Dissemination of IT for the Promotion of Materials Science (DoITPoMS)


What is a Tensor?

Tensors are simply mathematical objects that can be used to describe physical properties, just like scalars and vectors. In fact tensors are merely a generalisation of scalars and vectors; a scalar is a zero rank tensor, and a vector is a first rank tensor.

The rank (or order) of a tensor is defined by the number of directions (and hence the dimensionality of the array) required to describe it. For example, properties that require one direction (first rank) can be fully described by a 3×1 column vector, and properties that require two directions (second rank tensors), can be described by 9 numbers, as a 3×3 matrix. As such, in general an nth rank tensor can be described by 3n coefficients.

The need for second rank tensors comes when we need to consider more than one direction to describe one of these physical properties. A good example of this is if we need to describe the electrical conductivity of a general, anisotropic crystal. We know that in general for isotropic conductors that obey Ohm's law:

j = σE

Which means that the current density j is parallel to the applied electric field, E and that each component of j is linearly proportional to each component of E. (e.g. j1 = σE1).

However in an anisotropic material, the current density induced will not necessarily be parallel to the applied electric field due to preferred directions of current flow within the crystal (a good example of this is in graphite). This means that in general each component of the current density vector can depend on all the components of the electric field:

j1 = σ11E1 + σ12E2 + σ13E3
j2 = σ21E1 + σ22E2 + σ23E3
j3 = σ31E1 + σ32E2 + σ33E3

So in general, electrical conductivity is a second rank tensor and can be specified by 9 independent coefficients, which can be represented in a 3×3 matrix as shown below:

σ =
σ11 σ12 σ13
σ21 σ22 σ23
σ31 σ32 σ33

Other examples of second rank tensors include electric susceptibility, thermal conductivity, stress and strain. They typically relate a vector to another vector, or another second rank tensor to a scalar. Tensors of higher rank are required to fully describe properties that relate two second rank tensors (e.g. Stiffness (4th rank): stress and strain) or a second rank tensor and a vector (e.g. Piezoelectricity (3rd rank): stress and polarisation).

To view these and more examples, and to investigate how changing the components of the tensors affect these properties, go through the flash program below.