Experiments
The experimental work in naKnow is used to connect the technical parameters defined for each component family with the presence and quantity of materials. The aim is to move from assumptions about material composition to relationships that can be tested and supported by measurements.
The experimental work therefore follows the same logic as the component working groups. Parameters are first identified from the product and technology analysis. Their possible influence on material composition is then assessed, hypotheses are formulated, and samples are selected to test these hypotheses. The analytical results are finally used to validate, reject or refine the expected relationships and to improve the material models.
From component parameters to experiments
Each component working group identifies parameters that describe the component and may influence its material composition. These parameters can come from technology choices, dimensions, structure, manufacturing characteristics or other relevant product properties.
The experimental work examines how these parameters relate to materials. A parameter may influence the presence of a material, for example when a particular technology introduces a specific metal or material layer. A parameter may also influence the quantity of a material, for example when a larger surface area, a greater number of layers or a different thickness changes the amount of material required.
These expected relationships are converted into hypotheses that can be tested experimentally. Samples are then selected so that differences in the relevant parameters can be compared.
| Experimental stage | Purpose |
|---|---|
| Parameter identification | Identify the technical parameters used to describe the component. |
| Material relationship | Determine whether each parameter may influence material presence or material quantity. |
| Hypothesis formulation | Define the relationship expected between the parameter and the material composition. |
| Sample selection | Select samples that allow the hypothesis to be tested. |
| Experimental analysis | Measure the material composition of the selected samples. |
| Validation | Compare the measured results with the hypothesis and refine the relationship used in the model. |
Parameters → expected material relationship → hypothesis → experiment → measured material composition → validation → model refinement
Experimental analysis
The analytical method is selected according to the information required to test the hypothesis. For elemental composition, particularly metals and other inorganic elements, naKnow uses ICP-OES Analysis.
ICP-OES provides measured concentrations of elements in the analysed sample. These concentrations can be expressed as a mass fraction or converted into a material quantity when the mass of the analysed sample is known. The result therefore provides the quantitative information needed to compare samples and test whether a technical parameter explains a change in material composition.
Example of an experimental result
The result below illustrates the type of material-composition information obtained from the experimental analyses for a sample (example).
| Element / fraction | Content [%wt] | Content [g·t⁻¹] |
|---|---|---|
| Si | 14.86 | 148610 |
| Cu | 11.38 | 113837 |
| Mg | 6.74 | 67446 |
| Al | 3.89 | 38919 |
| Ca | 3.86 | 38615 |
| Na | 2.11 | 21051 |
| Zn | 0.15 | 1512 |
| Ag | 0.01 | 70 |
| Loss during pyrolysis | 23.82 | 238200 |
| Total measured fraction | 67.71 | 677070 |
The experimental result is not treated as an isolated material inventory. It is interpreted together with the parameters used to describe the sample. Measurements from different samples can therefore be compared to determine whether variations in material presence or quantity follow the relationship expected in the hypothesis.
From experimental results to model refinement
After analysis, the measured material composition is compared with the original hypothesis. When the expected relationship is supported by the measurements, the result can be used to define or refine the relationship between the parameter and the material quantity. When the relationship is not supported, the hypothesis is revised and other relevant parameters are considered.
This creates an iterative link between the component working groups and the experimental work. The working groups define the parameters and modelling needs, the experiments provide measured material information, and the results are returned to the models to improve how material presence and quantity are represented.
For the experimental method used to quantify elemental composition, see ICP-OES Analysis.
Discussion