Every design and selection contains one or more constraints which viable candidates must satisfy. Design constraints can be imposed on a single physical property, such as density or viscosity, or on a complex function of physical properties such as a heat transfer coefficient calculated by a Nusselt number correlation.
Each constraint contains a function name, a minimum value, a goal value and a maximum value. Some example constraints are shown in the following table.
|Freezing Point [°C]
|Liquid Density at 20°C [kg/m3]
|Heat Transfer Coefficient at 20°C [W/m2 K]
In this example we will enter a constraint for a graphical chemical design. The same constraint can be used for combinatorial chemical designs and chemical selections. In fact, you can copy and paste the constraints between these documents.
Similarly, the constraints used in a graphical mixture design can also be copied and pasted into combinatorial mixture designs and mixture selections.
See documentation on the Constraints Dialog for additional details on editing constraints.
The knowledge base's Compile Property Values command can be helpful in identifying the physical property limits to use for your constraints. (See documentation on Compile Propery Values for details.) For example, the following image shows a compilation of melting points in units of °C.
Using the dialog's various controls and displays you can analyze typical physical property ranges.
The physical properties of most design candidates and many selection candidates will need to be estimated in order to evaluate a constraint. These estimated property values, even those estimated by very accurate techniques, will contain estimation errors. It is important to consider this error when setting contraint limits.
For example, the evaluation of the "Tm: Joback Method" estimation technique is shown in the image below. (See documentation on the Technique Evaluation Dialog for details on evaluating estimation techniques.) The statistics were determined only for those chemicals whose melting points were between -100°C and 50°C.
The average absolute error (Avg Abs Error) shown in the dialog's Statistics section is 26.08. If our constraint is meant to select candidates with freezing points below -20°C, then we might consider an maximum limit on the constraint of 6.08°C, i.e.
limit = goal ± error
max limit = (-20.0) + (26.08) = 6.08
If we do not account for estimation error, then our constraint will be discarding candidates whose actual melting points are satisfactory but whose estimated melting points are not because they are estimated to be too high.
|Getting Started using Synapse
|provides a quick tour of Synapse's capabilities including examples of chemical product design.
|Designing Chemical Products
|a short video demonstrating how to use Synapse to design candidate chemicals that satisfy a set of physical property and molecular structure constraints.