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设计外文翻译外文译文题目 ：单轴和双轴搅拌机搅拌性能比较（题目用楷体3号字 ，居中）学 院:专 业:学 号:学生姓名:指导教师:日 期:Comparing mixing performance of uniaxial and biaxial bin blendersAmit Mehrotra, Fernando J. MuzzioDepartment of Chemical and Biochemical Engineering, Rutgers University, Piscataway, NJ, 08855, United Statesa b s t r a c ta r t i c l ei n f oArticle history:Received 17 February 2009Received in revised form 30 May 2009Accepted 14 June 2009Available online 27 June 2009Keywords:Powder mixingCohesionBlenderMixerRelative standard deviationNIRAcetaminophenThe dynamics involved in powder mixing remains a topic of interest for many researchers; however thetheory still remains underdeveloped. Most of the mixers are still designed and scaled up on empirical basis.In many industries, including pharmaceutical, the majority of blending is performed using “tumblingmixers”. Tumbling mixers are hollow containers which are partially loaded with materials and rotated forsome number of revolutions. Some common examples include horizontal drum mixers, v-blenders, doublecone blenders and bin blenders. In all these mixers while homogenization in the direction of rotation is fast,mediated by a convective mixing process, mixing in the horizontal (axial) direction, driven by a dispersiveprocess, is often much slower. In this paper, we experimentally investigate a new tumbling mixer that rotateswith respect to two axes: a horizontal axis (tumbling motion), and a central symmetry axis (spinningmotion). A detailed study is conducted on mixing performance of powders and the effect of criticalfundamental parameters including blender geometry, speed, fill level, presence of baffles, loading pattern,and axis of rotation. In this work Acetaminophen is used as the active pharmaceutical ingredient and theformulation contains commonly used excipients such as Avicel and Lactose. The mixing efficiency ischaracterized by extracting samples after pre-determined number of revolutions, and analyzing them usingNear Infrared Spectroscopy to determine compositional distribution. Results show the importance of processvariables including the axis of rotation on homogeneity of powder blends. 2009 Elsevier B.V. All rights reserved.1. IntroductionParticle blending is a required step in a variety of applicationsspanning the ceramic, food, glass, metallurgical, polymers, andpharmaceuticals industries. Despite the long history of dry solidsmixing (or perhaps because of it), comparatively little is known of themechanisms involved 13. A common type of batch industrial mixeris the tumbling blender, where grains flow bya combination of gravityand vessel rotation. Although the tumbling blender is a very commondevice, mixing and segregation mechanisms in these devices are notfully understood and the design of blending equipment is largelybased on empirical methods. Tumblers are the most common batchmixers in industry, and also find use in myriad of application as dryers,kilns, coaters, mills and granulators 48. While free-flowingmaterials in rotating drums have been extensively studied 9,10,cohesive granular flows in these systems are still not completelyunderstood. Little is known about the effect of fundamental param-eters such as blender geometry, speed, fill level, presence of baffles,loading pattern and axis of rotation on mixing performance ofcohesive powders or the scaling requirements of the devices.However, conventional tumblers, rotating around a horizontal axis,all share an important characteristic: while homogenization in thedirection of rotation is fast, mediated by a convective mixing process,mixing in the horizontal (axial) direction, driven by a dispersiveprocess, is often much slower.In this paper, we experimentally investigate a new tumbling mixerthat rotates with respect to two axes: a horizontal axis (tumblingmotion), and a central symmetryaxis (spinning motion). We examinethe effects of fill level, mixing time, loading pattern and axis ofrotation on the mixing performance of a free-flowing matrix of FastFlo lactose and Avicel 102, containing a moderately cohesive API,micronized Acetaminophen. We use extensive sampling to character-ize mixing by tracking the evolution of Acetaminophen homogeneityusing a Near Infrared spectroscopy detection method. After materialsand methods are described in Section 2, results are presented inSection 