mass spectrometry (MS)equipped with capillary sampling as shown in [66–70,44,49,71–73].Devices combining IR thermography for rapid hit identification and MS analysis have also been developed [40,74].See also Fig.3.3.3.Design of experiments (DoE)methodology (See also Figs.4and 5)DoE methodology,which involves the simultaneous modifi-cation of variables (usually called factors)and the avoidance of redundant experiments,is widely used in the domain of process engineering.Even though their algorithms are based on simple linear regression,DoE tools can be applied to different objectives that are of particular value in HT experimentation.By means of homogeneous sampling,DoE can be used to efficiently explore a large search space defined by many discrete variables,while guar-anteeing maximal efficiency in terms of the information gleaned from experiments.DoE methodology,when used for screening purposes,quantifies the effect of each individual variable on the targeted properties and identifies the variables relevant to further rounds of screening.On the other hand,when one seeks informa-tion regarding catalytic mechanisms or metal or metal–support synergisms,special DoE design also allows the quantification of in-teractions between variables.Finally,when all relevant variables have been identified,DoE planning is very efficient for the fine op-timization of both catalyst synthesis and process conditions.In this case,the most robust surface responses are generated as empirical models while minimizing the number of experiments.Recent pub-lications illustrate the versatility and power of DoE applied to HT catalyst experimentation.At TU Delft,three sequential DoEs were carried out to find a new one-pot route for the catalytic hydrogenation of acylated cyanohydrins to N -acyl β-amino alcohols [75].Both catalyst formulations and process conditions were varied within the first screening,as shown in Table 2.A selection of 24reactions out of the 320total possible combinations was performed through the use of a D-optimal algorithm.This design is appropriate in view of discarding irrelevant variables for further rounds of optimization.New insights derived from the first design allowed a second one to be carried out using the parameters indicated in Table 3.Variables showing very little impact were discarded.On the other hand,since the nature of the support appeared to bear major importance,a new support,silica,was introduced in the search space.The now considerably reduced parameter space rendered feasible a full-factorial design (i.e.,36combinations),providing accurate information on the main effects of the parameters and especially on the interactions between the parameters.In suchTable 2Definition of the parameter search space for the first screening round.Table 3Definition of the parameter search space for the second screening round.designs,about half the possible number of reactions are typically performed.Finally,a third design was performed in conventional reactors,taking into account other variables such as pressure and temperature.A strategy of sequential hierarchical designs is believed to be better than a single large one,because the information obtained from one design is used to improve the next.If one large DoE design had been chosen,many unnecessary reactions would have been performed.Preliminary designs (typically fewer than 25%of the possible reactions)are sufficient to allow differentiation between significant and insignificant parameters,and are therefore well-suited to reduce the search space in the early stages of the research effort.The search for selective CO oxidation catalysts for H 2purifica-tion applications has also been a context for using a very similar hi-erarchical strategy using a D-optimal design algorithm for primary screening [76].An a priori selection of elements and of combinato-rial rules for mixing them and generating multi-component cata-lysts was performed according to