^{}

2018-05-13

【譯者心語】：取樣永遠是第一步的！

樣品的代表性直接影響分析結果的可靠程度。如何合理取樣？發生OOS又如何做取樣環節的調查？大家常常并不重視取樣的細致合理化，出現問題又常常無從著手，難以判斷和下有指向意義的結論。這篇USPGIC文章從固體物料離散理論、取樣工具、取樣和分樣方式著手，體現各種具可操作性方法的優點同時也客觀闡述不足。與其說是給我們灌輸知識，不如說是引導我們形成有代表性取樣問題的良好思考習慣。如果仔細閱讀，還會發現一些我們習以為常的細節處理不一定合理或是最佳方式。

遍布公式、術語的文章翻起來累，讀起來也累！建議有興趣的親們分2-3次在閑暇時細品，篇幅較長，為便于閱讀，譯者已在精彩處以粗體字標出。為提升閱讀的流暢度，原文中取樣工具操作方法的具體介紹和三個附錄部分內容未引入，有興趣的讀者可再回溯原篇。

<1097> BULK POWDER SAMPLING PROCEDURES

<1097> 散裝粉末物料取樣規則

INTRODUCTION 介紹

The goals of this chapter are to provide guidance on bulk powder sampling procedures, identify important bulk powder sampling concepts, and collect a knowledge base of useful practices and considerations that can lead to the ideal physical sampling of bulk powder materials. The terminology used here is well established in the field of material sampling (see Appendix 3, for instance reference 7). Sampling is undertaken as part of an estimation process. The parameter of primary interest here is the mean level of some analyte in the bulk powder as a whole.

本文的目的，在于為散裝粉末物料提供取樣程序指南。包括明確散裝粉末樣品的重要取樣原則，形成基于科學知識的適用操作模式和思考方式，以實現理想的散裝粉末物理取樣。本文相關術語在物料取樣領域實踐中逐步形成（見原文附錄3，如第7條）。取樣其實是整個評估測試過程的一部分，散裝粉末物料取樣中首個要點在于獲取被分析物的平均水平。

The purpose of a sampling plan is to obtain a representative sample of a population so that reliable inferences about the population sampled can be drawn to a certain level or degree of confidence. Acquiring a representative sample from a lot is critical because without a representative sample all further analyses and data interpretations about the lot are in doubt. An ideal sampling processis a process in which every particle or at least every equal-size portion of the population has an equal probability of being chosen in the sample. In addition, sampling procedures should be reproducible, i.e., if the sampling protocol were repeated, a high probability should exist of obtaining similar results. Also, the integrity of the sample should be preserved during and after sampling. The details of how to sample depend on a variety of factors. For example, criteria for sampling to evaluate particle segregation may differ from criteria for evaluating moisture content or identification.

制定取樣計劃的目的在于從物料整體中獲取有代表性的樣品，以保證所取樣品的可信性達到一定水平或一定置信度。從批物料中獲取有代表性的樣品至為關鍵，因為無此前提則所有關于此批物料的后續分析和數據演繹皆可能被質疑。合理的取樣過程應保證每個個體顆粒，或至少整體的每個平均分部有相同的幾率被取為樣品的一部分。此外，取樣程序應具有可重復性，即，如果取樣方案被重復執行則很大幾率應得到相似的測試結果。還有，樣品的完整性在取樣過程中和取樣完成之后均應有保證。（最后），如何取樣的細節也依賴于各種因素，比如用于顆粒分布的取樣要求應和用于水分檢測或鑒別樣品的取樣要求有所區別。

Because of the propensity of a powder to segregate, heterogeneous powder systems can make it difficult to obtain an ideal sample. Thus, to extract representative samples requires careful development of a sampling plan that accounts for and mitigates the segregation tendencies of a particular powder system. Developinga general guidance for bulk powder sampling is challenging because every situation is different, and therefore different approaches must be used to deal with each situation. Thus, the goal of this general information chapter is to outline recommended steps for developing a sampling scheme or plan for aparticular system that is consistent with good sampling practices.