3, followed by conclusions and recommendations, which arepresented in Section 4.2. Materials and methodsThe materials used in the study are listed in Table 1, along withtheir size and morphology. Acetaminophen is blended with com-monly used excipients and is used as a tracer to evaluate the degree ofhomogeneity achieved as a function of number of revolutions.Acetaminophen is one of the drugs most widely used in mixingstudies, and Avicel and Lactose are commonly used pharmaceuticalPowder Technology 196 (2009) 17 Corresponding author. Tel.: +1 732 445 3357; fax: +1 732 445 2581.E-mail address: muzzio (F.J. Muzzio).0032-5910/$ see front matter 2009 Elsevier B.V. All rights reserved.doi:10.1016/j.powtec.2009.06.008Contents lists available at ScienceDirectPowder Technologyjournal homepage: /locate/powtecexcipients. In the interest of brevity their SEM images are not includedin this paper, but can be found in “Handbook of Pharmaceuticalexcipients”.2.1. Near infrared spectroscopyAcetaminophen homogeneity was quantified using near infraredspectroscopy. A calibration curve was constructed for a powdermixture containing (in average) 35% avicel PH 102, 62% lactose and 3%acetaminophen. Near infrared (NIR) spectroscopy can be a useful toolto characterize acetaminophen. Samples are prepared by keeping theratio of Avicel to lactose randomized in order to minimize effects ofimperfect blending of excipients during the actual experiments onthe accuracy of the results. The Rapid Content Analyzer instrumentmanufactured by FOSS NIR Systems (Silver Spring, MD) and Visionsoftware (version 2.1) is used for the analysis. The samples areprepared by weighing 1 g of mixture into separate optical scintillationvials; (Kimble Glass Inc. Vineland, NJ) using a balance with anaccuracy of 0.01 mg. Near-IR spectra are collected by scanning in therange 11162482 nm in the reflectance mode. Partial least square(PLS) regression is used in calibration model development using thesecond derivative mathematical pretreatment to minimize theparticle size effects. As shown in Fig. 1, excellent agreement isachieved between the calibrated and predicted values.2.2. Binblendersusedinthisstudy:uni-axialblender(Blender1),bi-axialblender (Blender 2)Due to its widespread use, a cylindrical blender 1 with a capacityof 30 L is chosen as a reference blender in the study. As shown inFig. 2, this blender has a circular cross section and tapers at thebottom. It can be used with or without baffles, which are mounted ona removable lid. In this study all the experiments are conductedwithout the use of baffles. Mixing performance in this device is usedto provide a base-line for evaluating the mixing performance of anewly developed blender 2 with a capacity of 40 L, which is alsocylindrical, in order to determine the effect of dual axis of rotation onmixing performance. The blender shown in Fig. 2(b) has two axis ofrotation. The spinning rate of precession relative tothe central axis ofsymmetry is geared tobe halfof thatof therateofrotationaroundthehorizontal axis.2.3. Experimental methodTwo types of initial powder loading used in the experiments: topbottom loading and sideloading, which are schematically repre-sented in Fig. 3. To avoid agglomeration, the API, acetaminophen, wasdelumped prior to loading it into the blender by passing it through a35mesh screen. In order tocharacterize mixingperformance, a groovesampler was used to extract samples from the blenders at 7.5, 15, 30,60, 120 revolutions. The thief was carefully inserted in the bin, and acore was extracted at each point of insertion (each “stab”) minimizingperturbation to the powder bed remaining in the blender. Approxi-mately 7 samples are taken from each thief stab, and a total of fivestabs are used at each sampling time, as shown in Fig. 4 so a total of35 samples are taken at each sampling point.The experimental plan used in this study is as follows: Fill level: blender 160% Fill level: blender 260%, 70%, 80% Loading pattern: blender 1 sideside loading, topbottom loading Loading pattern: blender 2 sideside loading, topbottom loading Speed: blender 115 rpm, 20 rpm, 25 rpm Speed: blender 2 rotational/spinning:15/7.5 rpm, 20/10 rpm,30/15 rpm Sampling time: blender 1, blender 27.5, 15, 30, 60, 120 revolutions3. ResultsThe homogeneity index used is the RSD, where C is theconcentration of each individual sample, C_is