We present CasADi, an open-source software framework for numerical optimization. CasADi is a general-purpose tool that can be used to model and solve optimization problems with a large degree of flexibility, larger than what is associated with popular algebraic modeling languages such as AMPL, GAMS, JuMP or Pyomo. Of special interest are problems constrained by differential equations, i.e. optimal control problems. CasADi is written in self-contained C++, but is most conveniently used via full-featured interfaces to Python, MATLAB or Octave. Since its inception in late 2009, it has been used successfully for academic teaching as well as in applications from multiple fields, including process control, robotics and aerospace. This article gives an up-to-date and accessible introduction to the CasADi framework, which has undergone numerous design improvements over the last seven years.

A series of mesoscopically ordered silicas with different pore sizes, pore connectivity, and pore geometry have been studied as carrier matrices for controlled drug delivery systems. Ibuprofen was used as a model drug, and the release processes were monitored under in vitro conditions. The adsorption of ibuprofen from hexane was shown to be of Langmuir type in all cases, and the degree of drug loading was dependent on the specific surface area and the pore diameter of the host matrix. The release process is found to be mainly diffusion controlled, but clear differences were observed between the studied materials, which we mainly ascribe to differences in the pore connectivity and pore geometry of the materials, and the aqueous stability of the matrix. The studied nanostructured silicas display a high degree of drug loading, and, depending on the host material, a controlled drug release can be provided for time periods varying from hours to weeks.

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