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GPC付費測試服務/分子量測試

簡要描(miao)述:GPC付費(fei)測(ce)(ce)試(shi)服務/分(fen)(fen)子(zi)量(liang)(liang)(liang)測(ce)(ce)試(shi)原理:1. 相對分(fen)(fen)子(zi)量(liang)(liang)(liang)測(ce)(ce)試(shi) 通(tong)過傳統(tong)GPC檢測(ce)(ce)樣(yang)品(pin)的(de)(de)分(fen)(fen)子(zi)量(liang)(liang)(liang),首先要通(tong)過一系(xi)列已知分(fen)(fen)子(zi)量(liang)(liang)(liang)的(de)(de)標準樣(yang)品(pin),建立分(fen)(fen)子(zi)量(liang)(liang)(liang)對流出時間/體積的(de)(de)標定曲(qu)線(xian),根(gen)據先前(qian)的(de)(de)標準曲(qu)線(xian),計(ji)算出相對分(fen)(fen)子(zi)量(liang)(liang)(liang)Mw, Mn,Mz及其分(fen)(fen)布。 2. 光散射(she)(she)和分(fen)(fen)子(zi)量(liang)(liang)(liang)測(ce)(ce)試(shi): 高分(fen)(fen)子(zi)的(de)(de)散射(she)(she)光符合(he)瑞利散射(she)(she)方(fang)程,在GPC樣(yang)品(pin)檢測(ce)(ce)濃(nong)度(du)(極稀(xi))條件下,當趨近于0度(du)角檢測(ce)(ce)散射(she)(she)光時,通(tong)過瑞利散射(she)(she)方(fang)程計(ji)算分(fen)(fen)子(zi)量(liang)(liang)(liang)。

  • 產品型號:量通技術
  • 廠商(shang)性質:代理商
  • 更新時(shi)間(jian):2020-08-20
  • 訪  問  量:9645

詳細介紹

品牌其他品牌應用領域醫療衛生,環保,化工,生物產業,石油

多檢測器凝膠滲透色譜GPC付費測試              

GPC付費(fei)測試項(xiang)目

測(ce)試(shi)編號

對外價格(含稅)RMB

說明

首檔

QFT-GPC-1

敬(jing)請(qing)來電 

·       其中如果(guo)首檔次收費標準可以通(tong)過產品線經理、產品專家(jia)、售后部門、實驗室應用經理/專家直接提供(gong)給有需求(qiu)用戶

·       成熟方法(fa)樣品,普通有(you)機流動相如(ru)THFDMF,三檢測器檢測分子量和(he)分子構象(xiang)信(xin)息

·  ;     成熟方法樣品,普通水相(NaNO3Na2SO4PBS等(deng)鹽類),三檢測(ce)器檢測(ce)分子量和分子構象信息

第二檔

QFT-GPC-2

敬(jing)請(qing)來電(dian)

·       第二檔次以(yi)上報價,包含方法摸索(suo),需要產品線經(jing)(jing)理(li)、產品專家和實驗室應(ying)用經(jing)(jing)理(li)/專家協商*,然后(hou)通過售后(hou)部門(men)給(gei)客戶報價

·       成(cheng)熟方法樣品,有機體系流動(dong)相(xiang)但屬于易制du流動(dong)相(xiang)(需要備案),如(ru)甲(jia)苯,氯fang,丙酮等(deng)流動(dong)相(xiang),如(ru)客戶自行提供流動(dong)相(xiang)可(ke)按照首檔收費。三(san)檢測器檢測分子量和分子構象信息

·       成熟方法樣(yang)品,特殊水性(xing)流動(dong)相(xiang),如(ru)甲酸(suan)、乙酸(suan)水溶液等流動(dong)相(xiang)。三檢(jian)測器檢(jian)測分(fen)子(zi)量(liang)和分(fen)子(zi)構象(xiang)信息

·       需要復(fu)雜操作的SELS方式(shi)操作(zuo)