由于粉末具有離散特性（譯者注：所謂離散特性，其實就是“塵歸塵、土歸土”的顆粒運動趨勢），從不均一的粉體獲取理想的樣品并不容易，因此，需要制定能夠反應和減輕粉體離散趨勢影響的取樣方案來獲取有代表性的樣品。制定一個粉末物料取樣的通用指南具有挑戰性，因為面臨的具體問題往往不一樣，客觀上就要求針對不同的情況制定不同的方式方法。因此，本通用資料篇（GIC）的目的也在于為特定的系統給出制定取樣計劃的推薦步驟，以符合規范合理化取樣的要求。

The primary difficulty in acquiring a representative sample is that the size of the sample for measurement, typically a few milligrams to grams, must be withdrawn from a large population on the order of hundreds to thousands of kilograms. The few milligrams analyzed in a laboratory must be taken from a large population of particles in a warehouse in such a manner that the measurement sample is representative of all the particles in the lot. Any bias or error in the sampling process will cause all future inferences to be in error. Over the years methods have been developed and refined to attempt to ensure that the measurement sample is representative of the whole population. A typical strategy is shown in Figure 1. The strategy is to sample in stages, starting with the initial gross or primary sample withdrawn directly from the received containers. In the laboratory, the gross sample must be reduced in size until it is the appropriate size for measurement. This should be done in a manner that minimizes the introduction of sampling errors. The key to reducing the sampling error is to ensure that every particle of the population has an equal probability of being included in the sample. However, because of segregation or the non random nature of powders, many obstacles can cause bias and contribute to sampling errors. Following the flow chart in Figure 1 andthe steps outlined in subsequent discussions will help to minimize sampling errors.

實現取樣代表性的首要困難在于，用于分析的樣品常常只有幾毫克到幾克，而這有限的樣品需要從幾乎成百上千公斤的大批物料中獲取。這幾毫克實驗樣品必須以有代表性的方式從倉庫中該批物料大量的顆粒中取出，取樣中任何偏離或差錯都可能導致相應分析結果錯誤。往事如歌，很多方法被優化和改良以嘗試保證分析樣品對于整體的代表性。一個典型的策略見圖1，策略是分步取樣，從直接在所接收的容器中獲取初始樣或一級樣開始。在實驗室，該一級樣品必須減少到適合檢測的（二級）樣品量，這個過程應最小化可能引入的取樣誤差。最小化誤差的關鍵則在于保證整體中每一顆粒有均等的機會被引入最終樣品。然而，由于顆粒具有離散性和非隨機特性，很多障礙可能導致偏離從而形成取樣誤差。流程圖1和后續的相關步驟討論，就會專注于最小化各種取樣誤差。

Figure1. Overall sampling strategy for reducing the sample size from the hundreds of kg scale to the mg scale.

圖1. 從百公斤級到毫克級取樣整體策略

To acquire a representative sample, a suitable sampling plan must be developed and implemented. A good sampling plan includes: (1) population determination and sample size selection, (2) a sample collection procedure and a method for sample size reduction, and (3) summary calculations that demonstrate that the sampling plan will yield samples that accurately characterize the population to within a stated level of acceptance. In addition, an infrastructure is needed to maintain the integrity of the samples and sampled materials.

要獲取有代表性的樣品，必須制定和執行合適的取樣計劃。一個良好的取樣計劃包括：（1）明確總量和確定樣品量，（2）制定（一級）樣品采集程序和（二級）樣品量縮減方法，以及（3）綜合計算以證明按照取樣計劃所獲取樣品可以在置信限度內準確表達整批物料。另外，也應建立可以保持物料和樣品完整性的基礎條件。

This chapter begins with a brief introduction to sampling theory and terminology. The technical content of the chapter requires a basic scientific understanding of physical particle characteristics (e.g., mass, density, shape, and size) and statistics (e.g., acceptance sampling and binomial distribution).

