  An open-source, Python-based Temporal Analysis of Products (TAP) reactor
simulation and processing program is introduced. TAPsolver utilizes algorithmic
differentiation for the calculation of highly accurate derivatives, which are
used to perform sensitivity analyses and PDE-constrained optimization. The tool
supports constraints to ensure thermodynamic consistency, which can lead to
more accurate parameters and assist in mechanism discrimination. The
mathematical and structural details of TAPsolver are outlined, as well as
validation of the forward and inverse problems against well-studied prototype
problems. Benchmarks of the code are presented, and a case study for extracting
thermodynamically-consistent kinetic parameters from experimental TAP
measurements of CO oxidation on supported platinum particles is presented.
TAPsolver will act as a foundation for future development and dissemination of
TAP data processing techniques.