第三(san)檔

QFT-GPC-3

敬請來(lai)電(dian)

·       成熟方法樣品,有(you)機(ji)體系流動相(xiang)(xiang)但是操作(zuo)復雜流動相(xiang)(xiang),如HFIPDMSO88%甲酸

方法摸(mo)索

QFT-GPC-4

敬請來電 

·       用戶樣品(pin)復(fu)雜,沒有成(cheng)熟方法,需要(yao)(yao)不(bu)同試(shi)劑摸(mo)索,需要(yao)(yao)不(bu)同樣品(pin)制備方式摸(mo)索,每摸(mo)索一個試(shi)劑條件,需要(yao)(yao)報價(jia)一次“方法摸(mo)索”費用

·       對于一(yi)些(xie)客戶提出的復雜實(shi)驗方案

典型分析樣品(pin):

色譜柱

流動相

典型樣品

苯乙烯-二乙烯基苯

THF

PS, PC, PVC, PBT, Nylon, XS(二甲苯溶出物),合成橡膠和,PLA(聚乳酸), PLGAPVAPolyanilinePBPolybutadiene),ABS樹脂,瀝青,聚對二氧環己酮,酚醛樹脂, PCL,聚噻吩, Polyvinyl Alcohol (PVOH) Polyvinyl Pyridine (PVP) 等等

苯乙烯-二乙烯基苯

DMF

聚氨酯,聚丙烯酸脂系列,PANPVDFPPS(戊聚糖多硫酸酯),Polyacrylamide (PAAm) Poly(N-isopropylacrylamide) (PNIPAm)dendrimer

苯乙烯-二乙烯基苯

DMAC

纖維素

苯乙烯-二乙烯基苯

氯fang

PET, PBTPLA

苯乙烯-二乙烯基苯

甲苯

硅油,硅氧烷,天然橡膠

苯乙烯-二乙烯基苯

HFIP

Nylon

苯乙烯-二乙烯基苯

DMSO

原淀粉,纖維素

丙烯酸酯

水(NaNO3

PEO/PEG,聚苯乙烯磺酸鈉,多糖,卡拉膠,水溶性纖維素系列,改性淀粉,透明質酸(HA,玻璃酸鈉),肝素,右旋糖酐,DNA,蒲璐蘭多糖,果膠,阿拉伯膠,PAA(聚丙烯酸),等等

陽離子化樹脂

水(乙酸)

殼聚糖,明膠,瓜爾膠等等

氧化硅

水(PBS

蛋白,IgG單抗,多肽,氨基酸 ,等等

 

結果報告:

色譜原始譜圖,重復性進樣結果,分子量MnMwMz和分子量分布PD,分子尺寸,Mark Houwink 曲線和參數

測試(shi)原理:

1.相對分(fen)子(zi)量(liang)

        傳統(tong)GPC/SEC配備一個濃度(du)(du)檢(jian)測器(示(shi)差檢(jian)測器或者紫外(wai)檢(jian)測器),檢(jian)測每個組分的流出(chu)時間和濃度(du)(du)。通過傳(chuan)統(tong)GPC檢測樣(yang)品的分(fen)(fen)子量(liang),首(shou)先(xian)要通過一(yi)系列已(yi)知分(fen)(fen)子量(liang)的標準樣(yang)品,建立分(fen)(fen)子量(liang)對流(liu)出(chu)時(shi)間/體(ti)積的標定曲線(xian)(如下圖)。然后注入(ru)待測樣品,根據先前(qian)建立(li)的標準曲線(xian),計算(suan)出(chu)相(xiang)對分(fen)子量Mw, MnMz及其分布和 PD = Mw/Mn  