本文以取樣理論和術語的介紹起篇。相關技術章節需要對于各種物理粒子特性（如質量、密度、形狀、粒度）和各統計學概念（如抽樣驗收、二項分配）科學含義有基本理解。

SAMPLING THEORY AND TERMINOLOGY 取樣理論和術語

Fundamental Sample Size(Sample Mass) 基本樣品量（樣品重量）

Sample size is considered from two perspectives: (1) the mass of the sample intended to represent the entire population, sometimes termed the composite sample, and (2) the number of samples taken with a mass sufficient to independently evaluate, compare, or provide confidence to ensure the reproducibility of the composite or the uniformity of the population. The key to obtaining an ideal sample is to understand and account for the degree of heterogeneity of the characteristic being evaluated in the system under study. For example, heterogeneity of a particle system arises from two sources: the intrinsic, constitutive, or compositional heterogeneity and the spatial distribution heterogeneity. The intrinsic heterogeneity of the powder system reflects the fundamental differences in the individual particles. Statistical heterogeneity (differences between individuals), or variance, is expected to maintain assumed properties. For a normal population the general expression for a statistical sample size suggests that the number of independent samples is proportional to the square of the normal quantile at the desired confidence level (Z) and the population variance (σ2) and is inversely proportional to the square of the minimum detectable difference required (δ), as shown in equation 1:

樣品量應從兩方面考慮：（1）用于反映整批物料的樣品重量，有時也稱樣品組成，以及（2）足夠的樣本數量（個數），這些樣本各具有一定量且可以進行獨立評估、用于比較或提供證據以保證可以再現物料整體的組成或一致性。獲取理想樣品的關鍵在于努力理解和克服顆粒系統里待測屬性的不均一程度。即，粉體不均一性其實是來源于兩個途徑的：一種是顆粒組成的，本質內在的不均一；另一種是空間分布的不均一。其中，粉體顆粒內在的不均一反映存在于個體顆粒內的根本的差別。而統計學不均一（個體顆粒間差異），或離變，則可望保留預想的（質量）屬性。對于一般的整體而言，基于統計學原理的樣品量通用公式為樣本數量與預期的置信限水平（Z）平方和整體標準差的平方值(σ2) 成正比，與最小可識別精度(δ)平方成反比，見方程1：

In order to apply the normal theory sample size equation to sample mass with adiscrete number of particles, consideration for material characteristics is needed. For a heterogeneous bulk material, such as a bulk powder, the sample mass required to ensure adequate representation of the intrinsic or fundamental population heterogeneity or variation is determined by the size, shape, and density of the particles. The total sampling error (TSE) measures the difference between the analyte concentration estimated in the sample (asample) and the mean analyte concentration in the lot (a lot) relative to the mean analyte concentration in the lot (alot), as shown in equation 2:

為了使一般樣品量理論方程適用于粒度離散分布的樣品，需要特別考慮物料的特性。對于不均一的整批物料，如整批粉末，為保證足以代表顆粒內在的不均一性或差異而所需的抽樣數取決于顆粒大小、形狀和顆粒密度。總取樣誤差（TSE）為被分析物濃度水平與整批濃度水平的差值，除以整批濃度水平，如方程（2）：

When ideal sampling is employed, the TSE is reduced to a fundamental sampling error, limited only by the intrinsic heterogeneity of the material. The relative variance of the fundamental sampling error (Sfse2) has been empirically estimated in particle size applications by characterizing the critical particle mass, heterogeneity, size (diameter), shape, density, and weights of the material. Empirical estimates require a thorough and complete knowledge of the material and process. Established material characterization and methods are critical aspects of avoiding unacceptable estimates. As shownin equation 3:

一旦實現理想取樣，TSE將被降低到基本取樣誤差（fse）水平而僅局限于物料顆粒內在不均一。基本取樣誤差的方差(Sfse2) 已可以通過粒度軟件從經驗上估測，這種經驗估測基于測定關鍵的顆粒集合、顆粒不均一性、粒徑、形狀、密度和物料量等等信息。經驗估測要求對物料和工藝的全面徹底的了解。所確定的物料特性和所應用的方法是避免不可接受的評估的關鍵方面。具體如方程（3）：