literature data and pre-existing knowledge.Four groups of elements were considered:noble met-als (Pt,Pd,Ru,Rh and Au),oxides (transition metal oxides of Cr,Co,Mn,La,Sm and Mo),dopants (alkali or earth alkali Li,Cs and Ca)and supports (Al 2O 3,CeO 2,ZrO 2,ZnO and C).One of the a priori rules established was that all catalysts were to be composed of one sup-port and two noble metals and,optionally,of one transition metal and one dopant.The weight percentages of noble metal,as well as transition metal and dopant (when present),were fixed at 0.5%,20%and 1%,respectively.The choice to employ two distinct noble metals per catalyst was based on the assumption that alloys may。

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a r X i v :h e p -p h /0102119v 1 9 F eb 2001DCPT/01/12DFTT 1/2001INFNCA-TH0101IPPP/01/06Parton Densities and Fragmentation Functions from Polarized ΛProduction in Semi-Inclusive DISM.Anselmino 1,M.Boglione 2,U.D’Alesio 3,E.Leader 4,∗,F.Murgia 31Dipartimento di Fisica Teorica,Universit`a di Torino and INFN,Sezione di Torino,Via P.Giuria 1,I-10125Torino,Italy2Department of Physics,University of Durham,Science Laboratories,South Road,Durham DH13LE,United Kingdom3INFN,Sezione di Cagliari and Dipartimento di Fisica,Universit`a di Cagliari,C.P.170,I-09042Monserrato (CA),Italy4Physics Department,Theory Division,Vrije Universiteit Amsterdam,De Boelelaan 1081,1081HV Amsterdam,The NetherlandsWe consider the longitudinal polarization of Λand ¯Λproduced in the cur-rent fragmentation region of polarized deep inelastic scattering.We show how the various cross sections can be used to test the underlying parton dynamics,and how one can extract information about certain parton densities which are poorly known,in particular the polarized strange density sum ∆s (x )+∆¯s (x ),and about fragmentation functions which are totally unknown and which are difficult to access by other means.We show also how one can obtain informa-tion concerning the intriguing question as to whether s (x )=¯s (x )and whether ∆s (x )=∆¯s (x ).PACS numbers:13.60.Hb,13.85.Ni,13.87.Fh,13.88.+eI.INTRODUCTIONAs has been emphasized in several papers [1–10],measurements of the polarization of Λbaryons produced in high energy deep inelastic lepton-hadron collisions offer an excellent test of the dynamics of spin transfer from partons to hadrons.In this paper we consider all possible semi-inclusive reactions involving unpolarized or longitudinally polarized leptons and nucleons,with or without the measurement of the lon-gitudinal polarization of Λor ¯Λproduced in the current fragmentation region.We draw theattention to another important aspect of such reactions,namely the information obtainable about the polarized parton densities,and about the unpolarized and polarized fragmentation functions DΛq,∆DΛq for a quark into aΛ(or¯Λ).Despite recent progress[11]some polarized parton densities are still relatively poorly determined.In principle,in semi-inclusive DIS, one can obtain information about the polarized strange quark density∆s(x)+∆¯s(x),which is poorly known,and also about the interesting question as to whether s(x)=¯s(x)and ∆s(x)=∆¯s(x).Regarding the fragmentation functions DΛq and∆DΛq very little is known.Indeed the ∆DΛq are not constrained at all by the present e+e−data.These can,in principle,all be determined in semi-inclusive DIS.They could also be accessed in the reaction pp→ΛX with a polarized proton beam or target[12].In this paper,as in[1],we work in LO QCD.Given the preliminary state of experiments in thisfield it does not seem sensible at this point to undertake the extremely complicated NLO analysis[4]or the somewhat simpler version given in[13].However,as emphasized in[13], it is important to remain vigilant about inaccuracies caused by using the LO formalism,and great attention should be paid to the various tests of the reliability of the LO treatment given in the following.For a more general discussion of this question and suggestions concerning the estimation of theoretical errors generated by the LO treatment,see Ref.