In this work, a hybrid simulation framework combining TCAD and Allpix2 is presented to investigate the sensor properties of MALTA2, a depleted monolithic active pixel sensor designed for future tracking. The study starts from 3D modeling and transient simulations in TCAD, with generic doping profiles and simple well structures. The resulting doping profiles and electric field are extracted and fed into Allpix2 for high-statistics Monte Carlo simulations in both DUT-only and full-telescope mode. Simulations reveal a strong dependence of sensor performance, specifically the detection efficiency and cluster size, on the doping concentration of the N-type blanket at the sensor surface. The doping concentration is then optimized by comparing simulations with measurement data. The active depth of the depleted region of the MALTA2 sensor is estimated in both simulations and measurements using a grazing angle method, in which the sensor is positioned at various inclinations relative to the beam, covering angles from 0 to 60 degrees. Excellent agreement on active depth is obtained with the optimal doping concentration, showing a deviation of 2\% from the measured value at a threshold of 450\,e−. Consequently, the framework offers a generic toolkit for sensor studies without requiring proprietary information.
Cite
@article{arxiv.2605.23860,
title = {TCAD + Allpi$\text{x}^2$ Simulation study of MALTA2, a Depleted Monolithic Active Pixel Sensor for future tracking},
author = {L. Li and P. Behera and D. V. Berlea and D. Bortoletto and C. Buttar and T. Chembakan and V. Dao and G. Dash and Y. Enari and L. Fasselt and S. Haberl and T. Inada and F. K. Isik and C. Issever and X. Li and Y. Okazaki and H. Pernegger and P. Riedler and W. Snoeys and C. A Solans Sanchez and A. Swoboda and I. Turk Cakir and M. van Rijnbach and A. Vijay and S. Worm},
journal= {arXiv preprint arXiv:2605.23860},
year = {2026}
}