wheref shape is a measure of cubicity or shape factor of the analyte particles; gCF, the granulometric factor, is an empirical correction factor of differences inparticle size; cmax is the compositional maximum heterogeneity and is calculated as if the material consists of the analyte particles and everything else; l, the liberation factor, is an empirical factor representing the proportion of critical content particles separated from the non-analyte containing particles of the lot; dmax is the particle diameter [e.g., the maximum diameter or the diameter (cm) of the size of the opening of a screen retaining 5% by weight of the lot to be sampled]; msample is the mass of the sample; and mlot isthe mass of the lot being sampled. [Note—A liberation factor is needed when the analyte does not appear as separate particles. A high liberation value (1.0) suggests heterogeneity of particles. A low liberation value (0.05) suggests very homogeneous particles. See Appendix 1 for examples of potential applications of equation 3 in the estimation of the fundamental sample mass needed to account for constitutional heterogeneity of the powder mixture.] Use of equation 3 requires prior estimates of fshape, gCF, cmax, I,and dmax.

其中，fshape是被分析顆粒的立體或形狀指數；gCF，是粒度指數，即顆粒間差異的經驗校正因子； cmax 是組成的最大不均一性（以物料由被分析顆粒和其他所有顆粒組成的方式計算）； l，釋放因子，是經驗指數，代表關鍵成分顆粒從該批非被分析物的顆粒中分離的比例；dmax 是粒徑[如，最大粒徑或過篩保留的整批物料5%的篩上物粒徑]；msample 是樣品量；mlot 是被取樣批次的總量。[注：當被分析物不是分離顆粒時，應賦予釋放因子。高的釋放值（1.0）代表顆粒不均勻，低的釋放值（0.05）代表分布非常不均勻。見附件1（未譯，參考原文）示例，方程3潛在應用于評估基本樣品量時，需要考慮混合粉末的內在不均一]方程3的應用需提前評價 fshape, gCF, cmax, I, and dmax.

Segregation Error 離散誤差

Distribution heterogeneity is the difference between samples or groups of particles spatially or temporally. For example, small particles are located preferentially in the lower portion of a powder bed. This type of situation can arise as a result of powder bed segregation and is common in some particle systems with a broad particle size distribution. In other words, smaller particles may not be randomly distributed throughout the lot. This spatial heterogeneity introduces variation in the sample and is a source of variation that contributes to the total variation. Together, fundamental and segregation error give rise to sampling error, which dictates how variable the samples will be, how large the sample size and numbers of samples should be (e.g., 10 containers, sampled at top and bottom, with sample sizes of 50 g each), and how hard it will be to obtain a representative sample.

分布不均一是樣品或顆粒集合空間上存在的或暫時存在的離變。比如，小的顆粒會優先分布在顆粒床較低部分。這種狀況會作為粉體離散的結果發生，且在一些具有寬粒度分布的粉體中很常見。換言之，小顆粒可能不會隨機分布于整個批次。這種空間不均一性給樣品引入離變并且構成整體離變的一個因素。內在誤差和離散誤差一起提升了取樣誤差，并決定了樣品多大程度存在離變，決定了樣品量應有多大，應取多少個樣本（比如，10個包裝，頂部和底部取樣，樣品量每份50g），以及獲取一個有代表性的樣品難度有多大。

Minimizing the effects of segregation error during lot material characterization while still ensuring a representative sample mass requires collecting many small samples that average out the variation of the segregation error. This assumes one is interested in estimating the overall average, not characterizing lot heterogeneity. Segregation error is difficult to control because segregation may be the result of changes in particle size, shape, and density, as well as inputs into the determination of sample mass. Minimizing the effects of segregation error when reducing the primary sample size requires adequate physical mixing or randomization of the primary samples before analysis, thus providing equal selection probability.