[13].To really extract the maximum of information from these reactions one should try to study the triply-differential cross section dσ/dxdydz where x,y,z are the usual semi-inclusive DIS variables[1].In this it is the y-dependence that tests the dynamics,whereas the parton densities and fragmentation functions emerge from the x and z-dependence.In Section II we define precisely what cross sections and polarizations we wish to consider. As mentioned we deal only with longitudinal(helicity)polarization of the leptons,nucleons andΛ’s.In Section III we introduce modified differential cross sections which are simply related to parton model soft functions and which allow tests of the underlying parton dynamics. In Section IV we study in detail what information can be extracted about the parton densities and fragmentation functions.Conclusions follow in Section V.II.THE INDEPENDENT OBSER V ABLES OF THE REACTIONWe consider the reactionℓ(λ)+N(µ)→H(h)+ℓ′+X(1) of a charged leptonℓwith helicityλ=±1/2on a nucleon N of helicityµ=±1/2producing, semi-inclusively,a spin1/2hyperon H with helicity h=±1/2.The hyperon H is such that its polarization can be determined from its decay distribution.We consider kinematical regions where Z exchange is negligible.The fundamental invariant differential cross section will be written asdσH hλµThe longitudinal or helicity polarization of H,as produced from a given initial state(λµ)is then given byP Hλµ=dσH+λµ−dσH−λµ2(dσH h+µ+dσH h−µ).(7)Because of(5)there will be only four independent cross sections or observables,instead of the original2×2×2=8.We shall take as the four independent cross sections:a)The unpolarized cross sectiondσH≡dσH00=12(dσH+++dσH+−).(8)b)The target-spin dependent cross section difference∆dσH≡dσH++−dσH+−.(9) c)The spin-transfer cross section from a polarized lepton with an unpolarized nucleondσH+−H−+0≡dσH++0−dσH−+0=P H+0dσH,(10)where we have chosen a positive helicity for the lepton and have used,via(5),dσH+0=dσH−0=dσH0+=dσH0−=dσH.(11) Clearly,also via(5)dσH+−H−+0=−dσH+−H−−0.(12)d)The spin-transfer cross section from a polarized nucleon with an unpolarized leptondσH+−H−0+≡dσH+0+−dσH−0+=P H0+dσH.(13)Since these are four linearly independent observables,all others can be written in terms of them.For example it is easy to see thatdσH+−H−++=dσH+−H−+0+dσH+−H−0+(14)anddσH+−H−+−=dσH+−H−+0−dσH+−H−0+.(15)In terms of the hyperon polarization,(14)and(15)implyP H++=1dσH++P H+0+P H0+ (16)andP H+−=1dσH+−P H+0−P H0+ .(17)Note that equations like(16)and(17)are not predictions of the detailed dynamics,but follow from parity invariance of the strong and electromagnetic interactions.Similar relations were given in[1].III.THE DYNAMICAL MODELIn LO pQCD,the general cross section(2)corresponding to the process in(1)is given bydσH hλµdy D H h qλq(z),(18)where the sum is over quarks and antiquarks,qµλq(x)is the parton number density for quarks of helicityλq in a proton of helicityµ,while D H h qλqis the fragmentation function for a quarkq of helicityλq to fragment into hyperon H with helicity h;dˆσλλq /dy is the lepton-quark(or antiquark)differential cross section for an initial state with the lepton having helicityλand the quark(or antiquark)helicityλq.The simple helicity structure of(18)reflects the fact that helicity is conserved for massless quarks inℓq→ℓq.There are two independent partonic cross sectionsdˆσ++dy =4πα2dy =dˆσ−+sxy2(1−y)2,(20)where s is the squared centre of mass energy corresponding to the process in Eq.(1).In order to simplify the expressions needed for theflavour analysis,we renormalize our four independent cross sections(8-10),(13),by dividing out certain common kinematic factors. Thus we work witha′)d˜σH(x,z)≡ 2πα2y2 −1dσH= q e2q q(x)D H q(z),(21)where q(x)and D H q(z)are the usual unpolarized parton density and fragmentationfunctions respectively,q(x)=q++(x)+q+−(x),D H q(z)=D H+q+(z)+D H−q+(z).b′)∆d˜σH(x,z)≡ 4πα2y2 −1∆dσH= q e2q∆q(x)D H q(z),(22) where∆q(x)=q++(x)−q+−(x)is the usual longitudinally polarized parton density. c′)d˜σH+−H−+0(x,z)≡ 2πα2y2 −1dσH+−H−+0= q e2q q(x)∆D H q(z),(23) where∆D H q(z)=D H+q+(z)−D H−q+(z)=D H+q+(z)−D H+q−(z).