      相對(dui)分子量檢測只需要一個(ge)RI檢測(ce)器和一套GPC前端分離系統,特點是(shi),結構簡單,但是(shi)相(xiang)(xiang)對分子(zi)(zi)(zi)量(liang)結果是(shi)相(xiang)(xiang)對于(yu)標(biao)準樣品(pin)(pin)(pin),忽略(lve)了待(dai)測樣品(pin)(pin)(pin)和(he)標(biao)準樣品(pin)(pin)(pin)之間(jian)的(de)(de)結構差異(主要(yao)是(shi)分子(zi)(zi)(zi)密度的(de)(de)差異),所以除非使用與(yu)待(dai)測樣品(pin)(pin)(pin)相(xiang)(xiang)同種類的(de)(de)標(biao)準樣品(pin)(pin)(pin)進行校正,其(qi)(qi)得(de)到(dao)的(de)(de)相(xiang)(xiang)對分子(zi)(zi)(zi)量(liang)和(he)其(qi)(qi)真實/分(fen)(fen)(fen)子量(liang)具有(you)較大(da)差異,其(qi)分(fen)(fen)(fen)子量(liang)分(fen)(fen)(fen)布和(he)其(qi)真實分(fen)(fen)(fen)布之間也有(you)所差別。如(ru)果使用不(bu)同種類(lei)的標準樣品(pin)進行色譜校正(zheng),將得(de)到不(bu)同的相(xiang)對分(fen)(fen)(fen)子量(liang)信息。色譜泵(beng)對于傳統(tong)校正(zheng)方(fang)法的影(ying)響大(da),如(ru)果色譜泵(beng)工(gong)作不(bu)正(zheng)常導(dao)致(zhi)樣品(pin)流出時間改(gai)變,會影(ying)響檢測結果的重復性(xing)。

    單一示差檢測器GPC大量存在于市場中,適合作為對于測試要求不高的檢測工具,尤其適合高分子生產過程中的QA/QC過程。

 2.光(guang)散射和分子(zi)量:

           光(guang)散射(she)(she)檢測(ce)器是檢測(ce)高分(fen)子(zi)分(fen)子(zi)量的直接方法(fa)。 高分(fen)子(zi)的散射(she)(she)光(guang)符合瑞(rui)利散射(she)(she)方程(cheng)。在GPC樣品檢測濃度(du)(極稀)條件下,當趨近于0度角(jiao)檢測散射光(guang)時,通(tong)過瑞利(li)散射方程(cheng)我們得到:

 

        其中Rθ|θ→0是瑞利比,代(dai)表樣品散射光強度(du),K’是常數,c是濃度,Mw是分子量

         凝膠滲(shen)透(tou)色譜GPC設備中,經(jing)常使用示差(cha)RI檢(jian)測器和光散射檢(jian)測器連(lian)用(yong),RI檢測(ce)器提供每個(ge)分(fen)離組(zu)(zu)分(fen)的濃度信息,而光(guang)散射檢測(ce)器檢測(ce)散射光(guang)強,二者配合(he)使用,檢測(ce)每一個(ge)流出組(zu)(zu)分(fen)的分(fen)子(zi)量信息

        光散射檢測器(qi)的(de)(de)使用,使得測試擺脫了對于標準(zhun)樣品、校正曲線的(de)(de)依賴,并且其得到的(de)(de)分子量和(he)分子量分布更加準(zhun)確的(de)(de)和(he)高(gao)分子的(de)(de)各種性能關聯起來。

 

3. 粘度檢測器

        在線粘度檢測器被設計為惠斯通橋的結構。

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" />

       其原理是測定樣品溶液通過四毛細管橋所產生的壓力差,從而得到每個被分離的組分的增比粘度,再通過濃度檢測器RI得到的組分濃度,我們可以計算出高分子的特性粘度,或者說分子密度的倒數:

  通過特性粘度,我們可以得到高分子的:特性粘度(IV),流體力學半徑 Rh(可小于1nm),Mark-Houwink曲線Ka值,分子結構信息,高分子構象信息(鏈折疊),高分子的支化度和支化頻率。

 

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