表征整批物料過程中要最小化離散誤差影響的同時，又要保證有代表性的樣品量，客觀上要求采集許多小份樣品以平均化離散誤差的變異。這客觀上要求著力估算整體平均值，而非表征整批不均一性。離散誤差很不可控，因為離散可能作為顆粒度、形狀、密度，還有用于測試的樣品量變化的結果存在。在降低一級樣品量的時候最小化離散誤差的影響，就要求充分的物理混合，或在分析前隨機化分布一級樣品以提供均等的選擇機會（以提取二級樣品）。

Total Sampling Method Error 取樣方法整體誤差

Intrinsicor compositional heterogeneity is a function of the powder system and represents the true characteristics of the material (e.g., equation 3). Thus, intrinsic heterogeneity is often the minimal variance a system can have. The difference between the true state of the system and what is actually measured when ideal sampling is employed is called the fundamental error (equation 2). The relative variance of TSE (S2Total) is represented in equation 4 as the sum of the relative variances of all error components:

（顆粒）內在不均一或組成不均一屬于粉體功能屬性，代表了物料的真實性特征（見方程3）。如此，內在不均一經常是粉體所能有的最小離變性。粉體實際狀態和基于理想樣品的實測結果之前的差異稱為基本誤差（見方程2）.整體取樣誤差（TSE）的方差 (S2Total)用方程4表示為所有誤差成分的方差和。

The S2Total can be reduced by employing ideal sampling. Ideal sampling will limit or adjust for the effects of error contributed by particle segregation, extraction error created by the sampling device, delimitation error created by not considering the three-dimensional nature of the bulk material, and sample handling errors such as product degradation. The total variation is the sum of these sources of error, illustrated in equation 4 as independent, additive components. To the end of reducing these errors, an important goal of material characterization by sampling is the determination of the relevant errors within the bulk sample. Knowing the source of the error helps determine how to best minimize these errors.

整體取樣誤差方差（ S2Total）可以通過利用理想樣品的方式減低。理想樣品可以限制或調節顆粒離散帶來的誤差影響，限制或調節取樣工具導致的取樣方式誤差影響，限制或調節由于忽略大批物料三維特性導致的分界誤差的影響，以及限制諸如產品降解的樣品管理誤差。總變異是所有這些誤差因素的集合，如方程4表達的獨立而相加的各因素。要降低這些誤差的最后一點：通過取樣表征物料的一個重要目的就在于測量批范圍內的誤差。了解清楚誤差源對于確定如何最好降低這些誤差會有所幫助。Fundamental error arises from the intrinsic heterogeneity of particles within a sample of the material population. Reducing fundamental error requires changing the intrinsic characteristics of the material, such as reducing the particle sizeby milling or grinding. Segregation error is the spatial distributional difference of particles across the population. This type of error can be minimized by mixing or randomization of the particles being selected. Segregation error is affected by the characteristics of fundamental error. Additionally, for the determination of both fundamental and segregation error, it is assumed that mechanical sampling is carried out correctly and is not invasive, i.e., that mechanical sampling does not alter the characteristics being measured and provides a true representation. In instances where sampling of the bulk material does not provide unbiased representation or is so invasive that it alters material characteristics, then, in order to obtain noninvasive, unbiased samples, operators may need to change sampling from a bulk form to a stream form of processing, either upstream or downstream from the sample point (see Appendix 2). The mechanical sampler may need to mix the sample sufficiently to facilitate random sampling with equal probability of selection in order to obtain an adequate representation of the entire bulk lot. The process may also require mixing or sampling from a location in the process that will provide a random sample from material that is susceptible to segregation.

基本誤差會伴隨整批批被抽樣顆粒的內在不均一而上升。降低基本誤差要求改變物料的本質特征，比如通過磨粉降低粒度。離散誤差是整批顆粒的空間分布離變，這種誤差可以通過混合和隨機化被選取顆粒的方式減低。離散誤差會被基本誤差的特征影響，另外，對于評價基本誤差和分散誤差，機械取樣應被正確應用而不應有破壞性，即機械取樣不應改變被測屬性并提供真實的代表性。比如取整批物料不提供無偏離的代表性或因具有太大破壞性而改變了物料的特征。因此，為了獲得不帶偏見，不具有破壞性的樣品，取樣員可能需要將從批量物料中取樣的方式改為在加工過程中從物料流體中取樣，既有取樣點（見附件2）處順流的，也有逆流的。機械取樣可能需要充分混合樣品以幫助實現均等幾率方式隨機取樣，從而獲得整批物料有充分代表性的取樣。該過程也可能需要混合，或者從工藝流程的某一個點取樣，這個點可以給對于離散敏感的物料提供隨機的樣品。

Extraction, delimitation, and handling errors occur as a result of the mechanical sampler and sample handling prior to analysis, which also are affected by fundamental error. Trends, shifts, and cycles are temporal sources of error that affecttotal error. The analytical error of the method of analysis contributes to the overall error of the reported result. In addition to obtaining representative subsamples from the bulk material, the method must also obtain a representative subsample from the particulate laboratory sample before analysis.