(24)d′)d˜σH+−H−0+(x,z)≡ 2πα2y2 −1dσH+−H−0+= q e2q∆q(x)∆D H q(z).(25)We see that for eachflavour,for a given hyperon H and for a given target,the four indepen-dent cross sections just correspond to different combinations of the four independent soft functions,q(x),∆q(x),D H q(z),∆D H q(z).It should be noted that the fact that d˜σH,∆d˜σH,d˜σH+−H−+0,d˜σH+−H−0+depend only onx and z(neglecting the known and mild dependence on Q2=xys,due to QCD evolution) is a direct consequence of the parton dynamics and should be tested experimentally.IV.EXTRACTION OF PARTON DENSITIES AND FRAGMENTATIONFUNCTIONSWe assume that the usual unpolarized parton densities u(x),d(x),¯u(x),¯d(x)are reason-ably well known and can be used as input in the following expressions.We consider the production ofΛand¯Λhyperons on both proton and neutron targets and show how one can systematically obtain information about the parton densities s(x),¯s(x),∆s(x),∆¯s(x)and about the fragmentation functions∆DΛu(z),∆DΛd(z),∆DΛs(z).We shall assume good enough control over systematic errors to allow us to combine cross sections for different targets and forΛand¯Λfinal particles.This is a non-trivial experi-mental issue,but well worth the effort,since it then becomes possible to obtain very simple expressions for the parton densities and fragmentation functions under study.A.Unpolarized cross sectionUsing only charge conjugation invariance,DΛq=D¯Λ¯q,(26) and isospin invariance,DΛd=DΛu,(27) we obtain from(21)the well known relations[13]d˜σΛ+¯Λ p−d˜σΛ+¯Λ n=13[u v(x)−d v(x)]DΛ−¯Λu(z),(29)where q v(x)is a valence quark density.Measurements of the cross section differences on the LHS of(28)and(29)thus enable adetermination of DΛ+¯Λu and DΛ−¯Λuand therefore of the individual DΛu and D¯Λu.Next we consider the combinationsd˜σΛ+¯Λ p+d˜σΛ+¯Λ n=59[s(x)+¯s(x)]DΛ+¯Λs(z),(30)d˜σΛ−¯Λ p+d˜σΛ−¯Λ n=59[s(x)−¯s(x)]DΛ−¯Λs(z).(31)Since we now know DΛ±¯Λu,(30)and(31)allow a determination of the productsS1(x,z)≡[s(x)+¯s(x)]DΛ+¯Λs(z)(32) andS2(x,z)≡[s(x)−¯s(x)]DΛ−¯Λs(z).(33) In usual DIS it is the combination(s+¯s)that appears,so if this is taken as reasonably welldetermined we can extract information on DΛ+¯Λs (z)from Eq.(32).Of more interest is thequestion of whether the nucleon possesses intrinsic strange quarks,such that s(x)=¯s(x)[14].Since DΛ−¯Λs (z)is likely to be relatively large,a measurement of(33)should enable oneto say whether(s−¯s)is compatible with zero.For further discussion of the evaluation of (s−¯s)see Ref.[13].B.Cross section for unpolarized lepton and polarized nucleon target Analogously to(28-31)we now have from(22)∆d˜σΛ+¯Λ p−∆d˜σΛ+¯Λ n=13[∆u v(x)−∆d v(x)]DΛ−¯Λu(z),(35)where∆q v is defined as∆q−∆¯q.As stressed in[13],(34)and(28)provide a stringent test for the reliability of the LO treatment.By taking their ratio one obtains in LO∆AΛ+¯Λp−n (x,z,Q2)≡∆d˜σΛ+¯Λ p−∆d˜σΛ+¯Λ n(F p1−F n1)LO(x,Q2),(36)where g1and F1are the usual polarized and unpolarized DIS structure functions,here evaluated in LO.The crucial feature of(36)is that,in principle,the LHS depends on three variables(x,z,Q2),and only in LO should it be independent of z,the so called passive variable[13].It is essential to test this feature in order to have any confidence in the LO treatment.For the experimental situation under discussion in this subsection we can write equations analogous to(30)and(31)via the substitutionsd˜σ→∆d˜σand q(x)→∆q(x).(37) In this case we learn about the products∆S1(x,z)≡[∆s(x)+∆¯s(x)]DΛ+¯Λs(z)(38) and∆S2(x,z)≡[∆s(x)−∆¯s(x)]DΛ−¯Λs(z).(39)Assuming DΛ+¯Λs has been determined as in Section A,(38)would give valuable informationabout(∆s+∆¯s)which is only poorly determined from polarized DIS[11].And(39)could provide an answer to the intriguing question as to whether or not∆s(x)=∆¯s(x),see comments after Eq.