the average concentra-tion of all samples and n is the total number of samples obtained at agiven sampling time.RSD =SC; where S =ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffinPC2PC2n n 1sWe examine the effect of fill level on mixing performance.Previously there have been studies on the effect of fill level in theBohle bin blender, Gallay bin blender and V-blender and double coneblender 1113. All the aforementioned blenders have only one axisof rotation, therefore the objective of this study is to examine howdual axis impact mixing performances at high fill levels. To avoidrepetition, studies for fill level are not conducted for bin blender 1.Results available from a previous study using MgSt as a tracer showedthat mixing in a uni-axial blender slowed down quite dramatically asthe fill level exceeded 70%. Moreover, results for acetaminophen canbe assumed to be similar to those obtained in previous work byMuzzio et al. 11,13, for a single axis rectangular bin blender 11,which have shown that even after few hundred revolutions homo-geneity achieved with a 80% fill level is very poor as compared to 60%fill level.To examine the effect of fill level in a dual axis blender, experi-ments were performed in blender 2 with the top-bottom loadingpattern for a rotational speed of 15 rpm and with spinning speed of7.5rpm.Thefilllevelsexaminedare60%,70% and80%respectivelyandsamples are taken after 7.5, 15, 30, 60,120 revolutions. Typical resultsare shown in Fig. 5, which shows the RSD vs. number of blenderrevolutions. As expected for non-agglomerating materials, the curvesTable 1Materials studied in this paper.NameSize and morphologyVendor, City, StateFast-Flo Lactose100 , sphericalForemost farms, Newark, NJAvicel PH 102 Microcrystallinecellulose90 , needle-likeFMC, Rothschild, WIAcetaminophen40 , needle-likeMallinckrodt, St Louis, MOFig. 1. Near Infrared (NIR) spectroscopy validation curve. The equation used to predictacetaminophen concentration is validated by testing samples with known amounts ofacetaminophen concentration. The y axis represents the concentration calculated fromthe equation and the x axis represents the actual concentration. Thus a perfectlystraight line at 45 would represent the best calibration model. Each point on the graphrepresents a single sample. The concentration of acetaminophen examined here rangesfrom 0 to 8%.2A. Mehrotra, F.J. Muzzio / Powder Technology 196 (2009) 17Fig. 2. Pictorial representation of (a) bin blender 1 and (b) bin blender 2 showing the corresponding axis of rotation.Fig. 3. Schematicoftheloadingpatternusedinthestudy.Intopbottomloading,AvicelisloadedfirstintotheblenderfollowedbyLactoseontopofitandfinallyAcetaminophenisuniformlysieved over. In sideside loading avicel is placed at the bottom and then Acetaminophen is only sieved only in half part of the blender and is sandwiched between lactose and Avicel.Fig. 4. (a) Thief sampler (b) top view of the sampling position scheme.Fig. 5. Mixing curves for different fill levels in blender 2. The RSD of acetaminophen is plotted as a function of number of revolutions. The loading pattern in top-bottom and theblender rotational speed is 15 rpm with spinning speed of 7.5 rpm.3A. Mehrotra, F.J. Muzzio / Powder Technology 196 (2009) 17show a rapidly decaying region. The slope of the curves in this region,in semi-logarithmic coordinates, is used to define the mixing rate. Thecurves then level off to a plateau that indicates the maximum degreeof homogeneity that is achievable in the blender for a give material.Similar to previous studies with other tumbling blenders we ob-servethat blending performance is adverselyaffected byincreasing filllevels. As shown in Fig. 5, the curve for 80% fill performs more poorlythan those for 60% and 70% fill; as fill level increases, RSD curves decaymore slowly, signifying a slower mixing process. However, the effect isnot as pronounced as in other bin blenders and after about only 100revolutions, the same plateau (the same asymptotic blend homo-geneity) is achieved for all three fill levels.Next, the effect of rotational speed is investigated in the blender 1with one axis of rotation and is compared to the blender 2 with dualrotation axis. Experiments were conducted for both blenders withtop-bottom and side-side loading. Experiments were performed at60% fill level and the rotation speeds considered