抽取、分界和操作誤差的出現其實是樣品分析前機械取樣器和樣品操作方式的結果，還受基本誤差的影響。趨勢、漂移和循環都是影響整體誤差的即時因素。分析方法帶來的誤差也部分構成了最后結果的總誤差。除了從大批量物料中獲得有代表性樣品之外，在執行樣品分析之前也必須從實驗室特定樣品中獲取有代表性的二級樣品用于檢驗。

**Sampling Strategy 取樣策略**

Atypical sampling strategy consists of two basic steps: (1) the primary or gross sample, followed by (2) the secondary sample, which reduces the primary sample to a size that is suitable for laboratory measurement. In short, the goal is to select from the lot a quantity of material suitable for measurement without significantly changing the attribute for which one is sampling. In parallel with the sample size reduction, sample size calculations must be done in such a way that the sampling strategy has sufficient statistical power to determine whether the attributes of interest lie within the specification ranges with a reasonable degree of certainty. Each step must be done correctly, or the sampling strategy as a whole will not provide a sample that is representative of the original population.

典型的取樣策略包括兩個基本步驟：（1）一級樣品或總樣品，然后是（2）二級樣品，該樣品將一級樣品的量降低到適合實驗室分析的水平。簡而言之，目的是從批物料中選取適合量用于分析而不對被測屬性造成顯著影響。樣品量的減少計算，應基于采用的取樣策略具有足夠的統計能力，可以使符合質量標準的被測結果有合理的可信度。每一步都必須正確應對，否則作為一個整體的取樣策略無法提供對于原始批具有代表性的樣品。

To successfully withdraw a sample from a bulk container that is representative of the population, one needs to have an idea of the population's heterogeneity, i.e., how segregated or stratified the system is. Knowing what factors can accentuate segregation and knowing the patterns of segregation that are likely will help one to account for segregation in a powder bed and to take better samples. Many factors can affect the degree of powder bed segregation. For segregation to occur, sufficient energy needs to be put into the powder bed to induce motion between particles. When a sufficient amount of energy is supplied, segregation can occur via three modes: percolation (in the powder bed), rolling (on the free surfaces of a powder bed), and free flight (when the powder bed is fluidized). These modes are illustrated in Figure 2.

為了從批包裝中成功獲取有整體代表性的樣品，應對整體不均一性有基本的了解，比如粉體是如何離散或分層的。知道什么因素可以加重離散，知道離散的具體方式，這些可以幫助解讀粉體的離散從而幫助獲取更好的樣品。許多因素都可以影響到粉體的離散度，對于離散的發生，需要針對粉體提供足夠的動能以誘導顆粒間移動。當賦予了足夠的動能，分散可以基于三種形式發生：（粉體內的）滲透、（粉體自由面的）滾動、還有自流（當粉體屬于流體）。這些形式具體見圖2.

Figure 2. Illustration of the three modes of particle segregation: percolation, rolling, and free flight.

圖2. 顆粒分散的三種形式的演示：滲透、滾動，和自流

Within the powder bed, segregation can occur by means of percolation, also called sifting segregation, as well as through the movement of coarse particles to the top via vibration. During sifting segregation, smaller particles acting under the influence of gravity can more easily migrate downward into the void spaces between larger particles when the particle bed is perturbed. The net effect of these movements is that the smaller particles percolate down into the powder bed, resulting in the top of the powder bed having a higher proportion of larger particles. A common example of sifting segregation is unpopped cornkernels that are found at the bottom of a bag of popped popcorn.

