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Looking for a new way to feed your libraries for chemical modelling? Reach new dimensions in efficient and flawless generation of analytical input data for chemometrics (PCA, PLS, neural networks), Hansen solubility parameters (HSP) or other applications by using HT analytics.

High Throughput (HT) Analytics

High Throughput (HT) Analytics 2017-05-30T14:37:03+00:00

Questions answered

  • How can I get a spectral library for chemometrics?
  • What are the Hansen solubility parameters of ‘compound X’?

Wanted: input data for chemical modelling

Chemical formulation design and quality control make use of computational chemistry methods, for which reliable input data are required.

Creation of such data libraries used to be tedious, costly and error-prone. But at Agfa-Labs, we managed to implement high throughput analytical workflows and overcome this bottleneck.

Applications of HT analytics

For the implementation of a multivariate factor analysis of NIR spectra (a.k.a chemometrics), which is widely used in quality control of mixtures, a consistent library of spectra from various blends of all components is needed.

By combining high throughput formulation and spectral measurements on solutions, we can efficiently create a meaningful spectral library of mixtures that covers the needed parameter space using up to several 100 different blends (see case ‘Feeding chemometrics via high throughput analysis’).

Since the HSPiP software package has become commercially available, solubility problems can be tackled straightforward by rigorous application of the solubility approach of Hansen et al.

Agfa-Labs has developed a dedicated HT analytics workflow to experimentally determine Hansen solubility parameters (HSP) of the target compound by analytical measurement of solubility, using the multiple solvent approach with up to 58 selected reference solvents (see case ‘HT determination of Hansen Solubility Parameters’).

Interested in applying HT Analytics to create a data library?

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