for blender 1 are15 rpm, 20 rpm and 25 rpm respectively. As shown in Figs. 6 and 7,whenplotted as a function of blender revolutions, there is not much ofan effect of rotation speed on the homogeneity index (RSD) ofacetaminophen at 60% fill level. It is observed that mixing perfor-manceat 20 rpmand25 rpmis slightly better than at 15 rpm,howeverthe differences in the performance of the blender under differentspeeds are probably too small to be significant. RSD curves decay withthe same slope, indicating similar mixing rates. In the study reportedhere, the fill level is only 60%, and all the rotational speeds are enoughto achieve homogenization. The aforementioned studies were con-ducted at 85% fill level. For such a high fill level, at low speeds, astagnant core is known to occur at the center of many blenders,requiring higher shear stress per unit volume to achieve homogeniza-tion. Moreover, the flow properties of MgSt are known to be stronglydifferent than those of most materials, and are known to have a deepFig. 6. Mixing curves for top-bottom loading experiments with 60% fill level. RSD is plotted as a function of number of revolutions. Dotted lines correspond to experiments in theblender 1, while solid lines represent data points from the blender 2.Fig. 7. Mixingcurvesforsidesideloadingexperimentswith60%filllevel.RSDisplottedasafunctionofnumberofrevolutions.Dottedlinescorrespondtoexperimentsintheblender1,while solid lines represent data points from the blender 2.4A. Mehrotra, F.J. Muzzio / Powder Technology 196 (2009) 17impact on the flow properties of the mixture as a whole. Furthermore,MgSt is famously known to be a shear sensitive material. Thus anexpectation that lubricated and unlubricated blends would showsimilar behavior with respect to shear is probably unwarranted.Subsequently, experiments were performed using the blender 2 atthree rotation speeds: 15 rpm, 20 rpm and 30 rpm, and as explainedbefore, the corresponding spinning speeds were 7.5 rpm, 10 rpm and15rpm.Filllevelconsideredfor both side-side andtop-bottomloadingwas 60%.Again, it was observed that varying rotation and spinning speedsdidnot makemuchdifferenceinmixingrate.As showninFigs.6and7,mixing curves for blender 2 vary only slightly with rotation speed. Forthe top-bottom loading pattern it appears that mixing improvesslightly when rotation speed is increased (the plateau is slightly lowerfor higher rotation speeds, indicating an improvement in the levels ofasymptotic homogeneity), but no significant changes with speed areobserved in side-side loading pattern.The blending performance of both blenders is compared atdifferent rotation speeds for both side-side and top-bottom loadingpatterns. To make a fair comparison, the fill level was kept as 60% forboth blenders, a condition for which both blenders achieve effectivemixing at long enough times. Due to geometric similarity of the twoblenders, this comparison help evaluate the effect of spin (rotationwith respect to the central symmetryaxis) on mixing performance. Asshown in Fig. 6, the mixing curves for the blender 2 lie below those forthe blender 1 for each rotation rate, indicating faster mixing. Note thatthe final RSD asymptote reached for both blenders is also different,with the blender 2 showing a lower asymptote (better final mixedstate, presumably due to a lesser effect of the slow mixing mode in thehorizontal direction) than blender 1.Similar results were obtained for the side-side loading pattern, asdisplayed in Fig. 7. The RSD curves for the blender 1 for all the threerotation rates lie above the blender 2. It is therefore confirmed thatspinning a blender in direction perpendicular to the rotation axishelps in enhancing mixture homogeneity; however, for the materialsexamined here, the rotation rate does not have much effect on mixingperformance.Finally, a comparison is madebetweenthe two loading patterns forboth blenders. Again, to achieve a fair comparison, all experiments areperformed at 15 rpm and 60% fill level. As evident in Fig. 8, in bothFig. 