在粉體內，離散可以滲透的方式發生，也稱為過篩離散，就如同粗顆粒能以振動方式運動到頂部。在過篩離散過程中，當顆粒床振動時小顆粒在重力影響下可以更輕易的通過大顆粒的孔隙遷移到底部。這種運動造成的影響就是小顆粒振動到粉體底部從而導致顆粒床頂部有更高比例的大顆粒。一個通俗的過篩離散的例子就是可以在一袋爆玉米花的袋子底部找到沒有爆開的玉米粒。

For free surfaces, rolling segregation can occur any time that particles can roll down a free surface. In other words, segregation can occur on any non-level surface that allows the relative movement of particles. When particles roll down these free surfaces, larger particles tend to tumble farther down the surface than the smaller particles (see Figure 3). For example, if a conical heap or pile is formed in the middle of a hopper during loading, larger particles are more likely to roll farther down the heap, toward the outer edge of the hopper. This creates a situation in which the smaller particles tend to be in the center of the hopper, and the larger particles accumulate toward the outer wall of the hopper. The formation of these free surfaces can be a major factor in segregation.

對于自由面，滾動離散可以在顆粒可以沿著自由面滾動的任何時候發生。換言之，在允許顆粒相對運動的任何非水平表面離散都可發生。當顆粒沿著這些自由面滾動時，大的顆粒會比小的顆粒“摔”的更遠（見圖3）.比如，如果在裝載過程中形成了錐體，大的顆粒更可能滾落到錐體下部外緣，這就造成了小的顆粒會在錐體的中心，而大的顆粒形成外墻。這種自由面的形成可以是離散的主要因素之一。

Figure 3. Example of extensive powder segregation within a drum.

圖3. 桶內粉末大量離散示例

When powder beds are fluidized, a large amount of air is incorporated into the powder bed and, when this air is moving, the air velocity may exceed the terminal velocity of the smaller particles. When this happens, the fine particles are suspended in the air stream while the coarse particles settle out. The fine particles eventually settle on top of the powder bed, forming a top layer that has a higher concentration of fine particles. This type of segregation, sometimes called elutriation segregation, can occur when a powderis discharged from a hopper, or is poured into the top of a hopper, and a large volume of air is displaced.

當粉體流態化，大量的氣體混入粉體。當空氣流動時，流速可能超過小顆粒的終極速度。一旦發生這種情況，細顆粒就會懸浮在氣流中而粗顆粒會沉降。細顆粒最終會沉降在粉體上部，從而在粉體形成一個有更高比例細顆粒的頂層。這種離散有時候叫淘洗離散，會在物料從漏斗內釋出時發生；或者往漏斗里傾倒粉末，伴隨相當體積的空氣被置換時也會發生。

In summary, for a highly segregating system, the powder bed could have a particle distribution similar to that shown in Figure 3, where, as a result of elutriation segregation, a layer of fine particles on the top overlies larger particles deposited by percolation segregation, and aradial distribution of larger particles appears toward the outer wall as aresult of rolling segregation.

總之，對于高度離散的粉末系，粉體可能出現類似圖3的顆粒分布。其中，作為淘洗離散的結果，粉體上方覆蓋一層微粉；部分稍大顆粒以滲透分離的方式存在底部；還有更大顆粒在錐體外圍以滾動分散的形式放射性分布。

In general, the primary factors that affect segregation are particle size and size distribution, density, and shape and shape distribution. Of secondary importance are surface roughness, surface coefficient of friction, moisturec ontent, and container shape and design. Particle size is the most important single factor, and subtle differences in particle size can cause measurable segregation. If the attribute of interest is associated with particle size,then this attribute will segregate along with the different particle sizes. For example, if a manufacturer makes a granulation in which the larger particles contain more drug than the smaller particles, then drug content can be very prone to segregation—i.e., drug content will show segregation patterns similar to those associated with particle size segregation.

