Automated gradient development

The basis of automated multiple development (AMD) is the use of different modes of multiple development in whieh the mobile phase eomposition (5j and Sy values) is ehanged after eaeh, or several, of the development steps. Figure 8.11 illustrates the prineiple of AMD employing a negative solvent-strength gradient (deereasing 5-p values). 

Figure 7.13 Separation of a test eixture using automated multiple development with a universal mobile phase gradient from acetonitrile through dlchloromethane to carbon disulfide on a silica gel HPTLC plate. The chromatogram was scanned at different wavelengths to enhance the chromatographic information.

Two-dimensional separations in planar chromatography are rather trivial to perform. All unidimensional multiple development techniques employ successive repeated development of the layer in the same direction, with removal of the mobile phase between developments. The main variants are multiple chromatography and incremental multiple development. The basis for automated multiple development (AMD) is the automation of unidimensional, incremental, multiple development with a reverse solvent strength gradient [998]. 2D TLC finds limited use, and is mainly a qualitative technique. 

Automated multiple development (AMD) has been successfully applied for the separation of compounds from plant extracts. AMD is a technique using the concentration gradient to separate substances differing... 

Figure 6.12. Separation of a mixture of polar crop-protecting agents on silica gel by automated multiple development. Shown are the gradient profile used for the separation, the use of multiple wavelength scanning for detection and an in situ UV spectra for one peak (=s 50 ng). Solvent compositions for the gradient 1 = aqueous ammonia 2 = acetonitrile 3 = dichloromethane 4 = formic acid and 5 = hexane. (Adapted from ref. [21] American Chemical Society).

Advances in stationary phase technology have led to commercial availability of adsorbents such as high performance sihcas, aluminas, polyamides, celluloses and derivatised silicas [9,10], The development of automated method development (AMD) systems [127] now allow multi-step gradients of different elution strengths to be achieved in a relatively short time compared to earlier manual approaches. AMD systems are ideally suited for separation of complex mixtures with a wide range of polarities. Further improvements in sample resolution and reduced method development times in TLC include the use of two-dimensional development approaches [128] and forced-flow development by over-pressure liquid chromatography (OPLC) [129]. 

A technique that can achieve the maximum attainable resolution in TLC on a given separation distance without forced flow is automated multiple development (AMD). This step-gradient technique was developed by Burger. With respect to peak capacity the technique can be compared to HPLC, but it still maintains all benefits of planar chromatography. The heart of the instrument is a specially designed vacuum-tight chamber. Following sample application... 

Gradient development. Gradient developments have been used to achieve separation of complex mixtures such as plant extracts, dyes, etc. However, their application to lipid separation is not very common. Golkiewicz (1996) discusses in detail stationary phase gradients and mobile phase gradients, the theory behind solvent selection, automated techniques and applications of gradient elution in TLC. 

Automated multiple development (AMD), providing automatic chromatogram development and drying, is a novel form of the PMD technique. Automated multiple development as an instrumental technique can be used to perform normal-phase chromatography with solvent gradients on HPTLC plates. Most of the AMD applications use typical gradients Starting with a very polar solvent, the polarity is varied by means of base solvent of medium polarity to a... 

Lodi, G. Betti, A. Menziani, E. Brandohni, V. Tosi, B. Some aspects and examples of automated multiple development (AMD) gradient optimization. J. Planar Chromatogr. 1991, 4 (3/4), 106-110. 

---