8. Comparisonbetweenthemixingcurvesof theblender2andtheblender1fortopbottomandsidesideloadingpattern.Dottedlinescorrespondtoexperimentsintheblender1,while solid lines represent data points from the blender 2. Experiments are performed at 15 rpm with 60% fill level.Fig. 9. A typical mixing plot, with RSD plotted against number of revolutions. The two solid lines emphasize on the two distinctive mixing regimes.5A. Mehrotra, F.J. Muzzio / Powder Technology 196 (2009) 17blenders topbottom loading gives a more rapid decay of the RSD,indicating faster homogenization as compared to sideside loadingpattern. However, for both loading modes, blender 2 achieves fasterhomogenization.As reported in previous studies, all the RSD curves in this paperexhibit a common trend with respect to time, characterized by aninitial period of rapid homogenization due to convective mixing, fol-lowed by a period of much slower homogenization typically con-trolled by dispersion or shear. This trend is shown schematically inFig. 9. The first regime is a fastexponential decayand thesecond oneisa slow exponential asymptote to a limiting plateau. The first partrepresents a rapid reduction in heterogeneity driven by the bulk flow(convection); the slope of the RSD curve, in semi-logarithmic coor-dinates, is the convective mixing rate. The second part is driven byindividual particle motion (dispersion) or by the slow erosion of APIagglomerates due to shear.When only one mixing mechanism is present (a situation that canbe achieved by careful control of the initial loading pattern), a simplemass-transfer model, represented in Eq. (1) can be used, as in paststudies 14, to capture the evolution of the RSD in powder systems. Inthis model, an exponential curve decaying towards a plateau is fittedto the mixing curves, where is the standard deviation, the finalstandard deviation, A is an integration constant, signifies the mixingrate constant, and N is the number of revolutions. This model predictsthat the experimental variance will decay exponentially with time asit approaches the random mixture state. In order to characterizenumerically the “mixing rate,” has to be computed for each blendingexperiment. = AeN1The values for parameters A and are calculated by minimizingthe sum of squares of errors between the data and an exponentialfunction. The value of final standard deviation () is taken as thelowest value of the varianceachieved in themixing studies.The valuesfor are computed for blending experiments with different per-centage fill, and loading pattern and the results are plotted in Figs.10and 11. As shown in Fig. 10, the mixing rate constant decreases withFig.10. Mixing performance was evaluated at three different fill levels for blender 2. Experiments were performed at 60%, 70% and 80% fill levels at 15 rpm with topbottom loading.Mixing rate constant () values is plotted as a function of fill level and found to increase with decrease in fill level.Fig. 11. Mixing performance of bin blenders along with loading pattern are compared at 20 rpm with 60% fill level. Mixing rate constant () values plotted for different loadingpatterns in bin blenders with and without baffle and as shown above, blender 2 givers a better mixing performance as compared to blender 1. There is also a pronounced effect ofloading pattern, and regardless of the blender used, topbottom loading always gives a better performance compared to sideside.6A. Mehrotra, F.J. Muzzio / Powder Technology 196 (2009) 17increase in percentage fill level. A broader comparison with two otherbin blenders is provided in Fig. 11, which displays the mixing rate forthe blender 2, for the blender 1 with and without baffles, and for acommercially available rectangular blender. The figure also illustratesthe effect of loading pattern on these four bin blenders, all of themrotated at 20 rpm. It is evident that blender 2 with dual axis of rotationhas the highest mixing rate constant of the entire group. For allblenders used in this study, there is also an effect of loading pattern onmixing; it was found that topbottom loading pattern gives bettermixing performance than side-side loading.4. ConclusionThe effects of fill level, mixing time, loading pattern and axis ofrotation on the mixing performance of a free-flowing matrix of FastFlo lactose and Avicel 102, containing a moderately cohesive API,micronized Acetaminophen was examined. Blending performancewas foundtobe adverselyaffected at increasingfill levels. Topbottomloading pattern was shown to lead to better mixing performance thanside-side loading pattern. It was also confirmed that spinning ablender in direction perpendicular to the rotation axis helps inenhancing mixture homogene