一般而言，影響離散的首要因素在于粒度大小和粒度分布、顆粒密度、顆粒形狀和形狀分布。次要因素包括顆粒表面粗糙度，表面摩擦系數、水分含量、包裝形態和設計。顆粒度是最重要的單一因素，顆粒度的細微差別都可以導致可測量的離散。如果被測屬性和顆粒度相關，這個被測屬性結果也會和不同的粒度大小伴隨離散。比如，如果一個工廠制粒的大顆粒比小顆粒含有更多的活性成分，那么活性成分含量就有離散的傾向，即活性成分含量會體現和粒度分布離散近似的離散模式。

Segregation can notably increase sampling error because it decreases the probability that certain particle types will be in the sample. In addition, the powder bed may already be segregated when material is received, and poor sample handling can also cause segregation. To avoid further segregation during sample handling, the operator should avoid situations that promote segregation, such as the following: pouring where the powder forms a sloping surface, pouring into the core of a hopper, vibrations, shaking, and stirring (unless done to promote mixing). In addition, the use of mass flow hoppers reduces segregation.

離散可以顯著增加取樣誤差，因為可以降低某個類型的顆粒存在于樣品中的幾率。另外，當物料被接收的時候，離散可能已在粉體中發生，而糟糕的樣品處理也會造成離散。為了避免在樣品處理過程中發生進一步的離散，取樣員應避免促進離散的情形，比如避免形成顆粒坡面、避免傾倒進錐體、避免振動、搖動和攪動（除非為了促進混勻）。另外，密相流料斗可以減少離散。

Two basic strategies help promote ideal sampling: (1) use of a sampling thief and (2) sampling from a moving powder stream.

兩個促進理想取樣的基本策略：（1）刺入式取樣，以及（2）從粉末流體中取樣。

As ampling thief is a long spearlike probe that can be inserted into the powder bed and, once inserted, can collect powder samples from points adjacent to the spear. With a sampling thief, particles from almost any point in the powder bed can be included in the sample. The second method relies on fundamental principles of sampling, namely that (1) a powder should always be sampled when in motion, and (2) the whole stream of powder should be sampled for many short periods rather than sampling a part of the stream for a longer period.

刺入式取樣器類似梭鏢可以探入粉體，而且一旦刺入，可以收集梭鏢毗連點的樣品到取樣器中。應用取樣器，顆粒床的幾乎任何點都有可能被收集到樣品中。第二種方法依賴于取樣的基本原則，即（1）總是在物料運動時取樣，以及（2）粉末流應全程多時間點取樣，而不是只在特定時間段。

For example, if the container to be sampled is emptied onto a conveyer belt, all the material will pass by a single point that can be sampled. Thus, no matter how segregated the system is, the collection of the powder at random time points ensures that every particle has an equal probability of being includedin the sample. The second fundamental principle accounts for material segregation on the conveyer belt: by collecting the entire stream, one gets across section of all the particles, no matter how much segregation occurs on the conveyer belt.

比如，如果一個將被取樣的包裝內物料被清空到傳輸帶上，所有物料會通過可被取樣的一點。這樣，無論該粉體如何離散，所有粉末顆粒在隨機時間點都能被取樣，從而可以保證每個顆粒有均等的幾率抽取為樣品。第二個基本原則對物料在傳輸帶上的離散具有意義：通過取整個流體，無論在傳輸帶上發生了多大程度的離散，都可以獲得所有顆粒的各個部分。Many methods are available for obtaining a sample from a powder system. Unfortunately, many of these methods involve setting the powder bed in motionor performing in-process sampling. Because of concerns about cross-contamination and containment of potentially toxic materials, most of these methods are impractical for the bulk sampling required for compliance with current Good Manufacturing Practices (cGMPs). Hence, most of the sampling done in the pharmaceutical industry is static sampling, done by either (1) scoop or grab sampling or (2) stratified sampling, typically employing a sampling thief. The choice of method is dictated by the distribution of the attribute being sampled in the container, as discussed below.

從粉體中取樣有許多方法可供使用。很不幸，其中許多種是讓顆粒床處于運動中時取樣，或執行過程種取樣。由于擔心交叉污染，以及可能含有毒性物料，這些方法大多對于要求符合cGMP規則的散裝取樣不具有可操作性。因此，在制藥工業，幾乎所有的取樣都是靜態取樣，以（1）勺鏟取樣或（2）層次取樣，一般用刺入式取樣器。方法的選擇取決于取樣待測屬性在包裝內的分布，詳見下述。