(33).In addition the ratios∆S1(x,z)s(x)+¯s(x),(40)∆S2(x,z)s(x)−¯s(x),(41)should be independent of the passive variable z.C.PolarizedΛand¯Λproduction with polarized lepton and unpolarized nucleonWith a polarized lepton beam and unpolarized nucleon target,the difference between cross sections to produceΛ’s or¯Λ’s with helicity±1/2is given by(23).To simplify the notation,let us writed˜σΛ+−Λ−+0≡d˜σ∆Λ+0,etc (42)Then,from(23)we obtain four equations analogous to(28),(29),(30),(31):d˜σ∆Λ+∆¯Λ+0 p−d˜σ∆Λ+∆¯Λ+0 n=13[u v(x)−d v(x)]∆DΛ−¯Λu(z),(44)from which we can determine∆DΛu(z)and∆D¯Λu(z),andd˜σ∆Λ+∆¯Λ+0 p+d˜σ∆Λ+∆¯Λ+0 n=59[s(x)+¯s(x)]∆DΛ+¯Λs(z),(45)d˜σ∆Λ−∆¯Λ+0 p+d˜σ∆Λ−∆¯Λ+0 n=59[s(x)−¯s(x)]∆DΛ−¯Λs(z),(46)yielding information on the productsS3(x,z)≡[s(x)+¯s(x)]∆DΛ+¯Λs(z),(47)S4(x,z)≡[s(x)−¯s(x)]∆DΛ−¯Λs(z).(48)Eq.(47)yields information on∆DΛ+¯Λs (z)and(48)provides a further test of whether s(x)=¯s(x).D.PolarizedΛand¯Λproduction with polarized nucleon and unpolarized lepton Analogous to(43)and(44),we haved˜σ∆Λ+∆¯Λ0+ p−d˜σ∆Λ+∆¯Λ0+ n=13[∆u v(x)−∆d v(x)]∆DΛ−¯Λu(z).(50)The ratio of(49)and(43)provides a further test of the reliability of a LO treatment.One hasd˜σ∆Λ+∆¯Λ0+ p−d˜σ∆Λ+∆¯Λ0+n(F p1−F n1)LO(x,Q2),(51) in LO.The analogues of(45)and(46)are obtained by the substitutiond˜σ∆Λ±∆¯Λ+0→d˜σ∆Λ±∆¯Λ0+and q(x)→∆q(x),(52)and yield information on∆S3(x,z)=[∆s(x)+∆¯s(x)]∆DΛ+¯Λs(z),(53)∆S4(x,z)=[∆s(x)−∆¯s(x)]∆DΛ−¯Λs(z).(54) The ratios∆S3(x,z)(55)s(x)+¯s(x)and∆S4(x,z)(56)s(x)−¯s(x)should be independent of z in LO and should equal the ratios∆S1/S1and∆S2/S2respec-tively,determined in Section B[see(40)and(41)].V.CONCLUSIONSThe study of the angular distribution of theΛ→pπdecay allows a simple and direct measurement of the components of theΛpolarization vector.ForΛ’s produced in the cur-rent fragmentation region in DIS processes,the components of the polarization vector are related to spin properties of the quark inside the nucleon,to spin properties of the quark hadronization,and to spin dynamics of the elementary interactions.All this information, concerning quark distribution functions,quark fragmentation functions and spin properties of elementary dynamics are essentially factorized in LO QCD and separated as depending on three different variables,respectively x,z,y.The Q2-evolution and dependence of distribu-tion and fragmentation functions somewhat mix the three variables,but smoothly,keeping separated the main properties of each of the different aspects of the process.Moreover,such Q2-dependence is perturbatively well known and under control.We have discussed all dif-ferent longitudinal polarization states of spin-1/2baryons,obtainable in the fragmentation of a quark in DIS with longitudinally polarized initial leptons and nucleons.We have shown how one can extract new information,not attainable in unpolarized in-clusive DIS,about parton densities,and new information,not extractable from e+e−→hadrons,about fragmentation functions.In particular one can learn about the poorly known polarized strange quark density∆s(x)+∆¯s(x)and one can get some information relevant to the question as to whether s(x)=¯s(x)and whether∆s(x)=∆¯s(x).The connection between the theoretical quantities and the combinations of measured cross sections is very simple,but the challenge will be an experimental one,namely to have sufficient control over systematic errors so as to permit the combining of different measurements.We hope this will soon be possible.ACKNOWLEDGMENTSWe are very grateful to P.Mulders and the Theory Division of the Physics Department, Vrije Universiteit Amsterdam,where this work was initiated,for the warm hospitality.M.B. is most grateful for support from the EU-TMR Program,Contract No.CT98-0169.U.D. and F.M.are grateful to COFINANZIAMENTO MURST-PRIN for partial support. 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